Prevalence of lifestyle-related behavioral information in claims data in the U.S

Jessica L Schwartz; Elyse C Lasser; Christopher Kitchen; Kendrick B Gwynn; Chintan Pandya; Jonathan P Weiner; Kimberly A Gudzune

doi:10.1016/j.ypmed.2023.107826

Prevalence of lifestyle-related behavioral information in claims data in the U.S

Prev Med. 2024 Jan:178:107826. doi: 10.1016/j.ypmed.2023.107826. Epub 2023 Dec 18.

Authors

Jessica L Schwartz¹, Elyse C Lasser², Christopher Kitchen³, Kendrick B Gwynn⁴, Chintan Pandya³, Jonathan P Weiner³, Kimberly A Gudzune⁵

Affiliations

¹ Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
² Center for Population Health IT, Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. Electronic address: Elasser1@jhu.edu.
³ Center for Population Health IT, Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
⁴ Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Johns Hopkins Community Physicians, Baltimore, MD, USA.
⁵ Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Center for Population Health IT, Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

PMID: 38122938
DOI: 10.1016/j.ypmed.2023.107826

Abstract

Objective: Given their association with varying health risks, lifestyle-related behaviors are essential to consider in population-level disease prevention. Health insurance claims are a key source of information for population health analytics, but the availability of lifestyle information within claims data is unknown. Our goal was to assess the availability and prevalence of data items that describe lifestyle behaviors across several domains within a large U.S. claims database.

Methods: We conducted a retrospective, descriptive analysis to determine the availability of the following claims-derived lifestyle domains: nutrition, eating habits, physical activity, weight status, emotional wellness, sleep, tobacco use, and substance use. To define these domains, we applied a serial review process with three physicians to identify relevant diagnosis and procedure codes within claims for each domain. We used enrollment files and medical claims from a large national U.S. health plan to identify lifestyle relevant codes filed between 2016 and 2020. We calculated the annual prevalence of each claims-derived lifestyle domain and the proportion of patients by count within each domain.

Results: Approximately half of all members within the sample had claims information that identified at least one lifestyle domain (2016 = 41.9%; 2017 = 46.1%; 2018 = 49.6%; 2019 = 52.5%; 2020 = 50.6% of patients). Most commonly identified domains were weight status (19.9-30.7% across years), nutrition (13.3-17.8%), and tobacco use (7.9-9.8%).

Conclusion: Our study demonstrates the feasibility of using claims data to identify key lifestyle behaviors. Additional research is needed to confirm the accuracy and validity of our approach and determine its use in population-level disease prevention.

Keywords: Insurance claim review; Life style; Population health.

MeSH terms

Humans
Insurance, Health*
Life Style*
Prevalence
Retrospective Studies