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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.

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.

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.