Literature DB >> 15471771

Use of Medicare claims data to monitor provider-specific performance among patients with severe chronic illness.

John E Wennberg1, Elliott S Fisher, Thérèse A Stukel, Sandra M Sharp.   

Abstract

This study illustrates that Medicare claims can be used to measure population-based, provider-specific rates of resource inputs, utilization, and Medicare spending. The target populations are seventy-seven cohorts of chronically ill Medicare enrollees who received most of their care from seventy-seven well-known U.S. hospitals. Striking variations are documented in resource inputs and use of services during the last six months of life. The patterns of care seen in the progression of chronic illness correlate highly with care received during previous periods. We believe that hospital-specific measures can be helpful in identifying providers with acceptable quality indices who are also relatively efficient in managing chronic illness.

Entities:  

Mesh:

Year:  2004        PMID: 15471771     DOI: 10.1377/hlthaff.var.5

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


  19 in total

1.  Chronic care improvement in primary care: evaluation of an integrated pay-for-performance and practice-based care coordination program among elderly patients with diabetes.

Authors:  Peter J Fagan; Alyson B Schuster; Cynthia Boyd; Jill A Marsteller; Michael Griswold; Shannon M E Murphy; Linda Dunbar; Christopher B Forrest
Journal:  Health Serv Res       Date:  2010-09-17       Impact factor: 3.402

2.  The relationship between health plan performance measures and physician network overlap: implications for measuring plan quality.

Authors:  Daniel D Maeng; Dennis P Scanlon; Michael E Chernew; Tim Gronniger; Walter P Wodchis; Catherine G McLaughlin
Journal:  Health Serv Res       Date:  2010-04-09       Impact factor: 3.402

3.  Physician visits, hospitalizations, and socioeconomic status: ambulatory care sensitive conditions in a canadian setting.

Authors:  Leslie L Roos; Randy Walld; Julia Uhanova; Ruth Bond
Journal:  Health Serv Res       Date:  2005-08       Impact factor: 3.402

4.  Hospital spending and inpatient mortality: evidence from California: an observational study.

Authors:  John A Romley; Anupam B Jena; Dana P Goldman
Journal:  Ann Intern Med       Date:  2011-02-01       Impact factor: 25.391

5.  The structure of risk adjustment for private plans in Medicare.

Authors:  Joseph P Newhouse; Jie Huang; Richard J Brand; Vicki Fung; John T Hsu
Journal:  Am J Manag Care       Date:  2011-06-01       Impact factor: 2.229

6.  Waste in the U.S. Health care system: a conceptual framework.

Authors:  Tanya G K Bentley; Rachel M Effros; Kartika Palar; Emmett B Keeler
Journal:  Milbank Q       Date:  2008-12       Impact factor: 4.911

7.  Variability in carotid endarterectomy at a single medical center: an outcome and cost analysis.

Authors:  Sibu P Saha; Peter M Rodgers-Fischl; David J Minion; Victor A Ferraris; Daniel L Davenport
Journal:  Int J Angiol       Date:  2012-12

8.  Case finding for patients at risk of readmission to hospital: development of algorithm to identify high risk patients.

Authors:  John Billings; Jennifer Dixon; Tod Mijanovich; David Wennberg
Journal:  BMJ       Date:  2006-06-30

9.  Electronic health records vs Medicaid claims: completeness of diabetes preventive care data in community health centers.

Authors:  Jennifer E Devoe; Rachel Gold; Patti McIntire; Jon Puro; Susan Chauvie; Charles A Gallia
Journal:  Ann Fam Med       Date:  2011 Jul-Aug       Impact factor: 5.166

10.  The quality of care provided to hospitalized patients at the end of life.

Authors:  Anne M Walling; Steven M Asch; Karl A Lorenz; Carol P Roth; Tod Barry; Katherine L Kahn; Neil S Wenger
Journal:  Arch Intern Med       Date:  2010-06-28
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.