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Comparison of Data Collection for Healthcare-Associated Infection Surveillance in Nursing Homes

Published online by Cambridge University Press:  03 October 2016

Lauren Epstein ,
Nimalie D. Stone ,
Lisa LaPlace ,
Jane Harper ,
Ruth Lynfield ,
Linn Warnke ,
Tory Whitten ,
Meghan Maloney ,
Richard Melchreit  and
Richard Rodriguez
...Show all authors
Lauren Epstein*
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Nimalie D. Stone
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Lisa LaPlace
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Jane Harper
Affiliation:
Minnesota Department of Health, St Paul, Minnesota
Ruth Lynfield
Affiliation:
Minnesota Department of Health, St Paul, Minnesota
Linn Warnke
Affiliation:
Minnesota Department of Health, St Paul, Minnesota
Tory Whitten
Affiliation:
Minnesota Department of Health, St Paul, Minnesota
Meghan Maloney
Affiliation:
Connecticut Department of Public Health, Hartford, Connecticut
Richard Melchreit
Affiliation:
Connecticut Department of Public Health, Hartford, Connecticut
Richard Rodriguez
Affiliation:
Connecticut Department of Public Health, Hartford, Connecticut
Gail Quinlan
Affiliation:
New York-Rochester Emerging Infections Program and University of Rochester Medical Center, Rochester, New York
Cathleen Concannon
Affiliation:
New York-Rochester Emerging Infections Program and University of Rochester Medical Center, Rochester, New York
Ghinwa Dumyati
Affiliation:
New York-Rochester Emerging Infections Program and University of Rochester Medical Center, Rochester, New York
Deborah L. Thompson
Affiliation:
New Mexico Department of Health, Santa Fe, New Mexico
Nicola Thompson*
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
*
*Address correspondence to Lauren Epstein, MD, MSc, Division of Healthcare Quality Promotion Centers for Disease Control & Prevention, 1600 Clifton Road Mailstop A-24, Atlanta, Georgia 30329 (Xdd0@cdc.gov) or to Nicola Thompson, PhD, Division of Healthcare Quality Promotion, Centers for Disease Control & Prevention, 1600 Clifton Road Mailstop A-24, Atlanta, Georgia 30329 (dvq0@cdc.gov).
*Address correspondence to Lauren Epstein, MD, MSc, Division of Healthcare Quality Promotion Centers for Disease Control & Prevention, 1600 Clifton Road Mailstop A-24, Atlanta, Georgia 30329 (Xdd0@cdc.gov) or to Nicola Thompson, PhD, Division of Healthcare Quality Promotion, Centers for Disease Control & Prevention, 1600 Clifton Road Mailstop A-24, Atlanta, Georgia 30329 (dvq0@cdc.gov).
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Abstract

OBJECTIVE

To facilitate surveillance and describe the burden of healthcare-associated infection (HAI) in nursing homes (NHs), we compared the quality of resident-level data collected by NH personnel and external staff.

DESIGN

A 1-day point-prevalence survey

SETTING AND PARTICIPANTS

Overall, 9 nursing homes among 4 Centers for Disease Control and Prevention (CDC) Emerging Infection Program (EIP) sites were included in this study.

METHODS

NH personnel collected data on resident characteristics, clinical risk factors for HAIs, and the presence of 3 HAI screening criteria on the day of the survey. Trained EIP surveillance officers collected the same data elements via retrospective medical chart review for comparison; surveillance officers also collected available data to identify HAIs (using revised McGeer definitions). Overall agreement was calculated among residents identified by both teams with selected risk factors and HAI screening criteria. The impact of using NH personnel to collect screening criteria on HAI prevalence was assessed.

RESULTS

The overall prevalence of clinical risk factors among the 1,272 residents was similar between NH personnel and surveillance officers, but the level of positive agreement (residents with factors identified by both teams) varied between 39% and 87%. Surveillance officers identified 253 residents (20%) with ≥1 HAI screening criterion, resulting in 67 residents with an HAI (5.3 per 100 residents). The NH personnel identified 152 (12%) residents with ≥1 HAI screening criterion; 42 residents had an HAI (3.5 per 100 residents).

CONCLUSION

We identified discrepancies in resident-level data collection between surveillance officers and NH personnel, resulting in varied estimates of the HAI prevalence. These findings have important implications for the design and implementation of future HAI prevalence surveys.

Infect Control Hosp Epidemiol 2016;1440–1445

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 37 , Issue 12 , December 2016 , pp. 1440 - 1445
Copyright
© 2016 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

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