Identifying risk factors for healthcare-associated infections from electronic medical record home address data

Jeffrey S. Wilson, David C. Shepherd, Marc Rosenman, Abel N. Kho

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Background: Residential address is a common element in patient electronic medical records. Guidelines from the U.S. Centers for Disease Control and Prevention specify that residence in a nursing home, skilled nursing facility, or hospice within a year prior to a positive culture date is among the criteria for differentiating healthcare-acquired from community-acquired methicillin-resistant Staphylococcus aureus (MRSA) infections. Residential addresses may be useful for identifying patients residing in healthcare-associated settings, but methods for categorizing residence type based on electronic medical records have not been widely documented. The aim of this study was to develop a process to assist in differentiating healthcare-associated from community-associated MRSA infections by analyzing patient addresses to determine if residence reported at the time of positive culture was associated with a healthcare facility or other institutional location.Results: We identified 1,232 of the patients (8.24% of the sample) with positive cultures as probable cases of healthcare-associated MRSA based on residential addresses contained in electronic medical records. Combining manual review with linking to institutional address databases improved geocoding rates from 11,870 records (79.37%) to 12,549 records (83.91%). Standardization of patient home address through geocoding increased the number of matches to institutional facilities from 545 (3.64%) to 1,379 (9.22%).Conclusions: Linking patient home address data from electronic medical records to institutional residential databases provides useful information for epidemiologic researchers, infection control practitioners, and clinicians. This information, coupled with other clinical and laboratory data, can be used to inform differentiation of healthcare-acquired from community-acquired infections. The process presented should be extensible with little or no added data costs.

Original languageEnglish
Article number47
JournalInternational Journal of Health Geographics
Volume9
DOIs
StatePublished - Sep 17 2010

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Electronic medical equipment
Patient-Centered Care
Electronic Health Records
Cross Infection
Delivery of Health Care
Nursing
Methicillin-Resistant Staphylococcus aureus
Geographic Mapping
Disease control
Infection Control Practitioners
Databases
Skilled Nursing Facilities
Standardization
Home Nursing
Community-Acquired Infections
Hospices
Centers for Disease Control and Prevention (U.S.)
Infection
Nursing Homes
Risk factors

ASJC Scopus subject areas

  • Computer Science(all)
  • Business, Management and Accounting(all)
  • Public Health, Environmental and Occupational Health

Cite this

Identifying risk factors for healthcare-associated infections from electronic medical record home address data. / Wilson, Jeffrey S.; Shepherd, David C.; Rosenman, Marc; Kho, Abel N.

In: International Journal of Health Geographics, Vol. 9, 47, 17.09.2010.

Research output: Contribution to journalArticle

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