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Lack of Patient Understanding of Hospital-Acquired Infection Data Published on the Centers for Medicare and Medicaid Services Hospital Compare Website

Published online by Cambridge University Press:  23 November 2015

Max Masnick ,
Daniel J. Morgan ,
John D. Sorkin ,
Elizabeth Kim ,
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:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland Veterans Affairs Maryland Healthcare System, Baltimore, Maryland
John D. Sorkin
Affiliation:
Veterans Affairs Maryland Healthcare System Geriatrics Research, Education, and Clinical Center, Baltimore, Maryland
Elizabeth Kim
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, 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, PhD, 10 S. Pine St, MSTF 362A, Baltimore, MD 21201 (max@masnick.net).
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Abstract

BACKGROUND

Public reporting of hospital quality data is a key element of US healthcare reform. Data for hospital-acquired infections (HAIs) are especially complex.

OBJECTIVE

To assess interpretability of HAI data as presented on the Centers for Medicare and Medicaid Services Hospital Compare website among patients who might benefit from access to these data.

METHODS

We randomly selected inpatients at a large tertiary referral hospital from June to September 2014. Participants performed 4 distinct tasks comparing hypothetical HAI data for 2 hospitals, and the accuracy of their comparisons was assessed. Data were presented using the same tabular formats used by Centers for Medicare and Medicaid Services. Demographic characteristics and healthcare experience data were also collected.

RESULTS

Participants (N=110) correctly identified the better of 2 hospitals when given written descriptions of the HAI measure in 72% of the responses (95% CI, 66%–79%). Adding the underlying numerical data (number of infections, patient-time, and standardized infection ratio) to the written descriptions reduced correct responses to 60% (55%–66%). When the written HAI measure description was not informative (identical for both hospitals), 50% answered correctly (42%–58%). When no written HAI measure description was provided and hospitals differed by denominator for infection rate, 38% answered correctly (31%–45%).

CONCLUSIONS

Current public HAI data presentation methods may be inadequate. When presented with numeric HAI data, study participants incorrectly compared hospitals on the basis of HAI data in more than 40% of the responses. Research is needed to identify better ways to convey these data to the public.

Infect. Control Hosp. Epidemiol. 2016;37(2):182–187

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 37 , Supplement 2 , February 2016 , pp. 182 - 187
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

REFERENCES

1. Centers for Medicare and Medicaid Services. Hospital inpatient quality reporting program. CMS website. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/HospitalRHQDAPU.html. Updated September 13, 2013. Accessed January 12, 2015.Google Scholar
2. Patient Protection and Affordable Care Act. Public Law. 2010:111-148. http://legcounsel.house.gov/Comps/Patient%20Protection%20And%20Affordable%20Care%20Act.pdf. Updated April 27, 2015. Accessed October 10, 2015.Google Scholar
3. Medicare Hospital Compare Quality of Care. Medicare website. http://www.medicare.gov/hospitalcompare/. Accessed January 28, 2015.Google Scholar
4. Centers for Disease Control and Prevention. CDC’s healthcare-associated infection progress report: questions and answers. CDC website. http://www.cdc.gov/HAI/surveillance/QA_stateSummary.html#b6. Updated January 13, 2015. Accessed January 28, 2015.Google Scholar
5. Rajwan, YG, Barclay, PW, Lee, T, Sun, I-F, Passaretti, C, Lehmann, H. Visualizing central line-associated blood stream infection (CLABSI) outcome data for decision making by health care consumers and practitioners—an evaluation study. Online J Public Health Inform 2013;5:218.CrossRefGoogle ScholarPubMed
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