Health Information Technologies: Which Nursing Homes Adopted Them?
Long-term care facilities have lagged heavily behind other health providers in adopting health information technology (IT). This article examines the facility characteristics that are associated with health IT adoption.



This study is a secondary data analysis of information gathered between 2005 and 2011 about nursing facility characteristics contained in the Online Certification & Reporting (OSCAR) files and information about health IT adoption in each nursing home contained in the Healthcare Information and Management Systems Society (HIMSS) Analytics Database. Multivariate regression analysis is conducted.



Nursing homes with licensed nursing staff levels above the state average were 20% more likely to adopt computer-provided order entry (CPOE) than homes with licensed nursing staff below average. Resident resources (more Medicare-paid patients and fewer Medicaid patients) were positively correlated to health IT adoption, particularly to a clinical data repository (CDR), clinical decision support systems (CDSS), and an order entry (OE) system. Other characteristics, including chain affiliation, ownership, and market competition, are also related to some health IT adoption within nursing homes.



Nursing homes with more personnel or resident resources are more likely to adopt health IT. Other factors such as market competition are also important predictors. Future research is needed to examine what factors motivate nursing homes to adopt health IT.
Department of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA; Meyers Primary Care Institute and Division of Geriatrics Medicine, University of Massachusetts Medical School, Worcester, MA. Electronic address: ningzhang@schoolph.umass.edu.
Ning
N
Zhang
Department of Management, Krannert School of Management, Purdue University, West Lafayette, ID.
Susan F
SF
Lu
Department of Management, School of Government, Nanjing University, Nanjing, Jiangsu, P.R. China.
Biao
B
Xu
Economics Department, School of Art and Science, Rutgers, State University of New Jersey, New Brunswick.
Bingxiao
B
Wu
Department of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA.
Rosa
R
Rodriguez-Monguio
Meyers Primary Care Institute and Division of Geriatrics Medicine, University of Massachusetts Medical School, Worcester, MA.
Jerry
J
Gurwitz
D004059:Diffusion of Innovation; D006801:Humans; D008490:Medical Informatics; D009735:Nursing Homes; D011787:Quality of Health Care; D012044:Regression Analysis; D011795:Surveys and Questionnaires; D014481:United States
Health information technology; facility characteristics; nursing homes; quality of care in nursing homes