A methodological approach to extracting patterns of service utilization from a cross-continuum high dimensional healthcare dataset to support care delivery optimization for patients with complex problems
Date
2024
Authors
Bambi, Jonas
Santoso, Yudi
Sadri, Hanieh
Moselle, Ken
Rudnick, Abraham
Robertson, Stan
Chang, Ernie
Kuo, Alex
Howie, Joseph
Dong, Gracia Yunruo
Journal Title
Journal ISSN
Volume Title
Publisher
BioMedInformatics
Abstract
Background: Optimizing care for patients with complex problems entails the integration of clinically appropriate problem-specific clinical protocols, and the optimization of service-system-encompassing clinical pathways. However, alignment of service system operations with Clinical Practice Guidelines (CPGs) is far more challenging than the time-bounded alignment of procedures with protocols. This is due to the challenge of identifying longitudinal patterns of service utilization in the cross-continuum data to assess adherence to the CPGs. Method: This paper proposes a new methodology for identifying patients’ patterns of service utilization (PSUs) within sparse high-dimensional cross-continuum health datasets using graph community detection. Result: The result has shown that by using iterative graph community detections, and graph metrics combined with input from clinical and operational subject matter experts, it is possible to extract meaningful functionally integrated PSUs. Conclusions: This introduces the possibility of influencing the reorganization of some services to provide better care for patients with complex problems. Additionally, this introduces a novel analytical framework relying on patients’ service pathways as a foundation to generate the basic entities required to evaluate conformance of interventions to cohort-specific clinical practice guidelines, which will be further explored in our future research.
Description
Keywords
clinical pathways, clinical practice guidelines, decision support, graph community detection, health information management, health service system, Louvain algorithm, machine learning algorithms
Citation
Bambi, J., Santoso, Y., Sadri, H., Moselle, K., Rudnick, A., Robertson, S., Chang, E., Kuo, A., Howie, J., Dong, G. Y., Olobatuyi, K., Hajiabadi, M., & Richardson, A. (2024). A methodological approach to extracting patterns of service utilization from a cross-continuum high dimensional healthcare dataset to support care delivery optimization for patients with complex problems. BioMedInformatics, 4(2), Article 2. https://doi.org/10.3390/biomedinformatics4020053