An Exploratory Clustering Analysis of Digital Readiness and Maturity for Electronic Medical Record Implementation in Indonesia

Abstract

The Satu Sehat platform for Electronic Medical Records (EMR), launched in Indonesia in 2022, represents an important step toward national health data integration. However, variation in hospital digital readiness may affect the implementation of EMR systems across regions. This study aimed to explore digital maturity and EMR readiness profiles among hospitals in Indonesia.

Methods: A cross-sectional secondary dataset from 711 hospitals was analyzed using an exploratory, unsupervised machine-learning approach. K-means clustering and Principal Component Analysis (PCA) were used to identify hospital digital maturity profiles and visualize clustering patterns.

Results: The analysis identified six hospital clusters with heterogeneous digital maturity characteristics across provinces. Information Systems and Infrastructure, Standards and Interoperability, and Human Capital had the highest overall average scores, whereas Data Analytics had the lowest. Hospitals from East Java, Central Java, and Lampung were distributed across multiple clusters, while hospitals from Papua and Maluku were more concentrated in lower digital maturity profiles.

Conclusions: Overall, the findings suggest that hospital readiness for EMR implementation in Indonesia is multidimensional and unevenly distributed. Exploratory clustering may help identify distinct readiness profiles and support more targeted planning for digital health implementation.