How Can Routine Health Information Systems Improve Health Systems Functioning in Low- and Middle-Income Countries? Assessing the Evidence Base

Author(s):  
David R. Hotchkiss ◽  
Mark L. Diana ◽  
Karen G. Fleischman Foreit
2020 ◽  
pp. 183335832092872 ◽  
Author(s):  
Klesta Hoxha ◽  
Yuen W Hung ◽  
Bridget R Irwin ◽  
Karen A Grépin

Background: Routine health information systems (RHISs) are crucial to informing decision-making at all levels of the health system. However, the use of RHIS data in low- and middle-income countries (LMICs) is limited due to concerns regarding quality, accuracy, timeliness, completeness and representativeness. Objective: This study systematically reviewed technical, behavioural and organisational/environmental challenges that hinder the use of RHIS data in LMICs and strategies implemented to overcome these challenges. Method: Four electronic databases were searched for studies describing challenges associated with the use of RHIS data and/or strategies implemented to circumvent these challenges in LMICs. Identified articles were screened against inclusion and exclusion criteria by two independent reviewers. Results: Sixty studies met the inclusion criteria and were included in this review, 55 of which described challenges in using RHIS data and 20 of which focused on strategies to address these challenges. Identified challenges and strategies were organised by their technical, behavioural and organisational/environmental determinants and by the core steps of the data process. Organisational/environmental challenges were the most commonly reported barriers to data use, while technical challenges were the most commonly addressed with strategies. Conclusion: Despite the known benefits of RHIS data for health system strengthening, numerous challenges continue to impede their use in practice. Implications: Additional research is needed to identify effective strategies for addressing the determinants of RHIS use, particularly given the disconnect identified between the type of challenge most commonly described in the literature and the type of challenge most commonly targeted for interventions.


2018 ◽  
Vol 15 (2) ◽  
pp. 43-46 ◽  
Author(s):  
Shalini Ahuja ◽  
Rahul Shidhaye ◽  
Maya Semrau ◽  
Graham Thornicroft ◽  
Mark Jordans

Mental health information systems are increasingly being used to measure the effectiveness of mental health interventions. Little or no data is available for mental health service availability and service uptake in low- and middle-income countries. Through a narrative review, this paper illustrates the importance of routine monitoring data and suggests methods for developing, implementing and evaluating mental health indicators in low- and middle-income countries with a primary focus on India.


2020 ◽  
pp. 183335832093680
Author(s):  
Heidi W Reynolds ◽  
Shannon Salentine ◽  
Eva Silvestre ◽  
Elizabeth Millar ◽  
Ashley Strahley ◽  
...  

Background: Evidence-based interventions are necessary for planning and investing in health information systems (HIS) and for strengthening those systems to collect, manage, sort and analyse health data to support informed decision-making. However, evidence and guidance on HIS strengthening in low- and middle-income countries have been historically lacking. Objective: This article describes the approach, methods, lessons learned and recommendations from 5 years of applying our learning agenda to strengthen the evidence base for effective HIS interventions. Methods: The first step was to define key questions about characteristics, stages of progression, and factors and conditions of HIS performance progress. We established a team and larger advisory group to guide the implementation of activities to build the evidence base to answer questions. We strengthened learning networks to share information. Results: The process of applying the learning agenda provided a unique opportunity to learn by doing, strategically collecting information about monitoring and evaluating HIS strengthening interventions and building a body of evidence. There are now models and tools to strengthen HIS, improved indicators and measures, country HIS profiles, documentation of interventions, a searchable database of HIS assessment tools and evidence generated through syntheses and evaluation results. Conclusion: The systematic application of learning agenda processes and activities resulted in increased evidence, information, guidance and tools for HIS strengthening and a resource centre, making that information accessible and available globally. Implications: We describe the inputs, processes and lessons learned, so that others interested in designing a successful learning agenda have access to evidence of how to do so.


Author(s):  
Anne Mills

This article focuses on the limited attention paid to the economic dimensions of low- and middle-income countries (LMICs) health systems relative to those of high-income countries, and the restricted evidence base. The aim is to provide an economic analysis of LMIC health systems and policy implications, and to interpret the relevance to LMIC settings. It analyzes the economic dimensions of health systems in LMIC, including how they differ from those of high-income countries. It helps to identify distinctive characteristics of low- and middle-income countries that affect the policy recommendations that can be derived from the application of economic thinking to their health systems. Finally, it discusses the key areas of debate that remain unresolved.


Author(s):  
R. Mayston ◽  
K. Ebhohimen ◽  
K. Jacob

Abstract Effective health information systems are essential to the delivery of high-quality community-based care for chronic disease which will be needed to address the changing healthcare needs of populations in low and middle-income country settings. Health management information systems (health service data collected at facility level) and electronic health records (data organised by individual patients) may support the measurement-based, collaborative approach that is central to the chronic care model, which has been adopted as the basis for task-shared models of care for mental health and non-communicable disease. We used the performance of routine information systems management to guide our commentary on the evidence-base about information systems to support chronic care. We found that, despite an appetite for using the information to support decision-making around service planning, this rarely happens in practice, reasons include that data is not perceived to be of good quality or fit for purpose. There is often a mismatch between technology design and the availability of specialised knowledge and infrastructure. However, when data collection is designed in collaboration with local stakeholders, there is some evidence of success, demonstrated by completion and accuracy of data forms. Whilst there are global targets for the development of health information systems and progress on these is undoubtedly being made, indicators for chronic disease are seldom prioritised by national governments and there is insufficient decentralisation to facilitate local data-driven decision-making. Our recommendations for future research and development, therefore, focus upon the need to integrate context into the design of information systems: through building strong multisectoral partnerships, ensuring newly developed indicators are well aligned to service models and using technology that is a good fit with local infrastructure. This approach will be necessary if information systems are to deliver on their potential to drive improvements in care for chronic disease.


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