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Table 1 Characteristics of identified tools

From: Population segmentation based on healthcare needs: a systematic review

Segmentation tool Segment formulation Segmentation base type Peer-reviewed validation Proprietary Need for comprehensive electronic medical record Number of segments
Lynn et al.’s Bridges to Health model Expert driven Medical No No No 8
Hewner et al.’s Complexedex Expert driven Medical, lifestyle No Yes Yes 4
Kaiser Permanente’s Senior Segmentation Algorithm (SSA) Expert driven Medical Yes Yes Yes 4
Delaware Population Grouping Expert driven Medical No No Yes 20
Lombardy Segmentation Expert driven Medical, demographic, utilization No No Yes 8
3M’s Clinical Risk Group (CRG) Expert driven Medical, demographic Yes Yes Yes 6–269
Joynt et al.’s Medicare claims-based segmentation Expert driven Medical, frailty indicators, demographic Yes No Yes 6
British Columbia Health System Matrix Expert driven Medical, demographic, utilization No No Yes 14
Singapore MOH (Ministry of Health) Segmentation framework Expert driven Medical, utilization Yes No Yes 6
Northwest London Segmentation Scheme Data, expert driven Medical, demographic, functional No No Yes 10
John Hopkins Adjusted Clinical Group (ACG) Data, expert driven Medical, demographic Yes Yes Yes 92
Van der Laan et al.’s Demand-driven segmentation model Data driven Medical, functional, social Yes No No 5
Liu et al.’s Latent Class Analysis (LCA) of Taiwan National Health Interview Survey (NHIS) Data driven Medical, functional, socio-demographic Yes No No 4
Lafortune et al.’s LCA of SIPA (French acronym for System of Integrated Care for the frail elderly) Trial Data driven Medical, functional, socio-demographic Yes No No 4
Vuik et al.’s utilization-based segmentation Data driven Utilization No No Yes 8
Low et al.’s utilization-based segmentation Data driven Utilization, demographic Yes No Yes 5