Abstract
BackgroundThe quality of data in national health information systems has been questionable in most developing countries. However, the mechanisms of errors in the case identification process are not fully understood. This study aimed to investigate the mechanisms of errors in the case identification process in the existing routine health information system (RHIS) in the Philippines by measuring the risk of committing errors for health program indicators used in the Field Health Services Information System (FHSIS 1996), and characterizing those indicators accordingly.MethodsA structured questionnaire on the definitions of 12 selected indicators in the FHSIS was administered to 132 health workers in 14 selected municipalities in the province of Palawan. A proportion of correct answers (difficulty index) and a disparity of two proportions of correct answers between higher and lower scored groups (discrimination index) were calculated, and the patterns of wrong answers for each of the 12 items were abstracted from 113 valid responses.ResultsNone of 12 items reached a difficulty index of 1.00. The average difficulty index of 12 items was 0.266 and the discrimination index that showed a significant difference was 0.216 and above. Compared with these two cut-offs, six items showed non-discrimination against lower difficulty indices of 0.035 (4/113) to 0.195 (22/113), two items showed a positive discrimination against lower difficulty indices of 0.142 (16/113) and 0.248 (28/113), and four items showed a positive discrimination against higher difficulty indices of 0.469 (53/113) to 0.673 (76/113).ConclusionsThe results suggest three characteristics of definitions of indicators such as those that are (1) unsupported by the current conditions in the health system, i.e., (a) data are required from a facility that cannot directly generate the data and, (b) definitions of indicators are not consistent with its corresponding program; (2) incomplete or ambiguous, which allow several interpretations; and (3) complete yet easily misunderstood by health workers.Taking systemic factors into account, the case identification step needs to be reviewed and designed to generate intended data in health information systems.
Highlights
The quality of data in national health information systems has been questionable in most developing countries
This study aimed to investigate the mechanisms of committing errors in the case identification step in the existing routine health information system (RHIS) by measuring the level and disparity of health workers’ understanding of health program indicators used in the Field Health Services Information System (1996 version) in the Philippines, and characterizing those indicators
The present study described three characteristics of definitions of indicators in the case identification step of RHIS such as those that are (1) unsupported by the current conditions in the health system, i.e., (a) data are required from a facility that cannot directly generate the data and, (b) definitions of indicators are not consistent with its corresponding program; (2) incomplete or ambiguous, which allow several interpretations; and (3) complete yet misunderstood by health workers
Summary
The quality of data in national health information systems has been questionable in most developing countries. Problems have been repeatedly reported on RHIS, such as (a) unreliable data [2,3], (b) incomplete and delayed reports [4,5], (c) putting too much burden on health workers [6,7] and (d) low use of data [8] This situation hampers evidence-based decision-making, especially in local health systems that depend on data available mostly on RHIS. DOH-National Epidemiology Center has made continual interventions, such as computerization of data-handling processes, simplification of indicators and revision of standardized forms Despite these efforts, effective ways to improve the quality of data in FHSIS remain unclear [13]
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