Background Data from national surveys of low- and middle income countries indicates that there is still a need to improve the quality of healthcare in resource-poor settings. This study aims to understand the benefit of an integral, facility-driven, indicator-based approach used as a decision-making tool to define effective quality improvement interventions in Kenya.
Objective The aim of the study is to understand whether the integral approach developed leads to effective interventions.
Methods Categorical data is collected from ten health facilities covered by the Integrated Quality Management System (IQMS) project in Kenya. First the information on concrete improvement interventions implemented within the facilities is collected and merged into five different intervention topics. Second, groups of facilities with similar quality improvement interventions are selected to compare between the first and second quality assessment rounds. Those IQMS indicators matching the content of the intervention topic are extracted from the software VISOTOOL. In a third step, the data is summarised using means and SD. A one sample T-test is applied on the mean changes and SD. Frequency counts and percentages were used for the presentation of categorical data.
Results All improvement interventions resulted in positive and higher change values (T2-T1). Four of five intervention topics, show statistically significant improvements including neonatal mortality (42%; p<0.0001), waiting time (39%; p=0.0490), infection prevention control (28%; p=0.0007) and with shortages of staffing and transport in remote areas (32%; p=0.0194).
Conclusions In all facilities the interventions selected have a positive impact, some of which markedly improved. It demonstrates that this integral quality improvement approach in Kenya can serve as an effective decision-making tool for identification and prioritisation of interventions. Those targeted interventions, being performed under institutionalisation in form of coaching and tutoring, effectively contribute to improving the quality of care in resource poor settings.
- decision making
- quality improvement
- qualitative research
- quality measurement
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Contributors CN analysed the IQMS data and improvement interventions, performed the statistics, interpreted the results and wrote the manuscript. MN was project manager, accompanied the improvement interventions and supervised the facilities continuously. IO gave support to IQMS implementation; MB contributed to IQMS data management and analysis. IM, CK and FP-F gave advice regarding the IQMS process and contributed in writing the manuscript. JS gave advice to the scientific approach and design of the study. LB gave advice to the data analysis and contributed in writing the manuscript. MM was the supervisor of designing the study and of the methodological approach, was involved in the IQMS project, and was a major contributor in writing the manuscript. All authors read and approved the final manuscript.
Funding The IQMS quality improvement project was supported by the GIZ (reference no. 81135455, project no. 2010.2035.3). This retrospectively performed research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Patient consent for publication Not required.
Ethics approval Ethics approval for the IQMS audits at the Kenyan facilities has been given by the Institutional Research Ethics Committee at Moi University, Kenya. Further retrospective analysis has been exempted from requiring ethics approval by the Ethics commission of the Faculty of Medicine Heidelberg, Germany (S-673/2015).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon request.
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