Literature DB >> 35272981

Associations between illness burden and care experiences among Medicare beneficiaries before or after a cancer diagnosis.

Lisa M Lines1, Julia Cohen2, Justin Kirschner2, Daniel H Barch3, Michael T Halpern4, Erin E Kent5, Michelle A Mollica4, Ashley Wilder Smith4.   

Abstract

INTRODUCTION: To understand associations between a new measure of illness burden and care experiences in a large, national sample of Medicare beneficiaries surveyed before or after a cancer diagnosis.
MATERIALS AND METHODS: The SEER-CAHPS Illness Burden Index (SCIBI) was previously developed using Surveillance, Epidemiology, and End Results (SEER)-Consumer Assessment of Healthcare Providers and Systems (CAHPS) linked data. The SCIBI provides a standardized morbidity score based on self- and other-reported information from 8 domains and proxies relative risk of 12-month, all-cause mortality among people surveyed before or after a cancer diagnosis. We analyzed a population of Medicare beneficiaries (n = 116,735; 49% fee-for-service and 51% Medicare Advantage [MA]; 73% post-cancer diagnosis) surveyed 2007-2013 to understand how their SCIBI scores were associated with 12 different care experience measures. Frequentist and Bayesian multivariable regression models adjusted for standard case-mix adjustors, enrollment type, timing of cancer diagnoses relative to survey, and survey year. RESULTS AND DISCUSSION: SCIBl scores were associated (P < .001) in frequentist models with better ratings of Health Plan (coefficient ± standard error: 0.33 ± 0.08) and better Getting Care Quickly scores (0.51 ± 0.09). In Bayesian models, individuals with higher illness burden had similar results on the same two measures and also reported reliably worse Overall Care experiences (coefficient ± posterior SD: -0.17 ± 0.06). Illness burden may influence how people experience care or report those experiences. Individuals with greater illness burdens may need intensive care coordination and multilevel interventions before and after a cancer diagnosis.
Copyright © 2022 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cancer; Care experiences; Claims data; Comorbidity; Survey data

Mesh:

Year:  2022        PMID: 35272981      PMCID: PMC9233114          DOI: 10.1016/j.jgo.2022.02.017

Source DB:  PubMed          Journal:  J Geriatr Oncol        ISSN: 1879-4068            Impact factor:   3.929


  25 in total

1.  Less Use of Extreme Response Options by Asians to Standardized Care Scenarios May Explain Some Racial/Ethnic Differences in CAHPS Scores.

Authors:  Lauren A Mayer; Marc N Elliott; Ann Haas; Ron D Hays; Robin M Weinick
Journal:  Med Care       Date:  2016-01       Impact factor: 2.983

2.  Care experiences among dually enrolled older adults with cancer: SEER-CAHPS, 2005-2013.

Authors:  Lisa M Lines; Julia Cohen; Michael T Halpern; Ashley Wilder Smith; Erin E Kent
Journal:  Cancer Causes Control       Date:  2019-08-17       Impact factor: 2.506

3.  The influence of comorbidities on overall survival among older women diagnosed with breast cancer.

Authors:  Jennifer L Patnaik; Tim Byers; Carolyn Diguiseppi; Thomas D Denberg; Dana Dabelea
Journal:  J Natl Cancer Inst       Date:  2011-06-30       Impact factor: 13.506

4.  Case-mix adjustment of the CAHPS Hospital Survey.

Authors:  A James O'Malley; Alan M Zaslavsky; Marc N Elliott; Lawrence Zaborski; Paul D Cleary
Journal:  Health Serv Res       Date:  2005-12       Impact factor: 3.402

5.  The health care experience of patients with cancer during the last year of life: Analysis of the SEER-CAHPS data set.

Authors:  Michael T Halpern; Matthew P Urato; Erin E Kent
Journal:  Cancer       Date:  2016-09-21       Impact factor: 6.860

Review 6.  Impact of age and comorbidity on treatment and outcomes in elderly cancer patients.

Authors:  Ronald C Chen; Trevor J Royce; Martine Extermann; Bryce B Reeve
Journal:  Semin Radiat Oncol       Date:  2012-10       Impact factor: 5.934

7.  Prostate cancer treatment and survival: evidence for men with prevalent comorbid conditions.

Authors:  Cathy J Bradley; Bassam Dahman; Mitchell Anscher
Journal:  Med Care       Date:  2014-06       Impact factor: 2.983

8.  Random survival forests using linked data to measure illness burden among individuals before or after a cancer diagnosis: Development and internal validation of the SEER-CAHPS illness burden index.

Authors:  Lisa M Lines; Julia Cohen; Justin Kirschner; Michael T Halpern; Erin E Kent; Michelle A Mollica; Ashley Wilder Smith
Journal:  Int J Med Inform       Date:  2020-10-21       Impact factor: 4.046

9.  Current guidelines have limited applicability to patients with comorbid conditions: a systematic analysis of evidence-based guidelines.

Authors:  Marjolein Lugtenberg; Jako S Burgers; Carolyn Clancy; Gert P Westert; Eric C Schneider
Journal:  PLoS One       Date:  2011-10-20       Impact factor: 3.240

10.  Psychometric properties of an instrument to assess Medicare beneficiaries' prescription drug plan experiences.

Authors:  Steven C Martino; Marc N Elliott; Paul D Cleary; David E Kanouse; Julie A Brown; Karen L Spritzer; Amy Heller; Ron D Hays
Journal:  Health Care Financ Rev       Date:  2009
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