Routine Health Information System (RHIS) improvements for strengthened health system management

What could improve surgical data system at health facilities with high surgical volume in Ethiopia?

BACKGROUND

The effective management of surgical and anesthesia care relies on quality data and its readily availability for both patient-centered decision-making and facility-level improvement efforts. Recognizing this critical need, the Strengthening Systems for Improved Surgical Outcomes (SSISO) project addressed surgical care data management and information use practices across 23 health facilities from October 2019 to September 2022. This study aimed to evaluate the effectiveness of SSISO interventions in enhancing practices related to surgical data capture, reporting, analysis, and visualization.

METHODS

This study employed a mixed method, pre- post intervention evaluation design to assess changes in data management and utilization practices at intervention facilities. The intervention packages included capacity building trainings, monthly mentorship visits facilitated by a hub-and-spoke approach, provision of data capture tools, and reinforcement of performance review teams. Data collection occurred at baseline (February - April 2020) and endline (April - June 2022). The evaluation focused on the availability and appropriate use of data capture tools, as well as changes in performance review practices. Appropriate use of registers was defined as filling all the necessary data onto the registers, and this was verified by completeness of selected key data elements in the registers.

RESULTS

The proportion of health facilities with Operation Room (OR) scheduling, referral, and surgical site infection registers significantly increased by 34.8%, 56.5% and 87%, respectively, at project endline compared to baseline. Availability of OR and Anesthesia registers remained high throughout the project, at 91.3% and 95.6%, respectively. Furthermore, the appropriate use of these registers improved, with statistically significant increases observed for OR scheduling registers (34.8% increase). Increases were also noted for OR register (9.5% increase) and anesthesia register (4.5% increase), although not statistically significant. Assessing the prior three months reports, the report submissions to the Ministry of Health/Regional Health Bureau (MOH/RHB) rose from 85 to 100%, reflecting complete reporting at endline period. Additionally, the proportion of surgical teams analyzing and displaying data for informed decision-making significantly increased from 30.4% at baseline to 60.8% at endline period.

CONCLUSION

The implemented interventions positively impacted surgical data management and utilization practice at intervention facilities. These positive changes were likely attributable to capacity building trainings and regular mentorship visits via hub-and-spoke approach. Hence, we recommend further investigation into the effectiveness of similar intervention packages in improving surgical data management, data analysis and visualization practices in low- and middle-income country settings.

An Entity Extraction Pipeline for Medical Text Records Using Large Language Models: Analytical Study

BACKGROUND

The study of disease progression relies on clinical data, including text data, and extracting valuable features from text data has been a research hot spot. With the rise of large language models (LLMs), semantic-based extraction pipelines are gaining acceptance in clinical research. However, the security and feature hallucination issues of LLMs require further attention.

OBJECTIVE

This study aimed to introduce a novel modular LLM pipeline, which could semantically extract features from textual patient admission records.

METHODS

The pipeline was designed to process a systematic succession of concept extraction, aggregation, question generation, corpus extraction, and question-and-answer scale extraction, which was tested via 2 low-parameter LLMs: Qwen-14B-Chat (QWEN) and Baichuan2-13B-Chat (BAICHUAN). A data set of 25,709 pregnancy cases from the People's Hospital of Guangxi Zhuang Autonomous Region, China, was used for evaluation with the help of a local expert's annotation. The pipeline was evaluated with the metrics of accuracy and precision, null ratio, and time consumption. Additionally, we evaluated its performance via a quantified version of Qwen-14B-Chat on a consumer-grade GPU.

RESULTS

The pipeline demonstrates a high level of precision in feature extraction, as evidenced by the accuracy and precision results of Qwen-14B-Chat (95.52% and 92.93%, respectively) and Baichuan2-13B-Chat (95.86% and 90.08%, respectively). Furthermore, the pipeline exhibited low null ratios and variable time consumption. The INT4-quantified version of QWEN delivered an enhanced performance with 97.28% accuracy and a 0% null ratio.

CONCLUSIONS

The pipeline exhibited consistent performance across different LLMs and efficiently extracted clinical features from textual data. It also showed reliable performance on consumer-grade hardware. This approach offers a viable and effective solution for mining clinical research data from textual records.

Process analysis of the patient pathway for automated data collection: an exemplar using pituitary surgery

Introduction

Automation of routine clinical data shows promise in relieving health systems of the burden associated with manual data collection. Identifying consistent points of documentation in the electronic health record (EHR) provides salient targets to improve data entry quality. Using our pituitary surgery service as an exemplar, we aimed to demonstrate how process mapping can be used to identify reliable areas of documentation in the patient pathway to target structured data entry interventions.

Materials and methods

This mixed methods study was conducted in the largest pituitary centre in the UK. Purposive snowball sampling identified frontline stakeholders for process mapping to produce a patient pathway. The final patient pathway was subsequently validated against a real-world dataset of 50 patients who underwent surgery for pituitary adenoma. Events were categorized by frequency and mapped to the patient pathway to determine critical data points.

Results

Eighteen stakeholders encompassing all members of the multidisciplinary team (MDT) were consulted for process mapping. The commonest events recorded were neurosurgical ward round entries (N = 212, 14.7%), pituitary clinical nurse specialist (CNS) ward round entries (N = 88, 6.12%) and pituitary MDT treatment decisions (N = 88, 6.12%) representing critical data points. Operation notes and neurosurgical ward round entries were present for every patient. 43/44 (97.7%) had a pre-operative pituitary MDT entry, pre-operative clinic letter, a post-operative clinic letter, an admission clerking entry, a discharge summary, and a post-operative histopathology pituitary multidisciplinary (MDT) team entries.

Conclusion

This is the first study to produce a validated patient pathway of patients undergoing pituitary surgery, serving as a comparison to optimise this patient pathway. We have identified salient targets for structured data entry interventions, including mandatory datapoints seen in every admission and have also identified areas to improve documentation adherence, both of which support movement towards automation.

Mapping Factors That Affect the Uptake of Digital Therapeutics Within Health Systems: Scoping Review

BACKGROUND

Digital therapeutics are patient-facing digital health interventions that can significantly alter the health care landscape. Despite digital therapeutics being used to successfully treat a range of conditions, their uptake in health systems remains limited. Understanding the full spectrum of uptake factors is essential to identify ways in which policy makers and providers can facilitate the adoption of effective digital therapeutics within a health system, as well as the steps developers can take to assist in the deployment of products.

OBJECTIVE

In this review, we aimed to map the most frequently discussed factors that determine the integration of digital therapeutics into health systems and practical use of digital therapeutics by patients and professionals.

METHODS

A scoping review was conducted in MEDLINE, Web of Science, Cochrane Database of Systematic Reviews, and Google Scholar. Relevant data were extracted and synthesized using a thematic analysis.

RESULTS

We identified 35,541 academic and 221 gray literature reports, with 244 (0.69%) included in the review, covering 35 countries. Overall, 85 factors that can impact the uptake of digital therapeutics were extracted and pooled into 5 categories: policy and system, patient characteristics, properties of digital therapeutics, characteristics of health professionals, and outcomes. The need for a regulatory framework for digital therapeutics was the most stated factor at the policy level. Demographic characteristics formed the most iterated patient-related factor, whereas digital literacy was considered the most important factor for health professionals. Among the properties of digital therapeutics, their interoperability across the broader health system was most emphasized. Finally, the ability to expand access to health care was the most frequently stated outcome measure.

CONCLUSIONS

The map of factors developed in this review offers a multistakeholder approach to recognizing the uptake factors of digital therapeutics in the health care pathway and provides an analytical tool for policy makers to assess their health system's readiness for digital therapeutics.

Regular measurement is essential but insufficient to improve quality of healthcare

Ambrose Agweyu and colleagues argue that large scale improvements in quality of healthcare require strong change management as well as health information systems that can provide continuous and rapid feedback

Routine health information system utilization and associated factors among health professionals in public health facilities in Dire Dawa, eastern Ethiopia: A cross-sectional study

Background

Using reliable evidence from routine health information system (RHIS) over time is a vital aid to improve health outcome, tackling disparities, enhancing efficiency, and encouraging innovation. In Ethiopia, utilization of routine health data for improving the performance and quality of care was not well-studied in grassroot health facilities.

Objective

This study was conducted to determine the level of RHIS utilization and associated factors among health professionals in public health facilities of Dire Dawa, eastern Ethiopia.

Methods

An institution-based cross-sectional study was conducted among 378 health professionals from June 10 to July 20, 2020. Self-administered pretested-structured questionnaire was used to collect data from the participants. Data were entered using EpiData 3.1 and analyzed using Stata 16.0. Descriptive statistics was used to describe the basic characteristics of the participants, and multivariable logistic regression analysis was conducted to identify factors associated with RHIS utilization. Adjusted odds ratio (AOR) (95% CI) was used to report association and significance declared at a P-value <0.05.

Results

Good RHIS utilization among health professionals was 57.7% (95% CI: 52.6%, 62.6%). Good organizational support (AOR = 3.91, 95% CI: 2.01, 7.61), low perceived complexity of RHIS formats (AOR = 2.20, 95% CI: 1.23, 3.97), good self-efficacy (AOR = 2.52, 95% CI: 1.25, 5.10), and good decision-making autonomy (AOR = 3.97, 95% CI: 2.12, 7.43) were important factors associated with good RHIS utilization.

Conclusions

The level of good RHIS utilization among health professionals was low. Lack of self-confidence and empowerment, complexity of RHIS formats, and poor organizational support were significantly reducing RHIS utilization. Therefore, improving self-efficacy and decision-making capacity of health professionals through comprehensive training, empowerment, and organizational support would be essential.

Characterising performance information use in the primary healthcare systems of El Salvador, Lebanon and Malawi: multiple qualitative case study protocol

INTRODUCTION

Governments in low-income and middle-income countries (LMICs) and official development assistance agencies use a variety of performance measurement and management approaches to improve the performance of healthcare systems. The effectiveness of such approaches is contingent on the extent to which managers and care providers use performance information. To date, major knowledge gaps exist about the contextual factors that contribute, or not, to performance information use by primary healthcare (PHC) decision-makers in LMICs. This study will address three research questions: (1) How do decision-makers use performance information, and for what purposes? (2) What are the contextual factors that influence the use or non-use of performance information? and (3) What are the proximal outcomes reported by PHC decision-makers from performance information use?

METHODS AND ANALYSIS

We present the protocol of a theory-driven, qualitative study with a multiple case study design to be conducted in El Salvador, Lebanon and Malawi.Data sources include semi structured in-depth interviews and document review. Interviews will be conducted with approximately 60 respondents including PHC system decision-makers and providers. We follow an interdisciplinary theoretical framework that draws on health policy and systems research, public administration, organisational science and health service research. Data will be analysed using thematic analysis to explore how respondents use performance information or not, and for what purposes as well as barriers and facilitators of use.

ETHICS AND DISSEMINATION

The ethical boards of the participating universities approved the protocol presented here. Study results will be disseminated through peer-reviewed journals and global health conferences.

Maternal Service Coverage and Its Relationship To Health Information System Performance: A Linked Facility and Population-Based Survey in Ethiopia

Coverage for most maternal services showed promising performance. Improving the health information system performance can further improve maternal service uptake and quality.

Background:

Studies in Ethiopia show an increasing trend in maternal health service use, such as having at least 4 visits of antenatal care (ANC4+) and skilled birth attendance (SBA). Improving the health information system (HIS) is an intervention that can improve service uptake and quality. We conducted a baseline study to measure current maternal service coverage, HIS performance status, and their relationship.

Methods:

We conducted a linked health facility-level and population-based survey from September 2020 to October 2020. The study covers all regions of Ethiopia. For the population-based survey, 3,016 mothers were included. Overall, 81 health posts, 71 health centers, and 15 hospitals were selected for the facility survey. A two-stage sampling procedure was applied to select target households. The study used modified Performance of Routine Information System Management tools for the facility survey and a structured questionnaire for the household survey. Multilevel logistic regression was employed to account for clustering and control for likely confounders.

Results:

Maternal service indicators, ANC4+ visits (54.0%), SBA (75.8%), postnatal care (70.6%), and cesarean delivery (9%) showed good service uptake. All data quality and use indicators showed lower performance compared to the national target of 90%. Maternal education and higher levels of wealth index were significantly and positively associated with all selected maternal service indicators. Longer distance from health facilities was significantly and negatively associated with SBA and the maternal care composite indicator. Among HIS-related indicators, availability of electronic HIS tools was significantly associated with maternal care composite indicator and ANC4+.

Conclusions:

Maternal service indicators showed promising performance. However, current HIS performance is suboptimal. Both service user and HIS-related factors were associated with maternal service uptake. Conducting similar research outside of the project sites will be helpful to have a wider understanding and better coverage.

Contribution of health information system to child immunization services in Ethiopia: baseline study of 33 woredas

Background

Monitoring progress using appropriate data, with a functional health information system (HIS), believed to be very crucial for success of immunization program. Baseline study was conducted to assess, immunization service coverage, HIS performance status, and their relationships.

Methods

A linked facility and population-based survey was conducted concurrently from September 21 to October 15, 2020. A total of 3016 households were reached to interview mothers having children aged 12–23 months in the 33 woredas. Overall 81 health posts, 71 health centers, and 15 hospitals were selected for the facility survey. The study used modified Performance of Routine Information System Management (PRISM) tools for the facility survey and a structured questionnaire for the household survey. Using STATA 14.0 software, mixed effect modeling was employed to control the effect of clustering and potential confounders.

Results

The proportion of fully immunized children was 58%. Coverages of measles (at least one dose) and penta3 immunization (received all 3 doses of DPT-HepB-Hib vaccine) were 86%, and 85% respectively. About 27% of mothers had missed their child immunization card mainly due to misplacing or lost. Except ‘source document completeness’ (85%) and ‘use of data for planning and target setting’ (84%), other data quality and use indicators like ‘data accuracy’ (63%), ‘data use for performance review and evidence-based decision making’ (50%), and ‘data use to produce analytical reports’ (31%) show low performance. The odds of fully immunized children is 37% lower in Muslims compared with Orthodox Christians (AOR, 0.63; 95%CI: 0.46, 0.88), higher by 42% with father’s secondary education compared with no education (AOR, 1.42; 95%CI: 1.05, 1.92), and highest wealth quintile compared with lowest quintile (AOR, 2.49; 95%CI: 1.54, 4.03). For each additional score of HIS infrastructure availability, the odds of fully immunized children increased by 22% (AOR:1.22; 95% CI: 1.03, 1.44).

Conclusions

Child immunization coverages are promising However, the current HIS performance is suboptimal. Both service user and HIS related factors are important for immunization service uptake. Documenting required information and advising mothers to keep immunization cards by health workers, and working to have functional HIS are recommended.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01796-8.

Community health workers at the dawn of a new era: 11. CHWs leading the way to "Health for All"

BACKGROUND

This is the concluding paper of our 11-paper supplement, "Community health workers at the dawn of a new era".

METHODS

We relied on our collective experience, an extensive body of literature about community health workers (CHWs), and the other papers in this supplement to identify the most pressing challenges facing CHW programmes and approaches for strengthening CHW programmes.

RESULTS

CHWs are increasingly being recognized as a critical resource for achieving national and global health goals. These goals include achieving the health-related Sustainable Development Goals of Universal Health Coverage, ending preventable child and maternal deaths, and making a major contribution to the control of HIV, tuberculosis, malaria, and noncommunicable diseases. CHWs can also play a critical role in responding to current and future pandemics. For these reasons, we argue that CHWs are now at the dawn of a new era. While CHW programmes have long been an underfunded afterthought, they are now front and centre as the emerging foundation of health systems. Despite this increased attention, CHW programmes continue to face the same pressing challenges: inadequate financing, lack of supplies and commodities, low compensation of CHWs, and inadequate supervision. We outline approaches for strengthening CHW programmes, arguing that their enormous potential will only be realized when investment and health system support matches rhetoric. Rigorous monitoring, evaluation, and implementation research are also needed to enable CHW programmes to continuously improve their quality and effectiveness.

CONCLUSION

A marked increase in sustainable funding for CHW programmes is needed, and this will require increased domestic political support for prioritizing CHW programmes as economies grow and additional health-related funding becomes available. The paradigm shift called for here will be an important step in accelerating progress in achieving current global health goals and in reaching the goal of Health for All.

Intelligent Algorithm-Based Picture Archiving and Communication System of MRI Images and Radiology Information System-Based Medical Informatization

Objective

The study aimed to explore the application value of picture archiving and communication system (PCAS) of MRI images based on radial basis function (RBF) neural network algorithm combined with the radiology information system (RIS).

Methods

551 patients who required MRI examination in a hospital from May 2016 to May 2021 were selected as research subjects. Patients were divided into two groups according to their own wishes. Those who were willing to use the RBF neural network algorithm-based PCAS of MRI images combined with RIS were set as the combined group, involving a total of 278 cases; those who were unwilling were set as the regular group, involving a total of 273 cases. The RBF neural network algorithm-based PCAS of MRI images combined with RIS was trained and tested for classification performance and then used for comparison analysis.

Result

The actual output (0.031259–0.038515) of all test samples was almost the same as the target output (0.000000) (P > 0.05). In the first 50,000 learnings, the iteration error of the RBF neural network dropped rapidly and finally stabilized at 0.038. The classification accuracy of the RBF neural network algorithm-based PCAS of MRI images combined with RIS for the head was 94.28%, that of abdomen was 97.22%, and it was 93.10% for knee joint, showing no statistically significant differences (P > 0.05), and the total classification accuracy was as high as 95%. The time spent in the examination in the combined group was about 2 hours, and that in the regular group was about 4 hours (P > 0.05). The satisfaction of the combined group (96.76%) was significantly higher than that of the control group (46.89%) (P > 0.05).

Conclusion

The RBF neural network has good classification performance for MRI images. To incorporate intelligent algorithms into the medical information system can optimize the system. RBF has good application prospects in the medical information system, and it is worthy of continuous exploration.

Researching, co-creating and testing innovations in paper-based health information systems (PHISICC) to support health workers' decision-making: protocol of a multi-country, transdisciplinary, mixed-methods research programme in three sub-Saharan countries

Background

Health information systems are crucial to provide data for decision-making and demand for data is constantly growing. However, the link between data and decisions is not always rational or linear and the management of data ends up overloading frontline health workers, which may compromise quality of healthcare delivery. Despite limited evidence, there is an increasing push for the digitalization of health information systems, which poses enormous challenges, particularly in remote, rural settings in low- and middle-income countries. Paper-based tools will continue to be used in combination with digital solutions and this calls for efforts to make them more responsive to local needs. Paper-based Health Information Systems in Comprehensive Care (PHISICC) is a transdisciplinary, multi-country research initiative to create and test innovative paper-based health information systems in three sub-Saharan African countries.

Methods/Design

The PHISICC initiative is being carried out in remote, rural settings in Côte d’Ivoire, Mozambique and Nigeria through partnership with ministries of health and research institutions. We began with research syntheses to acquire the most up-to-date knowledge on health information systems. These were coupled with fieldwork in the three countries to understand the current design, patterns and contexts of use, and healthcare worker perspectives. Frontline health workers, with designers and researchers, used co-creation methods to produce the new PHISICC tools. This suite of tools is being tested in the three countries in three cluster-randomized controlled trials. Throughout the project, we have engaged with a wide range of stakeholders and have maintained the highest scientific standards to ensure that results are relevant to the realities in the three countries.

Discussion

We have deployed a comprehensive research approach to ensure the robustness and future policy uptake of findings. Besides the innovative PHISICC paper-based tools, our process is in itself innovative. Rather than emphasizing the technical dimensions of data management, we focused instead on frontline health workers’ data use and decision-making. By tackling the whole scope of primary healthcare areas rather than a subset of them, we have developed an entirely new design and visual language for a suite of tools across healthcare areas. The initiative is being tested in remote, rural areas where the most vulnerable live.

Does an innovative paper-based health information system (PHISICC) improve data quality and use in primary healthcare? Protocol of a multicountry, cluster randomised controlled trial in sub-Saharan African rural settings

INTRODUCTION

Front-line health workers in remote health facilities are the first contact of the formal health sector and are confronted with life-saving decisions. Health information systems (HIS) support the collection and use of health related data. However, HIS focus on reporting and are unfit to support decisions. Since data tools are paper-based in most primary healthcare settings, we have produced an innovative Paper-based Health Information System in Comprehensive Care (PHISICC) using a human-centred design approach. We are carrying out a cluster randomised controlled trial in three African countries to assess the effects of PHISICC compared with the current systems.

METHODS AND ANALYSIS

Study areas are in rural zones of Côte d'Ivoire, Mozambique and Nigeria. Seventy health facilities in each country have been randomly allocated to using PHISICC tools or to continuing to use the regular HIS tools. We have randomly selected households in the catchment areas of each health facility to collect outcomes' data (household surveys have been carried out in two of the three countries and the end-line data collection is planned for mid-2021). Primary outcomes include data quality and use, coverage of health services and health workers satisfaction; secondary outcomes are additional data quality and use parameters, childhood mortality and additional health workers and clients experience with the system. Just prior to the implementation of the trial, we had to relocate the study site in Mozambique due to unforeseen logistical issues. The effects of the intervention will be estimated using regression models and accounting for clustering using random effects.

ETHICS AND DISSEMINATION

Ethics committees in Côte d'Ivoire, Mozambique and Nigeria approved the trials. We plan to disseminate our findings, data and research materials among researchers and policy-makers. We aim at having our findings included in systematic reviews on health systems interventions and future guidance development on HIS.

TRIAL REGISTRATION NUMBER

PACTR201904664660639; Pre-results.

Strengthening routine health data analysis in Ethiopia: the Operational Research and Coaching for Analysts (ORCA) experience

Many routine health information systems (RHIS) show persistent gaps between recording and reporting data and their effective use in solving problems. Strengthening RHIS has become a global priority to track and address national health goals. In Ethiopia, the Ministry of Health and Bill & Melinda Gates Foundation introduced the Operational Research and Coaching for Analysts (ORCA) capacity development project, co-designed with the London School of Hygiene & Tropical Medicine, which delivered training, coaching and mentoring support. We present the development, experiences, and perceptions of ORCA as a mechanism to enhance data quality, analysis, interpretation and use. ORCA integrated capacity development activities into national data analysts’ routine workload over a period of 2 years. Participating analysts were drawn from across the Ministry of Health directorates and two of its closely aligned agencies: the Ethiopian Public Health Institute and the Ethiopian Pharmaceutical Supply Agency. We used mixed methods (knowledge questionnaire, semi-structured interviews, programme records) to document the fidelity, feasibility, reach, and acceptability of ORCA and identify early signs of improved knowledge and changing institutional practices. Thirty-six participants completed the programme. Working in interdisciplinary groups on specific national health indicators, they received training workshops and support for study design, fieldwork, and analysis to build skills in assessing data quality and interpreting findings relevant to policy. Personal development grants and laptops provided incentives for sustained engagement. Participants appreciated ORCA’s applied and practical approach as well as good communication from administrators and clear links to national strategy. They also expressed frustration with delays, difficulties prioritising project work over routine responsibilities, and lack of formal accreditation. Knowledge and analytic skills increased and participants were able to integrate experiences from the project into their future work. Health system managers saw potential in longer-term improvements in data analysis and application to policy, although no clear changes were observed yet.

Routine Health Information Systems in the European Context: A Systematic Review of Systematic Reviews

(1) Background: The aim of this study is to provide a better understanding of the requirements to improve routine health information systems (RHISs) for the management of health systems, including the identification of best practices, opportunities, and challenges in the 53 countries and territories of the WHO European region. (2) Methods: We conducted an overview of systematics reviews and searched the literature in the databases MEDLINE/PubMed, Cochrane, EMBASE, and Web of Science electronic databases. After a meticulous screening, we identified 20 that met the inclusion criteria, and RHIS evaluation results were presented according to the Performance of Routine Information System Management (PRISM) framework. (3) Results: The reviews were published between 2007 and 2020, focusing on the use of different systems or technologies and aimed to analyze interventions on professionals, centers, or patients' outcomes. All reviews examined showed variability in results in accordance with the variability of interventions and target populations. We have found different areas for improvement for RHISs according to the three determinants of the PRISM framework that influence the configuration of RHISs: technical, organizational, or behavioral elements. (4) Conclusions: RHIS interventions in the European region are promising. However, new global and international strategies and the development of tools and mechanisms should be promoted to highly integrate platforms among European countries.

Definitions, components and processes of data harmonisation in healthcare: a scoping review

BACKGROUND

Data harmonisation (DH) has emerged amongst health managers, information technology specialists and researchers as an important intervention for routine health information systems (RHISs). It is important to understand what DH is, how it is defined and conceptualised, and how it can lead to better health management decision-making. This scoping review identifies a range of definitions for DH, its characteristics (in terms of key components and processes), and common explanations of the relationship between DH and health management decision-making.

METHODS

This scoping review identified relevant studies from 2000 onwards (date filter), written in English and published in PubMed, Web of Science and CINAHL. Two reviewers independently screened records for potential inclusion for the abstract and full-text screening stages. One reviewer did the data extraction, analysis and synthesis, with built-in reliability checks from the rest of the team. We developed a narrative synthesis of definitions and explanations of the relationship between DH and health management decision-making.

RESULTS

We sampled 61 of 181 included to synthesis definitions and concepts of DH in detail. We identified six common terms for data harmonisation: record linkage, data linkage, data warehousing, data sharing, data interoperability and health information exchange. We also identified nine key components of data harmonisation: DH involves (a) a process of multiple steps; (b) integrating, harmonising and bringing together different databases (c) two or more databases; (d) electronic data; (e) pooling data using unique patient identifiers; and (f) different types of data; (g) data found within and across different departments and institutions at facility, district, regional and national levels; (h) different types of technical activities; (i) has a specific scope. The relationship between DH and health management decision-making is not well-described in the literature. Several studies mentioned health providers' concerns about data completeness, data quality, terminology and coding of data elements as barriers to data utilisation for clinical decision-making.

CONCLUSION

To our knowledge, this scoping review was the first to synthesise definitions and concepts of DH and address the causal relationship between DH and health management decision-making. Future research is required to assess the effectiveness of data harmonisation on health management decision-making.