Nevin Manimala Statistics

Data quality and associated factors in the health management information system at health centers in Shashogo district, Hadiya zone, southern Ethiopia, 2021

BMC Med Inform Decis Mak. 2022 Jun 15;22(1):154. doi: 10.1186/s12911-022-01898-3.


BACKGROUND: Poor quality routine data contributes to poor decision-making, inefficient resource allocation, loss of confidence in the health system, and may threaten the validity of impact evaluations. For several reasons in most developing countries, the routine health information systems in those countries are described as ineffective. Hence, the aim of this study is to determine the quality of data and associated factors in the routine health management information system in health centers of Shashogo district, Hadiya Zone.

METHODS: A facility-based cross-sectional study was conducted from June 1, 2021, to July 1, 2021, and 300 participants were involved in the study through simple random sampling. The data was collected with a self-administered questionnaire by trained data collectors. After checking its completeness, the data was entered into EPI data version 3.1 and exported to SPSS version 25 for statistical analysis. Finally, variables with p < 0.05 during multivariable analysis were considered significant variables.

RESULT: A total of 300(100%) participant were included in the interview and HMIS data quality was 83% in Shashogo district health centers. The data quality in terms of accuracy, completeness, and timeliness was 79%, 86%, and 84%, respectively. Conducting supportive supervision [AOR 3.5 (1.4, 8.9)], checking accuracy [AOR 1.3 (1.5, 3.5)], filling registrations [AOR 2.7 (1.44, 7.7)], and confidence level [AOR 1.9 (1.55, 3.35)] were all rated positively found to be factors associated with data quality.

CONCLUSION: The overall level of data quality in Shashogo district health centers was found to be below the national expectation level. All dimensions of data quality in the district were below 90% in data accuracy, content completeness, and timeliness of data. Conducting supportive supervision, checking accuracy, filling registrations and confidence level were found to be factors associated with data quality. Hence, all stakeholders should give all necessary support to improve data quality in routine health information systems to truly attain the goal of providing good quality data for the decision-making process by considering the identified factors.

PMID:35705966 | DOI:10.1186/s12911-022-01898-3

By Nevin Manimala

Portfolio Website for Nevin Manimala