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Developing and Applying a Quality of Care Diagnostic
Effective targeting of performance-based incentives (PBI) and other quality improvement approaches require an initial assessment of areas where quality of care (QoC) currently falls short and interventions could yield high returns. The conceptual underpinnings, approach and implementation of such diagnostic tools are similar across countries.
The goal of this project was to develop a QoC diagnostic tool based on existing household and facility data from the Service Provision Assessment (SPA), a survey supported by the Demographic and Health Surveys (DHS) Program. Together these data contain a range of measures on structural and process quality of health services. Although the measures have been tabulated in data reports, they have not been used for a systematic assessment of QoC nor to identify potential areas for improvement.
As a case study, this tool was applied to Kenya with a focus on antenatal care quality (ANC). The tool is transferable to other settings with DHS and SPA data, and documented to allow for use of alternative secondary datasets.
The study utilized national data from Kenya’s 2010 Service Provision Assessment survey.
RESEARCH OBJECTIVES AND STUDY APPROACH
This study’s primary objectives were:
To develop a QoC diagnostic tool based on household and facility quality indicators from available SPA and DHS datasets.
To apply the QoC diagnostic tool to national data in Kenya in order to measure QoC, to identify potential areas for improvement, and to assess the heterogeneity and variations in QoC across geographic areas and providers.
A literature review identified six dimensions of quality of care to include in the diagnostic: effectiveness, efficiency, accessibility, acceptability/patient-centeredness, equity, and safety. Using these dimensions as a guide, 14 indicators from the SPA survey were selected as indicators of ANC quality.
Data from the 2010 Kenya SPA was used for analysis. The SPA data includes a facility audit questionnaire, health worker interviews, and clinical observations and exit interviews. Only facilities that reported providing ANC services were included in the analysis. Quality of care was calculated for each facility on a range from 0 to 1, with 1 being the highest quality. Quality scores were compared across facility type, management authority, and geographic region.
Findings from this study suggest that quality performance is low overall and that there is substantial variation across provinces, management authority and facility type. Overall, facilities performed highest in the dimensions of efficiency and acceptability/patient-centeredness, and lowest on effectiveness and accessibility. Public facilities generally performed worse or similarly to private or faith-based facilities. These results highlight the heterogeneity in quality of antenatal care in Kenya.
This analysis has helped to identify areas of concern that should be addressed in the design of policies and programs, including Kenya’s free maternal care program. The lower-scoring dimensions of quality, including effectiveness and accessibility, should be monitored closely during implementation. Conducting a baseline quality of care analysis using SPA data can help to inform RBF programs in Kenya and elsewhere. The results can help to design incentive structures that encourage overall improvements and address heterogeneities across facilities.
The results of this study were presented at the International Health Economics Association in July of 2015. The results were also published in the journal Health Policy and Planning in February of 2016.
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