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First Year of Mandatory Reporting of Healthcare-Associated Infections, Pennsylvania An Infection Control—Chart Abstractor Collaboration

Published online by Cambridge University Press:  21 June 2016

Kathleen G. Julian ,
Arlene M. Brumbach ,
Michelle K. Chicora ,
Carol Houlihan ,
Anna M. Riddle ,
Teanna Umberger  and
Cynthia J. Whitener
Kathleen G. Julian*
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Arlene M. Brumbach
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Michelle K. Chicora
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Carol Houlihan
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Anna M. Riddle
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Teanna Umberger
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Cynthia J. Whitener
Affiliation:
Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
*
Division of Infectious Diseases, Penn State Milton S. Hershey Medical Center, BMR Building, Room C6833, 500 University Drive, Hershey, PA 17033, (kjulian@psu.edu)
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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.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 9 , September 2006 , pp. 926 - 930
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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References

1.Berens, MJ. Infection epidemic carves deadly path: poor hygiene, overwhelmed workers contribute to thousands of deaths. Series: Tribune investigation: unhealthy hospitals. First of three parts. Chicago Tribune July 21, 2002:1.Google Scholar
2.Connolly, C. Data show scourge of hospital infections. Washington Post July 13, 2005:A1.Google Scholar
3.Association for Professionals in Infection Control and Epidemiology. Mandatory reporting of infection rates: where does my state stand? Available at: http://www.apic.org/Content/NavigationMenu/GovernmentAdvocacy/MandatoryReporting/state_legislation/state_legislation.htm. Accessed September 23, 2005.Google Scholar
4.Pennsylvania Health Care Costs Containment Council. Available at: http://www.phc4.org/. Accessed September 23, 2005.Google Scholar
5.Pennsylvania Health Care Costs Containment Council. PHC4 research brief—hospital-acquired infections in Pennsylvania. July 2005. Available at: http://www.phc4.org/reports/researchbriefs/071205/default.htm. Accessed September 23, 2005.Google Scholar
6.Pennsylvania Health Care Costs Containment Council. News release: first state report on hospital-acquired infections released in PA cost, quality issues raise grave concerns. July 13, 2005. Available at: http://www.phc4.org/reports/researchbriefs/071205/nr071205.htm. Accessed 23 September 2005.Google Scholar
7.Glover, L. Pa. hospitals underreport infection rates. Pittsburgh Business Times October 3, 2004. Available at: http://www.bizjournals.com/pittsburgh/stories/2004/10/04/storyl.html Accessed September 23, 2005.Google Scholar
8.McKibben, L, Horan, T, Tokars, JI, et al., Healthcare Infection Control Practices Advisory Committee. Guidance on public reporting of healthcare-associated infections: recommendations of the Healthcare Infection Control Practices Advisory Committee. Infect Control Hosp Epidemiol 2005; 26:580–587.CrossRefGoogle ScholarPubMed
9.Moro, ML, Morsillo, F. Can hospital discharge diagnoses be used for surveillance of surgical-site infections? J Hosp Infect 2004; 56:239–241.CrossRefGoogle ScholarPubMed
10.Aronsky, D, Haug, PJ, Lagor, C, Dean, NC. Accuracy of administrative data for identifying patients with pneumonia. Am J Med Qual 2005; 20: 319–328.CrossRefGoogle ScholarPubMed
11.Madsen, KM, Schonheyder, HC, Kristensen, B, Nielsen, GL, Sorensen, HT. Can hospital discharge diagnosis be used for surveillance of bacteremia? A data quality study of a Danish hospital discharge registry. Infect Control Hosp Epidemiol 1998; 19:175–178.CrossRefGoogle ScholarPubMed
12.Wong, ES, Rupp, ME, Mermel, L, et al. Public disclosure of healthcare-associated infections: the role of the Society for Healthcare Epidemiology of America. Infect Control Hosp Epidemiol 2005; 26:210–212.CrossRefGoogle ScholarPubMed