Identifying patterns of clinical conditions among high-cost older adult health care users using claims data: a latent class approach.

ABSTRACT:

Objectives

To identify patterns of clinical conditions among high-cost older adults health care users and explore the associations between characteristics of high-cost older adults and patterns of clinical conditions.

Methods

We analyzed data from the Shanghai Basic Social Medical Insurance Database, China. A total of 2927 older adults aged 60 years and over were included as the analysis sample. We used latent class analysis to identify patterns of clinical conditions among high-cost older adults health care users. Multinomial logistic regression models were also used to determine the associations between demographic characteristics, insurance types, and patterns of clinical conditions.

Results

Five clinically distinctive subgroups of high-cost older adults emerged. C

SUBMITTER: He X 

PROVIDER: S-EPMC9210624 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature