Literature DB >> 16941317

First year of mandatory reporting of healthcare-associated infections, Pennsylvania: an infection control-chart abstractor collaboration.

Kathleen G Julian1, Arlene M Brumbach, Michelle K Chicora, Carol Houlihan, Anna M Riddle, Teanna Umberger, Cynthia J Whitener.   

Abstract

BACKGROUND: In 2004, the Commonwealth of Pennsylvania mandated hospitals to report healthcare-associated infections (HAIs). The increased workload led our Infection Control staff to collaborate with Atlas, a group of chart abstractors.
OBJECTIVE: The objective of this study was to assess our first year of experience with mandatory reporting of HAIs--specifically, to assess Atlas' contribution to surveillance.
DESIGN: Cases were selected if they had 1 or more of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes designated by Pennsylvania as a possible HAI. After training by the Infection Control staff, Atlas applied National Nosocomial Infection Surveillance (NNIS) system case definitions for catheter-associated urinary tract infections (UTIs) and surgical site infections (SSIs), and they applied NNIS chest imaging criteria to eliminate cases that were not ventilator-associated pneumonia (VAP). To assess Atlas' performance, Infection Control staff conducted a parallel review.
RESULTS: For discharges from the hospital during the fourth quarter of 2004, a total of 410 UTIs, 59 SSIs, and 56 VAPs were identified on the basis of state-designated ICD-9-CM codes; review by Atlas/Infection Control determined that 15%, 15%, and 16% of cases met case definitions, respectively. Of cases reviewed by both Infection Control and Atlas, 87% of the assessments made by Atlas were correct for UTI, and 96% were correct for SSI. For VAP, Infection Control concluded that 39% of cases could be ruled out on the basis of chest imaging criteria; Atlas correctly dismissed these 12 cases but incorrectly dismissed an additional 6 (error, 19%). Surveillance was not timely: 1-2 months elapsed between the time of HAI onset and the earliest case review.
CONCLUSIONS: With ongoing training by Infection Control, Atlas successfully demonstrated a role in retrospective HAI surveillance. However, despite a major effort to comply with mandates, time lags and other design limitations rendered the data of low utility for Infection Control. States that are planning HAI-reporting programs should standardize an efficient surveillance methodology that yields data capable of guiding interventions to prevent HAI.

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Year:  2006        PMID: 16941317     DOI: 10.1086/507281

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  9 in total

1.  Computer surveillance of hospital-acquired infections: a 25 year update.

Authors:  R Scott Evans; Rouett H Abouzelof; Caroline W Taylor; Vickie Anderson; Sharon Sumner; Sharon Soutter; Ruth Kleckner; James F Lloyd
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

2.  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

3.  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

4.  The impact of hospital-acquired infection on outcome in acute pancreatitis.

Authors:  Bechien U Wu; Richard S Johannes; Stephen Kurtz; Peter A Banks
Journal:  Gastroenterology       Date:  2008-05-28       Impact factor: 22.682

5.  Nurse staffing, burnout, and health care-associated infection.

Authors:  Jeannie P Cimiotti; Linda H Aiken; Douglas M Sloane; Evan S Wu
Journal:  Am J Infect Control       Date:  2012-08       Impact factor: 2.918

6.  Can additional information be obtained from claims data to support surgical site infection diagnosis codes?

Authors:  David K Warren; Katelin B Nickel; Anna E Wallace; Daniel Mines; Victoria J Fraser; Margaret A Olsen
Journal:  Infect Control Hosp Epidemiol       Date:  2014-10       Impact factor: 3.254

7.  Validation of ICD-9-CM Diagnosis Codes for Surgical Site Infection and Noninfectious Wound Complications After Mastectomy.

Authors:  Margaret A Olsen; Kelly E Ball; Katelin B Nickel; Anna E Wallace; Victoria J Fraser
Journal:  Infect Control Hosp Epidemiol       Date:  2016-12-15       Impact factor: 3.254

8.  Changes in the accuracy of administrative data for the detection of surgical site infections.

Authors:  Brian T Bucher; Meng Yang; Julie Arndorfer; Cherie Frame; Jan Orton; Matthew H Samore; Kristin K Dascomb
Journal:  Infect Control Hosp Epidemiol       Date:  2020-12-17       Impact factor: 6.520

Review 9.  Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review.

Authors:  Maaike S M van Mourik; Pleun Joppe van Duijn; Karel G M Moons; Marc J M Bonten; Grace M Lee
Journal:  BMJ Open       Date:  2015-08-27       Impact factor: 2.692

  9 in total

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