management information systems case study

The success of a management information system in health care - a case study from Finland

Affiliation.

• 1 Central Finland Health Care District, Keskussairaalantie 19, FI-40620 Jyväskylä, Finland. [email protected]
• PMID: 22705086
• DOI: 10.1016/j.ijmedinf.2012.05.007

Purpose: The purpose of this article is to describe perspectives on information availability and information use among users of a management information system in one specialized health care organization. The management information system (MIS) is defined as the information system that provides management with information about financial and operational aspects of hospital management.

Methods: The material for this qualitative case study was gathered by semi-structured interviews. The interviewees were purposefully selected from one specialized health care organization. The organization has developed its management information system in recent years. Altogether 13 front-line, middle and top-level managers were interviewed. The two themes discussed were information availability and information use. The data were analyzed using inductive content analysis using ATLAS.ti computer program.

Results: The main category "usage of management information system" consisted of four sub-categories: (1) system quality, (2) information quality, (3) use and user satisfaction and (4) development of information culture.

Conclusions: There were many organizational and cultural aspects which influence the use of MIS in addition to factors concerning system usability and users. The connection between information culture and information use was recognized and the managers proposed numerous ways to increase the use of information in management work. The implementation and use of management information system did not seem to be planned as an essential tool in strategic information management in the health care organization studied.

Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Delivery of Health Care / organization & administration*
• Health Information Management / organization & administration*
• Management Information Systems*
• Models, Organizational*
• Organizational Culture*

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Management Information System: Case Study of Amazon.Com

Organizations under E commerce industry seek to attain core competence by creating and sustaining a unique process to collect personal information about customers and their purchasing trends. The report critically evaluates the how service based organization-Amazon use Management information systems as a vibrant tool in attaining competitive advantage through efficient management and acquisition of information. The study involves assessment of the best MIS practices in place for Amazon throughout its value chain activities. Uniqueness of MIS is being highlighted in the report through assessment of technology, process and the systems that Amazon use right from the initiation of the end user with the website till the payment and delivery mode is being selected. The last part of the report involves discussions on recommendations and suggestions for Amazon in order to enhance its existing MIS systems in place. The recommendations are based on the assessment of qualitative information and the extent of feasibility in implementing the proposed strategies.

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Management Information Systems: A Case Study of Walmart

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Management Information System: Operational Efficiency and Decision-Making Case Study

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Introduction

Business functions supported, how do they improve operational efficiency and decision making, problems solved., businesses most likely to benefit, the iphone is an industry changer.

Businesses require constant information to be processed and disseminated to the relevant stakeholders on time. To achieve this, they need Management Information systems.

A Management Information System is a set of connected apparatus, mostly computerized combinations that continuously acquire raw and needed data from within and outside a particular firm. Consequently, the data is processed and stored in a central place called database, where it is always updated and availed to those with authority to access it (Business Dictionary.com).

There are several applications that are described in the case study. In a community medical center known as Doylestown, an application, Meditech, is in place. In the same medical center, another application, titled Epocrates Essentials is described. Another application, which is ChainLinq Mobile application, is described as used in D.W. Morgan, being a supply chain, transportation and logistics service provider. Lastly, the iPhone camera is described in regards to a firm known as Aedas Sport.

Meditech conveys data on crucial signs, drugs, lab results, aversions, notes by nurses, results from remedial treatment, as well as patient food straight to the doctors’ phone. Epocrates Essentials, an aesculapian reference tool is used to help doctors to decode laboratory outcomes and procure medical data.

ChainLinq assists in updating of shipment information, collection of signatures, as well as provision of global positioning system locations to each individual box delivered. It has afforded Morgan the ability to present an attestation of delivery promptly. The iPhone camera has been used by designers and architects to take pictures of designs, models, and construction sites which are in turn sent to prospective clients to Aedas Sport.

Meditech application enables doctors to be on call wherever they may be through sending them sensitive alerts through their emails from their work stations. This allows the doctors to make decisions quickly and long before they even get to the hospital.

ChainLinq application has reduced the time needed to provide proof of delivery from half a day to immediate. The iPhone camera has enabled Aedas Sports to productivity jump to 400 percent. In addition, iPhone has facilitated the building of a large chronicle of observable assets almost effortlessly.

First and foremost, the problem of mobility was solved for doctors in Doylestown meaning that doctors can still communicate even while not in the vicinity of the hospital. Thanks to ChainLinq, Morgan does not have to make numerous phone calls so as to track and proof deliveries. The customers as well are in a position to be aware of the status of their deliveries by logging in to the company’s website which is updated by the servers throughout.

Among other businesses, the following will likely benefit. The Health sector will benefit when their employees are equipped with mobile digital devices. This will assist them in keeping in touch with their employers as well as patients’ history whenever needed. They can make decisions and communicate immediately. In addition, they will be able to make accurate calculations on laboratory results using the devices.

Courier businesses are to benefit as well through tracking of their parcels as well as tracking the exact position of the mode of delivery, for example, trucks among others. In addition, these businesses will get proof of delivery in real time thus increasing efficiency and therefore, staying calm without having to make numerous phone calls to track the process of delivery.

Designers and architectural businesses also stand to benefit from mobile devices. The iPhone will especially make it possible to get clear and professional photo shots, compile them into journals and send them to potential and actual clients.

Supply store chains like Wal-Mart are likely to benefit, too. As soon as a customer buys a certain item, the supplier through the iPhone is alerted to ship replacement for the item. The supplier is able to know what quantity is needed as well.

The banks are the ones that get lot of beneficiaries. The managers get real-time data in regard to customer complaints, network performance and line outages.

The motor industry is set to benefit greatly too. For instance, Toyota uses Toyota Production System to achieve high levels of efficiency and quality. This gives them a competitive edge over their rivals. This arises from the fact that they charge less for superior products, as well as give better responses to suppliers and customers through the system.

This statement is about the change in communicating with suppliers and customers. The industry has changed through using iPhone since communication is conducted in real time. In the supply chain, transportation and logistics industry, where D.W. Morgan belongs, the firm is able to track every detail; it takes few minutes to do so. In other words, they make delivery in real time while it takes their competitors up to twelve hours to do the same task.

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1. IvyPanda . "Management Information System: Operational Efficiency and Decision-Making." November 28, 2018. https://ivypanda.com/essays/management-information-systems-case-study/.

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Home » Management Case Studies » Case Study on MIS: Information System in Restaurant

Case Study on MIS: Information System in Restaurant

Case Summary:

A waiter takes an order at a table, and then enters it online via one of the six terminals located in the restaurant dining room. The order is routed to a printer in the appropriate preparation area: the cold item printer if it is a salad , the hot-item printer if it is a hot sandwich or the bar printer if it is a drink . A customer’s meal check-listing (bill) the items ordered and the respective prices are automatically generated. This ordering system eliminates the old three-carbon-copy guest check system as well as any problems caused by a waiter’s handwriting. When the kitchen runs out of a food item, the cooks send out an ‘out of stock’ message, which will be displayed on the dining room terminals when waiters try to order that item. This gives the waiters faster feedback, enabling them to give better service to the customers. Other system features aid management in the planning and control of their restaurant business. The system provides up-to-the-minute information on the food items ordered and breaks out percentages showing sales of each item versus total sales. This helps management plan menus according to customers’ tastes. The system also compares the weekly sales totals versus food costs, allowing planning for tighter cost controls. In addition, whenever an order is voided, the reasons for the void are keyed in. This may help later in management decisions, especially if the voids consistently related to food or service. Acceptance of the system by the users is exceptionally high since the waiters and waitresses were involved in the selection and design process. All potential users were asked to give their impressions and ideas about the various systems available before one was chosen.

• In the light of the system, describe the decisions to be made in the area of strategic planning , managerial control and operational control? What information would you require to make such decisions?
• What would make the system a more complete MIS rather than just doing transaction processing?
• Explain the probable effects that making the system more formal would have on the customers and the management.

Solution of Management Information System in Restaurant Case Study:

1. A management information system (MIS) is an organized combination of people, hardware, communication networks and data sources that collects, transforms and distributes information in an organization. An MIS helps decision making by providing timely, relevant and accurate information to managers. The physical components of an MIS include hardware, software, database, personnel and procedures.

Management information is an important input for efficient performance of various managerial functions at different organization levels. The information system facilitates decision making. Management functions include planning, controlling and decision making. Decision making is the core of management and aims at selecting the best alternative to achieve an objective. The decisions may be strategic, tactical or technical. Strategic decisions are characterized by uncertainty. They are future oriented and relate directly to planning activity. Tactical decisions cover both planning and controlling. Technical decisions pertain to implementation of specific tasks through appropriate technology. Sales region analysis, cost analysis, annual budgeting, and relocation analysis are examples of decision-support systems and management information systems.

There are 3 areas in the organization. They are strategic, managerial and operational control.

Strategic decisions are characterized by uncertainty. The decisions to be made in the area of strategic planning are future oriented and relate directly to planning activity. Here basically planning for future that is budgets, target markets, policies, objectives etc. is done. This is basically a top level where up-to-the minute information on the food items ordered and breaks out percentages showing sales of each item versus total sales is provided. The top level where strategic planning is done compares the weekly sales totals versus food costs, allowing planning for tighter cost controls. Executive support systems function at the strategic level, support unstructured decision making, and use advanced graphics and communications. Examples of executive support systems include sales trend forecasting, operating plan development, budget forecasting , profit planning , and manpower planning .

The decisions to be made in the area of managerial control are largely dependent upon the information available to the decision makers. It is basically a middle level where planning of menus is done and whenever an order is voided, the reasons for the void are keyed in which later helps in management decisions, especially if the voids are related to food or service. The managerial control that is middle level also gets customer feedback and is responsible for customer satisfaction.

The decisions to be made in the area of operational control pertain to implementation of specific tasks through appropriate technology. This is basically a lower level where the waiter takes the order and enters it online via one of the six terminals located in the restaurant dining room and the order is routed to a printer in the appropriate preparation area. The item’s ordered list and the respective prices are automatically generated. The cooks send ‘out of stock’ message when the kitchen runs out of a food item, which is basically displayed on the dining room terminals when waiter tries to order that item. This basically gives the waiters faster feedback, enabling them to give better service to the customers. Transaction processing systems function at the operational level of the organization. Examples of transaction processing systems include order tracking, order processing, machine control, plant scheduling, compensation, and securities trading.

The information required to make such decision must be such that it highlights the trouble spots and shows the interconnections with the other functions. It must summarize all information relating to the span of control of the manager. The information required to make these decisions can be strategic, tactical or operational information.

Advantages of an online computer system:

• Eliminates carbon copies
• Waiters’ handwriting issues
• Out-of-stock message
• Faster feedback, helps waiters to service the customers

Advantages to management:

• Sales figures and percentages item-wise
• Helps in planning the menu
• Cost accounting details

2. If the management provides sufficient incentive for efficiency and results to their customers, it would make the system a more complete MIS and so the MIS should support this culture by providing such information which will aid the promotion of efficiency in the management services and operational system. It is also necessary to study the keys to successful Executive Information System (EIS) development and operation. Decision support systems would also make the system a complete MIS as it constitutes a class of computer-based information systems including knowledge-based systems that support decision-making activities. DSSs serve the management level of the organization and help to take decisions, which may be rapidly changing and not easily specified in advance.

Improving personal efficiency, expediting problem solving (speed up the progress of problems solving in an organization), facilitating interpersonal communication, promoting learning and training, increasing organizational control, generating new evidence in support of a decision, creating a competitive advantage over competition, encouraging exploration and discovery on the part of the decision maker, revealing new approaches to thinking about the problem space and helping automate the managerial processes would make the system a complete MIS rather than just doing transaction processing.

3. The management system should be an open system and MIS should be so designed that it highlights the critical business, operational, technological and environmental changes to the concerned level in the management, so that the action can be taken to correct the situation. To make the system a success, knowledge will have to be formalized so that machines worldwide have a shared and common understanding of the information provided. The systems developed will have to be able to handle enormous amounts of information very fast.

An organization operates in an ever-increasing competitive, global environment. Operating in a global environment requires an organization to focus on the efficient execution of its processes, customer service, and speed to market. To accomplish these goals, the organization must exchange valuable information across different functions, levels, and business units. By making the system more formal, the organization can more efficiently exchange information among its functional areas, business units, suppliers, and customers.

As the transactions are taking place every day, the system stores all the data which can be used later on when the hotel is in need of some financial help from financial institutes or banks. As the inventory is always entered into the system, any frauds can be easily taken care of and if anything goes missing then it can be detected through the system.

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5 thoughts on “ Case Study on MIS: Information System in Restaurant ”

please give me solution of case study urgent.

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A small company has for some years being using a manual system for processing of billing, payment of creditors and payroll system. The company is considering purchasing a computer on which it will run these application and others that it will develop in the near future. You have been asked to prepare a report on the implication of this proposed course of action.

1. Identify and describe six major issues which would be considered in an investigation of the feasibility of the proposal. 2. Suggest the outline structure of the report.

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Management information system adoption at the farm level: evidence from the literature

British Food Journal

ISSN : 0007-070X

Article publication date: 2 November 2020

Issue publication date: 5 February 2021

This paper reviews the academic contributions that have emerged to date on the broad definition of farm-level management information systems (MISs). The purpose is twofold: (1) to identify the theories used in the literature to study the adoption of digital technologies and (2) to identify the drivers of and barriers to the adoption of such technologies.

Design/methodology/approach

The literature review was based on a comprehensive review of contributions published in the 1998–2019 period. The search was both automated and manual, browsing through references of works previously found via high-quality digital libraries.

Diffusion of innovations (DOIs) is the most frequently used theoretical framework in the literature reviewed, though it is often combined with other innovation adoption theories. In addition, farms’ and farmers’ traits, together with technological features, play a key role in explaining the adoption of these technologies.

Research limitations/implications

So far, research has positioned the determinants of digital technology adoption mainly within the boundaries of the farm.

Practical implications

On the practical level, the extensive determinants’ review has potential to serve the aim of policymakers and technology industries, to clearly and thoroughly understand adoption dynamics and elaborate specific strategies to deal with them.

Originality/value

This study’s contribution to the existing body of knowledge on the farm-level adoption of digital technologies is twofold: (1) it combines smart farming and existing technologies within the same category of farm-level MIS and (2) it extends the analysis to studies which not only focus directly on adoption but also on software architecture design and development.

• Smart farming
• Farm management information systems
• Enterprise resource planning
• Diffusion of innovation
• Digital divide

Giua, C. , Materia, V.C. and Camanzi, L. (2021), "Management information system adoption at the farm level: evidence from the literature", British Food Journal , Vol. 123 No. 3, pp. 884-909. https://doi.org/10.1108/BFJ-05-2020-0420

Emerald Publishing Limited

Copyright © 2020, Carlo Giua, Valentina Cristiana Materia and Luca Camanzi

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at: http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Agri-food systems are on the verge of a new revolution based on the use of digital innovations throughout the supply chain ( Lehmann et al. , 2012 ; Trendov et al. , 2019 ; Wolfert et al. , 2017 ). Scholars have applied different names to define this digitalisation, including “digital agriculture”, “agriculture 4.0” and “smart farming”. That notwithstanding, there is common agreement on the central role that data play in the agri-food supply chain’s virtualisation ( Verdouw et al. , 2016 ).

Despite the general agreement on the beneficial effects that this revolution will have for the agri-food system in terms of greater efficiency, effectiveness and sustainability ( Fabregas et al. , 2019 ; Lehmann et al. , 2012 ), the process of adopting innovative digital technologies requires resources and competences which not all the actors possess ( Poppe and Renwick, 2015 ). For instance, the literature shows that amongst internal resources, farm size and financial availability can be important barriers to overcome, especially for small and medium enterprises (SMEs) ( Bucci et al. , 2018 ; Lawson et al. , 2011 ). Amongst external resources, poor Internet connectivity, data transfer and privacy concerns are just some of the factors reported as obstacles to the adoption process ( Kernecker et al. , 2019 ; Pivoto et al. , 2019 ). In addition, not only resources but also specific competences need to be developed by firms – the so-called dynamic capabilities ( Teece et al. , 2008 ) – in order to achieve a suitable digital transformation of their business ( Bouwman et al. , 2018 ; Warner and Wäger, 2019 ; Zahra and George, 2002 ).

Disparities in the process of adopting digital technologies might further aggravate the unequal distribution of value that already exists in certain cases between small–medium (especially in upstream production stages) and large players (downstream production stages, especially distribution and retailers). This is particularly true for the European agri-food productive structure which predominantly comprises SMEs ( Capitanio et al. , 2009 ; FoodDrinkEurope, 2016 ; Materia et al. , 2017 ). Furthermore, the digitalisation process can be quite different depending on the nature of the digital technologies and on the challenges that arise in different supply chain stages ( Pivoto et al. , 2019 ; Poppe and Renwick, 2015 ).

In light of the above considerations, this study aims to provide a more specific systematisation of the factors that enable and hinder the adoption of different technologies.

To this end, this research focusses specifically on the farm-level adoption of smart-farming solutions since the digitalisation of the supply chain’s upstream stage is an essential condition to successfully exploit this revolution and ensure that all stakeholders benefit. Indeed, farmers (particularly in small and medium agri-food enterprises) have traditionally been reluctant to innovate ( Long et al. , 2016 ) and they often lack the required resources and competences, especially for human capital-intensive innovations ( Dicecca et al. , 2016 ; Materia et al. , 2017 ; Warren, 2002 ).

The study is based on a comprehensive review of contributions from the scientific literature dealing with the adoption of farm-level digital innovations, with a specific focus on management information system (MIS) technologies, defined as a set of software systems used to support human decision-making within farm management activities ( Fountas et al. , 2015a ; Verdouw et al. , 2015 ). This study reviews the theoretical frameworks used as well as the drivers and barriers, both within and beyond farm boundaries.

The paper is structured as follows: section 2 sets out the scope and the objective of the study by means of providing a definition of the technologies considered and presenting the research questions. Section 3 outlines the methodology and discusses the sources of literature considered. Section 4 describes the main results, including descriptive characteristics and evidence gathered concerning the theoretical frameworks adopted and main evidence found in the literature reviewed. Finally, section 5 includes a discussion of these findings together with some recommendations for future research.

2. The scope and objectives

2.1 management information systems at the farm level.

In recent years, a large number of digital technologies have become available for actors in upstream stages within agri-food chains. Amongst these, advanced decision support systems (DSSs) have garnered increasing attention, enabling farmers to make informed decisions not only related to farming practices (precision agriculture technologies) but also financial and managerial operations ( Fountas et al. , 2015a ).

Amongst such software solutions, scholars have placed particular focus on the farm management and information systems (FMISs) category. Sørensen et al. (2010 , p. 38) defined FMISs as “a planned system for the collecting, processing, storing and disseminating of data in the form of information needed to carry out the functions of the farm”. In addition, they point out that FMISs can be considered “an integral part of the overall management system of a firm […] and part of tools such as Enterprise Resource Planning (ERP) and overall Information Systems (IS)” ( Sørensen et al. , 2010 , p. 38). By contrast, ERP technologies are defined as standardised software packages which incorporate information systems for multiple business functions to create a single integrated system ( Verdouw et al. , 2015 ).

In fact, even if FMIS and ERP applications have followed different evolutionary paths, today they communicate and collaborate within agri-food enterprises’ information technology (IT) systems. On the one hand, modern FMISs were developed to organise the increasing amount of data generated by precision agriculture technologies and combined them with an economic and holistic management perspective ( Fountas et al. , 2015a ; Verdouw et al. , 2015 ). On the other hand, ERPs stem from manufacturing resource planning systems and the necessity to integrate both across and within the various functional silos found in modern manufacturing ( Jacobs and Weston, 2007 ). Initially, the rigid standards of early ERP solutions were not well suited to deal with the complexity of agricultural biological processes. Nonetheless, new web-based and customisable ERP systems are much more flexible ( Møller, 2005 ) and capable of ensuring the interoperability required to integrate “many FMISs, DSSs and many applications in between, all covering different aspects of farm management” ( Verdouw et al. , 2015 , p. 127).

This is why various authors argue that integrating FMIS and ERP research can result in numerous and promising research opportunities that are worth investigating ( Haberli et al. , 2019 ; Verdouw et al. , 2015 ).

Hence, for the purposes of the present study, the literature analysed includes research conducted on the farm-level adoption of both FMIS and ERP as well as the intersections between these two technologies. Given the fast-developing nature of digital technologies, by including contributions dealing with different versions of FMIS (both computer- and mobile-based systems, applications, software as a service [SaaS], etc.), this review provides the opportunity to consider as many different contributions to the topic as possible. In the rest of the paper, the term “farm-level MIS” refers to this combined group of management information technologies.

2.2 Research questions

The literature on the farm-level adoption of MIS has mostly focussed on FMIS technologies. To the best of the authors’ knowledge, the first specific contribution dates back to the end of last century ( Lewis, 1998 ). At that time, the technical characteristics and functionalities of software and devices used were more akin to computers assisting agricultural production as compared to how FMISs are used today ( Tummers et al. , 2019 ). Amongst most recent contributions, Tummers et al. (2019) reviewed the obstacles to FMIS development and adoption found in the literature, besides providing a more updated state of the art on device functionalities. Amongst these barriers, some are more related to technical traits such as data standards and system integration, while others relate more specifically to factors linked to lower adoption, such as the comprehensibility of software, insufficient skills amongst farmers and regional/language barriers.

Although Tummers et al. (2019) referred to specific obstacles, FMIS adoption has been analysed only partially to determine the explanatory variables behind their diffusion, not as the actual object of study. In fact, to the best of the authors’ knowledge, the available literature still lacks a review which focusses specifically on farm-level MIS adoption processes.

Which theories have scholars used to study the adoption of farm-level MISs?

What are the main determinants affecting the adoption of farm-level MISs?

What are the main drivers?

What are the main barriers?

3. Materials and methods

The process of searching, collecting, selecting and synthesising literature occurred between September 2019 and January 2020, following the literature review’s approach proposed by Hart, who defined it as “the selection of available documents (both published and unpublished) on the topic, (…) to fulfil certain aims or express certain views on the nature of the topic and how it is to be investigated, and the effective evaluation of these documents in relation to the research being proposed” ( Hart, 1998 , p. 13).

This approach has been integrated with both specific guidelines on how to structure the review ( Torraco, 2005 ; Vom Brocke et al. , 2009 ) and existing examples of structured literature reviews ( Boehm and Thomas, 2013 ; Cronin et al. , 2008 ; Della Corte et al. , 2018 ; Giacomarra et al. , 2020 ; Svejvig and Andersen, 2015 ; Tell et al. , 2016 ), with the aim to clearly present the analysis and results. Therefore, the review is organised in the following three phases: (1) search strategy, (2) screening and selection and (3) data extraction and analysis.

3.1 The search strategy

The automated research component implied using two of the key high-quality digital libraries available: the Institute for Scientific Information (ISI) Web of Science and Scopus. As recommended by Hart (1998) , after different attempts to identify the most inclusive string, the final research query combined various sets of keywords such as farm MISs, FMISs, ERP and adoption. Search results included journal articles, conference papers and proceedings, white papers, reports and book sections, all published in English as found in the most recent FMIS review carried out by Tummers et al. (2019) . In order to take the technological evolution of these management systems into account while also being aware of the quickly developing literature on IT in agriculture, texts were limited to the 1998–2019 period, starting from the first review on FMIS available in these sources ( Lewis, 1998 ). This search identified additional studies that were then added to the screening process through snowball techniques. The authors identified these additional texts by manually browsing through references of works previously found via the automated search. A preliminary refinement of articles was based on selecting Web of Science categories pertaining to agricultural economics and policy, agriculture multidisciplinary, computer science interdisciplinary applications and management. A total of 849 studies were identified in these digital libraries (576 from ISI WOS and 273 from Scopus). An initial selection was carried out before downloading the studies, based on their titles and reading their abstracts. In this stage, the authors considered each contribution related to FMIS design, use and adoption and ERP adoption at the farm level for further refinement. A final screened sample of 70 studies was downloaded from said digital libraries (35 from ISI WOS and 35 from Scopus).

3.2 Screening and selection

All the studies identified were imported into a single library and processed using Mendeley citation manager software. Using the “Check for duplicates” feature, 12 studies were deleted, reducing the number of papers retained for analysis to 58. The screening selection process was based on two steps as found in Giacomarra et al. (2020) . First , the authors established the following inclusion criteria: (1) all studies which focussed on FMISs (computer- or mobile-based) and ERP adoption used in the agri-food sector and (2) all studies which focussed on FMIS design, development and technological evolutions (traceability, big data, cross compliance and cloud-based platforms). A total of nine additional studies were eliminated as a result of the previous step. Second, studies were further screened based on the exclusion criteria listed in Table 1 below.

The final subset included 35 studies for analysis and study (see Figure 1 below). The authors could not access the full text of one study due to licence restrictions and had to eliminate it from the sample. Moreover, 22 other studies did not satisfy the exclusion criteria indicated above, while additional nine works were eventually added to the final selection by browsing references of selected studies.

At this step, the authors did not only consider academic contributions which focussed solely on adoption. They expanded the scope to focus on other types of studies dedicated to FMIS software design and development. This choice was made for several reasons. First, one deals with the user-centric approach found in several texts ( Kaloxylos et al. , 2012 ; Kruize et al. , 2016 ; Sørensen et al. , 2011 ), an approach which “assumes that the users’ ideas and requirements reactions concerning the speciffc characteristics of the designed technology are integrated in the subsequent design” ( Sorensen et al. , 2010 , p. 45). As several scholars acknowledge, end-user involvement during the early stage of the devices’ design and development makes it easier to satisfy user requirements and, as a result, make user acceptance and adoption more likely. An example of this approach is found in Nurkka et al. (2007) , where data from interviews, questionnaires and farms visits served to identify users’ needs, demands and capabilities before designing a specific MIS, recognising, at the same time, problems and limitations that might occur in the adoption and use of such devices.

In addition, considering actual technology adoption and design simultaneously allows for a more complete picture on adoption determinants, including factors which might not be attributable solely to the adopter. This way, a more thorough understanding is possible, though not only of technology adoption, per se , but also some of its disparate consequences, one of which is the digital divide in the agri-food sector ( Bronson and Knezevic, 2016 ; Trendov et al. , 2019 ). This refers to the situation in which a substantial proportion of the population, identified by one or more shared characteristics, lags significantly behind others in the adoption of a new technology ( Warren, 2002 ). Indeed, as Bronson (2019 , p. 3) argues that “The bifurcation in the market for smart farming technologies may not simply be an adoption issue beginning on the farm (and with farmers); rather, it at least partly results from partial and normatively motivated design decisions which are helping to produce digital farming ‘haves’ and ‘have-nots’”. For these reasons, this paper includes various types of studies (both qualitative–descriptive and quantitative–deterministic), with the aim being to capture all the different determinants of farm-level MIS adoption identified until now.

3.3 Data extraction and the analysis

The authors uploaded all 35 papers to the ATLAS.ti 8 platform, a widely used piece of software to undertake qualitative data analyses and literature reviews ( Haan et al. , 2018 ; Hossain, 2016 ; Hossain et al. , 2019 ). The authors read the selected studies thoroughly and coded them with references to an extraction form organised in a matrix structure as suggested by Finfgeld-Connett (2014) and Leonidou et al. (2018) , with the aim to “minimize human error and document this procedure for replicability purposes” ( Leonidou et al. , 2018 , p. 3) . The matrix’s structure is based on (1) research questions for the literature review in keeping with Hart's recommendations (1998), (2) the data extraction method used by previous literature reviews to classify FMISs ( Tummers et al. , 2019 ) and (3) the reading of a sample of randomly selected studies to iteratively adjust the structure ( Hossain et al. , 2019 ; Tummers et al. , 2019 ).

The initial matrix structure comprised several features with the following classifications: general information (author, title, publication year and type of document), study description (sector, main theme, methods used, stakeholders involved, etc.) and adoption (theoretical framework – if any and including drivers and barriers). During the coding process, the authors created new themes when needed to categorise new codes. Most of the description elements were used to build statistic elaborations on the studies collected and together with the section focussed on adoption, they served to answer the research questions posited.

This section summarises the data obtained distributed into two sections, in keeping with the review structures used by Radu (2016) and Tummers et al. (2019) . The first focusses on descriptive statistics on the composition and main characteristics of the final sample of texts; the second provides findings to answer the research questions outlined above.

Trends regarding the number of publications and the composition of the sample of contributions studied provide interesting insights. The overall number of contributions is rather stable, apart from two peaks registered in 2010–2011 and in 2017 (see Figure 2 ). Both peaks denote the academic attention to evolved versions of FMISs with respect to more basic information systems available until that moment. In several cases, these studies may have been encouraged by international research projects (such as the EU-funded FUTUREFARM project or the SmartAgrifood and FiSpace projects, part of the European Future Internet Public–Private Partnership programme (FI-PPP)) [1] .

As this paper includes studies with research focusses other than just technology adoption, the authors classified the contributions by the main themes addressed and synthesised the findings into the following key categories: adoption, software design and other types of studies.

The “User adoption studies” category primarily comprises papers focussed specifically on MIS adoption by agri-food users; the “Software design studies” group incorporates contributions that do not focus on adoption, per se , but on the development of a software architecture model. As explained above, due to the user-centric approach applied in these papers, the authors of this study were able to identify user requirements and barriers to FMIS adoption and use. Last, the “Other studies” category includes contributions with a broader focus. Some of the texts included in the latter group report on the state of the art of FMIS development and use, along with future perspectives ( Allen and Wolfert, 2011 ; Fountas et al. , 2015a ; Kuhlmann and Brodersen, 2001 ; Tsiropoulos et al. , 2017 ). Other contributions focus on the development of integrated platforms (software ecosystems) to make smart-farming technologies (such as FMIS) interoperable ( Barmpounakis et al. , 2015 ; Kruize et al. , 2016 ).

In this study, the authors classify the literature according to the type of research conducted (qualitative vs quantitative): 20 studies were classified as qualitative and the remaining 15 as quantitative [2] . Table 2 below shows how all these studies are distributed.

While almost all the qualitative texts are included in the “Software architectural models” and “Other studies” categories, only two of the 15 studies on MIS adoption are qualitative. In the next sections, the authors discuss additional details on adoption studies.

4.1 The oretical and methodological approaches in adoption studies

Studies which focussed specially on farm-level MIS adoption are listed in Table 3 below. A technological evolution occurred in the devices objects of adoption studies, from computer-based management information systems ( Alvarez and Nuthall, 2006 ; Batte, 2005 ; Lewis, 1998 ; Tiffin and Balcombe, 2011 ) to more sophisticated, application-based and Internet-connected versions ( Carrer et al. , 2017 ; Fox et al. , 2018 ; Pivoto et al. , 2019 ). A total of three papers focussed on ERP adoption at the farm level ( Haberli et al. , 2017 , 2019 ; Verdouw et al. , 2016 ). The authors checked the technological coherence of this software with FMISs (discussed above) during the first selection step since only contributions that studied ERP as aligned with FMIS were considered in adoption studies.

In terms of theoretical approaches, 11 of the 15 studies in this group used at least one conceptual framework to study technology adoption. The most used theory was the diffusion of innovation (DOI), devised originally by Rogers (2003 , 1995) . DOI theory studies the spread of innovations and how they proliferate through different channels over time and within a particular social environment. According to Rogers, the innovation–decision process involves five steps: (1) knowledge, (2) persuasion, (3) decision, (4) implementation and (5) confirmation. These stages typically follow each other in a time-ordered manner. Adoption then depends on how individuals might perceive what Rogers (1982) defined as five innovation attributes, i.e. relative advantage, compatibility, complexity, trialability and observability.

Verdouw et al. (2015) are the only scholars in this review who used DOI as a unique framework. Also, two studies ( Haberli et al. , 2017 , 2019 ) integrated DOI with technology–organisation–environment (TOE), another widely used theory in adoption studies ( Molinillo and Japutra, 2017 ; Oliveira and Martins, 2011 ). The TOE framework identifies the process used by a company to adopt and implement innovations, taking into account the technological, organisational and environmental context ( De Pietro et al. , 1990 ). Fox et al. (2018) and Ibrahim et al. (2018) applied the unified theory of adoption and use of technology (UTAUT). UTAUT integrates eight theories on technology adoption: the technology acceptance model (TAM), the theory of reasoned action (TRA), DOI, the motivational model, the theory of planned behaviour, a combined theory of planned behaviour/ TAM, a model of personal computer use and social cognitive theory.

4.2 Adoption drivers reported in the literature

This section presents the major drivers behind the adoption of farm-level MIS found through the review. To ensure an efficient synthesis, only drivers coded at least four times are reported in this paper ( Tables A1 and A2 in the appendix) in keeping with Tummers et al. (2019) .

Results indicate that the most recurrent drivers are technology usability, farm size and farmer education level. Pignatti et al. (2015) categorised FMIS adoption drivers into three different groups: the innovations’ technological features, farm and farmer traits and external environment features. This study applies this same classification.

The International Organization for Standardization (ISO) defines usability/ease of use as follows: “the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use” ( Bevan and Carter, 2016 , p. 269). This driver can thus be considered part of the ‘technological features’ category. As found in ( Carli and Canavari, 2013 ; Husemann and Novkovic, 2014 ; Nikkilä et al. , 2010 ; Rosskopf and Wagner, 2003 ; Sopegno et al. , 2016 ) and Alvarez and Nuthall (2006) , important factors when deciding to adopt a given MIS include user-friendly interfaces and easy-to-use software to input data and retrieve data output from the system. Furthermore, the possibility of customising a farm-level MIS or its flexibility is another driver included in this category. Indeed, when customised technologies meet farms’ specific needs while providing standard functionalities, users are more likely to adopt them ( Mackrell et al. , 2009 ; Rosskopf and Wagner, 2003 ).

Another driver category is related to farm characteristics. Farm size – generally measured not only in terms of land extension but also in terms of gross sales in some cases ( Batte, 2005 ) or the number of paid workers ( Tiffin and Balcombe, 2011 ) – is the most recurrent driver. Larger farms have to manage more complex production processes and they need to gather and process more information (e.g. precision agriculture data); therefore, farm-level MIS have to organise management data and control complexity ( Carrer et al. , 2017 ; Pivoto et al. , 2019 ). Another driver included in this category is the farm’s initial technology, a factor which includes all the different technologies already in use on the farm (current IT systems, other smart-farming technologies, etc.) and which might favour the adoption of a complementary farm-level MIS ( Alvarez and Nuthall, 2006 ; Lewis, 1998 ).

The third most recurrent driver is farmers’ education, included in the user characteristics category. Several studies found that more educated farmers were more likely to adopt MIS ( Alvarez and Nuthall, 2006 ; Carrer et al. , 2017 ; Engler and Toledo, 2010 ; Kaloxylos et al. , 2014 ; Lewis, 1998 ; Tiffin and Balcombe, 2011 ). As explained by Carrer et al. : “Farmers with higher education manifest greater demand for information and stronger ability to evaluate the beneffts of using computers as a tool to support management decision-making” ( Carrer et al. , 2017 , p. 16). Another user characteristic which might have a positive influence on adoption is the existing level of IT skills needed to use management systems, including familiarity with computers or information systems ( Allen and Wolfert, 2011 ; Kuhlmann and Brodersen, 2001 ; Nurkka et al. , 2007 ) and with Internet usage ( Kaloxylos et al. , 2014 ). In addition, there are several important factors within this group related to users’ beliefs, perceptions and needs which drive farm-level MIS adoption. Amongst the individual perception factors, several studies point to the perceived relative advantage. Rogers defined this as “the degree to which an innovation is perceived as better than the idea it supersedes” ( Rogers, 1982 , p. 213). In this sense, there are different interconnected subdimensions regarding relative advantages related to farm management: the degree of economic profitability, costs, benefits in terms of time and effort, etc. Haberli et al. (2019) , Rosskopf and Wagner (2003) , Tsiropoulos et al. (2017) and Verdouw et al. (2015) determined that perceived benefits include greater transparency, greater integration and improved efficiency, as well as expected profitability and other aspects related to the economic dimension of relative advantage.

When only considering studies that specifically focus on adoption, the most recurrent driving factors are limited to farms’ and farmers’ characteristics, such as size, education and relative advantage. No recurrent drivers were identified in the external environment group of features.

4.3 Adoption barriers reported in the literature

This study applied the same analysis to adoption barriers (see Table A1 in the appendix). When applying the same categorisation to factors which directly or indirectly impede adoption, it seems that technological features are the most relevant barriers.

As Tummers et al. (2019) described, problems related to interoperability or system integration between FMISs and their components hinder “interchangeability” between applications and platforms, reducing their applicability and, thus, the future adoption of such technology ( Kruize et al. , 2016 ). For Rosskopf and Wagner (2003) , an important requirement expressed by some farmers is the possibility of adapting/integrating new and old software. Interoperability issues are strictly connected to data standards since a lack of industry-wide data exchange protocols causes difficulties in data exchange, thus limiting farm-level MIS applicability ( Allen and Wolfert, 2011 ; Fountas et al. , 2015a ; Kruize et al. , 2016 ). Another aspect related to technological features refers to concerns regarding data ownership, privacy and security, representing issues for users and possible adopters ( Allen and Wolfert, 2011 ; Fountas et al. , 2009 ; Kaloxylos et al. , 2014 ; Zheleva et al. , 2017 ).

Included amongst technological factors which hinder adoption more directly is the complexity of these technologies; this not only includes unintuitive or excessively complicated interfaces but also too many features when compared to users’ actual needs, making farm-level MIS technologies difficult to implement, understand and use ( Haberli et al. , 2017 ; Nikkilä et al. , 2010 ; Verdouw et al. , 2015 ). This perceived complexity is one of the causes that makes these technologies time-consuming for possible adopters, especially in terms of learning how to use them ( Alvarez and Nuthall, 2006 ; Pivoto et al. , 2019 ), for example, when manually inputting data ( Mackrell et al. , 2009 ; Steffe, 2000 ). These aspects are inversely connected to usability as a driver as discussed in the previous section, underscoring how much software design influences its adoption.

Between the technological feature and farm resource categories, the cost of these technologies certainly plays a role in adoption decisions. For Allen and Wolfert (2011) , farmers are reluctant to invest too much in this software due to lower farm profitability and high market volatility. Kaloxylos et al. (2014) reported some concerns about the cost of other smart-farming technologies related to their implementation; these can be even more prohibitive in the case of smallholders or SMEs ( Zheleva et al. , 2017 ). Finally, when it comes to user characteristics, several studies cite age as a common adoption barrier ( Allen and Wolfert, 2011 ; Alvarez and Nuthall, 2006 ; Batte, 2005 ; Fountas et al. , 2015b ; Lewis, 1998 ; Tsiropoulos et al. , 2017 ). The common argument is that new generations of farmers are usually more educated and computer skilled, thus more willing to use new technologies. Again, when only considering studies specifically focussed on adoption, age is the most important adoption barrier ( Alvarez and Nuthall, 2006 ; Batte, 2005 ; Engler and Toledo, 2010 ; Lewis, 1998 ; Tiffin and Balcombe, 2011 ). Interestingly, a limited perception of the benefits of these tools is another recurrent barrier. Indeed, as Rosskopf and Wagner (2003 , p. 653) explained that “[...] While the scientists saw the cost of technology and the lack of user friendliness as the main problems, the participants of this study thought that lack of training and failure to understand the possible benefits were the greatest impediments”. In fact, cost is not found to be a recurrent barrier in these studies as opposed to their complexity in terms of the time required to assimilate these technologies ( Alvarez and Nuthall, 2006 ; Mackrell et al. , 2009 ; Pivoto et al. , 2019 ).

No features from the external environment were included amongst the most recurrent barriers. The only barrier which might be considered to belong to this group is infrastructural deficiency, specially the lack of network connectivity.

5. Discussion and conclusions

The aim of this paper was to review the literature on farm-level MIS adoption. Given the fast development of these technologies and our attempt to consider all the possible contributions to the research topic, the study considered different types of ITs used for farm management (both computer- and mobile-based FMIS and integrated farm-level ERP systems) and extended the analysis to studies which do not only focus directly on adoption but also on software architecture design and development.

When it comes to adoption determinants, the results obtained confirm other scholars’ previous findings ( Pierpaoli et al. , 2013 ; Tsiropoulos et al. , 2017 ; Tummers et al. , 2019 ), specifically that technologies’ technical features in fact seem to play an important role in shaping the diffusion of MIS at the farm level. On the one hand, “systemic” technical problems, such as a lack of interoperability amongst devices, a lack of data standards and elevated costs, can limit a given technology’s full potential; on the other hand, another key issue that seems to determine farm-level MIS adoption and the intention to use the latter is users’ individual perceptions (farmers and farm employees) of innovation attributes such as the technology’s relative advantage, usability, complexity and possible customisation. Furthermore, users’ characteristics together with farm features are also important adoption determinants. Age, education level and existing computer skills (users’ characteristics) as well as farm size and initial technology in use (farm features) are the most recurrent factors. When limiting the focus to studies which solely address adoption, the most recurrent determinant factors seem limited to farm size, user age and education and the technology’s perceived relative advantage.

5.1 Research implications

The main practical implications of this study stem from the provision of a comprehensive systematisation of factors which might determine MIS technologies adoption at the farm level. In facts, the inclusion of both conceptual and empirical types of contributions can reasonably show that adoption drivers and barriers might be due not only to users’ characteristics and resources but also to technology features ( Bronson, 2019 ). This is particularly relevant if seen as a cause behind today’s unequal access to technology, i.e. the digital divide ( Bronson, 2019 ; Carolan, 2016 ; van der Burg et al. , 2019 ). In this perspective, our results might be of particular interest and utility for policymakers who might find strategic to acknowledge the relevance at the same time of different types of determinants of adoption, when defining proper policies and when aiming at guaranteeing a fair and inclusive digitalisation of the agri-food sector. Moreover, technology providers and the related smart-farming technologies’ industry are another type of actors who might benefit from a deeper understanding of adoption determinants. It might be easier for them to understand and successfully satisfy the requirements their customers demand.

For what concerns the theoretical implications, this study deals not only with adoption determinants but it also provides a classification of studies in terms of research focus, methods and theoretical frameworks used. Studies which focus specifically on adoption are mainly quantitative in nature (see Table 3 ). Looking at the evolution of these studies over time, it seems that, until 2019, scholars focussed their attention predominantly on software design and development rather than on their adoption, though adoption analyses have grown in number due to the increasing attention paid to the whole group of smart-farming technologies ( Kernecker et al. , 2019 ; Knierim et al. , 2019 ; Pivoto et al. , 2019 ). When the theories used to investigate the adoption are analysed, results indicate that some scholars have used different conceptual frameworks such as DOI and TOE together to capture all the relevant factors (individual and organisational) which might drive MIS adoption and implementation ( Alvarez and Nuthall, 2006 ; Haberli et al. , 2017 , 2019 ; Lewis, 1998 ; Mackrell et al. , 2009 ). However, the majority of relevant factors identified in the literature so far seem to be limited to the individual action sphere. Accordingly, in the studies considered in the literature review, farmers (and, at times, both farm managers and farm employees) are generally considered the key decision-makers.

Nonetheless, in Tummers et al. 's (2019) recent review of FMIS literature, a wider scope of stakeholders is considered in the implementation and use of modern FMISs in the agri-food sector, as occurred in prior studies ( Barmpounakis et al. , 2015 ; Kaloxylos et al. , 2012 ). Moreover, in their review on big data and smart-farming technologies, Wolfert et al. referred to a new possible network of stakeholders built around farms which might produce a major shift in roles and power relations amongst different players in existing agri-food chains: “We observed the changing roles of old and new software suppliers in relation to Big Data and farming and emerging landscape of data-driven initiatives with prominent role of big tech and data companies like Google and IBM’’ ( Wolfert et al. , 2017 , p. 75). This suggests that not only actors but also factors beyond farms’ or farmers’ individual circumstances might play an even more relevant role in determining MIS diffusion and adoption.

In fact, main theoretical implications deriving from the recent literature on farm-level MIS adoption indicate that the main adoption determinants identified so far in the literature reside mainly within the boundaries of the farm, in adopter units' characteristics (farmers and farms) and the technology features themselves. This study confirms that this last factor is relevant when the analysis is extended to contributions which do not focus solely on adoption.

5.2 Limitations and implications for future research

The main limitations of the study relate to the literature review approach adopted. Although the authors followed a clear structure as found in many other contributions, the review remains non-systematic; thus, it poses some limits to the replicability of the results. To reduce potential biases, the authors made any effort to clearly explicit each stage of the review process as well as any reference to how the review has been structured. Furthermore, although the authors clearly defined the technologies to be considered within the review, technological development in digital agriculture is so quick that MISs might considerably change their characteristics and as a consequence, some of their adoption determinants.

Nonetheless, the study achieved manifold and insightful results in respect to methods and theories used in recent literature. Moreover, the determinants of adoption identified so far have been classified and broadly discussed. In this respect, especially when MIS technologies are considered part of smart-farming technologies with their related ecosystems and new stakeholder networks, several interesting avenue for future research can be identified. On the one hand, an interesting research direction in studying adoption determinants would be to extend the focus to the role of additional factors beyond individual dimension ( Klerkx et al. , 2019 ). In this regard, actors and organisational factors relative to the supply chain where farmers and farms carry out their activities might play an important explanatory role in unravelling the adoption and diffusion in the entire agri-food sector’s digitalisation.

Another aspect which might deserve attention, as some scholars have recently pointed out, is the role played by dynamic capabilities in the digital transformation of mature industries ( Warner and Wäger, 2019 ). Dynamic capabilities are defined as “the firm’s ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments” ( Teece et al. , 2008 , p. 516). Some authors explored how these might impact business model innovation (e.g. in scouting new digital technologies or developing collaborative approaches within the innovation ecosystem) and thus enable digital transformation of the industry. Although the agricultural industry has shown traditionally poor propensity to innovate, especially in the case of small and medium farms, how the development of dynamic capabilities together with digital innovation adoption might lead to business model innovations in the agri-food sector is a topic that deserves to be further explored.

Flow diagram of the review process

Time distribution of studies

Second-step selection criteria

Thetype of research (qualitative or quantitative) by research focus

Studies focussed on adoption

https://cordis.europa.eu/project/rcn/88262/reporting/en , https://www.fispace.eu/ , http://smartagrifood.eu/ .

It should be noted that, in some cases, quantitative methods (such as multivariate data analyses or econometric models) were preceded by qualitative methods such as interviews or focus groups ( Haberli et al. , 2019 ).

Allen , J. and Wolfert , S. ( 2011 ), Farming for the Future towards Better Information-Based Decision-Making and Communication Phase I: Australasian Stocktake of Farm Management Tools Used by Farmers and Rural Professionals , New Zealand Centre of Excellence in Farm Business Management , Wageningen , available at: https://edepot.wur.nl/194811 .

Alvarez , J. and Nuthall , P. ( 2006 ), “ Adoption of computer based information systems: the case of dairy farmers in Canterbury, NZ, and Florida, Uruguay ”, Computers and Electronics in Agriculture , Vol. 50 , pp. 48 - 60 , doi: 10.1016/j.compag.2005.08.013 .

Barmpounakis , S. , Kaloxylos , A. , Groumas , A. , Katsikas , L. , Sarris , V. , Dimtsa , K. , Fournier , F. , Antoniou , E. , Alonistioti , N. and Wolfert , S. ( 2015 ), “ Management and control applications in agriculture domain via a future internet business-to-business platform ”, Information Processing in Agriculture , Vol. 2 , pp. 51 - 63 , doi: 10.1016/j.inpa.2015.04.002 .

Batte , M.T. ( 2005 ), “ Changing computer use in agriculture: evidence from Ohio ”, Computers and Electronics in Agriculture , Vol. 47 No. 1 , pp. 1 - 13 , doi: 10.1016/j.compag.2004.08.002 .

Bevan , N. and Carter , J. ( 2016 ), “ Human-computer interaction–theory, design, development and practice ”, International Conference on Human-Computer Interaction , Springer , Cham , Vol. 9731 , pp. 268 - 278 , doi: 10.1007/978-3-319-39510-4 .

Boehm , M. and Thomas , O. ( 2013 ), “ Looking beyond the rim of one’s teacup: a multidisciplinary literature review of product-service systems in information systems, business management, and engineering and design ”, Journal of Cleaner Production , Vol. 51 , pp. 245 - 260 , doi: 10.1016/j.jclepro.2013.01.019 .

Bouwman , H. , Nikou , S. , Molina-Castillo , F.J. and de Reuver , M. ( 2018 ), “ The impact of digitalization on business models ”, Digital Policy, Regulator Government , Vol. 20 No. 2 , pp. 105 - 124 , doi: 10.1108/DPRG-07-2017-0039 .

Bronson , K. ( 2019 ), “ Looking through a responsible innovation lens at uneven engagements with digital farming ”, NJAS - Wageningen Journal of Life Sciences , Vols 90–91 , 100294 , doi: 10.1016/j.njas.2019.03.001 .

Bronson , K. and Knezevic , I. ( 2016 ), “ Big data in food and agriculture ”, Big Data Society , Vol. 3 , pp. 1 - 5 , doi: 10.1177/2053951716648174 .

Bucci , G. , Bentivoglio , D. and Finco , A. ( 2018 ), “ Precision agriculture as a driver for sustainable farming systems: state of art in litterature and research ”, Quality - Access to Success , Vol. 19 , pp. 114 - 121 .

Capitanio , F. , Coppola , A. and Pascucci , S. ( 2009 ), “ Indications for drivers of innovation in the food sector ”, British Food Journal , Vol. 111 , pp. 820 - 838 , doi: 10.1108/00070700910980946 .

Carli , G. and Canavari , M. ( 2013 ), “ Introducing direct costing and activity based costing in a farm management system: a conceptual model ”, Procedia Technology , Elsevier BV , Vol. 8 , pp. 397 - 405 .

Carolan , M. ( 2016 ), “ The politics of big data food governance meets ‘weak’ resistance ”, Agri-Environmental Governance as an Assemblage: Multiplicity, Power, and Transformation , pp. 195 - 212 .

Carrer , M.J. , de Souza Filho , H.M. and Batalha , M.O. ( 2017 ), “ Factors influencing the adoption of farm management information systems (FMIS) by Brazilian citrus farmers ”, Computers and Electronics in Agriculture , Vol. 138 , pp. 11 - 19 , doi: 10.1016/j.compag.2017.04.004 .

Cronin , P. , Ryan , F. and Coughlan , M. ( 2008 ), “ Undertaking a literature review: a step-by-step approach ”, British Journal of Nursing , Vol. 17 , pp. 38 - 43 , doi: 10.12968/bjon.2008.17.1.28059 .

Della Corte , V. , Del Gaudio , G. and Sepe , F. ( 2018 ), “ Ethical food and the kosher certification: a literature review ”, British Food Journal , Vol. 120 , pp. 2270 - 2288 , doi: 10.1108/BFJ-09-2017-0538 .

De Pietro , R. , Wiarda , E. and Fleischer , M. ( 1990 ), “ The context for change: organization, technology and environment ”, in Tornatzky , L.G. and Fleischer , M. (Eds), The Processes of Technological Innovation , Lexington , pp. 151 - 175 .

Dicecca , R. , Pascucci , S. and Contò , F. ( 2016 ), “ Understanding reconfiguration pathways of agri-food value chains for smallholder farmers ”, British Food Journal , Vol. 118 , pp. 1857 - 1882 , doi: 10.1108/BFJ-05-2016-0194 .

Engler , A. and Toledo , R. ( 2010 ), “ An analysis of factors affecting the adoption of economic and productive data recording methods of Chilean farmers ”, Ciencia e Investigacian Agraria , Vol. 37 , pp. 101 - 109 .

Fabregas , R. , Kremer , M. and Schilbach , F. ( 2019 ), “ Realizing the potential of digital development: the case of agricultural advice ”, Science , Vol. 366 , doi: 10.1126/science.aay3038 .

Finfgeld-Connett , D. ( 2014 ), “ Use of content analysis to conduct knowledge-building and theory-generating qualitative systematic reviews ”, Qualitative Research , Vol. 14 , pp. 341 - 352 , doi: 10.1177/1468794113481790 .

FoodDrinkEurope ( 2016 ), A Competitive EU Food and Drink Industry for Growth and Jobs , Bruxelles , available at: http://www.fooddrinkeurope.eu/uploads/publications_documents/Competitive_food_industry_growth_jobs_report.pdf .

Fountas , S. , Kyhn , M. , Jakobsen , H.L. , Wulfsohn , D. , Blackmore , S. and Griepentrog , H.W. ( 2009 ), “ A systems analysis of information system requirements for an experimental farm ”, Precision Agriculture , Vol. 10 , pp. 247 - 261 , doi: 10.1007/s11119-008-9098-5 .

Fountas , S. , Carli , G. , Sørensen , C.G. , Tsiropoulos , Z. , Cavalaris , C. , Vatsanidou , A. , Liakos , B. , Canavari , M. , Wiebensohn , J. and Tisserye , B. ( 2015a ), “ Farm management information systems: current situation and future perspectives ”, Computers and Electronics in Agriculture , Vol. 115 , pp. 40 - 50 , doi: 10.1016/j.compag.2015.05.011 .

Fountas , S. , Sorensen , C.G. , Tsiropoulos , Z. , Cavalaris , C. , Liakos , V. and Gemtos , T. ( 2015b ), “ Farm machinery management information system ”, Computers and Electronics in Agriculture , Vol. 110 , pp. 131 - 138 , doi: 10.1016/j.compag.2014.11.011 .

Fox , G. , Mooney , J. , Rosati , P. , Paulsson , V. and Lynn , T. ( 2018 ), “ Towards an understanding of farmers’ mobile technology adoption: a comparison of adoption and continuance intentions ”, Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018 , New Orleans, LA , available at: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054202435&partnerID=40&md5=d8d90a9ef7aa68f4be54bd5107c33db5 .

Giacomarra , M. , Galati , A. , Crescimanno , M. and Vrontis , D. ( 2020 ), “ Geographical cues: evidences from new and old world countries’ wine consumers ”, British Food Journal , Vol. 122 No. 4 , pp. 1252 - 1267 , doi: 10.1108/BFJ-08-2019-0580 .

Haan , M.M. , Van Gurp , J.L.P. , Naber , S.M. and Groenewoud , A.S. ( 2018 ), “ Impact of moral case deliberation in healthcare settings: a literature review ”, BMC Medical Ethics , Vol. 19 , pp. 1 - 15 , doi: 10.1186/s12910-018-0325-y .

Haberli , C. , Oliveira , T. and Yanaze , M. ( 2017 ), “ Understanding the determinants of adoption of enterprise resource planning (ERP) technology within the agrifood context: the case of the Midwest of Brazil ”, The International Food and Agribusiness Management Review , Vol. 20 , pp. 729 - 746 , doi: 10.22434/IFAMR2016.0093 .

Haberli , C.J. , Oliveira , T. and Yanaze , M. ( 2019 ), “ The adoption stages (evaluation, adoption, and routinisation) of ERP systems with business analytics functionality in the context of farms ”, Computers and Electronics in Agriculture , Vol. 156 , pp. 334 - 348 , doi: 10.1016/j.compag.2018.11.028 .

Hart , C. ( 1998 ), Doing a Literature Review: Realeasing the Social Science Research Immagination , SAGE Publications , London .

Hossain , M. ( 2016 ), “ Grassroots innovation: a systematic review of two decades of research ”, Journal of Cleaner Production , Vol. 137 , pp. 973 - 981 , doi: 10.1016/j.jclepro.2016.07.140 .

Hossain , M. , Leminen , S. and Westerlund , M. ( 2019 ), “ A systematic review of living lab literature ”, Journal of Cleaner Production , Vol. 213 , pp. 976 - 988 , doi: 10.1016/j.jclepro.2018.12.257 .

Husemann , C. and Novkovic , N. ( 2014 ), “ Farm management information systems: a case study on a German multifunctional farm ”, Ekonomika Poljoprivrede , Centre for Evaluation in Education and Science (CEON/CEES) , Vol. 61 No. 2 , pp. 441 - 453 .

Ibrahim , A.M. , Hassan , M.S. and Gusau , A.L. ( 2018 ), “ Factors influencing acceptance and use of ICT innovations by agribusinesses ”, Journal of Global Information Management , Vol. 26 , pp. 113 - 134 , doi: 10.4018/jgim.2018100107 .

Jacobs , R.F. and Weston , T.F.C. ( 2007 ), “ Enterprise resource planning (ERP)-A brief history ”, Journal of Operations Management , Vol. 25 , pp. 357 - 363 , doi: 10.1016/j.jom.2006.11.005 .

Kaloxylos , A. , Eigenmann , R. , Teye , F. , Politopoulou , Z. , Wolfert , S. , Shrank , C. , Dillinger , M. , Lampropoulou , I. , Antoniou , E. , Pesonen , L. , Nicole , H. , Thomas , F. , Alonistioti , N. and Kormentzas , G. ( 2012 ), “ Farm management systems and the future internet era ”, Computers and Electronics in Agriculture , Vol. 89 , pp. 130 - 144 , doi: 10.1016/j.compag.2012.09.002 .

Kaloxylos , A. , Groumas , A. , Sarris , V. , Katsikas , L. , Magdalinos , P. , Antoniou , E. , Politopoulou , Z. , Wolfert , S. , Brewster , C. , Eigenmann , R. and Maestre Terol , C. ( 2014 ), “ A cloud-based farm management system: architecture and implementation ”, Computers and Electronics in Agriculture , Vol. 100 , pp. 168 - 179 , doi: 10.1016/j.compag.2013.11.014 .

Kernecker , M. , Knierim , A. , Wurbs , A. , Kraus , T. and Borges , F. ( 2019 ), “ Experience versus expectation: farmers’ perceptions of smart farming technologies for cropping systems across Europe ”, Precision Agriculture . doi: 10.1007/s11119-019-09651-z .

Klerkx , L. , Jakku , E. and Labarthe , P. ( 2019 ), “ A review of social science on digital agriculture, smart farming and agriculture 4.0: new contributions and a future research agenda ”, NJAS - Wageningen Journal of Life Sciences , Vols 90-91 , 100315 , doi: 10.1016/j.njas.2019.100315 .

Knierim , A. , Kernecker , M. , Erdle , K. , Kraus , T. , Borges , F. and Wurbs , A. ( 2019 ), “ Smart farming technology innovations – insights and reflections from the German smart-AKIS hub ”, NJAS - Wageningen Journal of Life Sciences , Vols 90-91 , 100314 , doi: 10.1016/j.njas.2019.100314 .

Kruize , J.W. , Wolfert , J. , Scholten , H. , Verdouw , C.N. , Kassahun , A. and Beulens , A.J.M. ( 2016 ), “ A reference architecture for farm software ecosystems ”, Computers and Electronics in Agriculture , Vol. 125 , pp. 12 - 28 , doi: 10.1016/j.compag.2016.04.011 .

Kuhlmann , F. and Brodersen , C. ( 2001 ), “ Information technology and farm management: developments and perspectives ”, Computers and Electronics in Agriculture , Vol. 30 , pp. 71 - 83 , doi: 10.1016/S0168-1699(00)00157-5 .

Lawson , L.G. , Pedersen , S.M. , Sørensen , C.G. , Pesonen , L. , Fountas , S. , Werner , A. , Oudshoorn , F.W. , Herold , L. , Chatzinikos , T. , Kirketerp , I.M. and Blackmore , S. ( 2011 ), “ A four nation survey of farm information management and advanced farming systems: a descriptive analysis of survey responses ”, Computers and Electronics in Agriculture , Vol. 77 , pp. 7 - 20 , doi: 10.1016/j.compag.2011.03.002 .

Lehmann , R.J. , Reiche , R. and Schiefer , G. ( 2012 ), “ Future internet and the agri-food sector: state-of-the-art in literature and research ”, Computers and Electronics in Agriculture , Vol. 89 , pp. 158 - 174 , doi: 10.1016/j.compag.2012.09.005 .

Leonidou , E. , Christofi , M. , Vrontis , D. and Thrassou , A. ( 2018 ), “ An integrative framework of stakeholder engagement for innovation management and entrepreneurship development ”, Journal of Business Research , Elsevier , pp. 1 - 14 , doi: 10.1016/j.jbusres.2018.11.054 , in press .

Lewis , T. ( 1998 ), “ Evolution of farm management information systems ”, Computers and Electronics in Agriculture , Vol. 19 , pp. 233 - 248 , doi: 10.1016/S0168-1699(97)00040-9 .

Long , T.B. , Blok , V. and Coninx , I. ( 2016 ), “ Barriers to the adoption and diffusion of technological innovations for climate-smart agriculture in Europe: evidence from The Netherlands, France, Switzerland and Italy ”, Journal of Cleaner Production , Vol. 112 , pp. 9 - 21 , doi: 10.1016/j.jclepro.2015.06.044 .

Mackrell , D. , Kerr , D. and von Hellens , L. ( 2009 ), “ A qualitative case study of the adoption and use of an agricultural decision support system in the Australian cotton industry: the socio-technical view ”, Decision Support Systems , Vol. 47 , pp. 143 - 153 , doi: 10.1016/j.dss.2009.02.004 .

Materia , V.C. , Pascucci , S. and Dries , L. ( 2017 ), “ Are in-house and outsourcing innovation strategies correlated? Evidence from the European agri-food sector ”, Journal of Agricultural Economics , Vol. 68 No. 1 , pp. 249 - 268 , doi: 10.1111/1477-9552.12206 .

Molinillo , S. and Japutra , A. ( 2017 ), “ Organizational adoption of digital information and technology: a theoretical review ”, Bottom Line , Vol. 30 , pp. 33 - 46 , doi: 10.1108/BL-01-2017-0002 .

Møller , C. ( 2005 ), “ ERP II: a conceptual framework for next-generation enterprise systems? ”, Journal of Enterprise Information Management , Vol. 18 , pp. 483 - 497 , doi: 10.1108/17410390510609626 .

Nikkilä , R. , Seilonen , I. and Koskinen , K. ( 2010 ), “ Software architecture for farm management information systems in precision agriculture ”, Computers and Electronics in Agriculture , Vol. 70 , pp. 328 - 336 , doi: 10.1016/j.compag.2009.08.013 .

Nurkka , P. , Norros , L. and Pesonen , L. ( 2007 ), Improving Usability and User Acceptance of Information Systems in Farming , EFITA 2007 Proceeding , Glas , p. 6 .

Oliveira , T. and Martins , M.F. ( 2011 ), “ Literature review of information technology adoption models at firm level ”, Electronic Journal of Information Systems Evaluation , Vol. 14 , pp. 110 - 121 .

Pierpaoli , E. , Carli , G. , Pignatti , E. and Canavari , M. ( 2013 ), “ Drivers of precision agriculture technologies adoption: a literature review ”, Procedia Technol , Vol. 8 , pp. 61 - 69 , doi: 10.1016/j.protcy.2013.11.010 .

Pignatti , E. , Carli , G. and Canavari , M. ( 2015 ), “ What really matters? A qualitative analysis on the adoption of innovations in agriculture ”, Journal of Agricultural Informatics , Vol. 6 , doi: 10.17700/jai.2015.6.4.212 .

Pivoto , D. , Barham , B. , Waquil , P.D. , Foguesatto , C.R. , Corte , V.F.D. , Zhang , D. and Talamini , E. ( 2019 ), “ Factors influencing the adoption of smart farming by Brazilian grain farmers ”, The International Food and Agribusiness Management Review , Vol. 22 , pp. 571 - 588 , doi: 10.22434/ifamr2018.0086 .

Poppe , K. and Renwick , A. ( 2015 ), “ A European perspective on the economics of big data dairy farm systems for the future view project ”, Farm Policy Journal , Vol. 12 No. 1 , pp. 11 - 19 .

Radu , L.D. ( 2016 ), “ Determinants of green ICT adoption in organizations: a theoretical perspective ”, Sustainable Times , Vol. 8 , doi: 10.3390/su8080731 .

Rogers , E.M. ( 1982 ), Diffusion of Innovations , The Free Press , New York, NY , doi: 10.4324/9780203710753-35 .

Rogers , E.M. ( 1995 ), “ Lessons for guidelines from the diffusion of innovations ”, Joint Commission Journal on Quality Improvement , Vol. 21 , pp. 324 - 328 , doi: 10.1016/S1070-3241(16)30155-9 .

Rogers , E.M. ( 2003 ), “ Diffusion of innovations ”, Diffusion of Innovations , Free Press , New York, NY , pp. 118 - 125 .

Rosskopf , K. and Wagner , P. ( 2003 ), “ Requirement for agricultural software - results of empirical studies ”, European Federation for Information Technologies in Agriculture (EFITA) , Debrecen , pp. 651 - 657 .

Sopegno , A. , Calvo , A. , Berruto , R. , Busato , P. and Bocthis , D. ( 2016 ), “ A web mobile application for agricultural machinery cost analysis ”, Computers and Electronics in Agriculture , Vol. 130 , pp. 158 - 168 .

Sørensen , C.G. , Fountas , S. , Nash , E. , Pesonen , L. , Bochtis , D. , Pedersen , S.M. , Basso , B. , Blackmore , S.B. , Sorensen , C.G. , Fountas , S. , Nash , E. , Pesonen , L. , Bochtis , D. , Pedersen , S.M. , Basso , B. and Blackmore , S.B. ( 2010 ), “ Conceptual model of a future farm management information system ”, Computers and Electronics in Agriculture , Vol. 72 , pp. 37 - 47 , doi: 10.1016/j.compag.2010.02.003 .

Sorensen , C.G. , Pesonen , L. , Fountas , S. , Suomi , P. , Bochtis , D. , Bildsøe , P. and Pedersen , S.M. ( 2010 ), “ A user-centric approach for information modelling in arable farming ”, Computers and Electronics in Agriculture , Vol. 73 , pp. 44 - 55 , doi: 10.1016/j.compag.2010.04.003 .

Sørensen , C.G. , Pesonen , L. , Bochtis , D.D. , Vougioukas , S.G. and Suomi , P. ( 2011 ), “ Functional requirements for a future farm management information system ”, Computers and Electronics in Agriculture , Vol. 76 , pp. 266 - 276 , doi: 10.1016/j.compag.2011.02.005 .

Steffe , J. ( 2000 ), “ Evolution of the farm environment: the need to produce a general information system ”, PACIOLI 7 Agenda 2000 and the FADN Agenda Workshop Report .

Svejvig , P. and Andersen , P. ( 2015 ), “ Rethinking project management: a structured literature review with a critical look at the brave new world ”, International Journal of Project Management , Vol. 33 , pp. 278 - 290 , doi: 10.1016/j.ijproman.2014.06.004 .

Teece , D.J. , Pisano , G. and Shuen , A. ( 2008 ), “ Dynamic capabilities and strategic management ”, Technological Know-How, Organ Capabilities Strategic Management Business Strategy Enterprise Development Competitive Environment , Vol. 18 , pp. 27 - 52 , doi: 10.1142/9789812834478_0002 .

Tell , J. , Hoveskog , M. , Ulvenblad , P. , Ulvenblad , P.O. , Barth , H. and Ståhl , J. ( 2016 ), “ Business model innovation in the agri-food sector: a literature review ”, British Food Journal , Vol. 118 , pp. 1462 - 1476 , doi: 10.1108/BFJ-08-2015-0293 .

Tiffin , R. and Balcombe , K. ( 2011 ), “ The determinants of technology adoption by UK farmers using Bayesian model averaging: the cases of organic production and computer usage ”, The Australian Journal of Agricultural and Resource Economics , Vol. 55 , pp. 579 - 598 , doi: 10.1111/j.1467-8489.2011.00549.x .

Torraco , R.J. ( 2005 ), “ Writing integrative literature reviews: guidelines and examples ”, Human Resource Development Review , Vol. 4 , pp. 356 - 367 , doi: 10.1177/1534484305278283 .

Trendov , M.N. , Varas , S. and Zeng , M. ( 2019 ), Digital Technologies in Agriculture and Rural Areas – Status Report , FAO , Rome .

Tsiropoulos , Z. , Carli , G. , Pignatti , E. and Fountas , S. ( 2017 ), “ Future perspectives of farm management information systems ”, in Pedersen , S.M. and Lind , K.M. (Eds), Precision Agriculture: Technology and Economic Perspectives , Springer International Publishing , Cham , pp. 181 - 200 , doi: 10.1007/978-3-319-68715-5_9 .

Tummers , J. , Kassahun , A. and Tekinerdogan , B. ( 2019 ), “ Obstacles and features of farm management information systems: a systematic literature review ”, Computers and Electronics in Agriculture , Vol. 157 , pp. 189 - 204 , doi: 10.1016/j.compag.2018.12.044 .

van der Burg , S. , Bogaardt , M.J. and Wolfert , S. ( 2019 ), “ Ethics of smart farming: current questions and directions for responsible innovation towards the future ”, NJAS - Wageningen Journal of Life Sciense , Vols 90-91 , 100289 , doi: 10.1016/j.njas.2019.01.001 .

Verdouw , C.N. , Robbemond , R.M. and Wolfert , J. ( 2015 ), “ ERP in agriculture: lessons learned from the Dutch horticulture ”, Computers and Electronics in Agriculture , Vol. 114 , pp. 125 - 133 , doi: 10.1016/j.compag.2015.04.002 .

Verdouw , C.N. , Wolfert , J. , Beulens , A.J.M. and Rialland , A. ( 2016 ), “ Virtualization of food supply chains with the internet of things ”, Journal of Food Engineering , Vol. 176 , pp. 128 - 136 , doi: 10.1016/j.jfoodeng.2015.11.009 .

Vom Brocke , J. , Simons , A. , Niehaves , B. , Riemer , K. , Plattfaut , R. and Cleven , A. ( 2009 ), “ Reconstructing the giant: on the importance of rigour in documenting the literature search process ”, 17th European Conference on Information Systems, ECIS 2009 , Verona, Italy .

Warner , K.S.R. and Wäger , M. ( 2019 ), “ Building dynamic capabilities for digital transformation: an ongoing process of strategic renewal ”, Long Range Planning , Vol. 52 , pp. 326 - 349 , doi: 10.1016/j.lrp.2018.12.001 .

Warren , M. ( 2002 ), “ Digital divide and the adoption of information and communication technology in UK ”, International Journal of Information Technology and Management , Vol. 1 , pp. 385 - 405 .

Wolfert , S. , Ge , L. , Verdouw , C. and Bogaardt , M.J. ( 2017 ), “ Big data in smart farming – a review ”, Agricultural Systems , Vol. 153 , pp. 69 - 80 , doi: 10.1016/j.agsy.2017.01.023 .

Zahra and George ( 2002 ), “ Absorptive capacity: a review, reconceptualization, and extension ”, Academy of Management , Vol. 27 , pp. 185 - 203 .

Zheleva , M. , Bogdanov , P. , Zois , D.S. , Xiong , W. , Chandra , R. and Kimball , M. ( 2017 ), “ Smallholder agriculture in the information age: limits and opportunities ”, LIMITS 2017 - Proceeding 2017 Work Computing Within Limits , pp. 59 - 70 , doi: 10.1145/3080556.3080563 .

Acknowledgements

Corrigendum: It has come to our attention that “Management information system adoption at the farm level: evidence from the literature” by Carlo Giua, Valentina Cristiana Materia and Luca Camanzi, published in the British Food Journal , [Vol. ahead-of-print No. ahead-of-print, 10.1108/BFJ-05-2020-0420], contained several mistakes within the author affiliations. This has now been corrected in the online article. The authors sincerely apologise for this.

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Updated On: May 28, 2024

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Top 5 Benefits of Knowledge Management for CX + Case Studies 

Did you know that to automate multiple workflows, companies are using an average of 367 different software? Ironically, instead of helping organizations, these software apps are creating more data silos.   This results in employees spending almost 30% of their workweek solely on searching for information. This is where a knowledge management system (KMS) comes in. A KMS consolidates all organizational information in one place. This reduces information search time, boosts agent productivity & improves CX.  

In this post, we’ll learn more about knowledge management system and the top 5 benefits of using it.   

Table of contents

• What is a knowledge management system? 

Top 5 Benefits of Knowledge Management

• Benefits of Knowledge Management: Case Studies 

What is a knowledge management system? 

A knowledge management system (KMS) is a software that helps you unify your organization’s knowledge under a single roof, creating a single source of truth. With a KMS you can easily create, store, manage, and share information across your organization. 

How to choose a Knowledge Management System in 2024?

Download Checklist

#1 Instantly access the right information 

Customer service agents struggle to perform even basic tasks when they refer to multiple sources of information. Customers’ patience is tested while your agents put them on hold to look for relevant information.  

When your agents can’t find the right information on their own, they ask peers and supervisors for support, which is time-consuming. By the time they find the right solution, customers are already frustrated.  

When information is cluttered, agents also run into the risk of making fatal errors .  

With a knowledge management system, you can bring all the information scattered across PDFs, SharePoint , Jira etc under one roof. With well-organized and categorized information, your agents can access relevant knowledge instantly and help customers with the right solutions.   

Now with the Gen AI led KM tools like Knowmax, your agents can converse with the knowledge base , doing away with the need to remember exact keywords to find information. This boosts agent productivity and customer satisfaction with instant, on-point answers.  

#2 Keep your information fresh and reliable

Agents are bound to make mistakes when they end-up using outdated information, due to the lack of proper version control. A knowledge base system helps you track changes and notify your agents about the latest updates.  

It also gives you actionable insights about your knowledge base health; how agents are engaging with the knowledge, what are the top performing content topics, which content topics are resulting in failed searches.  

These insights help you update your knowledge base content strategically. 

#3 Improve your customer satisfaction  

Dealing with customer queries gets even more stressful for agents, when they need to consume lengthy SOPs or articles under pressure.  

A knowledge management system enables you to simplify knowledge for agents by creating easy-to-understand visual guides, next-best-action workflows, FAQs , etc. 

This guided knowledge would allow agents to identify the root cause of customer queries easily and provide effective solutions quickly.  

Empowering your agents to solve customer queries efficiently will inevitably lead to improving customer satisfaction.  

#4 Collect feedback easily

You never really know how useful your content is and how you can improve it, unless you get user feedback.  

A knowledge management system provides the users an option to rate or comment on your knowledge base content . This allows you to effectively improve your content to better serve your users. 

#5 Reduce agent workload 

A customer-facing knowledge base consisting of support articles, interactive FAQs, videos, and visual guides can help resolve their own queries quickly 

This reduces agent workload and allows them to dedicate their time towards resolving more complex queries. 

Benefits of Knowledge Management: Case Studies 

1. the key to cx transformation for jupiter .

Jupiter is a digital bank, and in 2019 they were struggling to provide exceptional CX due to: 

• Scattered and unorganized SOPs . 
• Longer agent learning curves  
• Outdated and wrong information delivery  

Knowmax helped Jupiter improve its customer experience by creating a single source of truth for their knowledge.  

Uncover the full story here .

2. A unicorn fintech’s journey of seamlessly serving 2 million users

The FinTech Unicorn startup found it hard to provide exceptional customer experience due to – 

• Scattered product and process data, which made it hard to follow SOPs.  
• Knowledge not being actionable, which resulted in delayed and poor customer service.  

Knowmax helped them by providing a single source of truth for all their organisational data, enabling exceptional customer experience, and faster agent onboarding.  

Here’s what they say:  “We have achieved a 12% increase in FCR and 10% reduction in AHT. We’re now providing seamless customer service to over 2 million users. Knowmax has transformed our CX function and helped us increase our C-SAT scores by 28%. We’re lucky to have found a Knowledge Partner that delivered promising results and supported us throughout our Knowledge Management journey.”        Chief Operating Officer.  

Uncover their journey to exceptional CX here .

Looking to supercharge your CX?

Yatharth Jain

Yatharth has over 8 years of experience in CX, KM, and BPM. He founded Knowmax to make knowledge a genuine superpower for CX teams. He blends his experience working with CX and KM leaders across industries with the latest technology trends to build products people love.

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Related posts.

Content Management vs Knowledge Management: Which is better?  

Top 7 AI Knowledge Management Tools for 2024 

20 Ways to Improve Call Center Customer Service

5 Types of Knowledge Management | Explicit, Declarative, Implicit, Tacit & Procedural

Retail Knowledge Management: Boost CX with AI Solutions

Top 10 Knowledge Management Features to Elevate Your CX Game in 2024 

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Integrated hydrological and hydraulic modeling for predicting sediment transport in hydraulic road structure design: the case of oued ait ourir, high atlas, Morocco

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• Oumayma Nassiri 2  

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The design and sizing of hydraulic road structures, such as bridges and trestle bridges, situated in wadis characterized by high sediment transport rates necessitate a systematic consideration of sediment transport in conjunction with fluid flow dynamics. In our investigation, we employ a sophisticated modeling approach to forecast sediment transport fluxes and deposition heights upstream of the RP 2009 structure along the Ait Ourir River, located within the "Ghdat" wadi watershed in the High Atlas region of Morocco, for a 100-year return period. Despite its recent construction in 2020, the existing structure is already susceptible to clogging following liquid flood events. Our modeling framework comprises a primary "sediment transport modeling" model incorporating 12 semi-empirical formulas, encompassing "local" and "global" sediment transport equations, renowned for their widespread utilization and recognition worldwide. Additionally, auxiliary models and tools, including ArcGIS modeling, HECHMS software, HECRAS hydraulic simulation, and granulometric curve analysis, are employed to calibrate the main model parameters, ensuring precise results. Furthermore, we adopt a confrontational approach with available field data to validate our model outcomes. Our analysis reveals a wide spectrum of specific solid flow values ranging from 0.001 m 3 /s/m (Einstein) to 2.667 m 3 /s/m (Schoklitsch). Notably, formulas such as Meyer Peter and Müller, Watanabe, Smart and Jaeggi, Ribberink, Camenen, and Larson, and Parker yield congruent results averaging 0.0028 m 3 /s/m, with centennial deposit heights akin to experimental measurements (2 m). These results predominantly conform to a dimensionless bedding mode represented by \({a\times \left( \theta -\theta cr\right)}^{b}\) , characterized by empirical coefficients a and b. Furthermore, our findings suggest the potential extension of these models to river torrential floods (Froude number > 1) with a slope I = 2.6% and d50 = 13.3 mm, indicating broader applicability to sites within the Moroccan High Atlas exhibiting similar hydrological characteristics. While our study underscores the limitations of "global" formulas, it accentuates the significant role of solid transport (bedloading), despite the lack of field data and measurements.

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Sediment Yield in Mountain Basins, Analysis, and Management: The SMART-SED Project

Assessing the nature of sediment transport with bridge scour by 1D sediment transport model in the sub-catchment basin of Bhagirathi–Hooghly river

The Impact of Deflectors on Sediment Transport Processes on the Basis of Modelling and Simulations

Benselama O, Hasbaia M, Djoukbala O, Boutaghane H, Ferhati A, Djerbouai S (2022) Suspended sedimentary dynamics under Mediterranean semi-arid environment of Wadi El Maleh watershed. Algeria Modeling Earth Syst Environ 8(1):1013–1023

Article   Google Scholar  

Camenen B, Larson M (2008) A general formula for noncohesive suspended sediment transport. J Coast Res 24(3):615–627. https://doi.org/10.2112/06-0694.1

Camenen B and Melun G (2021) Guide technique pour la mesure et la modélisation du transport solide. Office français de la Biodiversité

Chow VT, Maidment DR, Mays LW (1988) Applied Hydrology. MacGraw-Hill

Couvert B, Lefebvre B, Lefort Ph, Morin E (1991) Etude générale sur les seuils de correction torrentielle et les plages de dépôts. La Houille Blanche 46(6):449–456. https://doi.org/10.1051/lhb/1991043

Degoutte G (2001) Hydraulique et dynamique fluviale. ENGREFF. Cours Du DEA Hydrologie, Hydrogéologie, Géostatistique et Géochimie (Univ. Pierre et Marie Curie, Ecole Des Mines de Paris, ENGREF, Univ. Paris Sud)

Dias R, Hadani M, Machado IL, Adnane N, Hendaq Y, Madih K, Matos C (2011) Variscan structural evolution of the western High Atlas and the Haouz plain (Morocco). J Afr Earth Sc 61(4):331–342

Einstein HA (1950) The bed-load function for sediment transportation in open channel flows. US Department of Agriculture, Technical Bulletin, No. 1026

Ellero A, Ottria G, Malusà MG and Ouanaimi H (2012) New constraints on the geological evolution of the High-Atlas (Morocco): insights from the Siroua window. Geol Soc Am Bull 124(9-10):1401–1420.  https://doi.org/10.1130/B30592.1

Engelund F and Hansen E (1967) A monograph on sediment transport in alluvial streams. Technical University of Denmark 0stervoldgade 10, Copenhagen K

Fourar FZ, Fourar A, Khanfouf O, Khelladi S, Massouh F, Zeroual A (2023) Numerical modeling of hydrodynamics and sediment transport in open channel flows using finite volume method. J Hydrol 620:129432.  https://doi.org/10.1016/j.jhydrol.2023.129432

Ghosh A, Roy MB, Roy PK, Mukherjee S (2021) Assessment of sediment transport and channel morphodynamics in river systems: a case study of the Ganga River, India. Geomorphology 380:107611.  https://doi.org/10.1016/j.geomorph.2021.107611

Lefort P (1991) Fundamentals of hydraulic engineering. Prentice Hall

Marchane A, Tramblay Y, Hanich L, Ruelland D, Jarlan L (2017) Climate change impacts on surface water resources in the Rheraya catchment (High Atlas, Morocco). Hydrol Sci J 62(6):979–995

Meyer-Peter E and Müller R (1948) Formulas for bed-load transport. IAHSR 2nd Meeting, Stockholm, Appendix 2

Parker G, Klingeman PC (1982) On why gravel bed streams are paved. Water Resour Res 18(5):1409–1423.  https://doi.org/10.1029/WR018i005p01409

Recking A, Liébault F, Peteuil C and Jolimet T (2010) Evaluation des formules de transport solide en rivière avec prise en compte de l’échelle temporelle. CEMAGREF, Grenoble

Ribberink JS (1998) Bed-load transport for steady flows and unsteady oscillatory flows. Coast Eng 34(1–2):59–82.  https://doi.org/10.1016/S0378-3839(98)00018-7

Rickenmann D (1991) Hyperconcentrated flow and sediment transport at steep slopes. J Hydraul Eng 117(11):1419–1439

Van Rijn LC (1984) Sediment transport. Part I: bed load transport. J Hydraul Eng 110(10):1431–1456.  https://doi.org/10.1061/(ASCE)0733-9429(1984)110:10(1431)

Rouse H, Koloseus HJ, Davidian J (1963) The role of the Froude number in open-channel resistance. J Hydraul Res 1(1):14–19

Sabokruhie P, Akomeah E, Rosner T, Lindenschmidt KE (2021) Proof-of-concept of a quasi-2d water-quality modelling approach to simulate transverse mixing in rivers. Water 13(21):3071

Schoklitsch A (1962) Hydraulics of sediment transport. American Society of Civil Engineers

Sequeiros OE (2012) Estimating turbidity current conditions from channel morphology: A Froude number approach. J Geophys Res Oceans. 117(C4)

Shields, A. (1936). Application of similarity principles and turbulence research to bed-load movement.

Smart GM, Jaeggi MNR (1983) Sediment transport on steep slopes. Mitteilungen Der Versuchsanstalt Für Wasserbau, Hydrologie Und Glaziologie an der ETH Zürich, No. 64

Sogreah G (1991) Hydraulic and sediment transport modeling. Sogreah Consultants Report

Valembois J (1960) Etude sur modele du transport littoral conditions de similitude. Coastal Eng Proc 7:18

Watanabe A (1982) A fundamental study on coastal sediment transport due to waves and currents. Coastal Eng Japan 25(1):19–46.  https://doi.org/10.1080/05785634.1982.11924477

Zerhouni J, Filali FR, Bennani MN, EL Hmaidi A (2019) Utilisation des systemes d’informations geographiques (sig) et interpolation pour la caracterisation de la pollution des eaux souterraines en milieu rural de la ville de sebaa ayoune (bassin de sais, maroc). J Water Environ Sci 3(1):471–484

Google Scholar  

Zkhiri W, Tramblay Y, Hanich L, Berjamy B (2017) Regional flood frequency analysis in the High Atlas mountainous catchments of Morocco. Nat Hazards 86:953–967

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Hafida Messaoudi & Abdessamad Najine

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Key Findings to note:

1. A notable discrepancy was observed in the values obtaine from the 12 sediment transport formulas, with a range of 0.002 m3/s (Rickenmann) to 41.34 m3/s (Schoklitsch).

2. The majority of the formulas that yielded comparable results were of the "local" type. The most validated formulas include Meyer-Peter, Watanabe, Parker, Camenen, and Larson, often expressed in the dimensionless form: a × (θ – θcr) ^b, with a and b as empirical coefficients.

3. Systematic sediment transport analysis is recommended for designing structures in the High Atlas region of Morocco, ensuring improved formula calibration.

4. The substantial 2 m solid deposition height identified in this study should be a pivotal consideration, along with the highest water level PHE (0.64 m), when determining the dimensions of the proposed structure to facilitate centennial flood evacuation without submersion risks.

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Messaoudi, H., Wafik, A., Najine, A. et al. Integrated hydrological and hydraulic modeling for predicting sediment transport in hydraulic road structure design: the case of oued ait ourir, high atlas, Morocco. Model. Earth Syst. Environ. (2024). https://doi.org/10.1007/s40808-024-02045-9

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DOI : https://doi.org/10.1007/s40808-024-02045-9

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Health workers’ adherence to malaria case management protocols in Northern Sudan: a qualitative study

• Sahar Khalid Mohamed 1 , 2 ,
• Duha Khalid Mohamed 1 ,
• Khansaa Ahmed 1 ,
• Fadwa Saad 1 &
• Dejan Zurovac 3  

Malaria Journal volume  23 , Article number:  170 ( 2024 ) Cite this article

Metrics details

Nonadherence to national standards for malaria diagnosis and treatment has been reported in Sudan. In this study, qualitative research examined the clinical domains of nonadherence, factors influencing nonadherent practices and health workers’ views on how to improve adherence.

In September 2023, five Focus Group Discussions (FGDs) were undertaken with 104 health workers from 42 health facilities in Sudan’s Northern State. The participants included medical assistants, doctors, nurses, laboratory personnel, pharmacists and public health officers. The FGDs followed a semi-structured guide reflecting the national malaria case management protocol. Qualitative thematic analysis was performed.

Nonadherent practices included disregarding parasitological test results, suboptimal paediatric artemether–lumefantrine (AL) dosing, lack of counselling, use of prohibited artemether injections for uncomplicated and severe malaria, artesunate dose approximations and suboptimal preparations, lack of AL follow on treatment for severe malaria; and rare use of primaquine for radical Plasmodium vivax treatment and dihydroartemisinin-piperaquine as the second-line treatment for uncomplicated malaria. Factors influencing nonadherence included stock-outs of anti-malarials and RDTs; staff shortages; lack of training, job aids and supervision; malpractice by specialists; distrust of malaria microscopy and RDTs; and patient pressure for diagnosis and treatment. Health workers recommended strengthening the supply chain; hiring personnel; providing in-service protocol training including specialists; establishing external quality assurance for malaria diagnosis; and providing onsite supportive supervision and public health campaigns.

Conclusions

This study revealed a broad spectrum of behavioural and systemic challenges in malaria management among frontline health workers in Northern Sudan, including nonadherence to protocols due to resource shortages, training gaps, a lack of supportive supervision and patient pressure. These insights, including health workers’ views about improvements, will inform evidence-based interventions by Sudan’s National Malaria Control Programme to improve health systems readiness and the quality of malaria case management.

Malaria, a significant public health concern, continues to cast a shadow over Sudan’s healthcare landscape. The malaria burden in Sudan was estimated to be 3.7 million cases, and 1760 deaths accounted for 17.0% of the number of outpatients admitted and 14.7% of the total number of hospital admissions in 2021 [ 1 , 2 ]. Plasmodium falciparum accounts for 87.6%, Plasmodium vivax accounts for 8.1%, and other Plasmodium species account for approximately 4.3% of malaria infections [ 2 ]. The country’s struggle with malaria is further complicated by the COVID-19 pandemic [ 3 ], the persistent spectre of war [ 4 ] and the ensuing internal displacement of populations [ 5 ]. In this fragile environment, effective evidence-based management of malaria cases is paramount, safeguarding the well-being of communities and alleviating the economic burden associated with the disease. Sudan malaria case management standards reflect the WHO 2010 “test and treat” recommendations [ 6 ], and promote a shift from presumptive treatment of fevers to confirmed malaria diagnosis with either malaria microscopy or rapid diagnostic tests (RDT) and targeted treatment with artemisinin-based combination therapy (ACT) with appropriate weight-based dosing, drug dispensing and patient counselling [ 7 ]. Artemether–lumefantrine (AL) and dihydroartemisinin–piperaquine (DHAP) are the recommended first- and second-line artemisinin-based combinations for both P. falciparum and P. vivax uncomplicated malaria, while patients with P. vivax should also receive radical primaquine treatment. Regarding severe malaria management, the 2023 protocols have unambiguously recommended the use of artesunate injections and reserved parenteral quinine only when artesunate is contraindicated or unavailable [ 8 ]. Injectable artemether has been policy discontinued and banned since 2017 due to its prior irrational use [ 7 , 9 ].

Despite evidence-based policies and recommendations, health worker adherence to national guidelines is the key factor determining the real-world cost-effectiveness of the “test and treat” policy for malaria [ 10 ]. Improved adherence to malaria guidelines decreases malaria mortality [ 11 ] and highlights the importance of poor quality of care as a major contributor to mortality in low- and middle-income countries [ 12 ]. The levels, trends and factors of healthcare providers’ adherence to national malaria guidelines have been studied across Africa [ 13 , 14 , 15 , 16 ]. Despite some improvements, adherence was found to be insufficient in many settings [ 17 , 18 , 19 , 20 ] with series of studies evaluating outpatient malaria case management and observing deviations from testing indications [ 21 , 22 ]. Additionally, a tendency to prescribe non-recommended anti-malarials even for confirmed cases [ 23 , 24 ] and provide irrational anti-malarial treatments to patients who test negative for malaria has commonly been reported [ 25 , 26 ]. Furthermore, a number of studies highlighted missed opportunities in delivering timely anti-malarial treatment at healthcare facilities [ 27 , 28 ]. With respect to inpatient management, suboptimal quality-of-care has also been observed. Specifically, low testing rates of febrile patients on admission, persistence of presumptive anti-malarial treatment without testing or despite negative malaria tests, lack of parasitological monitoring, use of non-recommended anti-malarials and incomplete treatments are only few of the clinical deficiencies observed [ 29 , 30 , 31 , 32 , 33 ].

In Sudan, the quality of malaria case management, characterized by health workers’ adherence to national protocols, has been a challenge [ 2 ]. Nonadherence to standards for diagnosing and treating uncomplicated and severe malaria has been reported in different settings [ 9 , 34 , 35 , 36 ]. For instance, despite the availability of test and treat commodities for malaria, a national outpatient survey revealed that 67% of febrile patients tested, 64% of confirmed cases treated with ACT, 17% of test-negative patients treated for malaria, 6% of prescribed ACT patients weighed, 3% promptly administered the first ACT dose and 87%, 61% and 3% of patients, respectively, counselled on dosing, treatment completion and vomiting [ 9 ]. Inpatient management of severe malaria was less commonly evaluated, however a 20-hospital survey in Gezira State suggested that only 54% of severe malaria patients received the correct dose and dosing regimen [ 36 ].

Quantitative research can estimate the magnitude of the problem, but there is a need for qualitative research to understand the subtle factors and provide more nuanced recommendations for policy implementers to improve adherence. In the absence of such data in Sudan, this qualitative study embarks on an exploration of nonadherence among healthcare providers to malaria case management protocols in the Northern State of Sudan. Delving into the intricate web of healthcare practices, this research endeavours to unearth factors undermining adherence, as perceived by the very individuals entrenched in the frontline of healthcare delivery. Furthermore, it seeks to harness their collective wisdom by capturing their recommendations, thereby paving the way towards enhanced adherence.

Study design

This study utilized a qualitative research design with focus group discussions (FGDs) to explore healthcare providers’ adherence to national malaria case management protocols, specifically to identify nonadherent practices, factors influencing such practices, and gather health workers’ views on how to improve adherence to national protocols.

Northern State, one of Sudan’s 18 states, covers 348,765 km, with Dongola as its capital. Comprising seven localities, it is home to an estimated population of 1,511,442 primarily residing in rural areas along the River Nile [ 37 ]. Malaria transmission is hypoendemic, and the Sahara Desert is constrained, with an estimated incidence of 175 cases per 1000 population [ 37 ]. The selection of Northern State for the study area involved the delivery of in-service malaria case management training for health workers, an implementation platform conveniently used for the conduct of FGDs prior to training sessions. The state hosts 314 health facilities and 2345 healthcare providers distributed across various levels of care, including family health units, primary health centres, primary hospitals, and secondary and tertiary facilities [ 38 ]. At primary healthcare (PHC) facilities, RDTs serve as the exclusive diagnostic method, especially at the family health units, where the lower PHC level is operated by medical assistants (clinical practitioners with basic medical training). Health centres, representing the higher PHC levels, provide malaria microscopy services conducted by medical laboratory technologists and outpatient services provided by medical doctors. Malaria microscopy is also available at laboratories in local, general, referral, and teaching hospitals, encompassing secondary and tertiary levels of care, where outpatient and inpatient curative services are overseen by medical doctors [ 39 ]. Malaria services are supervised by the Federal and State Ministries of Health, which also oversee tasks such as updating protocols and providing training on them. The Ministry of Health also ensures the provision of essential supplies, including malaria RDTs and anti-malarial medications, most of which are free of charge. However, malaria microscopy services are still subject to charges. In 2023, a significant increase in population and healthcare providers occurred with the influx of internally displaced people, many of whom were originally from regions with high malaria transmission [ 40 , 41 ].

Study participants

A total of five FGDs were held at Primary Health Care Directorate venues in five out of seven localities within Sudan’s Northern State in September 2023. Healthcare providers from 42 health facilities participated in the FGDs (Fig.  1 ). The participants, who had diverse professional backgrounds, were chosen by the state and locality malaria control programmes to attend orientation training sessions (total of 8 training sessions for 200 health workers) on the updated malaria case management protocol [ 8 ]. The FGDs included all health workers attending an orientation session, and all study participants provided informed consent. The point of saturation through iterative data analysis after each FGD was reached after the completion of five FGD sessions, which included 104 participants in total (Fig.  2 ).

Map of Sudan showing Northern State and participant’s health facilities along the River Nile

Schematic flow of the sampling process

Data collection

At the initiation of the orientation sessions, the collection of demographic data were collected, encompassing participants’ occupations, gender, and workplace locations. FGDs were purposefully directed toward understanding healthcare providers’ adherence to the national case management protocol, unravelling factors influencing nonadherence, and soliciting recommendations to enhance adherence. Each session of these FGDs was conducted in the Arabic language, spanning approximately 2 to 3 h, punctuated with breaks and composed of a total of 104 healthcare providers and 19 to 25 participants at each FGD. The manuscript author (SKM), following semistructured guide tailored to reflect on the study objectives on adherence to malaria case management protocols, factors affecting adherence, and recommendations to improve adherence [ 8 ], moderated the discussions. The guide, with respect to the management of uncomplicated malaria, included inquiries into participants’ knowledge regarding malaria symptoms, diagnostic procedures, first- and second-line treatments, dosage specifics, and patient counselling. Regarding severe malaria management, the guide comprised inquiries on symptoms, signs, laboratory findings, diagnostic criteria, initial management strategies, treatment locations, dosage calculations, drug preparation and administration techniques, treatment duration, discharge protocols, and second-line management. Additional questions delved into the diagnosis and management of malaria in pregnant women. Prior to its use, the guide was pretested with health workers not involved in the study (Additional file 1 ). Finally, participant responses prompted exploration of the underlying causes of nonadherence to the protocols, eliciting valuable suggestions to improve the training at which focus group discussions were conducted and to provide potential improvement recommendations to the Federal Ministry of Health. During the discussions, the moderator preserved neutrality and ensured that all participants felt comfortable and similarly engaged. Simultaneously with discussions, notes were taken in Arabic language, which subsequently underwent dual forward translation by two investigators (SKM and DKM) into English and transcription for comprehensive analysis.

Data analysis

Qualitative thematic analysis was conducted [ 42 ]. It comprised seven sequential stages leveraging transcripts from FGDs and handwritten notes. Initially, all transcripts and notes were collected. Subsequently, the researcher thoroughly reviewed sample files, identifying words, phrases, or sentences pertaining to adherence to malaria diagnosis and treatment protocols. Following this, coding categories were developed using a deductive approach, with the protocol serving as the analytical framework. The fourth stage involved the coding of all files and text. The fifth stage encompassed scrutiny of the consistency in code, subthemes, and theme utilization. The sixth step entailed the interpretation of themes, drawing inferences from observed patterns, relationships, and codes, subthemes, and theme attributes. Finally, the seventh stage encompassed the presentation of findings, complemented by supporting quotes and verbatim quotes. A total of four to five themes was identified answering the research questions on healthcare providers’ adherence, factors and recommendations (Additional file 2 ).

Characteristics of participants

Of 104 participants across five FGDs, most of them were males (68.2%) and most worked at the primary health care facilities (75.5%). The number of participants ranged between FGDs from 19 in Al-Golead to 25 in Dongola locality (Table  1 ). Healthcare providers from various backgrounds participated in the study, most commonly medical assistants (59; 56.7%), followed by doctors (13; 12.5%), public health officers (13; 12.5%), nurses (9; 8.7%), laboratory personnel (7; 6.7%) and pharmacists (3; 2.9%).

Nonadherence to national malaria protocols

Four main themes reflecting health worker clinical practices nonadherent with national malaria case management protocols were identified in the analysis (Table  2 ). These included malaria diagnosis practices based on parasitological tests and clinical practices related to the treatment of uncomplicated malaria, severe malaria and patients harbouring P. vivax and mixed malaria infections.

Nonadherence to malaria diagnosis based on parasitological tests

Universal testing of fevers and targeted anti-malarial treatment is the backbone of malaria case management in Sudan. Healthcare providers reported common ordering of a parasitological test upon suspecting malaria but highlighted distrust in the test results and many reported practicing presumed malaria diagnosis. Specifically, regarding uncomplicated malaria, several health workers reported that patients with negative test results are still diagnosed presumptively and treated for malaria:

“Sometimes the test result comes negative for malaria, I test other causes of fever, and if all of them come negative I presume that patient has malaria” (Medical assistant)

Higher cadres of health workers also reported presumptive treatment practices, as medical officer managing hospital outpatients similarly observed.

“After excluding other causes of fever, even if the parasitological test is negative I treat patients as malaria and prescribe Coartem” (Medical doctor)

Regarding the management of severely ill patients, most health workers did not mention parasitological testing and reported that anti-malarial treatment is the standard management for severe disease, as observed by medical officer working at a secondary hospital.

“Febrile comatose patients are treated with broad spectrum antibiotic, antiviral therapy and anti-malarial treatment usually quinine, this is an umbrella approach commonly used” (Medical doctor)

Nonadherence to uncomplicated malaria treatment

The AL treatment of uncomplicated malaria was highly accepted by health workers, and most participants were knowledgeable about adult doses and schedules, particularly about the importance of the second dose administration 8 h after the first dose and the third dose administered 24 h after the first dose. However, some healthcare providers have shown little knowledge about paediatric dosage schedules potentially resulting in the underdosing and overdosing of malaria patients, as demonstrated by medical assistant practicing at outpatient health centre.

“From five to ten kilograms that is one tab of Coartem, from ten to twenty that is two tabs of Coartem, from twenty to thirty that is three tabs of Coartem” (Medical assistant)

Most health workers during the FGDs acknowledged a lack of AL dispensing and counselling knowledge on the administration of the first dose under observation, AL dosing with a fatty meal, repeating the dose if the patient vomited within 30 min and stressing the point of taking the dose as prescribed. Some, however, highlighted that forgetfulness and unclear counselling responsibilities between different health worker cadres encountering malaria patients within health facilities contribute to poor practices. Hospital doctor and pharmacist echoed these observations.

“I try my best to counsel all the patients but sometimes I forget” (Medical doctor). “Usually we do not counsel patients and we presume that their doctor told them how to take the drug” (Pharmacist)

Oral administration of dihydroartemisinin–piperaquine is the recommended second-line treatment for uncomplicated malaria in Sudan. However, its availability is scarce, dosing knowledge is low and health workers do not prescribe it. A healthcare provider humorously remarked on DHAP:

“DHAP (dihydroartemisinin–piperaquine) is as rare as gold (referring to the literal meaning of Dhap in Arabic), and it is nowhere to be found” (Medical assistant)

In this context, patients considered to have AL treatment failure are often prescribed artesunate injections reserved for severe malaria—the practice justified by the scarcity and unavailability of DHAP in the public and private sectors, as highlighted by the hospital doctor:

“Patients may present with recurrent malaria even after taking Coartem, DHAP is not available, we have no other choice but to prescribe artesunate injections” (Medical doctor)

Finally, despite high acceptance of AL by health workers, healthcare providers at lower levels of care (PHCs and family health units) reported the use of artemether injections as a treatment for uncomplicated malaria upon patient request:

“Sometimes the patient refuse it when I prescribe them tabs and insist that they want the oily injections (known name for artemether injections in Sudan) and I have no other choice but to prescribe it to them” (Medical assistant)

Nonadherence to severe malaria treatment

Health workers reported several treatment practices nonadherent to protocols for the management of severe malaria. Such practices spanned from the selection of non-recommended parenteral anti-malarial treatments to the lack of weight-based dosing; poor parenteral solution preparation, administration and disposal; and compromised completion of follow on ACT treatment after parenteral therapies. Participants acknowledged the frequent use of artemether injections, partly due to the patients’ pressure but also due to a lack of understanding of why artemether was prohibited while remaining available on the market. Most significantly, continued artemether use by consultants and specialists acting as supervisors and role models for front-line clinicians further undermined the treatment policy, as clearly stated by several participants of different cadres:

“I know we should not use artemether injections, but I should do what my boss says” (Medical doctor)

A medical assistant added,

“When a specialist prescribes artemether injections, I find myself wondering, who am I not to do the same?”

Most participants acknowledged not weighing adult patients but uniformly administering a 120 mg dose corresponding to a single vial of artesunate, which in turn, based on artesunate dosing recommendations of 2.4 mg/kg, results in dosing needs for patients weighing 50 kg. A lack of weighing practice in adults was well observed by the hospital doctor:

“Usually we prescribe 120 mg to all adults, we don’t weigh them and calculate the dose accordingly, weight dependant dosage are common in paediatrics but not the common in adults” (Medical doctor)

While weighing was probably more common in children, some healthcare providers acknowledged that the lack of weight-based artesunate dosing may also occur among paediatric patients:

“I usually weigh the child before prescribing any medication not just malaria medications, but sometimes, when the load is heavy in the ER or the clinic I just estimate the child’s weight” (Medical doctor)

Most participants reported uncertainties about how to prepare and administer injectable artesunate, particularly clinicians whose responsibility was related to prescribing artesunate but not to the preparing and administering of parenteral therapy:

“We don’t prepare artesunate since it’s a nurse responsibility, but when we find ourselves in a position to do this, when nurses aren’t available, we check the directions in the box, but we weren’t trained on this before” (Registrar)

Nurses were, however, less comfortable with IM artesunate preparations as well as with determining the number of vials needed for preparation, preparing solutions other than 120 mg for adults and disposing of unused solutions. The following remarks from hospital nurses illustrate these concerns:

“We usually prepare IV artesunate solutions but we are not familiar with IM preparations” (Nurse) “We are used to a standard dose of 120mg of artesunate injection, mixing vials to accommodate it to the patient needed dose isn’t a regular practice for us” (Nurse) “We usually use the remaining solution for the next dose, we don’t dispose it and we think it will be better to save it in the refrigerator” (Nurse)

The full course of AL should follow on IV artesunate treatment, which is administered to severe malaria patients upon admission, repeated minimally at 12 h and 24 h, and thereafter once a day until the patient can tolerate oral medicines and be discharged on oral AL therapy. Most participants, however, expressed a lack of awareness about AL follow on treatment, as clearly noted by the medical doctor:

“I didn’t hear about this before, but if it’s in the protocol then I will do it” (Medical doctor)

Moreover, incompletion of three minimally required IV artesunate doses at the hospital was common and discharge on injectable artesunate treatments for home administration was commonly reported:

“I’m used to neighbours knocking my door asking me to give a patient artesunate injections at home” (Medical assistant) “It’s true, I get the same neighbours asking for similar favours, and to be honest, if the patient is vitally stable we discharge him on artesunate at home” (Medical doctor)

Nonadherence to P. vivax and mixed infection treatments

While most participants were aware of radical P. vivax treatment with primaquine, the scarcity of primaquine on the market contributed to the low number of prescriptions. When primaquine is prescribed, health workers often have limited knowledge about primaquine doses, glucose-6-phosphate dehydrogenase (G6PD) risks, and adjusted dosing schedules for G6PD-deficient patients, as shown below:

“If a patient has P. vivax I prescribe them with 15 mg primaquine tabs twice daily for 2 weeks, I don’t ask specific questions to get a clue if the patient has G6PD honestly” (Medical assistant) “I didn’t know about the contraindication of primaquine with G6PD, even the paediatric weight dependant dose, I’m used to prescribe 7.5 mg tabs once per day for 14 days to all paediatric patients” (House officer)

Moreover, heath workers were less familiar with the possibility of mixed infections, particulary with test result interpretations, as observed by medical assistant below:

“Sometimes the RDT shows both P. falciparum and P. vivax, I don’t know what the meaning of this is, I presume that the RDT is not working well and I diagnose the patient with having P. falciparum infection” (Medical assistant)

Factors influencing nonadherence to protocols

Four broad themes describing factors influencing nonadherence to case management protocols were identified (Table  3 ). These included lack of commodities and shortage of human resources, poor knowledge of health workers about case management protocols, distrust in parasitological test results and patient pressure on modalities of clinical malaria management.

Lack of commodities and shortage of human resources

The absence of diagnostics and medicines precludes adherence to case management protocols. Common stock-outs of anti-malarials and RDTs at public health facilities, the reliance upon the private sector for costly purchases and the nearly universal absence of primaquine and DHAP from the market have been commonly reported by most participants, as illustrated by the hospital doctor:

“Malaria medications and RDTs aren’t always available in the hospital, most can be found in the private pharmacies and laboratories, except for primaquine and DHAP, they are hard to find” (Medical doctor)

The lack of commodities is limited not only to medicines and diagnostics but also to basic facility equipment, such as weighing scales, which are required to implement appropriate weight-based dosing of patients. The majority of participants seconded the frustrations highlighted by the medical assistant:

“I don’t have a weight scale in my centre, how am I supposed to adopt a weight dependent approach?!” (Medical assistant)

Moreover, even when commodities are available a major effort may be required to adhere to the protocols due to high patient workloads in the face of staff shortages, as also well observed by the hospital nurse:

“Now I understand I should prepare quinine dose just before administration, but I’m working alone and usually I have many patients to observe, this will definitely be a challenge” (Nurse)

Lack of training and lack of continuous support for protocol adherence

Participants commonly attributed nonadherence to a lack of knowledge and information transfer through interventions such as regular in-service training and supportive supervision, including the delivery of reminders about good practices. For instance, the role of job aids such as poster wall charts and protocol booklets was repeatedly emphasized by the participants:

“If I have a poster in my centre it will remind me if I forget” (Medical assistant)

This was similarly echoed by medical doctors in hospital settings:

“Posters help us train our house officers and as he said it helps reminding us if we forget” (Registrar)

With respect to more formal capacity building, in-service training has been acknowledged as a valuable intervention in transmitting knowledge and enhancing case management readiness for all health workers, however, it appears that consultants and specialists have not been sufficiently reached:

“When prestigious consultants treat malaria differently than us, we lose patients trust” (Medical assistant)

Finally, most participants acknowledged that the lack of supportive supervision to address the availability of commodities and provide on-job support and problem solving for front-line health workers may further facilitate nonadherent practices:

“You ask us to do things but at the same time you don’t avail the needed requirements for us, why don’t you come and see the setting at which we are practicing first?” (Medical assistant)

Distrust in parasitological test results

Treatment nonadherent to malaria test results due to the distrust of malaria microscopy and doubtful quality of laboratory services was a recurrent theme among the participants:

“Sometimes a patient presents with fever, we exclude all other causes, but if the microscopic test results come back negative from the lab, we do not trust, we manage as malaria, and we observe dramatic improvement in patients.” (Medical officer)

Notably, clinicians’ distrust in malaria microscopy has been exclusively directed towards negative test results, as well remarked by laboratory specialist:

“If I provide a negative result, the healthcare provider will not trust me, and they will send the patient to another lab that gives them positive results” (Laboratory specialist)

Discontinuation of external quality assurance systems for laboratories and a lack of recent refresher training for malaria microscopists does not mitigate the distrust in test results:

“Previously the program used to take slides from our lab for verification and provide training if the staff is giving wrong readings, but now this is not happening!” (Laboratory specialist)

Finally, similar levels of distrust were reported with respect to malaria RDT results. Furthermore, much of the confusion was reported in the PHC facilities with regard to the appropriate performance and interpretation of RDTs produced by different companies:

“The RDTs I have only gives me a negative result no matter what, I suspect it might be due to storage conditions” (Medical assistant) “I don’t understand how to use RDTs, some companies require waiting for 15 min, some for more or less, having RDTs from different companies each time is tiring and exhausting because I’m already overworked” (Medical assistant)

Patient pressure

In addition to health worker and health system factors, patient pressure may also influence health worker adherence to malaria case management protocols and alter health worker clinical practices. For instance, some health workers illustrated how patients may influence diagnosing practices for malaria:

“When you ask the patient what are you complaining from he says malaria! And when I try to explain that I’m asking about the symptoms he says I know my malaria just order me the test” (Medical doctor) “Patients insist it’s malaria even if the test is negative” (Medical assistant)

The other participants illustrated how patients may influence treatment practices:

“Patients insist its malaria even if the test is negative, they insist on being treated for malaria and if I didn’t write the drug they will buy it themselves” (Medical assistant) “Sometimes the patient have malaria but he demands injectable treatment although they should just take tabs, some insist on taking artemether injections even after I counsel them about it” (Medical doctor)

Health worker recommendations to improve adherence

The participants provided valuable insights into what could be done to address the identified challenges and improve adherence to malaria case management protocols, as summarized in Table  4 .

Ensuring the availability of case management commodities

Health workers emphasized the responsibility of the Ministry of Health to strengthen the effective supply chain for malaria commodities and ensure the universal, continuous and affordable availability of malaria diagnostic and treatment commodities. Such steps would present a basic prerequisite for adherence improvements:

“If RDTs are free and available we can take a step towards accurate diagnosis of malaria” (Medical assistant) “I don’t prescribe primaquine for patients with P. vivax because it’s not available, same goes for DHAP” (Medical assistant)

Improving the balance between human resources and workload

Quality of care is dependent on adequate human resources and calls for additional personnel to balance heavy workloads were the theme of transpiring discussions across the cadres of participants:

“Now I understand I should prepare quinine dose just before administration, but I’m working alone and usually I have many patients to observe, this will definitely be a challenge, I need more people to work with me” (Nurse) “Being overworked and not have much sleep can alter your cognitive skills! This is scientifically proven! The Ministry of Health should decrease our workload because this isn’t just affecting malaria management, this is affecting all patient’s health outcome” (Medical doctor)

In-service training on case management protocols

Participants emphasized the importance of continuous training for all health workers. Recognizing the influential role played by specialists and consultants in hospital settings, they also underscored the importance of targeted training and interventions for these professionals:

“Now, I know the updated protocol, but my boss doesn’t, I may adhere to it in my private outpatient clinic but in the hospital it’s the consultant’s decision, not mine, you have to orient him too with the protocol” (Medical officer)

Moreover, whether implemented during training or through separate communication channels, health workers expected clarifications about the reasons for artemether injection prohibitions:

“The consultant in my unit is prescribing artemether injection, I do too since I don’t understand why is it prohibited at the first place, if you are afraid of the resistance because of the mono-therapies, why would you put artesunate injection in the protocol?” (Medical doctor)

Quality assurance for malaria diagnosis and supervision activities

Most of the participants called for external quality assessments at public laboratories through onsite supervisory visits for malaria microscopy and RDTs:

“I don’t trust the lab results, supervising the lab and making sure it’s well equipped and its staff is qualified will be great” (Medical doctor) “The RDTs I have only give a negative result, I would like if the Ministry of Health came and saw if it’s working or not or if its storage is well or not” (Medical assistant)

Some hospital clinicians further emphasized MoH supervision at public pharmacies and laboratories with respect to the enforcement of free policy for government procured RDTs and artesunate vials:

“When artesunate is available in the hospital, only the first dose is free, the patient has to buy other doses from the private pharmacy, you should talk to them to make sure they provide all doses for free” (Medical officer)

Finally, participants highlighted the importance of extending supervision to the private pharmacies to ensure the delivery of quality products and compliance with artmether injection prohibition:

“If artemether is prohibited then why the government doesn’t enforce its prohibition by law? Supervise the private pharmacies!” (Medical assistant) “Artesunate injection isn’t available in the public hospital, patients buy it from the private pharmacies and the quality of the drug available isn’t good” (Medical doctor)

Health promotion campaigns

Participants emphasized that public campaigns are necessary to promote malaria diagnosis based on parasitological test results and to increase the understanding of the rational use of anti-malarial medicines:

“Patients and co-patients don’t trust the parasitological test and insist on the malaria diagnosis, the concept “I know my Malaria” needs to be fought” (Medical assistant) “Patients insist on being treated for malaria even they don’t have malaria, and if they do they insist on being treated through injections rather than tabs, let alone those who request artemether injections” (Medical doctor)

Sudan health workers from Northern State revealed a broad spectrum of protocol nonadherent malaria case management practices, factors influencing such practices and recommendations of relevance for policy implementers to improve the adherence to and quality of malaria care. The problem of malaria diagnosis transpired throughout the study. Stock-outs of diagnostic commodities such as RDTs, distrust of malaria microscopy, but also RDTs, limited in-service training and lack of supportive supervision for laboratories and clinicians have been highlighted in this study, as similarly observed in various settings across Africa [ 26 , 27 , 28 , 29 , 43 , 44 ]. More recently, compliance with test negative test results and the rational use of anti-malarials have improved in other countries [ 14 , 25 ], and many of these achievements have been attributed to the implementation of quality assurance programmes for malaria diagnosis supported with systems readiness and case management monitoring [ 15 , 45 ]. In Sudan, as also suggested by the study findings, the quality assurance programmes traditionally targeting malaria microscopy should be re-established but also expanded to include RDTs through the onsite supervision of non-laboratory personnel, in line with recently developed quality assurance guidelines [ 46 ]. To mitigate human resource issues, outpatient use of RDTs for initial febrile visits should be promoted at all levels of care, including hospitals, while complex to perform malaria microscopy should be reserved for follow-up of treatments and monitoring of parasitaemia for severely admitted patients [ 47 , 48 ].

Another quality of care aspect severely compromising the effectiveness of malaria case management is nonadherence to treatment recommendations [ 47 ]. Health workers revealed several suboptimal treatment practices. First, lack of patients’ weighing and the practice of dose approximations, the clinical deficiencies not unique to Sudan [ 29 , 33 ], are widespread and inevitably result in overdosed and underdosed treatments. Although the lack of weighing scales may provide a plausible explanation, uniformed artesunate prescriptions for adults based on a single 120 mg vial may also reflect cost considerations, ease of administration and waste minimization. Second, paediatric anti-malarial misdosing reported by health workers may not only be due to the absence of weighing scales but also due to deficient dosing knowledge. Third, suboptimal counselling practices, as similarly observed for outpatients in other settings [ 9 , 28 , 34 ], are important components of malaria case management, compromising the promptness of the treatment, patient adherence, cure rates, and follow-up needs [ 49 , 50 ]. While acknowledged in the protocols, patient counselling has been a neglected topic and has indeed not been addressed during case management in-service trainings for health workers in Sudan [ 51 ]. Fourth, while the first-line treatment recommendations for uncomplicated malaria are highly accepted by health workers, the use of injectable artemether due to patient pressure seems to compromise the implementation of the treatment policy. This irrational treatment pattern was observed during earlier national surveys [ 9 , 40 ], raised concerns about drug resistance and ultimately led to the prohibition of injectable artemether in Sudan [ 7 ]. Although the findings of this study suggest persistent artemether use for uncomplicated malaria, quantitative assessments are required to estimate the scale of this malpractice. Fifth, regarding the treatment of severe malaria, the widespread use of injectable artemether, the inferior anti-malarial choice for this category of patients, as well as incomplete ACT follow on treatments are the nonadherent aspects of care described previously [ 29 , 30 ], and are perhaps the most concerning since they directly compromise patient outcomes [ 52 , 53 ]. Artemether preferences, especially common among role model cadres such as consultants and specialists, might reflect a lack of updates about treatment effectiveness but also weak regulatory enforcements given the banned status of the product on the market. Finally, the recommended management of the treatment failures and radical treatment of P. vivax infections is uncommon in Sudan due to the very low availability of respective treatments for these special patient groups, DHAP and primaquine.

Quality improvement initiatives targeting the readiness of health systems and the adherence of health workers to evidence-based case management protocols are malaria control priorities in Sudan [ 36 ]. Reinforcement of the test and treat practices is important not only for delivering quality of care and curbing malaria mortality but also for establishing reliable disease surveillance and malaria elimination foundations to which the country, and in particular the northern states of Sudan, are aspiring to. The study health workers in the Northern State suggested several valuable interventions that concur with broad strategic plans of the National Malaria Control Program (NMCP) [ 37 ]. Quality assurance for malaria diagnosis, the programmatic intervention mentioned earlier, is one of the control priorities. Regarding the initiatives targeting clinicians, only smaller-scale, multifaceted projects have been piloted [ 54 ], while programmatic interventions focusing mainly on supply, protocols and training have had limited reach [ 2 ]. In the following years, the Sudan NMCP plans to implement a package of multifaceted, evidence-based, country-adapted, quality improvement interventions focusing on the provision of diagnostics and medicines; supportive supervision, including audit, feedback and mentorship; and in-service training coupled with monitoring and group problem solving, interventions that have been shown to have significant positive effects [ 55 ]. Clinical algorithms in the format of job aids will be integral components of the multifaceted training and supervision interventions, required to remind health workers but also policy makers about key case management standards. However, it should be emphasized that improved performance through health worker supportive interventions such as job aids, training and supervision can be realized only if basic prerequisites are in place, i.e., universal and continuous availability of “test and treat” commodities and services for malaria [ 56 ]. Finally, regular assessments of the quality of care will be established to provide reliable quantitative indicators to inform progress in health system readiness and adherence to outpatient and inpatient malaria case management protocols [ 9 , 33 , 57 ].

In addition to health system interventions, health campaigns have been suggested for Sudan’s Northern State to mitigate patient pressure by increasing public awareness of parasitological diagnosis and decreasing demand for injectable medicines, especially for artemether injections. Other countries reported differing effects of patient pressure on anti-malarial prescriptions [ 58 ]. In Sudan, further quantitative research is needed to assess relation between appropriate counselling, patient pressure and patient satisfaction level. Finally, while staff shortages are a pertinent health system problem in Sudan and additional hiring, as requested by health workers, is a long-term solution, more effective use of available resources such as task shifting of RDT performance is a more realistic palliative solution in the short term.

Several study limitations should be acknowledged. First, while the study findings represent Northern State health workers, they may not be generalizable to other parts of Sudan. Second, the study did not include policy makers and implementers what limited insights into adherence factors only to the recipients of the case management interventions. Third, while the social desirability bias in reporting clinical behaviour cannot be excluded, this bias appeared to be controlled given the extent of reported nonadherent practices. Finally, the identification and exploration of nonadherent topics were guided by case management protocols and not by quantitative adherence data in the study area. Future studies exploring adherence to protocols should deploy mixed methods designs.

This study revealed a broad spectrum of behavioural and systemic challenges in malaria management among Northern Sudan’s frontline health workers, including nonadherence to protocols due to resource shortages, training gaps, lack of supportive supervision and patient pressure. These insights, including health workers’ views about improvements, will inform evidence-based interventions by Sudan’s National Malaria Control Programme to improve health system readiness and the quality of malaria case management.

Availability of data and materials

The datasets used and analysed during the current study are available from the corresponding author upon reasonable request.

WHO. World malaria report 2023. Geneva: World Health Organization; 2023.

Google Scholar  

Federal Ministry of Health—Sudan. Malaria program review, 2023. National Malaria Control Program; 2023.

World Bank. Socioeconomic impact of COVID-19 on Sudanese households. Central Bureau of Statistics—Sudan. December 2020. https://documents1.worldbank.org/curated/en/394981620725892919/pdf/Socioeconomic-Impact-of-COVID-19-on-Sudanese-Households.pdf . Accessed 24 Feb 2024.

WHO. Three months of violence in Sudan: health hanging in the balance. WHO—Regional Office for Africa; 2023. https://www.afro.who.int/news/three-months-violence-sudan-health-hanging-balance . Accessed 10 Dec 2023.

WHO. Health needs heighten as Sudan conflict displaces millions of people. WHO—Eastern Mediterranean region; 2023. http://www.emro.who.int/media/news/health-needs-heighten-as-sudan-conflict-displaces-millions-of-people.html . Accessed 10 Dec 2023.

WHO. Guidelines for the treatment of malaria, 2nd edition. Geneva: World Health Organization; 2010. https://www.paho.org/en/documents/guidelines-treatment-malaria-second-edition-2010 . Accessed 10 Dec 2023.

Federal Ministry of Health—Sudan. Sudan malaria case management protocol. National Malaria Control Programme; 2017.

Federal Ministry of Health—Sudan. Sudan malaria case management protocol. National Malaria Control Program; 2023.

Abdelgader I, Elmardi KA, Githinji S, Zurovac D, Snow RW, Noor AM. Quality of malaria case-management in Sudan. BMC Public Health. 2012;12:11.

Article   PubMed   PubMed Central   Google Scholar  

Lubell Y, Reyburn H, Mbakilwa H, Mwangi R, Chonya K, Whitty CJM, et al. The cost-effectiveness of parasitologic diagnosis for malaria-suspected patients in an era of combination therapy. Am J Trop Med Hyg. 2007;77:128–32.

Article   PubMed   Google Scholar  

Biai S, Rodrigues A, Gomes M, Ribeiro I, Sodemann M, Alves F, et al. Reduced in-hospital mortality after improved management of children under 5 years admitted to hospital with malaria: randomised trial. BMJ. 2007;335:862.

Kruk M, Gage A, Joseph N, Danaei G, García-Saisó S, Salomon J, et al. Mortality due to low-quality health systems in the universal health coverage era: a systematic analysis of amenable deaths in 137 countries. Lancet. 2018;392:2203–12.

Amboko B, Stepniewska K, Malla L, Machini B, Bejon P, Snow RW, et al. Determinants of improvement trends in health workers’ compliance with outpatient malaria case-management guidelines at health facilities with available “test and treat” commodities in Kenya. PLoS ONE. 2021;16: e0259020.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Amboko B, Stepniewska K, Macharia PM, Machini B, Bejon P, Snow RW, et al. Trends in health workers’ compliance with outpatient malaria case-management guidelines across malaria epidemiological zones in Kenya, 2010–2016. Malar J. 2020;19:406.

Amboko B, Stepniewska K, Machini B, Bejon P, Snow RW, Zurovac D. Factors influencing health workers’ compliance with outpatient malaria ‘test and treat’ guidelines during the plateauing performance phase in Kenya, 2014–2016. Malar J. 2022;21:68.

Bawate C, Callender-Carter ST, Nsajju B, Bwayo D. Factors affecting adherence to national malaria treatment guidelines in management of malaria among public healthcare workers in Kamuli District, Uganda. Malar J. 2016;15:112.

Muhindo Mavoko H, Ilombe G, Inocêncio da Luz R, Kutekemeni A, Van Geertruyden J-P, Lutumba P. Malaria policies versus practices, a reality check from Kinshasa, the capital of the Democratic Republic of Congo. BMC Public Health. 2015;15:352.

Salomão CA, Sacarlal J, Chilundo B, Gudo ES. Prescription practices for malaria in Mozambique: poor adherence to the national protocols for malaria treatment in 22 public health facilities. Malar J. 2015;14:483.

Bulafu D, Nagawa Tamale B, Ninsiima LR, Baguma JN, Namakula LN, Niyongabo F, et al. Adherence to malaria treatment guidelines among health care workers in private health facilities in Kampala’s informal settlements, Uganda. PLoS Global Public Health. 2023;3: e0002220.

Baraka V, Nhama A, Aide P, Bassat Q, David A, Gesase S, et al. Prescription patterns and compliance with World Health Organization recommendations for the management of uncomplicated and severe malaria: a prospective, real-world study in sub-Saharan Africa. Malar J. 2023;22:215.

Plucinski MM, Ferreira M, Ferreira CM, Burns J, Gaparayi P, Joao L, et al. Evaluating malaria case management at public health facilities in two provinces in Angola. Malar J. 2017;16:186.

Plucinski MM, Guilavogui T, Camara A, Ndiop M, Cisse M, Painter J, et al. How far are we from reaching universal malaria testing of all fever cases? Am J Trop Med Hyg. 2018;99:670–9.

Bruxvoort KJ, Leurent B, Chandler CIR, Ansah EK, Baiden F, Bjorkman A, et al. The impact of introducing malaria rapid diagnostic tests on fever case management: a synthesis of ten studies from the ACT Consortium. Am J Trop Med Hyg. 2017;97:1170–9.

O’Boyle S, Bruxvoort KJ, Ansah EK, Burchett HED, Chandler CIR, Clarke SE, et al. Patients with positive malaria tests not given artemisinin-based combination therapies: a research synthesis describing under-prescription of antimalarial medicines in Africa. BMC Med. 2020;18:17.

Boyce MR, O’Meara WP. Use of malaria RDTs in various health contexts across sub-Saharan Africa: a systematic review. BMC Public Health. 2017;17:470.

Kabaghe AN, Visser BJ, Spijker R, Phiri KS, Grobusch MP, van Vugt M. Health workers’ compliance to rapid diagnostic tests (RDTs) to guide malaria treatment: a systematic review and meta-analysis. Malar J. 2016;15:163.

Namuyinga RJ, Mwandama D, Moyo D, Gumbo A, Troell P, Kobayashi M, et al. Health worker adherence to malaria treatment guidelines at outpatient health facilities in southern Malawi following implementation of universal access to diagnostic testing. Malar J. 2017;16:40.

Steinhardt LC, Chinkhumba J, Wolkon A, Luka M, Luhanga M, Sande J, et al. Quality of malaria case management in Malawi: results from a nationally representative health facility survey. PLoS ONE. 2014;9: e89050.

Ojo AA, Maxwell K, Oresanya O, Adaji J, Hamade P, Tibenderana JK, et al. Health systems readiness and quality of inpatient malaria case-management in Kano State. Malar J. 2020;19:384.

Signorell A, Awor P, Okitawutshu J, Tshefu A, Omoluabi E, Hetzel MW, et al. Health worker compliance with severe malaria treatment guidelines in the context of implementing pre-referral rectal artesunate in the Democratic Republic of the Congo, Nigeria, and Uganda: an operational study. PLoS Med. 2023;20: e1004189.

Achan J, Tibenderana J, Kyabayinze D, Mawejje H, Mugizi R, Mpeka B, et al. Case management of severe malaria-a forgotten practice: experiences from health facilities in Uganda. PLoS ONE. 2011;6: e17053.

Shah MP, Briggs-Hagen M, Chinkhumba J, Bauleni A, Chalira A, Moyo D, et al. Adherence to national guidelines for the diagnosis and management of severe malaria: a nationwide, cross-sectional survey in Malawi. Malar J. 2016;15:369.

Zurovac D, Machini B, Kiptui R, Memusi D, Amboko B, Kigen S, et al. Monitoring health systems readiness and inpatient malaria case-management at Kenyan County Hospitals. Malar J. 2018;17:213.

Elmannan AAA, Elmardi KA, Idris YA, Spector JM, Ali NA, Malik EM. Anti-malarial prescribing practices in Sudan eight years after introduction of artemisinin-based combination therapies and implications for development of drug resistance. BMC Pharmacol Toxicol. 2015;16:3.

Bilal JA, Gasim GI, Abdien MT, Elmardi KA, Malik EM, Adam I. Poor adherence to the malaria management protocol among health workers attending under-five year old febrile children at Omdurman Hospital Sudan. Malar J. 2015;14:34.

Elnour FA, Alagib MEA, Bansal D, Farag EABA, Malik EM. Severe malaria management: current situation, challenges and lessons learned from Gezira State, Sudan. Malar J. 2019;18:170.

Federal Ministry of Health—Sudan. Sudan malaria strategic plan 2021–2026, update March 2023. National Malaria Control Programme; 2023.

WHO. Understanding the labour market of human resources for health in Sudan. Working Paper, November 2013. https://www.who.int/publications/m/item/2013-sudan-hrh-labour-market . Accessed 15 Dec 2023.

Ebrahim EMA, Ghebrehiwot L, Abdalgfar T, Juni MH. Health care system in Sudan: review and analysis of strength, weakness, opportunity, and threats (SWOT analysis). Sudan J Med Sci. 2017;12:133–50.

Article   Google Scholar  

Federal Ministry of Health—Sudan. Sudan malaria indicator survey 2016. Directorate of Communicable and Non-communicable Diseases Control; 2017.

Office for the Coordination of Humanitarian Affairs. Sudan situation report, 2 November 2023. https://www.unocha.org/publications/report/sudan/sudan-situation-report-2-november-2023-enar . Accessed 16 Dec 2023.

Nowell LS, Norris JM, White DE, Moules NJ. Thematic analysis: striving to meet the trustworthiness criteria. Int J Qual Methods. 2017;16:160940691773384.

Hanson K, Goodman C. Testing times: trends in availability, price, and market share of malaria diagnostics in the public and private healthcare sector across eight sub-Saharan African countries from 2009 to 2015. Malar J. 2017;16:205.

Kuupiel D, Bawontuo V, Drain PK, Gwala N, Mashamba-Thompson TP. Supply chain management and accessibility to point-of-care testing in resource-limited settings: a systematic scoping review. BMC Health Serv Res. 2019;19:519.

Ashton RA, Worges M, Zeh Meka A, Yikpotey P, Domkam Kammogne I, Chanda-Kapata P, et al. Can outreach training and supportive supervision improve competency in malaria service delivery? An evaluation in Cameroon, Ghana, Niger, and Zambia. Am J Trop Med Hyg. 2023;4: tpmd230150.

Federal Ministry of Health—Sudan. Sudan quality assurance guide for parasitological diagnosis of malaria (draft). National Malaria Control Programme; 2023.

WHO. Malaria microscopy—quality assurance manual. Geneva: World Health Organization; 2016.

Galactionova K, Tediosi F, de Savigny D, Smith T, Tanner M. Effective coverage and systems effectiveness for malaria case management in sub-Saharan African countries. PLoS ONE. 2015;10: e0127818.

Mace KE, Mwandama D, Jafali J, Luka M, Filler SJ, Sande J, et al. Adherence to treatment with artemether–lumefantrine for uncomplicated malaria in rural Malawi. Clin Infect Dis. 2011;53:772–9.

Article   CAS   PubMed   Google Scholar  

Talisuna AO, Oburu A, Githinji S, Malinga J, Amboko B, Bejon P, et al. Efficacy of text-message reminders on paediatric malaria treatment adherence and their post-treatment return to health facilities in Kenya: a randomized controlled trial. Malar J. 2017;16:46.

Federal Ministry of Health—Sudan. Malaria case management training manual. Directorate of Communicable and Non Communicable Disease; 2023.

Phu NH, Tuan PQ, Day N, Mai NT, Chau TT, Chuong LV, et al. Randomized controlled trial of artesunate or artemether in Vietnamese adults with severe falciparum malaria. Malar J. 2010;9:97.

Hetzel MW, Okitawutshu J, Tshefu A, Omoluabi E, Awor P, Signorell A, et al. Effectiveness of rectal artesunate as pre-referral treatment for severe malaria in children under 5 years of age: a multi-country observational study. BMC Med. 2022;20:343.

Mohammed NMA. Impact of multifaceted clinical pharmacist interventions on implementation of national malaria protocol, in Wad Madani Maternity Hospital, Gezira State, Sudan (2020). PhD Thesis—University of Gezira; July 2022.

Rowe AK, Rowe SY, Peters DH, Holloway KA, Chalker J, Ross-Degnan D. Effectiveness of strategies to improve health-care provider practices in low-income and middle-income countries: a systematic review. Lancet Glob Health. 2018;6:1163–75.

Bernard YM, Ahmed J, Mostel J, Ba T, Ciceron AC, Busiga M, et al. Clinical outreach training and supportive supervision quality-of-care analysis: impact of readiness factors on health worker competencies in malaria case management in Cameroon, Mali, and Niger. Am J Trop Med Hyg. 2023;26: tpmd230479.

Zurovac D, Githinji S, Memusi D, Kigen S, Machini B, Muturi A, et al. Major improvements in the quality of malaria case-management under the “test and treat” policy in Kenya. PLoS ONE. 2014;9: e92782.

Chandler CI, Mwangi R, Mbakilwa H, Olomi R, Whitty CJ, Reyburn H. Malaria overdiagnosis: is patient pressure the problem? Health Policy Plan. 2008;23:170–8.

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Acknowledgements

The authors would like to thank all the health workers who participated in the study. The authors are grateful to Dr. Mujahid Abdin for the creation of the study area map and Dr. Mariam Adam Babiker for comments on the manuscript. The authors express their sincere gratitude to the Primary Health Care Directorate which funded orientation training for health workers which were used as operational avenues for the study FGDs. Special thanks to the Federal Ministry of Health, the Northern State Ministry of Health and the National Malaria Control Programme for continued study support.

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Sahar Khalid Mohamed, Duha Khalid Mohamed, Khansaa Ahmed & Fadwa Saad

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Contributions

SKM conceived and designed the study, collected the data, performed the analyses, interpreted the study findings and wrote the first draft of the manuscript. KA, DKM, FMS and DZ contributed to the interpretation of the study findings and revision of the manuscript. All the authors have read and approved the final manuscript.

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Correspondence to Sahar Khalid Mohamed .

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Khalid Mohamed, S., Khalid Mohamed, D., Ahmed, K. et al. Health workers’ adherence to malaria case management protocols in Northern Sudan: a qualitative study. Malar J 23 , 170 (2024). https://doi.org/10.1186/s12936-024-04998-9

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Received : 17 March 2024

Accepted : 23 May 2024

Published : 30 May 2024

DOI : https://doi.org/10.1186/s12936-024-04998-9

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