Evaluating and Enhancing the Fitness-for-Purpose of Electronic Health Record Data: Qualitative Study on Current Practices and Pathway to an Automated Approach Within the Medical Informatics for Research and Care in University Medicine Consortium.

BACKGROUND: Leveraging electronic health record (EHR) data for clinical or research purposes heavily depends on data fitness. However, there is a lack of standardized frameworks to evaluate EHR data suitability, leading to inconsistent quality in data use projects (DUPs). This research focuses on the Medical Informatics for Research and Care in University Medicine (MIRACUM) Data Integration Centers (DICs) and examines empirical practices on assessing and automating the fitness-for-purpose of clinical data in German DIC settings. OBJECTIVE: The study aims (1) to capture and discuss how MIRACUM DICs evaluate and enhance the fitness-for-purpose of observational health care data and examine the alignment with existing recommendations and (2) to identify the requirements for designing and implementing a computer-assisted solution to evaluate EHR data fitness within MIRACUM DICs. METHODS: A qualitative approach was followed using an open-ended survey across DICs of 10 German university hospitals affiliated with MIRACUM. Data were analyzed using thematic analysis following an inductive qualitative method. RESULTS: All 10 MIRACUM DICs participated, with 17 participants revealing various approaches to assessing data fitness, including the 4-eyes principle and data consistency checks such as cross-system data value comparison. Common practices included a DUP-related feedback loop on data fitness and using self-designed dashboards for monitoring. Most experts had a computer science background and a master's degree, suggesting strong technological proficiency but potentially lacking clinical or statistical expertise. Nine key requirements for a computer-assisted solution were identified, including flexibility, understandability, extendibility, and practicability. Participants used heterogeneous data repositories for evaluating data quality criteria and practical strategies to communicate with research and clinical teams. CONCLUSIONS: The study identifies gaps between current practices in MIRACUM DICs and existing recommendations, offering insights into the complexities of assessing and reporting clinical data fitness. Additionally, a tripartite modular framework for fitness-for-purpose assessment was introduced to streamline the forthcoming implementation. It provides valuable input for developing and integrating an automated solution across multiple locations. This may include statistical comparisons to advanced machine learning algorithms for operationalizing frameworks such as the 3×3 data quality assessment framework. These findings provide foundational evidence for future design and implementation studies to enhance data quality assessments for specific DUPs in observational health care settings.

[The Medical Informatics Initiative at a glance-establishing a health research data infrastructure in Germany]. / Die Medizininformatik-Initiative im Überblick ­ Aufbau einer Gesundheitsforschungsdateninfrastruktur in Deutschland.

The Medical Informatics Initiative (MII) funded by the Federal Ministry of Education and Research (BMBF) 2016-2027 is successfully laying the foundations for data-based medicine in Germany. As part of this funding, 51 new professorships, 21 junior research groups, and various new degree programs have been established to strengthen teaching, training, and continuing education in the field of medical informatics and to improve expertise in medical data sciences. A joint decentralized federated research data infrastructure encompassing the entire university medical center and its partners was created in the form of data integration centers (DIC) at all locations and the German Portal for Medical Research Data (FDPG) as a central access point. A modular core dataset (KDS) was defined and implemented for the secondary use of patient treatment data with consistent use of international standards (e.g., FHIR, SNOMED CT, and LOINC). An officially approved nationwide broad consent was introduced as the legal basis. The first data exports and data use projects have been carried out, embedded in an overarching usage policy and standardized contractual regulations. The further development of the MII health research data infrastructures within the cooperative framework of the Network of University Medicine (NUM) offers an excellent starting point for a German contribution to the upcoming European Health Data Space (EHDS), which opens opportunities for Germany as a medical research location.

Regulatory Issues in Electronic Health Records for Adolescent HIV Research: Strategies and Lessons Learned.

BACKGROUND: Electronic health records (EHRs) are a cost-effective approach to provide the necessary foundations for clinical trial research. The ability to use EHRs in real-world clinical settings allows for pragmatic approaches to intervention studies with the emerging adult HIV population within these settings; however, the regulatory components related to the use of EHR data in multisite clinical trials poses unique challenges that researchers may find themselves unprepared to address, which may result in delays in study implementation and adversely impact study timelines, and risk noncompliance with established guidance. OBJECTIVE: As part of the larger Adolescent Trials Network (ATN) for HIV/AIDS Interventions Protocol 162b (ATN 162b) study that evaluated clinical-level outcomes of an intervention including HIV treatment and pre-exposure prophylaxis services to improve retention within the emerging adult HIV population, the objective of this study is to highlight the regulatory process and challenges in the implementation of a multisite pragmatic trial using EHRs to assist future researchers conducting similar studies in navigating the often time-consuming regulatory process and ensure compliance with adherence to study timelines and compliance with institutional and sponsor guidelines. METHODS: Eight sites were engaged in research activities, with 4 sites selected from participant recruitment venues as part of the ATN, who participated in the intervention and data extraction activities, and an additional 4 sites were engaged in data management and analysis. The ATN 162b protocol team worked with site personnel to establish the necessary regulatory infrastructure to collect EHR data to evaluate retention in care and viral suppression, as well as para-data on the intervention component to assess the feasibility and acceptability of the mobile health intervention. Methods to develop this infrastructure included site-specific training activities and the development of both institutional reliance and data use agreements. RESULTS: Due to variations in site-specific activities, and the associated regulatory implications, the study team used a phased approach with the data extraction sites as phase 1 and intervention sites as phase 2. This phased approach was intended to address the unique regulatory needs of all participating sites to ensure that all sites were properly onboarded and all regulatory components were in place. Across all sites, the regulatory process spanned 6 months for the 4 data extraction and intervention sites, and up to 10 months for the data management and analysis sites. CONCLUSIONS: The process for engaging in multisite clinical trial studies using EHR data is a multistep, collaborative effort that requires proper advanced planning from the proposal stage to adequately implement the necessary training and infrastructure. Planning, training, and understanding the various regulatory aspects, including the necessity of data use agreements, reliance agreements, external institutional review board review, and engagement with clinical sites, are foremost considerations to ensure successful implementation and adherence to pragmatic trial timelines and outcomes.

Implementation of the electronic health record in the German healthcare system: an assessment of the current status and future development perspectives considering the potentials of health data utilisation by representatives of different stakeholder groups.

Introduction: The digitalisation of the German healthcare system enables a wide range of opportunities to utilize healthcare data. The implementation of the EHR in January 2021 was a significant step, but compared to other European countries, the implementation of the EHR in the German healthcare system is still at an early stage. The aim of this paper is to characterise the structural factors relating to the adoption of the EHR in more detail from the perspective of representatives of stakeholders working in the German healthcare system and to identify existing barriers to implementation and the need for change. Methods: Qualitative expert interviews were conducted with one representative from each of the stakeholder groups health insurance, pharmacies, healthcare research, EHR development and panel doctors. Results: The interviews with the various stakeholders revealed that the implementation process of the EHR is being delayed by a lack of a viable basis for decision-making, existing conflicts of interest and insufficient consideration of the needs of patients and service providers, among other things. Discussion: The current status of EHR implementation is due to deficiency in legal regulations as well as structural problems and the timing of the introduction. For instance, the access rights of various stakeholders to the EHR data and the procedure in the event of a technical failure of the telematics infrastructure are remain unclear. In addition, insufficient information and communication measures have not led to the desired acceptance of EHR use among patients and service providers.

Changing US Support for Public Health Data Use Through Pandemic and Political Turmoil.

Policy Points This study examines the impact of several world-changing events in 2020, such as the pandemic and widespread racism protests, on the US population's comfort with the use of identifiable data for public health. Before the 2020 election, there was no significant difference between Democrats and Republicans. However, African Americans exhibited a decrease in comfort that was different from other subgroups. Our findings suggest that the public remained supportive of public health data activities through the pandemic and the turmoil of 2020 election cycle relative to other data use. However, support among African Americans for public health data use experienced a unique decline compared to other demographic groups. CONTEXT: Recent legislative privacy efforts have not included special provisions for public health data use. Although past studies documented support for public health data use, several global events in 2020 have raised awareness and concern about privacy and data use. This study aims to understand whether the events of 2020 affected US privacy preferences on secondary uses of identifiable data, focusing on public health and research uses. METHODS: We deployed two online surveys-in February and November 2020-on data privacy attitudes and preferences using a choice-based-conjoint analysis. Participants received different data-use scenario pairs-varied by the type of data, user, and purpose-and selected scenarios based on their comfort. A hierarchical Bayes regression model simulated population preferences. FINDINGS: There were 1,373 responses. There was no statistically significant difference in the population's data preferences between February and November, each showing the highest comfort with population health and research data activities and the lowest with profit-driven activities. Most subgroups' data preferences were comparable with the population's preferences, except African Americans who showed significant decreases in comfort with population health and research. CONCLUSIONS: Despite world-changing events, including a pandemic, we found bipartisan public support for using identifiable data for public health and research. The decreasing support among African Americans could relate to the increased awareness of systemic racism, its harms, and persistent disparities. The US population's preferences support including legal provisions that permit public health and research data use in US laws, which are currently lacking specific public health use permissions.

A national evaluation analysis and expert interview study of real-world data sources for research and healthcare decision-making.

Real-world data (RWD) can provide intel (real-world evidence, RWE) for research and development, as well as policy and regulatory decision-making along the full spectrum of health care. Despite calls from global regulators for international collaborations to integrate RWE into regulatory decision-making and to bridge knowledge gaps, some challenges remain. In this work, we performed an evaluation of Austrian RWD sources using a multilateral query approach, crosschecked against previously published RWD criteria and conducted direct interviews with representative RWD source samples. This article provides an overview of 73 out of 104 RWD sources in a national legislative setting where major attempts are made to enable secondary use of RWD (e.g. law on the organisation of research, "Forschungsorganisationsgesetz"). We were able to detect omnipresent challenges associated with data silos, variable standardisation efforts and governance issues. Our findings suggest a strong need for a national health data strategy and data governance framework, which should inform researchers, as well as policy- and decision-makers, to improve RWD-based research in the healthcare sector to ultimately support actual regulatory decision-making and provide strategic information for governmental health data policies.

Repeated surveys of people who inject drugs: The exception, not the rule.

HIV surveillance is the continuous, systematic collection, analysis and interpretation of HIV-related data needed for the planning, implementation, and evaluation of the HIV response. Some communities are affected by HIV more than others and require more focused responses; one of these communities are people who inject drugs (PWID.) We reviewed HIV surveillance among PWID across all countries. We identified countries with specific repeated surveys among PWID using data submitted to the UNAIDS Global AIDS Monitoring system, supplemented by national reports from countries that do not report to UNAIDS. Countries with four or more surveys since 2011, with at least one since 2017, were sent a brief survey to ask the use and relevance of the collected data for their respective HIV responses and the challenges they foresaw. Thirty-two countries were polled, of which 17 responded. Respondents highlighted the utility of the surveys to measure HIV prevalence, antiretroviral treatment and other service use. Future funding and maintaining capacity to implement surveys are current or coming challenges.

Outcomes and Costs of the Transition From a Paper-Based Immunization System to a Digital Immunization System in Vietnam: Mixed Methods Study.

BACKGROUND: The electronic National Immunization Information System (NIIS) was introduced nationwide in Vietnam in 2017. Health workers were expected to use the NIIS alongside the legacy paper-based system. Starting in 2018, Hanoi and Son La provinces transitioned to paperless reporting. Interventions to support this transition included data guidelines and training, internet-based data review meetings, and additional supportive supervision visits. OBJECTIVE: This study aims to assess (1) changes in NIIS data quality and use, (2) changes in immunization program outcomes, and (3) the economic costs of using the NIIS versus the traditional paper system. METHODS: This mixed methods study took place in Hanoi and Son La provinces. It aimed to analyses pre- and postintervention data from various sources including the NIIS; household and health facility surveys; and interviews to measure NIIS data quality, data use, and immunization program outcomes. Financial data were collected at the national, provincial, district, and health facility levels through record review and interviews. An activity-based costing approach was conducted from a health system perspective. RESULTS: NIIS data timeliness significantly improved from pre- to postintervention in both provinces. For example, the mean number of days from birth date to NIIS registration before and after intervention dropped from 18.6 (SD 65.5) to 5.7 (SD 31.4) days in Hanoi (P<.001) and from 36.1 (SD 94.2) to 11.7 (40.1) days in Son La (P<.001). Data from Son La showed that the completeness and accuracy improved, while Hanoi exhibited mixed results, possibly influenced by the COVID-19 pandemic. Data use improved; at postintervention, 100% (667/667) of facilities in both provinces used NIIS data for activities beyond monthly reporting compared with 34.8% (202/580) in Hanoi and 29.4% (55/187) in Son La at preintervention. Across nearly all antigens, the percentage of children who received the vaccine on time was higher in the postintervention cohort compared with the preintervention cohort. Up-front costs associated with developing and deploying the NIIS were estimated at US $0.48 per child in the study provinces. The commune health center level showed cost savings from changing from the paper system to the NIIS, mainly driven by human resource time savings. At the administrative level, incremental costs resulted from changing from the paper system to the NIIS, as some costs increased, such as labor costs for supportive supervision and additional capital costs for equipment associated with the NIIS. CONCLUSIONS: The Hanoi and Son La provinces successfully transitioned to paperless reporting while maintaining or improving NIIS data quality and data use. However, improvements in data quality were not associated with improvements in the immunization program outcomes in both provinces. The COVID-19 pandemic likely had a negative influence on immunization program outcomes, particularly in Hanoi. These improvements entail up-front financial costs.

Attitude towards consent-free research use of personal medical data in the general German population.

Background: The design of appropriate consent procedures for the secondary use of personal health data is a key concern of current medical research. In Germany, the concept of 'data donation' has recently come into focus, defined as a legal entitlement to the research use of personal medical data without prior consent, combined with an easy-to-exercise right of the data subjects to opt-out. Methods: Standardized online interviews of 3,013 individuals, representative of the German online population, were conducted in August 2022 to determine their attitude towards data donation for medical research. Results: A majority of participants supported a consent-free data donation regulation, both for publicly funded (85.1%) and for private medical research (66.4%). Major predictors of a positive attitude towards data donation included (i) sufficient appreciation of the respective kind of research (i.e. public or private), (ii) a reciprocity attitude that patients who benefit from research have a duty to support research, and (iii) sufficient trust in data protection and data control. Conclusion: People's attitude towards data donation to medical research is generally positive in Germany and depends upon factors that can be curbed by legislation and internal rules of procedure. Worthy of note, designing data donation in the form of an opt-out regulation does not necessarily mean that the paradigm of informedness has to be abandoned. Rather the process of information provision must be shifted towards the creation of basic knowledge in the general population about the risks and benefits of data-intensive medical research ('health data literacy').

Intention to Use an Electronic Community Health Information System Among Health Extension Workers in Rural Northwest Ethiopia: Cross-Sectional Study Using the Unified Theory of Acceptance and Use of Technology 2 Model.

BACKGROUND: IT has brought remarkable change in bridging the digital gap in resource-constrained regions and advancing the health care system worldwide. Community-based information systems and mobile apps have been extensively developed and deployed to quantify and support health services delivered by community health workers. The success and failure of a digital health information system depends on whether and how it is used. Ethiopia is scaling up its electronic community health information system (eCHIS) to support the work of health extension workers (HEWs). For successful implementation, more evidence was required about the factors that may affect the willingness of HEWs to use the eCHIS. OBJECTIVE: This study aimed to assess HEWs' intentions to use the eCHIS for health data management and service provision. METHODS: A cross-sectional study design was conducted among 456 HEWs in 6 pilot districts of the Central Gondar zone, Northwest Ethiopia. A Unified Theory of Acceptance and Use of Technology model was used to investigate HEWs' intention to use the eCHIS. Data were cleaned, entered into Epi-data (version 4.02; EpiData Association), and exported to SPSS (version 26; IBM Corp) for analysis using the AMOS 23 Structural Equation Model. The statistical significance of dependent and independent variables in the model was reported using a 95% CI with a corresponding P value of <.05. RESULTS: A total of 456 HEWs participated in the study, with a response rate of 99%. The mean age of the study participants was 28 (SD 4.8) years. Our study revealed that about 179 (39.3%; 95% CI 34.7%-43.9%) participants intended to use the eCHIS for community health data generation, use, and service provision. Effort expectancy (ß=0.256; P=.007), self-expectancy (ß=0.096; P=.04), social influence (ß=0.203; P=.02), and hedonic motivation (ß=0.217; P=.03) were significantly associated with HEWs' intention to use the eCHIS. CONCLUSIONS: HEWs need to be computer literate and understand their role with the eCHIS. Ensuring that the system is easy and enjoyable for them to use is important for implementation and effective health data management.

Combining methods to conduct a systematic review and propose a conceptual and theoretical framework in socio-environmental research.

This study aims to present a combination of methods and propose robust theoretical and conceptual frameworks for solving socio-environmental issues. This proposal included the Problem, Intervention, Context, and Outcome (PICO) framework and Protocol and Reporting result with Search, Appraisal, Synthesis, and Analysis framework, and develop (PSALSAR) method through SODIP steps: (i) Systematic review and meta-analysis defining the study from guiding questions; (ii) Open-source related to software and data; (iii) Data visualization and design information; (iv) Identification of gaps, challenges and trends through automation and lexicometric analysis; and (v) Proposal of theoretical and conceptual frameworks. This proposal defines the steps as support to combine and systematize information necessary to facilitate the production of this type of document using open-access software in the visualization and design of information. All these steps are replicable and essential to propose a conceptual and theoretical framework to contribute to the construction of knowledge in socio-environmental research and to propose solutions by filling in the gaps. In summary, this combination of methods shows:•The use of SODIP steps provides robustness and efficiency in carrying out review studies, facilitating the way to propose theoretical or conceptual frameworks.•Choosing to use open-source tools is essential for better evaluation and visualization of qualitative and quantitative data in review studies.•The combination of methods and data in the systematic review (scientific, political documents. and databases) supports the proposal of robust theoretical and conceptual frameworks.

Achieving Procedural Parity in Managing Access to Genomic and Related Health Data: A Global Survey of Data Access Committee Members.

Data access committees (DACs) are critical players in the data sharing ecosystem. DACs review requests for access to data held in one or more repositories and where specific constraints determine how the data may be used and by whom. Our team surveyed DAC members affiliated with genomic data repositories worldwide to understand standard processes and procedures, operational metrics, bottlenecks, and efficiencies, as well as their perspectives on possible improvements to quality review. We found that DAC operations and systemic issues were common across repositories globally. In general, DAC members endeavored to achieve an appropriate balance of review efficiency, quality, and compliance. Our results suggest a similarly proportionate path forward that helps DACs pursue mutual improvements to efficiency and compliance without sacrificing review quality.

National routine data for low birthweight and preterm births: Systematic data quality assessment for United Nations member states (2000-2020).

OBJECTIVE: Low birthweight (<2500 g) and preterm birth (<37 weeks) are markers of newborn vulnerability. To facilitate informed decisions about investments in prevention and care, it is imperative to enhance data quality and use. Hence, the objective of this study is to systematically assess the quality of data concerning low birthweight and preterm births within routine administrative data sources. DESIGN: Systematic data quality assessment by adopting the WHO Data Quality Framework. SETTING: National routine data system from UN member states. POPULATION: Livebirths. METHODS: National routine administrative data on low birthweight and preterm births for 195 countries from 2000 to 2020 were systematically collated, totalling >700 million live births. The WHO data quality framework was adapted to undertake standardised data quality assessments. MAIN OUTCOME MEASURES: Availability, reporting quality, internal and external consistency of low birthweight and preterm data. RESULTS: Most United States Member States (64%: 124/195) had national data on low birthweight and (40%: 82/195) had data on preterm birth. Routine data system reporting was highest in North America, Australasia and Europe, where more than 95% live births had data on low birthweight and over 75% had data preterm births. In contrast, data reporting was lowest in sub-Saharan Africa (13% for low birthweight, 8% for preterm births) and Southern Asia (16% for low birthweight, 5% for preterm births). Most countries collect individual-level data; but, aggregate data reporting from hospital-based systems remain common in sub-Saharan Africa and Southern Asia. While data quality was generally high in North America, Australasia and Europe, gaps remain in the availability of gestational age metadata. Consistency between low birthweight and preterm rates were poor in Southern Asia and sub-Saharan Africa regions across time. There was high external consistency between low birthweight rates obtained from routine administrative data compared with low birthweight rates obtained from survey data for countries with high data quality. CONCLUSIONS: Sub-Saharan Africa and South Asia countries have data gaps but also opportunities for rapid progress. Most births occure in facilities, electronic health information systems already include low birthweight, and adding accurate gestational age including with ultrasound assessment is becoming increasingly attainable. Moving toward the collection of individual level data would enable monitoring of quality of care and longer-term outcomes. This is crucial for every child and family and essential for measuring progress towards relevant sustainable development goals. The assessment will inform countries' actions for data quality improvement at national level and use of data for impact.

Public Preferences for Digital Health Data Sharing: Discrete Choice Experiment Study in 12 European Countries.

BACKGROUND: With new technologies, health data can be collected in a variety of different clinical, research, and public health contexts, and then can be used for a range of new purposes. Establishing the public's views about digital health data sharing is essential for policy makers to develop effective harmonization initiatives for digital health data governance at the European level. OBJECTIVE: This study investigated public preferences for digital health data sharing. METHODS: A discrete choice experiment survey was administered to a sample of European residents in 12 European countries (Austria, Denmark, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) from August 2020 to August 2021. Respondents answered whether hypothetical situations of data sharing were acceptable for them. Each hypothetical scenario was defined by 5 attributes ("data collector," "data user," "reason for data use," "information on data sharing and consent," and "availability of review process"), which had 3 to 4 attribute levels each. A latent class model was run across the whole data set and separately for different European regions (Northern, Central, and Southern Europe). Attribute relative importance was calculated for each latent class's pooled and regional data sets. RESULTS: A total of 5015 completed surveys were analyzed. In general, the most important attribute for respondents was the availability of information and consent during health data sharing. In the latent class model, 4 classes of preference patterns were identified. While respondents in 2 classes strongly expressed their preferences for data sharing with opposing positions, respondents in the other 2 classes preferred not to share their data, but attribute levels of the situation could have had an impact on their preferences. Respondents generally found the following to be the most acceptable: a national authority or academic research project as the data user; being informed and asked to consent; and a review process for data transfer and use, or transfer only. On the other hand, collection of their data by a technological company and data use for commercial communication were the least acceptable. There was preference heterogeneity across Europe and within European regions. CONCLUSIONS: This study showed the importance of transparency in data use and oversight of health-related data sharing for European respondents. Regional and intraregional preference heterogeneity for "data collector," "data user," "reason," "type of consent," and "review" calls for governance solutions that would grant data subjects the ability to control their digital health data being shared within different contexts. These results suggest that the use of data without consent will demand weighty and exceptional reasons. An interactive and dynamic informed consent model combined with oversight mechanisms may be a solution for policy initiatives aiming to harmonize health data use across Europe.

Transforming the Information System for Research in Primary Care (SIDIAP) in Catalonia to the OMOP Common Data Model and Its Use for COVID-19 Research.

Purpose: The primary aim of this work was to convert the Information System for Research in Primary Care (SIDIAP) from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Our second aim was to provide a descriptive analysis of COVID-19-related outcomes among the general population. Patients and Methods: We mapped patient-level data from SIDIAP to the OMOP CDM and we performed more than 3,400 data quality checks to assess its readiness for research. We established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or tested positive for, hospitalised with, admitted to intensive care units (ICU) with, died with, or vaccinated against COVID-19 up to 30th June 2022. Results: After verifying the high quality of the transformed dataset, we included 5,870,274 individuals in the general population cohort. Of those, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation, 5,642 had an ICU admission, and 11,233 died with COVID-19. A total of 4,584,515 received a COVID-19 vaccine. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised and those who died. Conclusion: We successfully transformed SIDIAP to the OMOP CDM. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19-related outcomes over time were described. The transformed SIDIAP database is a valuable resource that can enable distributed network research in COVID-19 and beyond.

Improving data use in decision-making and utilization of maternal healthcare services through a data-informed platform for health approaches in districts of the Gedeo Zone, southern Ethiopia, 2023: a cluster-randomized control trial.

Background: In low-resource countries such as Ethiopia, the utilization of local data for planning and decision-making health systems was frequently constrained. In addition, despite several government initiatives, maternal health services were not completely utilized. On the other hand, efforts to effectively utilize the local data available to improve the utilization level of maternal healthcare services were insufficient, necessitating the need for a different approach. Objective: This implementation study aims to test and validate the effectiveness of a data-informed platform for health (DIPH) strategies on data use for decision-making and utilization of maternal health services in districts of the Gedeo Zone, southern Ethiopia. Methods: A two-arm parallel group, type II hybrid, cluster-randomized control trial design has been implemented to conduct the study between 1 September 2022 and 29 February 2024. Six woredas/districts have been assigned to the intervention arm and the other six to the control arm. Baseline and end-line data have been collected from 120 eligible health management staff (from both intervention arm and control arm). In the intervention arm, district health management staff have been given specialized training and continuous technical assistance as a package called the DIPH strategy by embedding it with the district's current decision-making platform such as Performance Review Team meetings. The DIPH strategy has mainly focused on five-step approaches such as situational assessment, stakeholder engagement, defining/setting priorities, planning, and follow-up. Health management staff in the control arm have performed their regular daily activities. The χ2 and t-tests have been used to check the effect of the intervention. In addition, difference-in-differences estimates have been calculated because the change may inherently occur over time. A P-value of <0.05 and a 95% confidence interval have been used to declare the significance of the intervention. Discussion: The findings of this study were supposed to give insights into implementation strategies that improve data use in decision-making and utilization of maternal healthcare services at the woreda level and uncover contextual factors that boost the response of these strategies.

Utilization of health data and associated factors among department heads in public health facilities in Eastern Ethiopia: A cross-sectional study in Harari region.

INTRODUCTION: Even though the information generated by routine health information systems is an essential element in the process of transforming the health sector, the information is systematically under-utilized by the health workers. Hence, this study was aimed to assess the utilization level and associated factors of routine health information system data among department heads in Eastern Ethiopia. METHODS: The cross-sectional study design was conducted among heads of departments in the health facilities of Harari region. The source populations and the study populations were all department heads. The data were collected by standardized tools through interviews, observations, and document reviews. The data were entered into Epi Data version 3.1 and then exported to SPSS version 25 for analysis. Multivariable logistic regression was performed to identify the associated factors and P-value < 0.05 was used to declare the statistically significant association. RESULT: Of the respondents, 51.8 % live in urban, 82.4 % participated in performance review meeting, 61.7 % received feedback, 80.6 % engage in HIS, and 91 % feel responsible to HIS. Routine health information system data utilization among department heads was 177 (79.7 %); 95 % CI: [73.8 %, 84.8 %] in the Harari region. Factors associated with data utilization were urban residence (AOR = 2.891; 95 %CI: 1.147-7.286), getting feedback (AOR = 3.136; 95 %CI: 1.311-7.499), active engagement in health information system activities (AOR = 2.560; 95 %CI: 1.010-6.490), participation in performance review meeting (AOR = 3.847; 95 %CI: 1.563-9.464), and feeling responsibility (AOR = 3.727; 95 %CI: 1.071-12.961). CONCLUSION: Level of data use in this study was higher than the one in other studies in Ethiopia. Residence, feedback, level of engagement in health information system activities, sense of responsibility towards health information system, and performance review meeting were the determinants of data utilization. Important attention should be given by the officials at various levels to expand the information communication technology infrastructures and strengthen the feedback system.

Proceedings from the CIHLMU 2022 Symposium: "Availability of and Access to Quality Data in Health".

Data is an essential tool for valid and reliable healthcare management. Access to high-quality data is critical to ensuring the early identification of problems, the design of appropriate interventions, and the effective implementation and evaluation of health intervention outcomes. During the COVID-19 pandemic, the need for strong information systems and the value of producing high-quality data for timely response and tracking resources and progress have been very evident across countries. The availability of and access to high-quality data at all levels of the health systems of low and middle-income countries is a challenge, which is exacerbated by multiple parallels and poorly integrated data sources, a lack of data-sharing standards and policy frameworks, their weak enforcement, and inadequate skills among those handling data. Completeness, accuracy, integrity, validity, and timeliness are challenges to data availability and use. "Big Data" is a necessity and a challenge in the current complexities of health systems. In transitioning to digital systems with proper data standards and policy frameworks for privacy protection, data literacy, ownership, and data use at all levels of the health system, skill enhancement of the staff is critical. Adequate funding for strengthening routine information systems and periodic surveys and research, and reciprocal partnerships between high-income countries and low- and middle-income countries in data generation and use, should be prioritized by the low- and middle-income countries to foster evidence-based healthcare practices.