Lisa M Lines1, Julia Cohen2, Justin Kirschner2, Daniel H Barch3, Michael T Halpern4, Erin E Kent5, Michelle A Mollica4, Ashley Wilder Smith4. 1. RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC 27709, United States of America; University of Massachusetts Chan Medical School, 55 Lake Ave., North Worcester, MA 01655, United States of America. Electronic address: llines@rti.org. 2. RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC 27709, United States of America. 3. RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC 27709, United States of America; Psychology Department, Tufts University, Medford, MA, United States of America. 4. National Cancer Institute, Division of Cancer Control and Population Sciences, Healthcare Delivery Research Program, United States of America. 5. Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, United States of America; University of North Carolina Lineberger Comprehensive Cancer Center, United States of America.
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.
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.
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
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
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
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
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
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