Literature DB >> 18371510

Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care-associated infections.

Kurt B Stevenson1, Yosef Khan, Jeanne Dickman, Terri Gillenwater, Pat Kulich, Carol Myers, David Taylor, Jennifer Santangelo, Jennifer Lundy, David Jarjoura, Xiaobai Li, Janice Shook, Julie E Mangino.   

Abstract

BACKGROUND: ICD-9-CM coding alone has been proposed as a method of surveillance for health care-associated infections (HAIs). The accuracy of this method, however, relative to accepted infection control criteria is not known.
METHODS: Retrospective analysis of patients at an academic medical center in 2005 who underwent surgical procedures or who were at risk for catheter-associated bloodstream infections or ventilator-associated pneumonia was performed. Patients previously identified with HAIs by Centers for Disease Control and Prevention's National Healthcare Safety Network surveillance methods were compared with those of the same risk group identified by secondary infection ICD-9-CM codes. Discordant cases identified by only coding were all rereviewed and adjusted prior to final analysis. When coding and surveillance were both negative, a sample of patients was used to estimate the proportion of false negatives in this group.
RESULTS: The positive predictive values (PPVs) ranged from 0.14 to 0.51 with an aggregate of 0.23, even after adjustment for additional cases detected on subsequent medical record review. The negative predictive values (NPVs) ranged from 0.91 to 1.00, with an aggregate of 0.96. The estimates of the true variance of PPVs and NPVs across surgical procedures were small (0.0129, standard error, 0.009; 0.000145, standard error, 0.00019, respectively) and could be mostly explained by variation in prevalence of surgical site infections.
CONCLUSION: Administrative coding alone appears to be a poor tool to be used as an infection control surveillance method. Its proposed use for routine HAI surveillance, public reporting of HAIs, interfacility comparisons, and nonpayment for performance should be seriously questioned.

Entities:  

Mesh:

Year:  2008        PMID: 18371510     DOI: 10.1016/j.ajic.2008.01.004

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  34 in total

1.  Comparison of two computer algorithms to identify surgical site infections.

Authors:  Mandar Apte; Timothy Landers; Yoko Furuya; Sandra Hyman; Elaine Larson
Journal:  Surg Infect (Larchmt)       Date:  2011-12-02       Impact factor: 2.150

2.  Use of diagnosis codes and/or wound culture results for surveillance of surgical site infection after mastectomy and breast reconstruction.

Authors:  Margaret A Olsen; Victoria J Fraser
Journal:  Infect Control Hosp Epidemiol       Date:  2010-05       Impact factor: 3.254

3.  A comparison of methods to detect urinary tract infections using electronic data.

Authors:  Timothy Landers; Mandar Apte; Sandra Hyman; Yoko Furuya; Sherry Glied; Elaine Larson
Journal:  Jt Comm J Qual Patient Saf       Date:  2010-09

4.  CMS changes in reimbursement for HAIs: setting a research agenda.

Authors:  Patricia W Stone; Sherry A Glied; Peter D McNair; Nikolas Matthes; Bevin Cohen; Timothy F Landers; Elaine L Larson
Journal:  Med Care       Date:  2010-05       Impact factor: 2.983

5.  An electronic surveillance tool for catheter-associated urinary tract infection in intensive care units.

Authors:  Heather E Hsu; Erica S Shenoy; Douglas Kelbaugh; Winston Ware; Hang Lee; Pearl Zakroysky; David C Hooper; Rochelle P Walensky
Journal:  Am J Infect Control       Date:  2015-03-31       Impact factor: 2.918

6.  Validity and Reliability of Administrative Coded Data for the Identification of Hospital-Acquired Infections: An Updated Systematic Review with Meta-Analysis and Meta-Regression Analysis.

Authors:  Olga Redondo-González; José María Tenías; Ángel Arias; Alfredo J Lucendo
Journal:  Health Serv Res       Date:  2017-04-11       Impact factor: 3.402

7.  The Seasonal Variability in Surgical Site Infections and the Association With Warmer Weather: A Population-Based Investigation.

Authors:  Chris A Anthony; Ryan A Peterson; Linnea A Polgreen; Daniel K Sewell; Philip M Polgreen
Journal:  Infect Control Hosp Epidemiol       Date:  2017-05-16       Impact factor: 3.254

8.  Healthcare-acquired infections in rehabilitation units of the Lombardy Region, Italy.

Authors:  M Tinelli; S Mannino; S Lucchi; A Piatti; L Pagani; R D'Angelo; M Villa; L Trezzi; M G Di Stefano; A Pavan; L Macchi
Journal:  Infection       Date:  2011-07-08       Impact factor: 3.553

9.  Has the rate of in-hospital infections after total joint arthroplasty decreased?

Authors:  Mohammad R Rasouli; Mitchell Gil Maltenfort; James J Purtill; William J Hozack; Javad Parvizi
Journal:  Clin Orthop Relat Res       Date:  2013-10       Impact factor: 4.176

10.  Central line-associated infections as defined by the Centers for Medicare and Medicaid Services' Hospital-acquired condition versus standard infection control surveillance: why hospital compare seems conflicted.

Authors:  Rebekah W Moehring; Russell Staheli; Becky A Miller; Luke Francis Chen; Daniel John Sexton; Deverick John Anderson
Journal:  Infect Control Hosp Epidemiol       Date:  2013-01-18       Impact factor: 3.254

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.