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Examining annual transitions in healthcare spending among U.S. medicare beneficiaries using multistate Markov models: Analysis of medicare current beneficiary survey data, 2003-2019
Li Lihua, Zhan Serena, Mckendrick Karen, Yang Chen, Mazumdar Madhu, Kelley Amy S, Aldridge Melissa D. Preventive medicine reports, 2023-03-24
Topic: Risk, prevention and care in population studies
Plain-language summary
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.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Lihua, L., Serena, Z., Karen, M., Chen, Y., Madhu, M., Kelley Amy, S., et al. (2023). Examining annual transitions in healthcare spending among U.S. medicare beneficiaries using multistate Markov models: Analysis of medicare current beneficiary survey data, 2003-2019. Preventive medicine reports. https://doi.org/10.1016/j.pmedr.2023.102171
Vancouver
Lihua L, Serena Z, Karen M, Chen Y, Madhu M, Kelley Amy S, et al. Examining annual transitions in healthcare spending among U.S. medicare beneficiaries using multistate Markov models: Analysis of medicare current beneficiary survey data, 2003-2019. Preventive medicine reports. 2023. doi:10.1016/j.pmedr.2023.102171. PMID: 36950178.
BibTeX
@article{lihua2023-36950178,
author = {Lihua, Li and Serena, Zhan and Karen, Mckendrick and Chen, Yang and Madhu, Mazumdar and Kelley Amy, S. and Aldridge Melissa, D.},
title = {{Examining annual transitions in healthcare spending among U.S. medicare beneficiaries using multistate Markov models: Analysis of medicare current beneficiary survey data, 2003-2019}},
journal = {Preventive medicine reports},
year = {2023},
doi = {10.1016/j.pmedr.2023.102171},
pmid = {36950178},
url = {https://doi.org/10.1016/j.pmedr.2023.102171}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
Key findings
- 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.
- 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.
Why it matters
This study used national survey data to track how Medicare beneficiaries move between low, medium, and high healthcare spending categories over three years. It is about spending patterns, not about treating, curing, or preventing Alzheimer's disease.
Study details
- Study designlongitudinal study
- Participants30,729
- Effect size44.1%; 44.6%; 11.3%
- Evidence strengthModerate
How this study scored 48/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Preventive medicine reports) |
| Journal's citation record | 1 / 4 | Preventive Medicine Reports: journal h-index 82 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2023 — within 6 year(s) of the newest study here |
| Sample size | 4 / 4 | 30,729 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 2 times (OpenAlex, 2026-10-17) |
| Citations per year | 0 / 5 | 0.4 citations a year over 5 year(s) since 2023 |
| Impact for its field and year | 1 / 6 | Cited 0.4× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 2 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Melissa D. Aldridge: h-index 26 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Icahn School of Medicine at Mount Sinai: institution h-index 1,325 (OpenAlex) |
| Multicenter collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 36950178) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 48 / 100 | — |
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