Monitoring and Evaluation Framework and Performance of Level 5 Referral Hospitals in Nairobi City County, Kenya
DOI:
https://doi.org/10.47941/jepm.3859Keywords:
Monitoring and Evaluation Framework, M&E Planning, M&E Data Collection, Level 5 Referral HospitalsAbstract
Purpose: The general objective of the study is to assess the influence of monitoring and evaluation framework on performance of level 5 referral hospitals in Nairobi City County, Kenya. Specifically, the study sought to assess the influence of M&E planning and M&E data collection on the performance of level 5 referral hospitals in Nairobi City County, Kenya. This study was guided by Results-Based Management (RBM) Theory and Theory of Change (ToC). Methodology: This study used a descriptive research design. The target population was 627 management and non-management employees working in level 5 referral hospitals in Nairobi City County, Kenya (Ministry of Health 2024). This study made use of Slovin's Formula to determine the study’s sample size of 244 respondents. The study’s primary data was obtained using structured questionnaires. The pretesting sample was made of 24 respondents, representing 10% of the sample size. Quantitative data was generated from the closed-ended questionnaire. Inferential and descriptive statistics were employed for analysis of quantitative data with the assistance of Statistical Package for Social Sciences (SPSS version 25).
Findings: The study showed that M&E planning has a positive and significant effect on performance of level 5 referral hospitals in Nairobi City County, Kenya. In addition, the study found that M&E data collection has a positive and significant effect on performance of level 5 referral hospitals in Nairobi City County, Kenya.
Unique Contribution to Theory, Practice and Policy: Based on the findings, the study recommends that level 5 referral hospitals in Kenya should strengthen standardized and technology-enabled M&E data collection systems by adopting integrated digital health information platforms, clear data collection protocols, and regular staff training to ensure accuracy, completeness, and timeliness of data.
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Copyright (c) 2026 Mark Kipkorir Maritim, Dr. Phyllis Mbutu
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