TY - JOUR
T1 - Examining annual transitions in healthcare spending among U.S. medicare beneficiaries using multistate Markov models
T2 - Analysis of medicare current beneficiary survey data, 2003–2019
AU - Li, Lihua
AU - Zhan, Serena
AU - Mckendrick, Karen
AU - Yang, Chen
AU - Mazumdar, Madhu
AU - Kelley, Amy S.
AU - Aldridge, Melissa D.
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/4
Y1 - 2023/4
N2 - Many studies have examined factors associated with individuals of high or low healthcare spending in a given year. However, few have studied how healthcare spending changes over multiple years and which factors are associated with the changes. In this study, we examined the dynamic patterns of healthcare spending over a three-year period, among a nationally representative cohort of Medicare beneficiaries in the U.S. and identified factors associated with these patterns. We extracted data for 30,729 participants from the national Medicare Current Beneficiary Survey (MCBS), for the period 2003–2019. Using multistate Markov (MSM) models, we estimated the probabilities of year-to-year transitions in healthcare spending categorized as three states (low (L), medium (M) and high (H)), or to the terminal state, death. The participants, 13,554 (44.1%), 13,715 (44.6%) and 3,460 (11.3%) were in the low, medium and high spending states at baseline, respectively. The majority of participants remained in the same spending category from one year to the next (L-to-L: 76.8%; M-to-M: 71.7%; H-to-H: 56.6 %). Transitions from the low to high spending state were significantly associated with older age (75–84, ≥85 years), residing in a long-term care facility, greater assistance with activities of daily living, enrollment in fee-for-service Medicare, not receiving a flu shot, and presence of specific medical conditions, including cancer, dementia, and heart disease. Using data from a large population-based longitudinal survey, we have demonstrated that MSM modelling is a flexible framework and useful tool for examining changes in healthcare spending over time.
AB - Many studies have examined factors associated with individuals of high or low healthcare spending in a given year. However, few have studied how healthcare spending changes over multiple years and which factors are associated with the changes. In this study, we examined the dynamic patterns of healthcare spending over a three-year period, among a nationally representative cohort of Medicare beneficiaries in the U.S. and identified factors associated with these patterns. We extracted data for 30,729 participants from the national Medicare Current Beneficiary Survey (MCBS), for the period 2003–2019. Using multistate Markov (MSM) models, we estimated the probabilities of year-to-year transitions in healthcare spending categorized as three states (low (L), medium (M) and high (H)), or to the terminal state, death. The participants, 13,554 (44.1%), 13,715 (44.6%) and 3,460 (11.3%) were in the low, medium and high spending states at baseline, respectively. The majority of participants remained in the same spending category from one year to the next (L-to-L: 76.8%; M-to-M: 71.7%; H-to-H: 56.6 %). Transitions from the low to high spending state were significantly associated with older age (75–84, ≥85 years), residing in a long-term care facility, greater assistance with activities of daily living, enrollment in fee-for-service Medicare, not receiving a flu shot, and presence of specific medical conditions, including cancer, dementia, and heart disease. Using data from a large population-based longitudinal survey, we have demonstrated that MSM modelling is a flexible framework and useful tool for examining changes in healthcare spending over time.
KW - Healthcare costs
KW - Medicare Advantage
KW - Medicare beneficiary
KW - Medicare current beneficiary survey
KW - Multistate Markov model
KW - Transition probability
UR - http://www.scopus.com/inward/record.url?scp=85149808043&partnerID=8YFLogxK
U2 - 10.1016/j.pmedr.2023.102171
DO - 10.1016/j.pmedr.2023.102171
M3 - Article
AN - SCOPUS:85149808043
SN - 2211-3355
VL - 32
JO - Preventive Medicine Reports
JF - Preventive Medicine Reports
M1 - 102171
ER -