Literature DB >> 26927625

Indirect Standardization Matching: Assessing Specific Advantage and Risk Synergy.

Jeffrey H Silber1,2,3,4,5, Paul R Rosenbaum5,6, Richard N Ross1, Justin M Ludwig1, Wei Wang1, Bijan A Niknam1, Alexander S Hill1, Orit Even-Shoshan1,5, Rachel R Kelz5,7, Lee A Fleisher3,5.   

Abstract

OBJECTIVE: To develop a method to allow a hospital to compare its performance using its entire patient population to the outcomes of very similar patients treated elsewhere. DATA SOURCES/
SETTING: Medicare claims in orthopedics and common general, gynecologic, and urologic surgery from Illinois, New York, and Texas from 2004 to 2006. STUDY
DESIGN: Using two example "focal" hospitals, each hospital's patients were matched to 10 very similar patients selected from 619 other hospitals. DATA COLLECTION/EXTRACTION
METHODS: All patients were used at each focal hospital, and we found the 10 closest matched patients from control hospitals with exactly the same principal procedure as each focal patient. PRINCIPAL
FINDINGS: We achieved exact matches on all procedures and very close matches for other patient characteristics for both hospitals. There were few to no differences between each hospital's patients and their matched control patients on most patient characteristics, yet large and significant differences were observed for mortality, failure-to-rescue, and cost.
CONCLUSION: Indirect standardization matching can produce fair audits of quality and cost, allowing for a comprehensive, transparent, and relevant assessment of all patients at a focal hospital. With this approach, hospitals will be better able to benchmark their performance and determine where quality improvement is most needed. © Health Research and Educational Trust.

Entities:  

Keywords:  Quality of care; cost; health care research; outcomes research

Mesh:

Year:  2016        PMID: 26927625      PMCID: PMC5134157          DOI: 10.1111/1475-6773.12470

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  15 in total

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Journal:  Stat Sci       Date:  2010-02-01       Impact factor: 2.901

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Authors:  Donald B Rubin
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4.  Sensitivity analysis for m-estimates, tests, and confidence intervals in matched observational studies.

Authors:  Paul R Rosenbaum
Journal:  Biometrics       Date:  2007-06       Impact factor: 2.571

5.  Hospital and patient characteristics associated with death after surgery. A study of adverse occurrence and failure to rescue.

Authors:  J H Silber; S V Williams; H Krakauer; J S Schwartz
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6.  Influence of patient and hospital characteristics on anesthesia time in medicare patients undergoing general and orthopedic surgery.

Authors:  Jeffrey H Silber; Paul R Rosenbaum; Xuemei Zhang; Orit Even-Shoshan
Journal:  Anesthesiology       Date:  2007-02       Impact factor: 7.892

7.  Template matching for auditing hospital cost and quality.

Authors:  Jeffrey H Silber; Paul R Rosenbaum; Richard N Ross; Justin M Ludwig; Wei Wang; Bijan A Niknam; Nabanita Mukherjee; Philip A Saynisch; Orit Even-Shoshan; Rachel R Kelz; Lee A Fleisher
Journal:  Health Serv Res       Date:  2014-03-03       Impact factor: 3.402

8.  A hospital-specific template for benchmarking its cost and quality.

Authors:  Jeffrey H Silber; Paul R Rosenbaum; Richard N Ross; Justin M Ludwig; Wei Wang; Bijan A Niknam; Philip A Saynisch; Orit Even-Shoshan; Rachel R Kelz; Lee A Fleisher
Journal:  Health Serv Res       Date:  2014-09-08       Impact factor: 3.402

9.  Medical and financial risks associated with surgery in the elderly obese.

Authors:  Jeffrey H Silber; Paul R Rosenbaum; Rachel R Kelz; Caroline E Reinke; Mark D Neuman; Richard N Ross; Orit Even-Shoshan; Guy David; Philip A Saynisch; Fabienne A Kyle; Dale W Bratzler; Lee A Fleisher
Journal:  Ann Surg       Date:  2012-07       Impact factor: 12.969

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Authors:  Andrea S Gershon; Michael A Campitelli; Ruth Croxford; Matthew B Stanbrook; Teresa To; Ross Upshur; Anne L Stephenson; Thérèse A Stukel
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Authors:  Jeffrey H Silber; Paul R Rosenbaum; Samuel D Pimentel; Shawna Calhoun; Wei Wang; James E Sharpe; Joseph G Reiter; Shivani A Shah; Lauren L Hochman; Orit Even-Shoshan
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Authors:  Sebastien Haneuse; José Zubizarreta; Sharon-Lise T Normand
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Authors:  Jeffrey H Silber; Paul R Rosenbaum; Bijan A Niknam; Richard N Ross; Joseph G Reiter; Alexander S Hill; Lauren L Hochman; Sydney E Brown; Alexander F Arriaga; Lee A Fleisher
Journal:  J Gen Intern Med       Date:  2019-11-12       Impact factor: 5.128

4.  Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System.

Authors:  Brenda M Vincent; Daniel Molling; Gabriel J Escobar; Timothy P Hofer; Theodore J Iwashyna; Vincent X Liu; Amy K Rosen; Andrew M Ryan; Sarah Seelye; Wyndy L Wiitala; Hallie C Prescott
Journal:  Med Care       Date:  2021-12-01       Impact factor: 2.983

5.  Emerging approaches to multiple chronic condition assessment.

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6.  Measuring quality of care in moderate and late preterm infants.

Authors:  Elizabeth G Salazar; Sara C Handley; Lucy T Greenberg; Erika M Edwards; Scott A Lorch
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7.  A method to reduce imbalance for site-level randomized stepped wedge implementation trial designs.

Authors:  Robert A Lew; Christopher J Miller; Bo Kim; Hongsheng Wu; Kelly Stolzmann; Mark S Bauer
Journal:  Implement Sci       Date:  2019-05-03       Impact factor: 7.327

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