@article{
 title = {Longitudinal Changes in Nursing Home Resident-Reported Quality of Life: The Role of Facility Characteristics},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {long-term care,longitudinal analysis,nursing homes},
 websites = {http://login.ezproxy.library.ualberta.ca/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=cmedm&AN=25651583&site=ehost-live&scope=site},
 month = {12},
 publisher = {Sage},
 city = {Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, USA tshippee@umn.edu.; Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, MN, USA.; Division of Health Policy},
 id = {db4f6b1c-1951-3abe-be2d-0c55fc31557d},
 created = {2016-08-20T16:55:46.000Z},
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 profile_id = {217ced55-4c79-38dc-838b-4b5ea8df5597},
 group_id = {408d37d9-5f1b-3398-a9f5-5c1a487116d4},
 last_modified = {2017-03-14T09:54:45.334Z},
 read = {false},
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 notes = {ID: 25651583; Accession Number: 25651583. Language: English. Date Revised: 20150205. Date Created: 20150204. Update Code: 20150206. Publication Type: JOURNAL ARTICLE. Journal ID: 7908221. Publication Model: Print-Electronic. Cited Medium: Internet. NLM ISO Abbr: Res Aging. Linking ISSN: 01640275. Date of Electronic Publication: 2014 Aug 12. ; Original Imprints: Publication: Beverly Hills, Calif., Sage.},
 folder_uuids = {3f8d7ce1-e3f4-4c64-add9-a1fb30f8c887},
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 abstract = {Improving quality of nursing homes (NHs) is a major social priority, yet few studies examine the role of facility characteristics for residents' quality of life (QOL). This study goes beyond cross-sectional analyses by examining the predictors of NH residents' QOL on the facility level over time. We used three data sources, namely resident interviews using a multidimensional measure of QOL collected in all Medicaid-certified NHs in Minnesota (N = 369), resident clinical data from the minimum data set, and facility-level characteristics. We examined change in six QOL domains from 2007 to 2010, using random coefficient models. Eighty-one facilities improved across most domains and 85 facilities declined. Size, staffing levels (especially activities staff), and resident case mix are some of the most salient predictors of QOL over time, but predictors differ by facility performance status. Understanding the predictors of facility QOL over time can help identify facility characteristics most appropriate for targeting with policy and programmatic interventions.; © The Author(s) 2014.},
 bibtype = {article},
 author = {Shippee, Tetyana P and Hong, Hwanhee and Henning-Smith, Carrie and Kane, Robert L},
 journal = {Research on aging}
}

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