Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006

Health Rep. 2010 Dec;21(4):27-33.


Background: Long-term care facilities (nursing homes) in British Columbia consist of a mix of for-profit, not-for-profit non-government, and not-for-profit health-region-owned establishments. This study assesses the extent to which staffing levels have changed by facility ownership category.

Data and methods: With data from Statistics Canada's Residential Care Facilities Survey, various types of care hours per resident-day were examined from 1996 through 2006 for the province of British Columbia. Random effects linear regression modeling was used to investigate the effect of year and ownership on total nursing hours per resident-day, adjusting for resident demographics, case mix, and facility size.

Results: From 1996 to 2006, crude mean total nursing hours per resident-day rose from 1.95 to 2.13 hours in for-profit facilities (p = 0.06); from 1.99 to 2.48 hours in not-for-profit non-government facilities (p < 0.001); and from 2.25 to 3.30 hours in not-for-profit health-region-owned facilities (p < 0.001). The adjusted rate of increase in total nursing hours per resident-day was significantly greater in not-for-profit health-region-owned facilities.

Interpretation: While total nursing hours per resident-day have increased in all facility groups, the rate of increase was greater in not-for-profit facilities operated by health authorities.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • British Columbia
  • Homes for the Aged / organization & administration*
  • Homes for the Aged / statistics & numerical data
  • Humans
  • Nursing Administration Research
  • Nursing Homes / organization & administration*
  • Nursing Homes / statistics & numerical data
  • Nursing Staff / organization & administration*
  • Nursing Staff / statistics & numerical data
  • Ownership / statistics & numerical data*
  • Personnel Staffing and Scheduling / organization & administration*
  • Personnel Staffing and Scheduling / statistics & numerical data
  • Socioeconomic Factors