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Improving the Understanding of Publicly Reported Healthcare-Associated Infection (HAI) Data

Published online by Cambridge University Press:  30 August 2016

Max Masnick ,
Daniel J. Morgan ,
Mark D. Macek ,
John D. Sorkin ,
Jessica P. Brown ,
Penny Rheingans  and
Anthony D. Harris
Max Masnick*
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Daniel J. Morgan
Affiliation:
Veterans Affairs Maryland Healthcare System, Baltimore, Maryland; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Mark D. Macek
Affiliation:
University of Maryland School of Dentistry, Baltimore, Maryland
John D. Sorkin
Affiliation:
Veterans Affairs Maryland Healthcare System Geriatrics Research, Education, and Clinical Center, Baltimore, Maryland
Jessica P. Brown
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Penny Rheingans
Affiliation:
Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, Maryland
Anthony D. Harris
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
*
Address correspondence to Max Masnick, 10 S. Pine Street, MSTF 362A, Baltimore, MD 21201 (max@masnick.net).
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Abstract

OBJECTIVE

Hospital-acquired infection (HAI) data are reported to the public on the Centers for Medicare and Medicaid Services (CMS) Hospital Compare website. We previously found that public understanding of these data is poor. Our objective was to develop an improved method for presenting HAI data that could be used on the CMS website.

DESIGN

Randomized controlled trial comparing understanding of data presented using the current CMS presentation strategy versus a new strategy.

SETTING

A 760-bed tertiary referral hospital.

PARTICIPANTS

A total of 61 patients were randomly selected within 24 hours of admission.

INTERVENTION

Participants were shown HAI data as presented on the CMS Hospital Compare website (control arm) or data formatted using a new method (experimental arm).

RESULTS

No statistically significant demographic differences were identified between study arms. Although 47% percent of participants said a website for comparing hospitals would have been helpful, only 10% had ever used such a website. Participants viewing data using the new presentation strategy compared hospitals correctly 56% of the time, compared with 32% in the control arm (P=.0002).

CONCLUSIONS

Understanding of HAI data increased significantly with the new data presentation method compared to the method currently used on the CMS Hospital Compare website. Many participants expressed interest in a website for comparing hospitals. Improved methods for presenting CMS HAI data, such as the one assessed here, should be adopted to increase public understanding.

Infect Control Hosp Epidemiol 2016;1–6

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 37 , Issue 11 , November 2016 , pp. 1349 - 1354
Copyright
© 2016 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

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