Timeliness of reporting process in the national routine health information system: The case of 19-year experience of Field Health Services Information System in Palawan, the Philippines.

INTRODUCTION: Routine health information system (RHIS) has been repeatedly updated to provide quality information. However, its timeliness has rarely been tracked. This study investigated the reporting status and the timeliness of quarterly reports of the national RHIS in the Philippines, based on its 19 years-operation in Palawan. METHODS: We analyzed the timeliness of 94.7% (1568/1656) of the quarterly reports that we obtained the date of receipt submitted by 22 health centers in Palawan from 1996 to 2014. The RHIS update in 2008 increased the number of reporting items and extended the submission due date since 2009 while computerized 15 health centers since 2011. We performed Fisher's exact test to examine changing the proportion of timely reports and multiple comparisons with permutation tests for changing the mean of the quarterly median lead times, median delays and interquartile ranges (IQR), for four periods of different operational requirements in the RHIS. RESULTS: The update increased the timely reports from 6.7% (70/1045) to 22.4% (117/523) (p<0.001). The delay remained stable from 14.2 days to 16.1 days (p = 0.654). However, the IQR widened 2.31 times (p = 0.004) compared to 15.7. Despite the increased burden, the continued manual data processing decreased the delay by 7.1 days (p = 0.023) and remained the IQR stable at 1.19 times (p = 0.670), while 15 health centers were computerized, it increased the delay by 6.4 days (p = 0.037) and widened the IQR by 2.87 times (p = 0). CONCLUSIONS: More attention must be paid to controlling the timeliness of RHIS when we introduce new interventions and perform daily management. Extending the due date increased timely reports. However, introducing unfamiliar tasks increased delay and uncertainty in timeliness. In a low-resource setting, an effective intervention needs to consider modest operating procedure changes that extend the existing routines to which the staff in charge has already accustomed.

Systemic factors of errors in the case identification process of the national routine health information system: a case study of Modified Field Health Services Information System in the Philippines.

BACKGROUND: The 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. METHODS: A 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. RESULTS: None 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). CONCLUSIONS: The 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.