Abstract:

Background: Routine Health Management Information System (RMMIS) is an integral component of health system management, which provides essential data for monitoring diseases trends and is important in planning essential health interventions. Despite the vital role the RMIS plays in the health management, the data in the low and middle income countries is unreliable.

Study Objective: To determine the quality of routine management information system data collected from health facilities in Ilemela Municipal Council from the period of October 2013 – March 2014.

Methods: A secondary data analysis study design was conducted on underfive children outpatient’s records on malaria, acute respiratory infections, acute diarrhoea and pneumonia from 10 randomly selected primary health care facilities. The data was entered into Excel software and exported to STATA version 11 for analysis. Completeness was calculated as the proportion of the monthly reports submitted on or before the due date to the total number of expected reports. Diagnoses reporting accuracy was computed as the discrepancy between the total diagnoses counted from the registers and the monthly reports submitted to the health management team.

Results: The study found out 62% of the expected data elements was complete. Private health facilities tended to enter complete data elements into the registers compared to the public health facilities (p value<0.001). Timelines in submitting the monthly report was 40%. Private facilities tended to submit monthly reports late compared to the public facilities (p-value = 0.039). There were 26% diagnoses over-reporting to the CHTM. Health centers to over-report the diagnoses by 11 times higher than the dispensaries (OR 11.3 95% CI 10.31 – 12.91 p<0.001). In addition, private owned health facilities (OR 6.23 95% CI 5.60 – 6.93 p<0.001).

Conclusion: The RMIS data collected through OPD registers on four common underfive illnesses at Ilemela municipality was of unsatisfactory quality for use in Health system decision making. Because the diagnoses are over-reported, the data may not reflect the true morbidities and inform the process of resource allocations in the comprehensive council health plan.