• Lisa Barbera, Hsien Seow, Rinku Sutradhar, Anna Chu, Fred Burge, Konrad Fassbender, Kim McGrail, Beverley Lawson, Ying Liu, Reka Pataky, and Alex Potapov.
• Odette Cancer Centre, University of Toronto; Institute for Clinical Evaluative Sciences, Toronto; McMaster University, Hamilton, Ontario; Dalhousie University, Halifax, Nova Scotia; University of Alberta, Edmonton, Alberta; Centre for Health Services and Policy Research, School of Population and Public Health, University of British Columbia; and Canadian Centre for Applied Research in Cancer Control, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada lisa.barbera@sunnybrook.ca.
• J Oncol Pract. 2015 May 1; 11 (3): e279-87.

PurposeTo develop data-driven and achievable benchmark rates for end-of-life quality indicators using administrative data from four provinces in Canada.MethodsIndicators of end-of-life care were defined and measured using linked administrative data for 33 health regions across British Columbia, Alberta, Ontario, and Nova Scotia. These were emergency department use, intensive care unit admission, physician house calls and home care visits before death, and death in hospital. An empiric benchmark was defined using indicator rates from the top-ranked regions to include the top decile of patients overall. Funnel plots were used to graph each region's age- and sex-adjusted indicator rates along with the overall rate and 95% confidence limits.ResultsRates varied approximately two- to four-fold across the regions, with physician house calls showing the greatest variation. Benchmark rates based on the top decile performers were emergency department use, 34%; intensive care unit admission, 2%; physician house calls, 34%; home care visits, 63%; and death in hospital, 38%. With the exception of intensive care unit admission, funnel plots demonstrated that overall indicator rates and their confidence limits were uniformly worse than benchmarks even after adjusting for age and sex. Few regions met the benchmark rates.ConclusionThere is significant variation in end-of-life quality indicators across regions in four provinces in Canada. Using this study's methods-deriving empiric benchmarks and funnel plots-regions can determine their relative performance with greater context that facilitates priority setting and resource deployment. Applying this study's methods can support quality improvement by decreasing variation and striving for a target.Copyright © 2015 by American Society of Clinical Oncology.

35 keywords...

hide…