Literature DB >> 29282576

Application of a simple, affordable quality metric tool to colorectal, upper gastrointestinal, hernia, and hepatobiliary surgery patients: the HARM score.

Justin T Brady1, Bona Ko2, Samuel F Hohmann3,4, Benjamin P Crawshaw1, Jennifer A Leinicke1, Scott R Steele5, Knut M Augestad6,7, Conor P Delaney8.   

Abstract

BACKGROUND: Quality is the major driver for both clinical and financial assessment. There remains a need for simple, affordable, quality metric tools to evaluate patient outcomes, which led us to develop the HospitAl length of stay, Readmission and Mortality (HARM) score. We hypothesized that the HARM score would be a reliable tool to assess patient outcomes across various surgical specialties.
METHODS: From 2011 to 2015, we identified colorectal, hepatobiliary, upper gastrointestinal, and hernia surgery admissions using the Vizient Clinical Database. Individual and hospital HARM scores were calculated from length of stay, 30-day readmission, and mortality rates. We evaluated the correlation of HARM scores with complication rates using the Clavien-Dindo classification.
RESULTS: We identified 525,083 surgical patients: 206,981 colorectal, 164,691 hepatobiliary, 97,157 hernia, and 56,254 upper gastrointestinal. Overall, 53.8% of patients were admitted electively with a mean HARM score of 2.24; 46.2% were admitted emergently with a mean HARM score of 1.45 (p < 0.0001). All HARM components correlated with patient complications on logistic regression (p < 0.0001). The mean length of stay increased from 3.2 ± 1.8 days for a HARM score < 2 to 15.1 ± 12.2 days for a HARM score > 4 (p < 0.001). In elective admissions, for HARM categories of < 2, 2-< 3, 3-4, and > 4, complication rates were 9.3, 23.2, 38.8, and 71.6%, respectively. There was a similar trend for increasing HARM score in emergent admissions as well. For all surgical procedure categories, increasing HARM score, with and without risk adjustment, correlated with increasing severity of complications by Clavien-Dindo classification.
CONCLUSIONS: The HARM score is an easy-to-use quality metric that correlates with increasing complication rates and complication severity across multiple surgical disciplines when evaluated on a large administrative database. This inexpensive tool could be adopted across multiple institutions to compare the quality of surgical care.

Entities:  

Keywords:  Colorectal; Hepatobiliary; Quality; Surgical outcomes

Mesh:

Year:  2017        PMID: 29282576     DOI: 10.1007/s00464-017-5998-7

Source DB:  PubMed          Journal:  Surg Endosc        ISSN: 0930-2794            Impact factor:   4.584


  23 in total

1.  Mortality after elective colon resection: the search for outcomes that define quality in surgical practice.

Authors:  Adrian T Billeter; Hiram C Polk; Samuel F Hohmann; Motaz Qadan; Donald E Fry; Jeffrey R Jorden; Michael H McCafferty; Susan Galandiuk
Journal:  J Am Coll Surg       Date:  2012-03-06       Impact factor: 6.113

2.  Quality of benchmarks for assessment of care will influence outcome.

Authors:  Lawrence Kim; Charles Mabry; V Suzanne Klimberg
Journal:  Ann Surg       Date:  2007-05       Impact factor: 12.969

3.  Empirically derived composite measures of surgical performance.

Authors:  Douglas O Staiger; Justin B Dimick; Onur Baser; Zhaohui Fan; John D Birkmeyer
Journal:  Med Care       Date:  2009-02       Impact factor: 2.983

4.  Reducing the risk of surgical site infections: did we really think SCIP was going to lead us to the promised land?

Authors:  Charles E Edmiston; Maureen Spencer; Brian D Lewis; Kellie R Brown; Peter J Rossi; Cindy R Henen; Heidi W Smith; Gary R Seabrook
Journal:  Surg Infect (Larchmt)       Date:  2011-07-18       Impact factor: 2.150

5.  Factors related to readmission after major elective surgery.

Authors:  Gregory C Wilson; R Cutler Quillin; Jeffrey M Sutton; Koffi Wima; Joshua J Shaw; Richard S Hoehn; Ian M Paquette; Daniel E Abbott; Shimul A Shah
Journal:  Dig Dis Sci       Date:  2014-07-27       Impact factor: 3.199

6.  Adherence to surgical care improvement project measures and the association with postoperative infections.

Authors:  Jonah J Stulberg; Conor P Delaney; Duncan V Neuhauser; David C Aron; Pingfu Fu; Siran M Koroukian
Journal:  JAMA       Date:  2010-06-23       Impact factor: 56.272

7.  Composite measures for profiling hospitals on surgical morbidity.

Authors:  Justin B Dimick; Douglas O Staiger; Bruce L Hall; Clifford Y Ko; John D Birkmeyer
Journal:  Ann Surg       Date:  2013-01       Impact factor: 12.969

8.  Association of postoperative complications with hospital costs and length of stay in a tertiary care center.

Authors:  Nadia A Khan; Hude Quan; Jennifer M Bugar; Jane B Lemaire; Rollin Brant; William A Ghali
Journal:  J Gen Intern Med       Date:  2006-02       Impact factor: 5.128

9.  Variation by center and economic burden of readmissions after liver transplantation.

Authors:  Gregory C Wilson; Richard S Hoehn; Audrey E Ertel; Koffi Wima; R Cutler Quillin; Sam Hohmann; Flavio Paterno; Daniel E Abbott; Shimul A Shah
Journal:  Liver Transpl       Date:  2015-07       Impact factor: 5.799

10.  Composite measures for profiling hospitals on bariatric surgery performance.

Authors:  Justin B Dimick; Nancy J Birkmeyer; Jonathan F Finks; David A Share; Wayne J English; Arthur M Carlin; John D Birkmeyer
Journal:  JAMA Surg       Date:  2014-01       Impact factor: 14.766

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