High-Need Phenotypes in Medicare Beneficiaries: Drivers of Variation in Utilization and Outcomes.

OBJECTIVES

High-need (HN) Medicare beneficiaries heavily use healthcare services at a high cost. This population is heterogeneous, composed of individuals with varying degrees of medical complexity and healthcare needs. To improve healthcare delivery and decrease costs, it is critical to identify the subpopulations present within this population. We aimed to (1) identify distinct clinical phenotypes present within HN Medicare beneficiaries, and (2) examine differences in outcomes between phenotypes.

DESIGN

Latent class analysis was used to identify phenotypes within a sample of HN fee-for-service (FFS) Medicare beneficiaries aged 65 years and older using Medicare claims and post-acute assessment data.

SETTING

Not applicable.

PARTICIPANTS

Two cross-sectional cohorts were used to identify phenotypes. Cohorts included FFS Medicare beneficiaries aged 65 and older who survived through 2014 (n = 415 659) and 2015 (n = 416 643).

MEASUREMENTS

The following variables were used to identify phenotypes: acute and post-acute care use, functional dependency in one or more activities of daily living, presence of six or more chronic conditions, and complex chronic conditions. Mortality, hospitalizations, healthcare expenditures, and days in the community were compared between phenotypes.

RESULTS

Five phenotypes were identified: (1) comorbid ischemic heart disease with hospitalization and skilled nursing facility use (22% of the HN sample), (2) comorbid ischemic heart disease with home care use (23%), (3) home care use (12%), (4) high comorbidity with hospitalization (32%), and (5) Alzheimer's disease/related dementias with functional dependency and nursing home use (11%). Mortality was highest in phenotypes 1 and 2; hospitalizations and expenditures were highest in phenotypes 1, 3, and 4.

CONCLUSIONS

Our findings represent a first step toward classifying the heterogeneity among HN Medicare beneficiaries. Further work is needed to identify modifiable utilization patterns between phenotypes to improve the value of healthcare provided to these subpopulations. J Am Geriatr Soc 68:70-77, 2019.