Pattern and Outcome of Medical Admissions at the University of Uyo Teaching Hospital: A 5-Year Hospitalization Analysis
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Keywords
Medical admission , pattern , communicable diseases, Non-Communicable Disease, Outcomes
Abstract
Background: The pattern of hospital admission is necessary for proper planning and budgeting in health care. It also provides insights into the burden of disease in a particular community. Additionally, admission patterns also assist in reviewing the morbidity and mortality over the duration of the study and allow for proper planning and prevention of these occurrences.
Methodology: This is a five-year retrospective study of patients admitted to the medical wards. Patients' case notes were retrieved from the hospital's records department. Demographic data such as age, sex, occupation, and religion were extracted from the case notes. Clinical data such as diagnosis, date of admission and discharge, duration of stay, and cause of death were also extracted. Kaplan-Meier survival curves were plotted, and a multivariate Cox proportional hazards model was used to determine the independent predictors of mortality.
Results: A total of 2634 patient records were retrieved. The ages of patients ranged from 15 to 102 years, with a mean of 54.8 ± 16.5 years. There were more males 1374 (52.2%) against 1269(47.8%) females), p<0.001. Noncommunicable diseases (NCDs) accounted for 2286 (86.8%), with 348 (13.2%) being communicable diseases. Chronic kidney disease (CKD) 21.5%, acute kidney injury (5.0%), Stroke (19.9%), Heart failure (17.6%), and Diabetes (20.7%) were the leading NCDs. On the other hand, Tuberculosis (4.0%), and Pneumonia (1.4%), were the leading communicable diseases causing hospitalization. Older age groups ≥60 years (p= 0.02), kidney disease, (p< 0.001). HIV. (p=0.01) were independently associated with mortality.
Conclusion: The epidemiological transition to NCDs is well established in the adult population of Akwa Ibom State. Older age, kidney diseases, stroke, and HIV infection were independent predictors of mortality.
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