Literature DB >> 19597221

Composite measures for predicting surgical mortality in the hospital.

Justin B Dimick1, Douglas O Staiger, Onur Baser, John D Birkmeyer.   

Abstract

Although payers increasingly report information on hospital volume and mortality from surgery, the value of these data is uncertain. Using national Medicare data for six surgical operations (covering the years 2003-2006), we created a composite measure based on these two quality indicators. We found that this simple measure was a strong predictor of future performance for all six operations. In this regard, it was more effective than the individual measures. Such measures would be useful for helping patients and payers identify low-mortality hospitals for major surgery.

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Year:  2009        PMID: 19597221     DOI: 10.1377/hlthaff.28.4.1189

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


  37 in total

1.  What is the best way to estimate hospital quality outcomes? A simulation approach.

Authors:  Andrew Ryan; James Burgess; Robert Strawderman; Justin Dimick
Journal:  Health Serv Res       Date:  2012-02-21       Impact factor: 3.402

2.  Ranking hospitals on surgical mortality: the importance of reliability adjustment.

Authors:  Justin B Dimick; Douglas O Staiger; John D Birkmeyer
Journal:  Health Serv Res       Date:  2010-08-16       Impact factor: 3.402

3.  Composite Measures of Health Care Provider Performance: A Description of Approaches.

Authors:  Michael Shwartz; Joseph D Restuccia; Amy K Rosen
Journal:  Milbank Q       Date:  2015-12       Impact factor: 4.911

Review 4.  The future of quality measurement in the United States.

Authors:  Fia Yi
Journal:  Clin Colon Rectal Surg       Date:  2014-03

5.  A pressure ulcer and fall rate quality composite index for acute care units: A measure development study.

Authors:  Diane K Boyle; Ananda Jayawardhana; Mary E Burman; Nancy E Dunton; Vincent S Staggs; Sandra Bergquist-Beringer; Byron J Gajewski
Journal:  Int J Nurs Stud       Date:  2016-09-01       Impact factor: 5.837

6.  Role of Hospital Volumes in Identifying Low-Performing and High-Performing Aortic and Mitral Valve Surgical Centers in the United States.

Authors:  Rohan Khera; Ambarish Pandey; Thomas Koshy; Colby Ayers; Brahmajee K Nallamothu; Sandeep R Das; Mark H Drazner; Michael E Jessen; Ajay J Kirtane; Timothy J Gardner; James A de Lemos; Deepak L Bhatt; Dharam J Kumbhani
Journal:  JAMA Cardiol       Date:  2017-12-01       Impact factor: 14.676

7.  The Hospital Compare mortality model and the volume-outcome relationship.

Authors:  Jeffrey H Silber; Paul R Rosenbaum; Tanguy J Brachet; Richard N Ross; Laura J Bressler; Orit Even-Shoshan; Scott A Lorch; Kevin G Volpp
Journal:  Health Serv Res       Date:  2010-10       Impact factor: 3.402

8.  Association Between 30-Day Mortality After Percutaneous Coronary Intervention and Education and Certification Variables for New York State Interventional Cardiologists.

Authors:  Sameed Ahmed M Khatana; Paul N Fiorilli; Ashwin S Nathan; Daniel M Kolansky; Nandita Mitra; Peter W Groeneveld; Jay Giri
Journal:  Circ Cardiovasc Interv       Date:  2018-09       Impact factor: 6.546

9.  Revenue, relationships and routines: the social organization of acute myocardial infarction patient transfers in the United States.

Authors:  Tiffany C Veinot; Emily A Bosk; K P Unnikrishnan; Theodore J Iwashyna
Journal:  Soc Sci Med       Date:  2012-07-27       Impact factor: 4.634

10.  Variation in hospital mortality rates with inpatient cancer surgery.

Authors:  Sandra L Wong; ShaʼShonda L Revels; Huiying Yin; Andrew K Stewart; Andrea McVeigh; Mousumi Banerjee; John D Birkmeyer
Journal:  Ann Surg       Date:  2015-04       Impact factor: 12.969

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