Utilizing a Patient Data-Based Digital System - Ceria Febiana; Leni Herfiyanti; Hadi Juwanda; Muhamad Rendi Hakim (STIKES Yayasan RS.Dr.Soetomo, 2026)
This study aims to analyze disease patterns among outpatients in type A hospitals, specifically those that have implemented digitalization systems in their services. The data were obtained from Electronic Medical Records (EMR) for the year 2024. The study employed a descriptive quantitative method with a retrospective approach. Samples were randomly selected from a population of 33,550 outpatient records using the Slovin formula (with a 5% margin of error), resulting in 400 samples. The analysis covered patients’ demographic characteristics, including gender, age, residence, and disease patterns based on the primary diagnosis. The results showed that female patients accounted for a higher proportion (57%) than males (43%), with the adult age group (19–59 years) being the most dominant (53.8%), and the majority of patients residing in Bandung City (68%). The five most common primary diagnoses were Follow-Up Examination After Unspecified Treatment for Other Conditions (Z09.9) (35%), Counselling, Unspecified (Z71.9) (17%), Follow-Up Examination After Other Treatment for Other Conditions (Z09.8) (9%), Pulpitis (K04.0) (7.8%), and Necrosis of Pulp (K04.1) (6%). The Cramer’s V test indicated no significant relationship between disease patterns and gender (V=0.242; p=0.219), but a significant association was found between disease patterns and age categories (V=0.463; p=0.000). These findings suggest that outpatient services in hospitals are predominantly utilized by patients with chronic conditions that require continuous monitoring, reflecting a shift in healthcare focus from acute illnesses to the management of chronic diseases.