Literature DB >> 25426765

A comparison of 2 surgical site infection monitoring systems.

Mila H Ju1, Clifford Y Ko2, Bruce L Hall3, Charles L Bosk4, Karl Y Bilimoria1, Elizabeth C Wick5.   

Abstract

IMPORTANCE: Surgical site infection (SSI) has emerged as the leading publicly reported surgical outcome and is tied to payment determinations. Many hospitals monitor SSIs using the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP), in addition to mandatory participation (for most states) in the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN), which has resulted in duplication of effort and incongruent data.
OBJECTIVE: To identify discrepancies in the implementation of the NHSN and the ACS NSQIP at hospitals that may be affecting the respective SSI rates. DESIGN, SETTING, AND PARTICIPANTS: A pilot sample of hospitals that participate in both the NHSN and the ACS NSQIP.
INTERVENTIONS: For each hospital, observed rates and risk-adjusted observed to expected ratios for year 2012 colon SSIs were collected from both programs. The implementation methods of both programs were identified, including telephone interviews with infection preventionists who collect data for the NHSN at each hospital. MAIN OUTCOMES AND MEASURES: Collection methods and colon SSI rates for the NHSN at each hospital were compared with those of the ACS NSQIP.
RESULTS: Of 16 hospitals, 11 were teaching hospitals with at least 500 beds. The mean observed colon SSI rates were dissimilar between the 2 programs, 5.7% (range, 2.0%-14.5%) for the NHSN vs 13.5% (range, 4.6%-26.7%) for the ACS NSQIP. The mean difference between the NHSN and the ACS NSQIP was 8.3% (range, 1.6%-18.8%), with the ACS NSQIP rate always higher. The correlation between the observed to expected ratios for the 2 programs was nonsignificant (Pearson product moment correlation, ρ = 0.4465; P = .08). The NHSN collection methods were dissimilar among interviewed hospitals. An SSI managed as an outpatient case would usually be missed under the current NHSN practices. CONCLUSIONS AND RELEVANCE: Colon SSI rates from the NHSN and the ACS NSQIP cannot be used interchangeably to evaluate hospital performance and determine reimbursement. Hospitals should not use the ACS NSQIP colon SSI rates for the NHSN reports because that would likely result in the hospital being an outlier for performance. It is imperative to reconcile SSI monitoring, develop consistent definitions, and establish one reliable method. The current state hinders hospital improvement efforts by adding unnecessary confusion to the already complex arena of perioperative improvement.

Entities:  

Mesh:

Year:  2015        PMID: 25426765     DOI: 10.1001/jamasurg.2014.2891

Source DB:  PubMed          Journal:  JAMA Surg        ISSN: 2168-6254            Impact factor:   14.766


  13 in total

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2.  Electronic Surveillance of Surgical Site Infections.

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Journal:  Surg Infect (Larchmt)       Date:  2017-04-12       Impact factor: 2.150

3.  Truth in Reporting: How Data Capture Methods Obfuscate Actual Surgical Site Infection Rates within a Health Care Network System.

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4.  Wound Concerns and Healthcare Consumption of Resources after Colorectal Surgery: An Opportunity for Innovation?

Authors:  Puja M Shah; Heather L Evans; Amy Harrigan; Robert G Sawyer; Charles M Friel; Traci L Hedrick
Journal:  Surg Infect (Larchmt)       Date:  2017-05-09       Impact factor: 2.150

5.  Identification of postoperative complications using electronic health record data and machine learning.

Authors:  Michael Bronsert; Abhinav B Singh; William G Henderson; Karl Hammermeister; Robert A Meguid; Kathryn L Colborn
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6.  Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.

Authors:  Jianlin Shi; Siru Liu; Liese C C Pruitt; Carolyn L Luppens; Jeffrey P Ferraro; Adi V Gundlapalli; Wendy W Chapman; Brian T Bucher
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

7.  Surgical site infection: comparing surgeon versus patient self-report.

Authors:  Julius Cuong Pham; Melinda J Ashton; Chieko Kimata; Della M Lin; Beau K Nakamoto
Journal:  J Surg Res       Date:  2015-12-30       Impact factor: 2.192

8.  Identification of urinary tract infections using electronic health record data.

Authors:  Kathryn L Colborn; Michael Bronsert; Karl Hammermeister; William G Henderson; Abhinav B Singh; Robert A Meguid
Journal:  Am J Infect Control       Date:  2018-12-04       Impact factor: 2.918

Review 9.  A systematic review and meta-synthesis of policy intervention characteristics that influence the implementation of government-directed policy in the hospital setting: implications for infection prevention and control.

Authors:  Sally M Havers; Elizabeth Kate Martin; Andrew Wilson; Lisa Hall
Journal:  J Infect Prev       Date:  2020-05-04

10.  Portable Automated Surveillance of Surgical Site Infections Using Natural Language Processing: Development and Validation.

Authors:  Brian T Bucher; Jianlin Shi; Jeffrey P Ferraro; David E Skarda; Matthew H Samore; John F Hurdle; Adi V Gundlapalli; Wendy W Chapman; Samuel R G Finlayson
Journal:  Ann Surg       Date:  2020-10       Impact factor: 13.787

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