Ang Ian Yi Han, Rahman Nabilah, Wong Shing Hei, Ng Sheryl Hui-Xian, Tan Kyle Xin Quan, Eh Ke Xin, Ling Zheng Jye, Lim Andrea Su En, Tan Kelvin Bryan, Toh Sue Anne
Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Biostatistics, Singapore Clinical Research Institute, Consortium for Clinical Research and Innovation, Singapore, Singapore.
PLoS One. 2025 Jan 13;20(1):e0317016. doi: 10.1371/journal.pone.0317016. eCollection 2025.
The population is heterogeneous with varying levels of healthcare needs. Clustering individuals into health segments with more homogeneous healthcare needs allows for better understanding and monitoring of health profiles in the population, which can support data-driven resource allocation.
Using the developed criteria, data from several of Singapore's national administrative datasets were used to classify individuals into the various health segments. Cross-sectional analysis of healthcare utilization charges was conducted. Validation was done for the framework's prognostic ability of clinically relevant outcomes measured in the following year.
The framework is comprised of twelve segments classed within four broad groups. The segments comprising individuals with cancer, with transitional care needs, and in the last year of their lives had the highest mean per resident healthcare charges. The segments comprising adults and seniors with complex chronic conditions and with transitional care needs had the highest percentage of individuals historically diagnosed with obesity. The framework was able to distinguish varying tiers of healthcare utilization charges and relative risk of death in the following year.
The framework was developed using a hybrid approach, with expert input and comprehensive national data that extended beyond the usual hospital patient population. The framework can be directly applied for use in program or policy design, evaluation, and cost-effectiveness analyses.
The HealthSCOPES framework was developed to segment the entire population in Singapore with similar healthcare needs.
人群具有异质性，医疗保健需求水平各不相同。将个体聚类为医疗保健需求更同质化的健康细分群体，有助于更好地理解和监测人群的健康状况，从而支持基于数据的资源分配。
利用制定的标准，使用新加坡多个国家行政数据集的数据将个体分类到不同的健康细分群体中。对医疗保健利用费用进行了横断面分析。对该框架预测次年临床相关结果的能力进行了验证。
该框架由四大类中的十二个细分群体组成。包含癌症患者、有过渡性护理需求者以及处于生命最后一年的人群的细分群体，其人均医疗保健费用最高。包含患有复杂慢性病且有过渡性护理需求的成年人和老年人的细分群体，历史上被诊断为肥胖的个体比例最高。该框架能够区分不同层次的医疗保健利用费用以及次年的相对死亡风险。
该框架采用混合方法开发，有专家意见以及涵盖常规医院患者群体之外的全面国家数据。该框架可直接应用于项目或政策设计、评估以及成本效益分析。
HealthSCOPES框架旨在对新加坡有相似医疗保健需求的全体人口进行细分。
