Operational Audit of Sub-Contract Dispatch Efficiency at Kenyatta National Hospital Using Python

This project involved a process performance audit at Kenyatta National Hospital’s Medical Research Department, assessing the efficiency and timeliness in forwarding official sub-contracts and mail to the Senior Director Clinical Services (SDCS). Using Python for data analysis, the study extracted and analyzed dispatch records from March to June 2025, focusing on identifying operational lags and opportunities for improvement. Objectives: Measure the average time taken between mail receipt and forwarding to the SDCS Identify trends, delays, and inconsistencies in dispatch logging Generate recommendations to improve documentation accuracy and maintain optimal turnaround time Data Source and Workflow: Source: Departmental dispatch book records compiled into Excel Fields: Incoming Date, Dispatch Date Tool: Python (likely using pandas for time delta calculations and descriptive statistics) Key Findings: Total records analyzed: 37 mails/sub-contracts Forwarded in <1 day: 51.4% (n = 19) Forwarded in exactly 1 day: 24.3% (n = 9) Forwarded in >1 day: 24.3% (n = 9) Median time taken: 0 days (suggesting same-day processing) Mean time: 1.30 days Interquartile range (IQR): 1 day Max delay: 9 days Some dispatches appeared to be logged as processed before their incoming date, likely due to retrospective entry or data entry inconsistencies. Recommendations: Improve date-entry accuracy in dispatch records to reflect true operational timelines Implement periodic internal audits on date logging fields Sustain the high efficiency observed in majority of dispatches (<1 day turnaround) Consider automating dispatch book entries with timestamped digital logs Skills and Impact Demonstrated: Applied Python-based data analysis to administrative process review Interpreted operational data metrics (mean, median, IQR) in a real-world healthcare setting Linked findings to actionable process optimization recommendations Demonstrated the use of data science in health administration and research governance