Literature DB >> 30615516

Characteristics And Spending Patterns Of Persistently High-Cost Medicare Patients.

José F Figueroa1, Xiner Zhou2, Ashish K Jha3.   

Abstract

One strategy for reducing health care spending is to target the Medicare beneficiaries who remain persistently high cost over time. Using a 20 percent sample of Medicare fee-for-service beneficiaries in the period 2012-14, we sought to identify the proportion of patients who remained persistently high cost (that is, in the top 10 percent of spending each year) and determine the characteristics and spending patterns that differentiated them from other patients. We found that 28.1 percent of patients who were high cost in 2012 remained persistently high cost over the subsequent two years. On average, persistently high-cost patients were younger, more likely to be members of racial/ethnic minority groups, eligible for Medicare based on having end-stage renal disease, and dually eligible for Medicaid, compared to transiently and never high-cost patients. Persistently high-cost patients had greater relative spending on outpatient care and medications, while very little of their spending was related to preventable hospitalizations. Health care systems and policy makers can use this information to better target spending reductions and care improvements over time.

Entities:  

Mesh:

Year:  2019        PMID: 30615516     DOI: 10.1377/hlthaff.2018.05160

Source DB:  PubMed          Journal:  Health Aff (Millwood)        ISSN: 0278-2715            Impact factor:   6.301


  18 in total

1.  Potentially Preventable Spending Among High-Cost Medicare Patients: Implications for Healthcare Delivery.

Authors:  Dhruv Khullar; Yongkang Zhang; Rainu Kaushal
Journal:  J Gen Intern Med       Date:  2020-02-26       Impact factor: 5.128

2.  Persistence of High-Need Status Over Time Among Fee-for-Service Medicare Beneficiaries.

Authors:  Tamra Keeney; Nina R Joyce; David J Meyers; Vincent Mor; Emmanuelle Belanger
Journal:  Med Care Res Rev       Date:  2020-01-23       Impact factor: 3.929

3.  Health Care Hotspotting - A Randomized, Controlled Trial.

Authors:  Amy Finkelstein; Annetta Zhou; Sarah Taubman; Joseph Doyle
Journal:  N Engl J Med       Date:  2020-01-09       Impact factor: 91.245

4.  Characteristics of patients with mental illness and persistent high-cost status: a population-based analysis.

Authors:  Claire de Oliveira; Joyce Mason; Paul Kurdyak
Journal:  CMAJ       Date:  2020-12-14       Impact factor: 8.262

5.  Mortality and Hospitalizations for Dually Enrolled and Nondually Enrolled Medicare Beneficiaries Aged 65 Years or Older, 2004 to 2017.

Authors:  Rishi K Wadhera; Yun Wang; Jose F Figueroa; Francesca Dominici; Robert W Yeh; Karen E Joynt Maddox
Journal:  JAMA       Date:  2020-03-10       Impact factor: 56.272

6.  Validity of Race and Ethnicity Codes in Medicare Administrative Data Compared With Gold-standard Self-reported Race Collected During Routine Home Health Care Visits.

Authors:  Olga F Jarrín; Abner N Nyandege; Irina B Grafova; XinQi Dong; Haiqun Lin
Journal:  Med Care       Date:  2020-01       Impact factor: 3.178

7.  Temporal Patterns of High-Spend Subgroups Can Inform Service Strategy for Medicare Advantage Enrollees.

Authors:  Samuel J Amodeo; Henrik F Kowalkowski; Halley L Brantley; Nicholas W Jones; Lauren R Bangerter; David J Cook
Journal:  J Gen Intern Med       Date:  2021-06-07       Impact factor: 6.473

8.  Determinants of Total End-of-Life Health Care Costs of Medicare Beneficiaries: A Quantile Regression Forests Analysis.

Authors:  Lihua Li; Liangyuan Hu; Jiayi Ji; Karen Mckendrick; Jaison Moreno; Amy S Kelley; Madhu Mazumdar; Melissa Aldridge
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2022-05-05       Impact factor: 6.591

9.  Subgroups of High-Risk Veterans Affairs Patients Based on Social Determinants of Health Predict Risk of Future Hospitalization.

Authors:  Dan V Blalock; Matthew L Maciejewski; Donna M Zulman; Valerie A Smith; Janet Grubber; Ann-Marie Rosland; Hollis J Weidenbacher; Liberty Greene; Leah L Zullig; Heather E Whitson; Susan N Hastings; Anna Hung
Journal:  Med Care       Date:  2021-05-01       Impact factor: 3.178

10.  Low Urologist Density Predicts High-Cost Surgical Treatment of Stone Disease.

Authors:  David B Bayne; Manuel Armas-Phan; Sudarshan Srirangapatanam; Justin Ahn; Timothy T Brown; Marshall Stoller; Thomas L Chi
Journal:  J Endourol       Date:  2020-11-06       Impact factor: 2.942

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.