Data Quality Validation and Performance of Donor-Supported Health Facilities in Sierra Leone: A Case Study of Selected Health Facilities Supported by Solthis in Sierra Leone

Abstract

This study assessed approaches and strategies used in data quality validation and how they influence the performance of those health facilities. The study is based on three objectives: to examine how data quality audit influences the performance of Solthis supported health facilities in Sierra Leone; to explore how joint supportive supervision influence performance of Solthis supported health facilities in Sierra Leone and to understand how staff capacity and performance influence quality service delivery in Solthis supported facilities in Sierra Leone. The theoretical framework covered Data quality Management (DQM) model, Organizational learning theory, Human capital theory and Donabedian model of quality healthcare. The study adopted a mixed method approaches to gather detailed understanding of the research variables and to afford the researcher the opportunity to make appropriate recommendations using evidence. The research site for the study were 35 health facilities supported by Solthis in Sierra Leone. The target population of 350 healthcare Workers comprising of facility In-charges, Midwives, HIV Counsellors and Nurses working in the targeted donor supported health facilities. A purposive sampling method was used to determine study sample and the researcher used questionnaires to collect data from 61 respondents. Open ended questionnaire was administered in person following focus group discussion method to collect primary data and secondary data from the review of HTC and eMTCT registers and summary forms. The research instrument was piloted in Waterloo CHC, a facility with same attribute as targeted donor supported health facilities that was used for this study. To test reliability, the research tools was piloted before actual data collections. Proper authorizations was secured from relevant institution to conduct the study and health facility performance scorecard was used to conduct quantitative data analysis and Atlas ti 23 for qualitative data. The results from the study indicates that data quality audit, joint supportive supervision and staff capacity positively influence the performance of Solthis supported health facilities. The overall average performances of each of the statements used across all data quality validation approaches were good, indicating that data quality audit, joint support supervision and staff capacity building had positive influence on performance. To conclude, the study highlighted the importance of data quality audit, joint supportive and staff capacity building in improving the performance of Solthis supported health facilities in Sierra Leone. To maintain good health facility performance, national data validation guideline and certification policy should be introduced to motivate health care workers performing well. Future research should be conducted at national level to help understand national performance of these data quality validation approaches especially in non-donor supported health facilities. Outcome will help to triangulate further methodology, approaches and strategies to influence policies and other decision-making processes.