Indicator Metadata
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- Detailed View
Name |
Experiencing Pain in Long-Term Care |
Short/Other Names |
Percentage of Residents With Pain |
Description |
This indicator looks at how many long-term care residents had pain. The consequences of pain include increased difficulty with activities of daily living (ADLs), depression and lower quality of life. The prevalence of persistent pain increases with age, and proper treatment of pain is necessary to improve the health status of residents. |
Interpretation |
Lower is better. It means that a lower percentage of residents had moderate daily pain or horrible/excruciating pain at any frequency. |
HSP Framework Dimension |
Health System Outcomes: Improve health status of Canadians |
Areas of Need |
Living With Illness, Disability or Reduced Function |
Geographic Coverage |
Newfoundland and Labrador, New Brunswick, Nova Scotia, Ontario, Manitoba, Saskatchewan, Alberta, British Columbia, Yukon |
Reporting Level/Disaggregation |
Province/Territory, Region, Facility, Corporation, Sector (residential and hospital-based continuing care) |
Indicator Results |
Name |
Experiencing Pain in Long-Term Care |
Short/Other Names |
Percentage of Residents With Pain |
Description |
This indicator looks at how many long-term care residents had pain. The consequences of pain include increased difficulty with activities of daily living (ADLs), depression and lower quality of life. The prevalence of persistent pain increases with age, and proper treatment of pain is necessary to improve the health status of residents. |
Calculation: Description |
This indicator examines the percentage of residents who had pain. It is calculated by dividing the number of residents who had moderate daily pain or horrible/excruciating pain at any frequency by the number of all residents with valid assessments within the applicable time period. Unit of Analysis: Resident |
Calculation: Geographic Assignment |
Place of service |
Calculation: Type of Measurement |
Percentage or proportion |
Calculation: Adjustment Applied |
The following covariates are used in risk adjustment:
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Calculation: Method of Adjustment |
Stratification, direct standardization, indirect standardization;
Standard Population: |
Denominator |
Description:
Exclusions:
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Numerator |
Description:
Exclusions:
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Rationale | CCRS quality indicators were developed by interRAI (www.interrai.org), an international research network, to provide organizations with measures of quality across key domains, including physical and cognitive function, safety and quality of life. Each indicator is adjusted for resident characteristics that are related to the outcome and independent of quality of care. The indicators can be used by quality leaders to drive continuous improvement efforts. They are also used to communicate with key stakeholders through report cards and accountability agreements. |
Interpretation | Lower is better. It means that a lower percentage of residents had moderate daily pain or horrible/excruciating pain at any frequency. |
HSP Framework Dimension | Health System Outcomes: Improve health status of Canadians |
Areas of Need | Living With Illness, Disability or Reduced Function |
Targets/Benchmarks | None |
References |
Canadian Institute for Health Information. CCRS Quality Indicators Risk Adjustment Methodology (PDF). 2013.
Canadian Institute for Health Information. When a Nursing Home Is Home: How Do Canadian Nursing Homes Measure Up on Quality? (PDF) 2013. Health Quality Ontario. Long-Term Care Benchmarking Resource Guide (PDF). 2013. Health Quality Ontario. Results From Health Quality Ontario's Benchmark Setting for Long-Term Care Indicators (PDF). 2017. Health Quality Ontario. Health Quality Ontario Indicator Library. Accessed October 4, 2017. Hirdes JP, Mitchell L, Maxwell CJ, White N. Beyond the "iron lungs of gerontology": Using evidence to shape the future of nursing homes in Canada. Canadian Journal on Aging. 2011. Hirdes JP, Poss JW, Caldarelli H, et al. An evaluation of data quality in Canada's Continuing Care Reporting System (CCRS): Secondary analyses of Ontario data submitted between 1996 and 2011. BMC Medical Informatics and Decision Making. 2013. Jones RN, Hirdes JP, Poss JW, et al. Adjustment of nursing home quality indicators. BMC Health Services Research. 2010. |
Data Sources |
CCRS |
Available Data Years |
Type of Year: |
Geographic Coverage |
Newfoundland and Labrador, New Brunswick, Nova Scotia, Ontario, Manitoba, Saskatchewan, Alberta, British Columbia, Yukon |
Reporting Level/Disaggregation |
Province/Territory, Region, Facility, Corporation, Sector (residential and hospital-based continuing care) |
Update Frequency |
Every year |
Indicator Results |
Web Tool: |
Updates |
Not applicable |
Caveats and Limitations |
This measure uses data collected by long-term care facilities using the Resident Assessment Instrument–Minimum Data Set 2.0 (RAI-MDS 2.0) and submitted to the Continuing Care Reporting System (CCRS). Users should be cautious when interpreting results from CCRS because the CCRS frame does not currently contain all facilities in all provinces and territories that make up the CCRS population of interest; thus the population covered by CCRS may not be representative of all continuing care facilities across Canada. Some jurisdictions have implemented or are in the process of implementing the new interRAI Long-Term Care Facilities (LTCF), the next-generation clinical assessment instrument for long-term care. Data collected using this assessment instrument will be submitted to the Integrated interRAI Reporting System (IRRS). Results for these jurisdictions as of the fiscal year of interRAI LTCF implementation are not available at this time. Historical results based on the RAI-MDS 2.0 are available.
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Trending Issues |
Since 2003, the number of facilities and jurisdictions submitting to CCRS has been increasing. With the addition of new jurisdictions, it is possible that differences in care practices may affect indicator rates; however, changes to the underlying population would be controlled for using risk adjustment. There is also evidence to suggest that trending and use of data from the entire time series is not an issue and that data quality is consistent over time (Hirdes et al., 2013). |
Comments |
The CCRS quality indicators use 4 rolling quarters of data for calculations in order to have a sufficient number of assessments for risk adjustment. Since residents are assessed on a quarterly basis, each resident can contribute to the indicator up to 4 times. Data for this indicator is also available in the Quick Stats tool, which includes results for both the residential and hospital-based continuing care sectors: https://www.cihi.ca/en/quick-stats |