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BMC Health Serv Res. 2018 Apr 5;18(1):246. doi: 10.1186/s12913-018-3052-7.

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.

Author information

1
Institute of Public Health, University of Heidelberg, Heidelberg, Germany. michael.marx@urz.uni-heidelberg.de.
2
Institute of Public Health, University of Heidelberg, Heidelberg, Germany.
3
Institute of Health Policy, Management and Research (IHPMR), Nairobi, Kenya.
4
Moi University, Eldoret, Kenya.
5
Institute for Applied Quality Improvement & Research in Health Care (AQUA), Göttingen, Germany.
6
Evaplan at the University Hospital, Heidelberg, Germany.
7
Swiss Tropical and Public Health Institute (TPH), Basel, Switzerland.
8
Department of Health Standards, Quality Assurance and Regulations, Ministry of Health, Nairobi, Kenya.
9
Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Health Programme, Nairobi, Kenya.

Abstract

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.

KEYWORDS:

Delivery of health care; Quality improvement; Quality of health care

PMID:
29622012
PMCID:
PMC5887241
DOI:
10.1186/s12913-018-3052-7
[Indexed for MEDLINE]
Free PMC Article

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