| dc.description.abstract | Most referral health facilities encounter challenges such as congestion of patients, strained/ limited resources (both human and material). The high volume of patients often slow rate of service delivery in terms of discharge and admission to the patients and as a result compromise the quality of medical care. The study therefore determined how admissions schedules are managed in the short-term such that the probability of ward overloading is acceptably low, while maintaining high bed utilisation, in various wards where beds might be availed for elective and emergency. A cross sectional study was conducted using a quantitative approach for data collection. One thousand six hundred and sixteen in-patient client records were purposively selected to be used in the study at the Jaramogi Oginga Odinga Referral Hospital in Kisumu, Western Kenya. Data was collected using structured questionnaire. The collected quantitative data were coded and analyzed using the STATA 13.0 Computer program, ODES model development, analysis and presentation were done using micro-saint sharp software. The quantitative data were then analyzed using the descriptive statistics and Kruskal-Wallis test was used to find the association between the admission and the days of the week. The research findings revealed a considerable connection between weekday of admission and patients’ Length of Stay, (P< .0001) and also weekday of admission and number of emergency admissions (P< .0001). The number of admissions per day was highest on Monday at 24 patients while Mean service time (length of stay) was 6.5 days with a negative skewness for the midnight bed occupancy (𝛾 ̂= -1.075). The mean number of admissions using the model was 21.97 against 22.71 from the actual mean number of admissions at the hospital. This shows 97.74% efficiency of the model. This is a new Data Driven approach intended to be utilized in the sub Saharan Africa to help manage our discharge and admission process to ensure efficiency in service delivery. The management of the hospital should apply this kind of Data Driven Decision Support System to help them plan and efficiently manage both Elective and emergency patients in order to avoid any negative outcome and accommodate all patients seeking medical care services. This will also aide in periodical planning with the available expensive resources such as doctors, nurses, ambulances and the theatre and surgical equipment. | en_US |