If you can't measure it- you can't change it - a longitudinal study on improving quality of care in hospitals and health centers in rural Kenya.

BACKGROUND: The Kenyan Ministry of Health- Department of Standards and Regulations sought to operationalize the Kenya Quality Assurance Model for Health. To this end an integrated quality management system based on validated indicators derived from the Kenya Quality Model for Health (KQMH) was developed and adapted to the area of Reproductive and Maternal and Neonatal Health, implemented and analysed. METHODS: An integrated quality management (QM) approach was developed based on European Practice Assessment (EPA) modified to the Kenyan context. It relies on a multi-perspective, multifaceted and repeated indicator based assessment, covering the 6 World Health Organization (WHO) building blocks. The adaptation process made use of a ten step modified RAND/UCLA appropriateness Method. To measure the 303 structure, process, outcome indicators five data collection tools were developed: surveys for patients and staff, a self-assessment, facilitator assessment, a manager interview guide. The assessment process was supported by a specially developed software (VISOTOOL®) that allows detailed feedback to facility staff, benchmarking and facilitates improvement plans. A longitudinal study design was used with 10 facilities (6 hospitals; 4 Health centers) selected out of 36 applications. Data was summarized using means and standard deviations (SDs). Categorical data was presented as frequency counts and percentages. RESULTS: A baseline assessment (T1) was carried out, a reassessment (T2) after 1.5 years. Results from the first and second assessment after a relatively short period of 1.5 years of improvement activities are striking, in particular in the domain 'Quality and Safety' (20.02%; p < 0.0001) with the dimensions: use of clinical guidelines (34,18%; p < 0.0336); Infection control (23,61%; p < 0.0001). Marked improvements were found in the domains 'Clinical Care' (10.08%; p = 0.0108), 'Management' (13.10%: p < 0.0001), 'Interface In/out-patients' (13.87%; p = 0.0246), and in total (14.64%; p < 0.0001). Exemplarily drilling down the domain 'clinical care' significant improvements were observed in the dimensions 'Antenatal care' (26.84%; p = 0.0059) and 'Survivors of gender-based violence' (11.20%; p = 0.0092). The least marked changes or even a -not significant- decline of some was found in the dimensions 'delivery' and 'postnatal care'. CONCLUSIONS: This comprehensive quality improvement approach breathes life into the process of collecting data for indicators and creates ownership among users and providers of health services. It offers a reflection on the relevance of evidence-based quality improvement for health system strengthening and has the potential to lay a solid ground for further certification and accreditation.

How to prioritise in quality improvement? Targeted implementation as a key for quality improvement in Kenyan health facilities.

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.