Literature DB >> 17001263

Data sources for measuring comorbidity: a comparison of hospital records and medicare claims for cancer patients.

Carrie N Klabunde1, Linda C Harlan, Joan L Warren.   

Abstract

BACKGROUND: Identifying appropriate comorbidity data sources is a key consideration in health services and outcomes research.
OBJECTIVE: Using cancer patients as an example, we compared comorbid conditions identified: 1) on the discharge facesheet versus full hospital medical record and 2) in the hospital record versus Medicare claims, both precancer diagnosis and associated with a cancer treatment-related index hospitalization.
METHODS: We used data from 1995 Surveillance, Epidemiology and End Results patterns of care studies for 1,382 patients. Comorbid conditions were ascertained from the hospital record associated with the most definitive cancer treatment and Medicare claims. We calculated the prevalence for and assessed concordances among 12 conditions derived from the hospital record facesheet; full hospital record; Medicare claims precancer diagnosis, with and without a rule-out algorithm applied; and Medicare claims associated with an index hospitalization.
RESULTS: The proportion of patients with one or more comorbid conditions varied by data source, from 21% for the facesheet to 85% for prediagnosis Medicare claims without the rule-out algorithm. Condition prevalences were substantially lower for the facesheet compared with the full hospital record. For prediagnosis Medicare claims, condition prevalences were more than 1.7 times greater in the absence of an algorithm to screen for rule-out diagnoses. Measures assessing concordance between the full hospital record and prediagnosis Medicare claims (rule-out algorithm applied) showed modest agreement.
CONCLUSIONS: The hospital record and Medicare claims are complementary data sources for identifying comorbid conditions. Comorbidity is greatly underascertained when derived only from the facesheet of the hospital record. Investigators using Part B Medicare claims to measure comorbidity should remove conditions that are listed for purposes of generating bills but are not true comorbidities.

Entities:  

Mesh:

Year:  2006        PMID: 17001263     DOI: 10.1097/01.mlr.0000223480.52713.b9

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


  74 in total

1.  Trends in anemia management in lung and colon cancer patients in the US Department of Veterans Affairs, 2002-2008.

Authors:  Elizabeth Tarlov; Kevin T Stroupe; Todd A Lee; Thomas W Weichle; Qiuying L Zhang; Laura C Michaelis; Howard Ozer; Margaret M Browning; Denise M Hynes
Journal:  Support Care Cancer       Date:  2011-09-20       Impact factor: 3.603

2.  Contribution of individual diseases to death in older adults with multiple diseases.

Authors:  Mary E Tinetti; Gail J McAvay; Terrence E Murphy; Cary P Gross; Haiqun Lin; Heather G Allore
Journal:  J Am Geriatr Soc       Date:  2012-06-26       Impact factor: 5.562

3.  Surgery and adjuvant chemotherapy use among veterans with colon cancer: insights from a California study.

Authors:  Denise M Hynes; Elizabeth Tarlov; Ramon Durazo-Arvizu; Ruth Perrin; Qiuying Zhang; Thomas Weichle; M Rosario Ferreira; Todd Lee; Al B Benson; Nirmala Bhoopalam; Charles L Bennett
Journal:  J Clin Oncol       Date:  2010-04-20       Impact factor: 44.544

4.  Metformin Improves Survival in Patients with Pancreatic Ductal Adenocarcinoma and Pre-Existing Diabetes: A Propensity Score Analysis.

Authors:  S Amin; G Mhango; J Lin; A Aronson; J Wisnivesky; P Boffetta; Aimee L Lucas
Journal:  Am J Gastroenterol       Date:  2016-07-19       Impact factor: 10.864

Review 5.  Validity of Claims Data for the Identification of Male Infertility.

Authors:  Yash S Khandwala; Chiyuan A Zhang; Shufeng Li; Mark R Cullen; Michael L Eisenberg
Journal:  Curr Urol Rep       Date:  2017-09       Impact factor: 3.092

6.  Using Self-reports or Claims to Assess Disease Prevalence: It's Complicated.

Authors:  Patricia St Clair; Étienne Gaudette; Henu Zhao; Bryan Tysinger; Roxanna Seyedin; Dana P Goldman
Journal:  Med Care       Date:  2017-08       Impact factor: 2.983

7.  Screening outcomes in older US women undergoing multiple mammograms in community practice: does interval, age, or comorbidity score affect tumor characteristics or false positive rates?

Authors:  Dejana Braithwaite; Weiwei Zhu; Rebecca A Hubbard; Ellen S O'Meara; Diana L Miglioretti; Berta Geller; Kim Dittus; Dan Moore; Karen J Wernli; Jeanne Mandelblatt; Karla Kerlikowske
Journal:  J Natl Cancer Inst       Date:  2013-02-05       Impact factor: 13.506

8.  Reduced feeding tube duration with intensity-modulated radiation therapy for head and neck cancer: A Surveillance, Epidemiology, and End Results-Medicare Analysis.

Authors:  Beth M Beadle; Kai-Ping Liao; Sharon H Giordano; Adam S Garden; Katherine A Hutcheson; Stephen Y Lai; B Ashleigh Guadagnolo
Journal:  Cancer       Date:  2016-09-23       Impact factor: 6.860

9.  Comparison of comorbidity collection methods.

Authors:  Dorina Kallogjeri; Sheila M Gaynor; Marilyn L Piccirillo; Raymond A Jean; Edward L Spitznagel; Jay F Piccirillo
Journal:  J Am Coll Surg       Date:  2014-03-19       Impact factor: 6.113

10.  The effect of statins on survival in patients with stage IV lung cancer.

Authors:  Jenny J Lin; Nicole Ezer; Keith Sigel; Grace Mhango; Juan P Wisnivesky
Journal:  Lung Cancer       Date:  2016-07-06       Impact factor: 5.705

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.