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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.
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http://dx.doi.org/10.1016/j.ypmed.2023.107826 | DOI Listing |
J Orthop Sci
September 2025
Department of Health Administration and Policy, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-Ku, Sendai, Miyagi 980-8574, Japan. Electronic address:
Background: Obesity is associated with an increased risk of complications after total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA), particularly in Western populations. However, the effect of severe obesity (body mass index [BMI] ≥ 35 kg/m) on postoperative complications in Japanese patients remains unclear.
Methods: We conducted a retrospective cohort study using Japan's Diagnosis Procedure Combination (DPC) database, including patients who underwent TKA or UKA between April 2016 and March 2023.
J Am Med Dir Assoc
September 2025
Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA. Electronic address:
Objectives: In 2017, the Chronic Condition Warehouse released a 30-condition Chronic Condition file (CC30), which fully replaced the prior 27-condition file (CC27) in 2022. CC30 shortened the look-back period for dementia identification from 3 to 2 years and raised the required outpatient/carrier claims from 1 to 2. This change may disproportionately affect individuals with limited access to health care.
View Article and Find Full Text PDFJ Affect Disord
September 2025
Department of Psychology, College of Social Sciences and Humanities, Koç University, Istanbul, Türkiye.
Background: Refugees face psychosocial challenges after resettling in host nations, including experienced stigma and microaggressions. Microaggressions are subtle/ambiguous discriminatory remarks or behaviors. There is a dearth of research and instruments examining microaggressions refugees face.
View Article and Find Full Text PDFEnviron Int
September 2025
Department of Environmental Health, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA. Electronic address:
Longer, more severe wildfire seasons are becoming the norm in fire-prone areas. Prescribed burning is a tool used to mitigate wildfire spread. However, prescribed burning also contributes to air pollution, including PM (particulate matter with aerodynamic diameter <= 2.
View Article and Find Full Text PDFSchizophr Res
September 2025
Columbia University and the New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032, United States of America.
Purpose: Heterogeneity among people diagnosed with schizophrenia-spectrum disorders (schizophrenia) and high prevalence of co-occurring disorders makes identification of optimal treatments difficult. This study identified behavioral health phenotypes using machine learning with Medicaid claims of adults with schizophrenia. We compared the phenotypes' clinical outcomes and psychotropic medication prescription patterns for clinical validity.
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