Abstract of Dissertation

Keyword : Health Management Information System (HMIS); Key Performance Indicator (KPI); Delivery Points; Data discrepancy

Background : Managers require a good quality data for evidence based decision making and future planning. There is always need of new facility and strengthening of existing delivery points. To identifies the potential facilities for upgradation, mapping has to be done which requires quality data. HMIS is a good source of data. Health Management Information System (HMIS) is web based system which generate predetermined indicators across different level of facilities based on a set of registers and other source documents at facilities. Thus it captures the data of all the delivery points and non-delivery points. Flow of data starts from the facility level through HMIS format which is 3 compiled at Block data operator in the HMIS portal and forwarded to the district and then further to the state. Key Performance Indicator (KPI) is a tool used for the assessment of performance of designated delivery points. It generates set of data giving information about delivery status, Human resource and commodity availability in the facility. Thus it captures the data of all the delivery points. Flow of data is similar to HMIS but it is a paper based reporting and format used is KPI format Since KPI reports data of delivery points and HMIS report data of all facilities both should have no discrepancies and following condition should be fulfilled-1) HMIS should include all the delivery points listed in KPI. 2) Total number of deliveries reported in HMIS >= Total number of deliveries reported in KPI. 3) Delivery points matched both in HMIS and KPI should have same number of deliveries. But the quality of data is questionable. Hence a study is required.

Methodology : To assess the data quality of HMIS, data was triangulated with data of KPI using common indicator which is “Number of deliveries conducted in the facility”. To do this exercise data of KPI of last financial 2014-15 was collected from blocks through email. HMIS data was extracted from the HMIS portal. To validate the data of both the sources primary data of deliveries were collected from the facility delivery register of last financial year and was compared. Data analysis was done using MS excel

Findings : During this study, it was found that there is inconsistency in the data of HMIS and KPI either due to missing data or due to reporting error. Though all the delivery points listed in the KPI also existed in HMIS but there was difference in the data. Data was compared on month wise and block wise basis. In both ways, HMIS data was less than the KPI data which was indicative reporting error i.e. either over reporting or under reporting. The third condition, that delivery data of HMIS and KPI of delivery point should have no discrepancies. On average 29 percent delivery points had inconsistency in data. On month wise analysis of data, difference in data of both the sources was 23 percent. Since there was difference in the data it was validated with actual physical data. Validation also indicated that data of HMIS and KPI had discrepancies but the difference between physical data and KPI was minimum. So there needs assess the causes of the discrepancies.