Attributes and consequences of health information systems data for antenatal care : Health status, health system performance and policy

Background: A routine health information system (RHIS) serves as an important source of data for monitoring health of clients and health system performance. All countries use RHIS data for some form of priority setting; the extent of use varies across settings depending on the nature and availability of data. In the West Bank, Palestine, the paper-based routine health information system consisting of manually aggregated data is currently undergoing a transformation to an electronic health registry (eRegistry) consisting of individual-level data collected at the point-of-care for antenatal care services in primary healthcare. Aim: The overall aim of the present study was to examine the consequences of the transformation from the existing RHIS based on manual aggregation, to an RHIS based on clinical records data for calculations of routine indicators and health system performance indicators. Various aspects of anticipated data-related changes were examined in the three papers constituting this PhD dissertation. In paper I, we calculated the routinely reported indicators from individual-level clinical data from antenatal paper records, and compared the values to the existing aggregate RHIS reports. In paper II, we calculated the coverage of at least one screening, coverage of appropriate number of screenings, and effective coverage of timely and appropriate screening of antenatal care interventions in public primary healthcare clinics, and explored selected infrastructure-related and maternal sociodemographic factors potentially associated with effective coverage. In paper III, we assessed the implications of using different available data sources in the health data ecosystem for modeling the scale up of antenatal care interventions in the Lives Saved Tool. Materials and methods: Four data sources were used. First, manually aggregated RHIS reports submitted by care providers for primary healthcare clinics were retrieved (2015). Second, a cross-sectional study was conducted, where data were extracted from paper-based clinical records of women attending antenatal care (2015) from a random sample of public primary healthcare clinics. Third, secondary data were exported from the eRegistry electronic clinical records (2017). Fourth, data were obtained from the Palestinian multiple indicator cluster survey (2014). Using the paper-based clinical records data, routinely reported indicators were calculated and compared to the aggregate RHIS reports (paper I). Data from paper-based clinical records were also used to generate coverage of clinical antenatal care interventions (paper II). All four sources of data were used to calculate distinct sets of values of input indicators in the Lives Saved Tool, and the mortality and morbidity averted through the scale-up of antenatal care interventions was modeled (paper III). Results: Paper I: The values of the routinely reported indicators were significantly different when computed with clinical records data, compared to aggregate RHIS reports. The magnitude of the difference varied across indicators. There was divergence in the coverage of anemia screening between the clinical records data and aggregate RHIS reports. Paper II: Effective coverage of antenatal care interventions was considerably lower than the coverage of at least one screening and coverage of the appropriate number of screenings for antenatal care interventions. Timely attendance at antenatal care in the clinics was low. Effective coverage of antenatal care interventions was higher in clinics with laboratory and ultrasound. Paper III: All indicators required for input in the Lives Saved Tool could be calculated directly from the clinical records. The various sources of data yielded notably different results for the number of deaths averted. With clinical records data, the number of maternal deaths, stillbirths, and anemia cases that could be averted with the scale-up of health interventions were higher compared to the RHIS aggregate reports and the multiple indicator cluster survey. Each of the data sources also yielded varying compositions of antenatal care interventions averting deaths. Conclusions: The transition from an RHIS based on manual aggregations to an RHIS based on individual-level clinical records data will lead to significant changes in the values of routinely-reported indicators, and the understanding of health system performance of antenatal care. Health systems managers should be aware of the underlying mechanisms of data-related changes. Paper I: Reliable and complete routine indicators can be generated when clinical records data are directly used for automated computations. In such a system, transcription errors involved in diagnosis and referral, and manual counting and application of indicator definitions are minimized, and the existing complex reporting structure can be circumvented. Paper II: The metric used to quantify antenatal care service provision has consequences for the understanding of health system performance. Effective coverage of antenatal care interventions in public clinics can be increased by improving the provision of care according to recommended guidelines, including timely ANC attendance. Paper III: The demonstrated variability in the Lives Saved Tool model output from using the various data sources highlights the importance of understanding the characteristics of data available in a health information system by program managers that use such planning tools for decision-making