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Clinical Corner: Intended and Unintended Consequences of Public Reporting

Posted on 06/11/14

Intended_and_Unintended_Consequences_of_Public_Reporting

At the APIC 2014 Conference in Anaheim, CA, Dr. Susan Huang, Medical Director of Epidemiology and Infection Prevention at UC Irvine, presented an excellent overview of where infection prevention has been as a profession, starting with the 1999 IOM Report “To err is human: building a safer healthcare system” and ending with a visionary look towards the future of public reporting of healthcare-associated infection (HAI) data.

In the past 15 years, several battles in infection prevention needed to be won. One of the major victories involved advocacy by both APIC and SHEA to use NHSN for data collection and analysis. NHSN reporting provides the ability to adjust for hospital type and special patient populations, identifies HAI-specific case mix adjustors using historical data, and provides SSI risk adjustment with variables other than age, ASA scores, and duration of procedure. Even with this strategic victory, there is much more to achieve. Infection preventionists and other data experts need to reassess adjustors with the influx of data into NHSN - CMS surgical performance metrics do not use CDC’s broader risk adjustment methodology - and the impact of socioeconomic factors on rates needs to be further evaluated.

Furthermore, reporting the data to the public has its own set of challenges. One of the major concerns is the public’s understanding of the data displayed. Even clinicians and healthcare executives often struggle with the concepts of rates of infection, patient days vs. patient admissions, confidence intervals, and standardized infection ratios vs. percentages. The difficulty of explaining that a SSI rate of 0 for one hospital and 8 for another hospital is still within normal limits compared to the state average of 4.5 is a difficult concept for the public (and even healthcare executives) to comprehend.

To address this issue, states like California and Washington have developed visual representations of hospital data and use color codes for hospitals to identify them as average, higher, lower, etc., to simplify the public’s review of this data. However, these representations are not the norm for the majority of states; the standardization of displaying hospital data at the state level for the public in a meaningful way remains an ongoing concern.

Dr. Huang commented that another consequence of public reporting is the disbelief that the data can be trusted. The additional complexity of trending the data is the changing definition to determine an HAI. NHSN definitions are open to interpretation, which can result in the misclassification of HAIs. Examples: 48 hours translate to 2 days or 3 days, CLABSI inter-rater reliability is poor, VAP is highly subjective and poor clinical correlates, SSI depends on how hard you look.

This confusion has prompted the CDC to make definitions of an HAI less subjective to interpretation and more clinically meaningful and objective.

The vision of the future for HAI surveillance is to make the search for “adverse events” programmable (automated) with vendor-assisted automated uploads to NHSN. One of the objectives of using the VAE definition for pneumonia surveillance was to make this data review programmable and eliminate subjectivity in the interpretation. This is the goal for other HAI definitions as well.

This transformation will drive the need for electronic-assisted surveillance to an all-time high, as it will become an essential tool for any healthcare organization mandated to report data to NHSN.

The era of the electronic-infection preventionist is already here, as articulated by Russell Olmsted in an editorial in AJIC back in December 2000¹. In the era of Value Based Purchasing, the consequences of not actively engaging in monitoring and improving performance will be acutely felt financially if we do not embrace the technology age with enthusiasm. What we seek is the truth surrounding adverse healthcare associated events. The use of electronic technology for surveillance, analysis and reporting of data is a new mandate we must all embrace or patient safety and outcomes will suffer the negative consequences of inaction.

Resources

¹ Turning information into knowledge to prevent health care–associated infections and other adverse events: The electronic ICP as an agent of change; RN Olmsted, AJIC, vol. 28, issue 6, pp. 389-91.

Implementation of Risk Evaluation and Mitigation Strategy Programs in a Health System

Topics: Infection Prevention

About the Author

Keith H. St. John, MT(ASCP), MS, CIC has served as an Infection Preventionist for the past 30 years, including over 17 years of managing Infection Prevention and Control programs and personnel at major tertiary teaching institutions that include pediatric as well as adult hospital settings. Keith is a clinical microbiologist by training and is certified in Infection Control & Epidemiology (CIC). Keith’s rich professional experience includes: Past President of the Certification board of Infection Control & Epidemiology (CBIC); publications in medical and infection control journals; presentation at national and regional conferences; and former faculty associate at Temple Dental and Medical School. Mr. St. John is also a former member of APIC’s Governmental Affairs Committee, Education Committee, Practice Guidance Council and Research Foundation. He has served APIC as Chapter President & Board member, Editorial Board and reviewer for AJIC, APIC Text Revision Task Force (x2) and Pharmacy chapter co-author. Keith has been a volunteer member of the United States Pharmacopeia Convention Expert Compounding Committee since 2005, sharing his expertise on the revision of USP Chapter <797>, Pharmaceutical Compounding – Sterile Preparations. In addition to APIC, he is an active member of the Healthcare Infection Society (UK) and the Society for Health Epidemiology of America (SHEA). Keith received his Master’s of Science degree in Clinical Microbiology from Thomas Jefferson University in Philadelphia and his Bachelor of Science degree in Medical Technology from the University of Delaware.