Development of an Interactive Tableau Dashboard for Visualizing BPJS Participant Visit Patterns in Tasikmalaya City, 2024
Aryanta Nariswari Utari, Diana Barsasella
https://doi.org/10.56014/jphi.v13i3.519
Keywords
BPJS Health interactive dashboard visit patterns data visualization tableau BPJS Keshatan dashboard interaktif pola kunjungan visualisasi data tableauAbstract
Research Objective: Static reports may limit rapid interpretation of healthcare utilization data. This study aimed to develop a prototype interactive Tableau dashboard for visualizing BPJS Kesehatan sample visit data in Tasikmalaya City during 2024 and to describe visit patterns according to month, sex, age group, and diagnosis. Methodology: This descriptive quantitative study used anonymized secondary BPJS Kesehatan sample visit records from January to December 2024. Data preparation included duplicate checking, missing-value assessment, standardization of date and demographic variables, and verification of diagnosis codes using the International Classification of Diseases, 10th Revision. The cleaned data were imported into Tableau and displayed through summary cards, monthly trend charts, demographic visualizations, diagnosis charts, and interactive filters. Dashboard totals were cross-checked against descriptive calculations from the final dataset. Results: The final analytic dataset contained 889 participant visits. The dashboard displayed visit patterns by month, sex, age group, and diagnosis. December had the highest number of visits, with 210 visits, while January had the lowest, with 39 visits. Female participants accounted for a greater proportion of visits than male participants. Higher visit frequencies were observed in selected productive-age and older-adult groups. Fever, classified under ICD-10 category R50, was the most frequently recorded diagnosis, with 59 visits. Conclusion: The prototype dashboard provides an interactive presentation of BPJS Kesehatan sample visit data and facilitates descriptive exploration of temporal, demographic, and diagnostic patterns. Because the dashboard was developed using historical sample data and was not evaluated through formal usability testing, its findings should not be interpreted as representing all BPJS utilization in Tasikmalaya City. Future development should include automated data updating, end-user usability testing, and integration with more complete service-utilization data.
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