Literature DB >> 17875841

Publicly available hospital comparison web sites: determination of useful, valid, and appropriate information for comparing surgical quality.

Michael J Leonardi1, Marcia L McGory, Clifford Y Ko.   

Abstract

OBJECTIVE: To explore hospital comparison Web sites for general surgery based on: (1) a systematic Internet search, (2) Web site quality evaluation, and (3) exploration of possible areas of improvement.
DESIGN: A systematic Internet search was performed to identify hospital quality comparison Web sites in September 2006. Publicly available Web sites were rated on accessibility, data/statistical transparency, appropriateness, and timeliness. A sample search was performed to determine ranking consistency.
RESULTS: Six national hospital comparison Web sites were identified: 1 government (Hospital Compare [Centers for Medicare and Medicaid Services]), 2 nonprofit (Quality Check [Joint Commission on Accreditation of Healthcare Organizations] and Hospital Quality and Safety Survey Results [Leapfrog Group]), and 3 proprietary sites (names withheld). For accessibility and data transparency, the government and nonprofit Web sites were best. For appropriateness, the proprietary Web sites were best, comparing multiple surgical procedures using a combination of process, structure, and outcome measures. However, none of these sites explicitly defined terms such as complications. Two proprietary sites allowed patients to choose ranking criteria. Most data on these sites were 2 years old or older. A sample search of 3 surgical procedures at 4 hospitals demonstrated significant inconsistencies.
CONCLUSIONS: Patients undergoing surgery are increasingly using the Internet to compare hospital quality. However, a review of available hospital comparison Web sites shows suboptimal measures of quality and inconsistent results. This may be partially because of a lack of complete and timely data. Surgeons should be involved with quality comparison Web sites to ensure appropriate methods and criteria.

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Mesh:

Year:  2007        PMID: 17875841     DOI: 10.1001/archsurg.142.9.863

Source DB:  PubMed          Journal:  Arch Surg        ISSN: 0004-0010


  8 in total

1.  Defining a high performance healthcare organisation.

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2.  Variation in surgical quality measure adherence within hospital referral regions: do publicly reported surgical quality measures distinguish among hospitals that patients are likely to compare?

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Journal:  Health Serv Res       Date:  2014-03-11       Impact factor: 3.402

3.  Building an Open Health Data Analytics Platform: a Case Study Examining Relationships and Trends in Seniority and Performance in Healthcare Providers.

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Journal:  J Healthc Inform Res       Date:  2018-04-16

4.  Public reporting of quality data for stroke: is it measuring quality?

Authors:  Adam Kelly; Joel P Thompson; Deborah Tuttle; Curtis Benesch; Robert G Holloway
Journal:  Stroke       Date:  2008-09-04       Impact factor: 7.914

5.  Epidemiology and outcomes of older adults with burn injury: an analysis of the National Burn Repository.

Authors:  Tam N Pham; C Bradley Kramer; Jin Wang; Frederick P Rivara; David M Heimbach; Nicole S Gibran; Matthew B Klein
Journal:  J Burn Care Res       Date:  2009 Jan-Feb       Impact factor: 1.845

6.  Method for Sorting and Pairwise Selection of Nanobodies for the Development of Highly Sensitive Sandwich Immunoassays.

Authors:  Martín A Rossotti; Macarena Pirez; Andres Gonzalez-Techera; Yongliang Cui; Candace S Bever; Kin S S Lee; Christophe Morisseau; Carmen Leizagoyen; Shirley Gee; Bruce D Hammock; Gualberto González-Sapienza
Journal:  Anal Chem       Date:  2015-11-18       Impact factor: 6.986

7.  Association between hospital-reported Leapfrog Safe Practices Scores and inpatient mortality.

Authors:  Leslie P Kernisan; Sei J Lee; W John Boscardin; C Seth Landefeld; R Adams Dudley
Journal:  JAMA       Date:  2009-04-01       Impact factor: 56.272

8.  The Patient- And Nutrition-Derived Outcome Risk Assessment Score (PANDORA): Development of a Simple Predictive Risk Score for 30-Day In-Hospital Mortality Based on Demographics, Clinical Observation, and Nutrition.

Authors:  Michael Hiesmayr; Sophie Frantal; Karin Schindler; Michael Themessl-Huber; Mohamed Mouhieddine; Christian Schuh; Elisabeth Pernicka; Stéphane Schneider; Pierre Singer; Olle Ljunqvist; Claude Pichard; Alessandro Laviano; Sigrid Kosak; Peter Bauer
Journal:  PLoS One       Date:  2015-05-22       Impact factor: 3.240

  8 in total

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