BACKGROUND: While demographic shifts project an increased need for long-term care for an aging population, hundreds of nursing homes close each year. We examine whether nursing home closures are geographically concentrated and related to local community characteristics such as the racial and ethnic population mix and poverty. METHODS: National Online Survey Certification and Reporting data were used to document cumulative nursing facility closures over a decade, 1999 through 2008. Census 2000 zip code level demographics and poverty rates were matched to study facilities. The weighted Gini coefficient was used to measure geographic concentration of closures, and geographic information system maps to illustrate spatial clustering patterns of closures. Changes in bed supply due to closures were examined at various geographic levels. RESULTS: Between 1999 and 2008, a national total of 1776 freestanding nursing homes closed (11%), compared with 1126 closures of hospital-based facilities (nearly 50%). Combined, there was a net loss of over 5% of beds. The relative risk of closure was significantly higher in zip code areas with a higher proportion of blacks or Hispanics or a higher poverty rate. The weighted Gini coefficient for closures was 0.55 across all metropolitan statistical areas and 0.71 across zip codes. Closures tended to be spatially clustered in minority-concentrated zip codes around the urban core, often in pockets of concentrated poverty. CONCLUSIONS: Nursing home closures are geographically concentrated in minority and poor communities. Since nursing home use among the minority elderly population is growing while it is declining among whites, these findings suggest that disparities in access will increase.
BACKGROUND: While demographic shifts project an increased need for long-term care for an aging population, hundreds of nursing homes close each year. We examine whether nursing home closures are geographically concentrated and related to local community characteristics such as the racial and ethnic population mix and poverty. METHODS: National Online Survey Certification and Reporting data were used to document cumulative nursing facility closures over a decade, 1999 through 2008. Census 2000 zip code level demographics and poverty rates were matched to study facilities. The weighted Gini coefficient was used to measure geographic concentration of closures, and geographic information system maps to illustrate spatial clustering patterns of closures. Changes in bed supply due to closures were examined at various geographic levels. RESULTS: Between 1999 and 2008, a national total of 1776 freestanding nursing homes closed (11%), compared with 1126 closures of hospital-based facilities (nearly 50%). Combined, there was a net loss of over 5% of beds. The relative risk of closure was significantly higher in zip code areas with a higher proportion of blacks or Hispanics or a higher poverty rate. The weighted Gini coefficient for closures was 0.55 across all metropolitan statistical areas and 0.71 across zip codes. Closures tended to be spatially clustered in minority-concentrated zip codes around the urban core, often in pockets of concentrated poverty. CONCLUSIONS: Nursing home closures are geographically concentrated in minority and poor communities. Since nursing home use among the minority elderly population is growing while it is declining among whites, these findings suggest that disparities in access will increase.
Authors: Deborah S Mack; Bill M Jesdale; Christine M Ulbricht; Sarah N Forrester; Pryce S Michener; Kate L Lapane Journal: Gerontologist Date: 2020-04-02
Authors: Momotazur Rahman; David C Grabowski; Pedro L Gozalo; Kali S Thomas; Vincent Mor Journal: Health Serv Res Date: 2013-12-19 Impact factor: 3.402
Authors: Lyndsey M Miller; Nathan F Dieckmann; Nora C Mattek; Karen S Lyons; Jeffrey A Kaye Journal: Res Gerontol Nurs Date: 2014-01-21 Impact factor: 1.571
Authors: Kali S Thomas; David Dosa; Kathryn Hyer; Lisa M Brown; Shailender Swaminathan; Zhanlian Feng; Vincent Mor Journal: J Am Geriatr Soc Date: 2012-09-24 Impact factor: 5.562