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Abstract Background Routine Health Information Systems data should be used in a systematic and institutionalised manner to support the making of plans, the monitoring of plans and in supportive supervision. To explore to what extent there is discussion about the linkage between planning, monitoring and supervision of sub-national programs using routine data we conducted a scoping review. The review question was: How are routine health information systems used in developing and monitoring health plans at district and facility level? Methods From a search of Ovid Medline (all), EMBASE and Web of Science along with a review of grey literature and involving a number of key stakeholders in identifying any missing resources a total of over 2200 documents were reviewed and data from 13 documents were extracted. Results Overall, there are many descriptions of how to implement and strengthen systems, ways to assess and improve data availability and quality, tools to improve the data use context, training in data use and mechanisms to involve stakeholders and strengthen infrastructure. However, there are gaps in examples of routine health data being used in the development, monitoring and supervision of plans at district and facility level. Conclusions There appears to be no institutionalised obligation of planners to monitor plans, very little guidance on how to practically monitor programs and minimal discussion about how to use the routinely available data to supportively supervise the implementation of the plans. To overcome these shortcomings, we recommend that practical procedures to ensure linkage of existing district plans to regular monitoring of priority programs are institutionalised, that mechanisms for making managers institutionally accountable for monitoring and supervising these plans are put in place, and that practical guidelines for linking plans with routine health information system data and regular monitoring and supportive supervision are developed.

Background: Routine Health Information Systems data should be used in a systematic and institutionalised manner to support the making of plans, the monitoring of plans and in supportive supervision. To explore to what extent there is discussion about the linkage between planning, monitoring and supervision of sub-national programs using routine data we conducted a scoping review. The review question was: How are routine health information systems used in developing and monitoring health plans at district and facility level? Methods: From a search of Ovid Medline (all), EMBASE and Web of Science along with a review of grey literature and involving a number of key stakeholders in identifying any missing resources a total of over 2200 documents were reviewed and data from 13 documents were extracted. Results: Overall, there are many descriptions of how to implement and strengthen systems, ways to assess and improve data availability and quality, tools to improve the data use context, training in data use and mechanisms to involve stakeholders and strengthen infrastructure. However, there are gaps in examples of routine health data being used in the development, monitoring and supervision of plans at district and facility level. Conclusions: There appears to be no institutionalised obligation of planners to monitor plans, very little guidance on how to practically monitor programs and minimal discussion about how to use the routinely available data to supportively supervise the implementation of the plans. To overcome these shortcomings, we recommend that practical procedures to ensure linkage of existing district plans to regular monitoring of priority programs are institutionalised, that mechanisms for making managers institutionally accountable for monitoring and supervising these plans are put in place, and that practical guidelines for linking plans with routine health information system data and regular monitoring and supportive supervision are developed. [ABSTRACT FROM AUTHOR]

Abstract COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People’s Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions.

COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People's Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions. [ABSTRACT FROM AUTHOR]

Abstract Background Increasing the performance of routine health information systems (RHIS) is an important policy priority both globally and in Senegal. As RHIS data become increasingly important in driving decision-making in Senegal, it is imperative to understand the factors that determine their use. Methods Semi-structured interviews were conducted with 18 high- and mid-level key informants active in the malaria, tuberculosis and HIV programmatic areas in Senegal. Key informants were employed in the relevant divisions of the Senegal Ministry of Health or nongovernmental / civil society organizations. We asked respondents questions related to the flow, quality and use of RHIS data in their organizations. A framework approach was used to analyze the qualitative data. Results Although the respondents worked at the strategic levels of their respective organizations, they consistently indicated that data quality and data use issues began at the operational level of the health system before the data made its way to the central level. We classify the main identified barriers and facilitators to the use of routine data into six categories and attempt to describe their interrelated nature. We find that data quality is a central and direct determinant of RHIS data use. We report that a number of upstream factors in the Senegal context interact to influence the quality of routine data produced. We identify the sociopolitical, financial and system design determinants of RHIS data collection, dissemination and use. We also discuss the organizational and infrastructural factors that influence the use of RHIS data. Conclusions We recommend specific prescriptive actions with potential to improve RHIS performance in Senegal, the quality of the data produced and their use. These actions include addressing sociopolitical factors that often interrupt RHIS functioning in Senegal, supporting and motivating staff that maintain RHIS data systems as well as ensuring RHIS data completeness and representativeness. We argue for improved coordination between the various stakeholders in order to streamline RHIS data processes and improve transparency. Finally, we recommend the promotion of a sustained culture of data quality assessment and use.

Abstract Background Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years, and that there is a growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications. Methods Using terms ‘routine health information system’, ‘health information system’, or ‘health management information system’ and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 202,019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed for inclusion based on pre-determined eligibility criteria and study characteristics were extracted from included articles using a piloted data extraction form. Results We identified 132 studies that met our inclusion criteria, originating in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan Africa and were published within the last 5 years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored. Conclusions Our study identified an increasing use of RHIS data for research purposes, with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessing services, and epidemiological studies in LMICs. RHIS data represent an underused source of data and should be made more available and further embraced by the research community in LMIC health systems.

Background: Increasing the performance of routine health information systems (RHIS) is an important policy priority both globally and in Senegal. As RHIS data become increasingly important in driving decision-making in Senegal, it is imperative to understand the factors that determine their use. Methods: Semi-structured interviews were conducted with 18 high- and mid-level key informants active in the malaria, tuberculosis and HIV programmatic areas in Senegal. Key informants were employed in the relevant divisions of the Senegal Ministry of Health or nongovernmental / civil society organizations. We asked respondents questions related to the flow, quality and use of RHIS data in their organizations. A framework approach was used to analyze the qualitative data. Results: Although the respondents worked at the strategic levels of their respective organizations, they consistently indicated that data quality and data use issues began at the operational level of the health system before the data made its way to the central level. We classify the main identified barriers and facilitators to the use of routine data into six categories and attempt to describe their interrelated nature. We find that data quality is a central and direct determinant of RHIS data use. We report that a number of upstream factors in the Senegal context interact to influence the quality of routine data produced. We identify the sociopolitical, financial and system design determinants of RHIS data collection, dissemination and use. We also discuss the organizational and infrastructural factors that influence the use of RHIS data. Conclusions: We recommend specific prescriptive actions with potential to improve RHIS performance in Senegal, the quality of the data produced and their use. These actions include addressing sociopolitical factors that often interrupt RHIS functioning in Senegal, supporting and motivating staff that maintain RHIS data systems as well as ensuring RHIS data completeness and representativeness. We argue for improved coordination between the various stakeholders in order to streamline RHIS data processes and improve transparency. Finally, we recommend the promotion of a sustained culture of data quality assessment and use. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years, and that there is a growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications.Methods: Using terms 'routine health information system', 'health information system', or 'health management information system' and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 202,019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed for inclusion based on pre-determined eligibility criteria and study characteristics were extracted from included articles using a piloted data extraction form.Results: We identified 132 studies that met our inclusion criteria, originating in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan Africa and were published within the last 5 years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored.Conclusions: Our study identified an increasing use of RHIS data for research purposes, with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessing services, and epidemiological studies in LMICs. RHIS data represent an underused source of data and should be made more available and further embraced by the research community in LMIC health systems. [ABSTRACT FROM AUTHOR]

Health decision-making is heavily premised on routinely reported data from lower levels of healthcare delivery to the national level. The reported data are of best use if their quality is high. Unfortunately, in many resource-limited settings in sub-Saharan Africa, the quality of reported data is often poor. Among the reasons attributed for poor data quality is use of sub-optimal modalities for collecting and transmitting data, such as paper-based and Short Message Service (SMS). Through a user-centered approach, we developed and implemented an Unstructured Supplementary Service Data (USSD)-based health data reporting intervention in a district in Uganda. The impact of the developed system on report accuracy, timeliness and completeness was evaluated against the expected 100% rates by the Ministry of Health (MoH). A total of 224 reports were submitted over the two-month study period. Of the submitted reports, 171 (76.3%) were complete (p < 0.0001) compared to MoH's required 100%). 161 (71.9%) were accurate (P < 0.0001), and 158 (70.5%) of the reports were submitted on time (p<0.0001). The deficiencies were largely attributed to a few facilities, as only 17.9% of facilities had data discrepancies with a mean of -2.11 (P=0.38), 96.4% (0.130) of the facilities had complete reports and 87.4% (0.100) of the facilities reported on time. Poor network coverage was an outstanding challenge to reporting. [ABSTRACT FROM AUTHOR]

Background: Improving a health system requires data, but too often they are unused or under-used by decision makers. Without interventions to improve the use of data in decision making, health systems cannot meet the needs of the populations they serve. In 2008, in Côte d'Ivoire, data were largely unused in health decision-making processes. Objective: To implement and evaluate an intervention to improve the use of data in decision making in Cote d'Ivoire. Design: From 2008 to 2012, Cote d'Ivoire sought to improve the use of national health data through an intervention that broadens participation in and builds links between data collection and decision-making processes; identifies information needs; improves data quality; builds capacity to analyze, synthesize, and interpret data; and develops policies to support data use. To assess the results, a Performance of Routine Information System Management Assessment was conducted before and after the intervention using a combination of purposeful and random sampling. In 2008, the sample consisted of the central level, 12 districts, and 119 facilities, and in 2012, the sample consisted of the central level, 20 districts, and 190 health facilities. To assess data use, we developed dichotomous indicators: discussions of analysis findings, decisions taken based on the analysis, and decisions referred to upper management for action. We aggregated the indicators to generate a composite, continuous index of data use. Results: From 2008 to 2012, the district data-use score increased from 40 to 70%; the facility score remained the same – 38%. The central score is not reported, because of a methodological difference in the two assessments. Conclusions: The intervention improved the use of data in decision making at the district level in Côte d'Ivoire. This study provides an example of, and guidance for, implementing a large-scale intervention to improve data-informed decision making.

Background: Improving a health system requires data, but too often they are unused or under-used by decision makers. Without interventions to improve the use of data in decision making, health systems cannot meet the needs of the populations they serve. In 2008, in Coˆte d’Ivoire, data were largely unused in health decision-making processes. Objective: To implement and evaluate an intervention to improve the use of data in decision making in Cote d’Ivoire. Design: From 2008 to 2012, Cote d’Ivoire sought to improve the use of national health data through an intervention that broadens participation in and builds links between data collection and decision-making processes; identifies information needs; improves data quality; builds capacity to analyze, synthesize, and interpret data; and develops policies to support data use. To assess the results, a Performance of Routine Information System Management Assessment was conducted before and after the intervention using a combination of purposeful and random sampling. In 2008, the sample consisted of the central level, 12 districts, and 119 facilities, and in 2012, the sample consisted of the central level, 20 districts, and 190 health facilities. To assess data use, we developed dichotomous indicators: discussions of analysis findings, decisions taken based on the analysis, and decisions referred to upper management for action. We aggregated the indicators to generate a composite, continuous index of data use. Results: From 2008 to 2012, the district data-use score increased from 40 to 70%; the facility score remained the same 38%. The central score is not reported, because of a methodological difference in the two assessments. Conclusions: The intervention improved the use of data in decision making at the district level in Coˆte d’Ivoire. This study provides an example of, and guidance for, implementing a large-scale intervention to improve data-informed decision making. [ABSTRACT FROM AUTHOR]

Health facility data are a critical source of local and continuous health statistics. Countries have introduced web-based information systems that facilitate data management, analysis, use and visualisation of health facility data. Working with teams of Ministry of Health and country public health institutions analysts from 14 countries in Eastern and Southern Africa, we explored data quality using national-level and subnational-level (mostly district) data for the period 2013-2017. The focus was on endline analysis where reported health facility and other data are compiled, assessed and adjusted for data quality, primarily to inform planning and assessments of progress and performance. The analyses showed that although completeness of reporting was generally high, there were persistent data quality issues that were common across the 14 countries, especially at the subnational level. These included the presence of extreme outliers, lack of consistency of the reported data over time and between indicators (such as vaccination and antenatal care), and challenges related to projected target populations, which are used as denominators in the computation of coverage statistics. Continuous efforts to improve recording and reporting of events by health facilities, systematic examination and reporting of data quality issues, feedback and communication mechanisms between programme managers, care providers and data officers, and transparent corrections and adjustments will be critical to improve the quality of health statistics generated from health facility data., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.)