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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