Patient Waiting Time and Service Type in The Outpatient Department of JM Kariuki Memorial Hospital

Long patient waiting times in outpatient departments (OPDs) continue to present a persistent challenge in healthcare delivery, with significant effects on patient satisfaction, clinical outcomes, and operational efficiency. This study aimed to investigate the correlation between patient waiting time and service type at the outpatient department of JM Kariuki Memorial Hospital in Nyandarua County, Kenya. A descriptive cross-sectional design was utilized, with a sample of 239 respondents selected through stratified and systematic random sampling. Data were collected using structured questionnaires and key informant interviews. Quantitative data were analyzed using SPSS Version 24, while qualitative insights were processed using NVivo. The findings revealed that the average patient waiting time was 3.4 hours, with significant variations across service types. Patients seeking surgical and medical services experienced the longest delays, averaging 5.05 and 4.31 hours, respectively, while emergency care patients faced the shortest waits, averaging 1.32 hours. Regression analysis showed a strong model fit (R² = 0.793), indicating that the service type, human resource factors, information technology (IT) infrastructure, and health information exchange (HIE) systems together accounted for 79.3% of the variance in patient waiting times. Human resource factors (β = 0.454, p = 0.000) were found to have the greatest impact, followed by HIE systems (β = 0.328), service type (β = 0.284), and IT infrastructure (β = 0.204). These findings underscore the need for targeted resource allocation, improved staffing, enhanced digital systems, and better integration of HIE to optimize outpatient service delivery. The study provides actionable recommendations for healthcare managers and policymakers focused on improving service efficiency and enhancing patient experiences in similar healthcare settings. Keywords: Patient waiting time, outpatient department, health information exchange, human resource factors, electronic medical records