Literature DB >> 17446824

Are regional variations in end-of-life care intensity explained by patient preferences?: A Study of the US Medicare Population.

Amber E Barnato1, M Brooke Herndon, Denise L Anthony, Patricia M Gallagher, Jonathan S Skinner, Julie P W Bynum, Elliott S Fisher.   

Abstract

OBJECTIVE: We sought to test whether variations across regions in end-of-life (EOL) treatment intensity are associated with regional differences in patient preferences for EOL care. RESEARCH
DESIGN: Dual-language (English/Spanish) survey conducted March to October 2005, either by mail or computer-assisted telephone questionnaire, among a probability sample of 3480 Medicare part A and/or B eligible beneficiaries in the 20% denominator file, age 65 or older on July 1, 2003. Data collected included demographics, health status, and general preferences for medical care in the event the respondent had a serious illness and less than 1 year to live. EOL concerns and preferences were regressed on hospital referral region EOL spending, a validated measure of treatment intensity.
RESULTS: A total of 2515 Medicare beneficiaries completed the survey (65% response rate). In analyses adjusted for age, sex, race/ethnicity, education, financial strain, and health status, there were no differences by spending in concern about getting too little treatment (39.6% in lowest spending quintile, Q1; 41.2% in highest, Q5; P value for trend, 0.637) or too much treatment (44.2% Q1, 45.1% Q5; P = 0.797) at the end of life, preference for spending their last days in a hospital (8.4% Q1, 8.5% Q5; P = 0.965), for potentially life-prolonging drugs that made them feel worse all the time (14.4% Q1, 16.5% Q5; P = 0.326), for palliative drugs, even if they might be life-shortening (77.7% Q1, 73.4% Q5; P = 0.138), for mechanical ventilation if it would extend their life by 1 month (21% Q1, 21.4% Q5; P = 0.870) or by 1 week (12.1% Q1, 11.7%; P = 0.875).
CONCLUSIONS: Medicare beneficiaries generally prefer treatment focused on palliation rather than life-extension. Differences in preferences are unlikely to explain regional variations in EOL spending.

Entities:  

Mesh:

Year:  2007        PMID: 17446824      PMCID: PMC2147061          DOI: 10.1097/01.mlr.0000255248.79308.41

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  18 in total

1.  Uncertainty, health-care technologies, and health-care choices.

Authors:  M McClellan
Journal:  Am Econ Rev       Date:  1995-05

2.  Stability of treatment preferences: although most preferences do not change, most people change some of their preferences.

Authors:  N Kohut; M Sam; K O'Rourke; D K MacFadden; I Salit; P A Singer
Journal:  J Clin Ethics       Date:  1997

3.  Geographic variation in expenditures for physicians' services in the United States.

Authors:  W P Welch; M E Miller; H G Welch; E S Fisher; J E Wennberg
Journal:  N Engl J Med       Date:  1993-03-04       Impact factor: 91.245

4.  Hospital readmission rates for cohorts of Medicare beneficiaries in Boston and New Haven.

Authors:  E S Fisher; J E Wennberg; T A Stukel; S M Sharp
Journal:  N Engl J Med       Date:  1994-10-13       Impact factor: 91.245

5.  Variation in the tendency of primary care physicians to intervene.

Authors:  Brenda E Sirovich; Daniel J Gottlieb; H Gilbert Welch; Elliott S Fisher
Journal:  Arch Intern Med       Date:  2005-10-24

6.  A controlled trial to improve care for seriously ill hospitalized patients. The study to understand prognoses and preferences for outcomes and risks of treatments (SUPPORT). The SUPPORT Principal Investigators.

Authors: 
Journal:  JAMA       Date:  1995 Nov 22-29       Impact factor: 56.272

7.  Rationing of intensive care unit services. An everyday occurrence.

Authors:  M J Strauss; J P LoGerfo; J A Yeltatzie; N Temkin; L D Hudson
Journal:  JAMA       Date:  1986-03-07       Impact factor: 56.272

8.  Variations in the utilization of coronary angiography for elderly patients with an acute myocardial infarction. An analysis using hierarchical logistic regression.

Authors:  C A Gatsonis; A M Epstein; J P Newhouse; S L Normand; B J McNeil
Journal:  Med Care       Date:  1995-06       Impact factor: 2.983

9.  Professional uncertainty and the problem of supplier-induced demand.

Authors:  J E Wennberg; B A Barnes; M Zubkoff
Journal:  Soc Sci Med       Date:  1982       Impact factor: 4.634

10.  Influence of patient preferences and local health system characteristics on the place of death. SUPPORT Investigators. Study to Understand Prognoses and Preferences for Risks and Outcomes of Treatment.

Authors:  R S Pritchard; E S Fisher; J M Teno; S M Sharp; D J Reding; W A Knaus; J E Wennberg; J Lynn
Journal:  J Am Geriatr Soc       Date:  1998-10       Impact factor: 5.562

View more
  174 in total

1.  Determinants of treatment intensity for patients with serious illness: a new conceptual framework.

Authors:  Amy S Kelley; R Sean Morrison; Neil S Wenger; Susan L Ettner; Catherine A Sarkisian
Journal:  J Palliat Med       Date:  2010-07       Impact factor: 2.947

2.  Toward an integrated research agenda for critical illness in aging.

Authors:  Eric B Milbrandt; Basil Eldadah; Susan Nayfield; Evan Hadley; Derek C Angus
Journal:  Am J Respir Crit Care Med       Date:  2010-06-17       Impact factor: 21.405

3.  Association of Occupation as a Physician With Likelihood of Dying in a Hospital.

Authors:  Saul Blecker; Norman J Johnson; Sean Altekruse; Leora I Horwitz
Journal:  JAMA       Date:  2016-01-19       Impact factor: 56.272

4.  Hospice admissions for cancer in the final days of life: independent predictors and implications for quality measures.

Authors:  Nina R O'Connor; Rong Hu; Pamela S Harris; Kevin Ache; David J Casarett
Journal:  J Clin Oncol       Date:  2014-08-25       Impact factor: 44.544

5.  Hospice Enrollment, Local Hospice Utilization Patterns, and Rehospitalization in Medicare Patients.

Authors:  Timothy R Holden; Maureen A Smith; Christie M Bartels; Toby C Campbell; Menggang Yu; Amy J H Kind
Journal:  J Palliat Med       Date:  2015-04-16       Impact factor: 2.947

6.  Dartmouth Atlas: putting end-of-life care on the map but missing psychosocial detail.

Authors:  Holly G Prigerson; Paul K Maciejewski
Journal:  J Support Oncol       Date:  2011-09-23

7.  Medicare Expenditures and Health Care Utilization in a Multiethnic Community-based Population With Dementia From Incidence to Death.

Authors:  Katherine A Ornstein; Carolyn W Zhu; Evan Bollens-Lund; Melissa D Aldridge; Howard Andrews; Nicole Schupf; Yaakov Stern
Journal:  Alzheimer Dis Assoc Disord       Date:  2018 Oct-Dec       Impact factor: 2.703

8.  Seniors' perceptions of health care not closely associated with physician supply.

Authors:  David J Nyweide; Denise L Anthony; Chiang-Hua Chang; David Goodman
Journal:  Health Aff (Millwood)       Date:  2011-02       Impact factor: 6.301

Review 9.  Using existing data to address important clinical questions in critical care.

Authors:  Colin R Cooke; Theodore J Iwashyna
Journal:  Crit Care Med       Date:  2013-03       Impact factor: 7.598

10.  Changes In End-Of-Life Care In The Medicare Shared Savings Program.

Authors:  Lauren G Gilstrap; Haiden A Huskamp; David G Stevenson; Michael E Chernew; David C Grabowski; J Michael McWilliams
Journal:  Health Aff (Millwood)       Date:  2018-10       Impact factor: 6.301

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.