Quality of end-of-life cancer care in Canada: a retrospective four-province study using administrative health care data

Original Article

Palliative Care

Quality of end-of-life cancer care in Canada: a retrospective four-province study using administrative health care data

L. Barbera, MD,*,, H. Seow, PhD§, R. Sutradhar, PhD, A. Chu, MHSc, F. Burge, MD, K. Fassbender, PhD#, K. McGrail, PhD**, B. Lawson, MSc, Y. Liu, MSc, R. Pataky, MSc††, A. Potapov, MSc#
*Odette Cancer Centre, Department of Radiation Oncology, Toronto, ON;, Department of Radiation Oncology, University of Toronto, Toronto, ON;, Institute for Clinical Evaluative Sciences, Toronto, ON;, §Department of Oncology, McMaster University, Hamilton, ON;, Department of Family Medicine, Dalhousie University, Halifax, NS;, #Department of Oncology, Division of Palliative Care Medicine, University of Alberta, Edmonton, AB;, **Centre for Health Services and Policy Research, School of Population and Public Health, University of British Columbia, Vancouver, BC;, ††Canadian Centre for Applied Research in Cancer Control, BC Cancer Research Centre, Vancouver, BC..

doi: http://dx.doi.org/10.3747/co.22.2636



The quality of data comparing care at the end of life (eol) in cancer patients across Canada is poor. This project used identical cohorts and definitions to evaluate quality indicators for eol care in British Columbia, Alberta, Ontario, and Nova Scotia.


This retrospective cohort study of cancer decedents during fiscal years 2004–2009 used administrative health care data to examine health service quality indicators commonly used and previously identified as important to quality eol care: emergency department use, hospitalizations, intensive care unit admissions, chemotherapy, physician house calls, and home care visits near the eol, as well as death in hospital. Crude and standardized rates were calculated. In each province, two separate multivariable logistic regression models examined factors associated with receiving aggressive or supportive care.


Overall, among the identified 200,285 cancer patients who died of their disease, 54% died in a hospital, with British Columbia having the lowest standardized rate of such deaths (50.2%). Emergency department use at eol ranged from 30.7% in Nova Scotia to 47.9% in Ontario. Of all patients, 8.7% received aggressive care (similar across all provinces), and 46.3% received supportive care (range: 41.2% in Nova Scotia to 61.8% in British Columbia). Lower neighbourhood income was consistently associated with a decreased likelihood of supportive care receipt.


We successfully used administrative health care data from four Canadian provinces to create identical cohorts with commonly defined indicators. This work is an important step toward maturing the field of eol care in Canada. Future work in this arena would be facilitated by national-level data-sharing arrangements.

KEYWORDS: Palliative care, quality indicators, health services research


Palliative care plays an important role on the cancer care continuum. In particular, it aims to enhance quality of life at the end of life (eol)1. Without effective health care interventions, many cancer patients have uncontrolled symptoms, poor quality of life, and unnecessary suffering29. The literature suggests that, over time, cancer care is becoming more aggressive near the eol10,11. The literature also suggests the presence of a discrepancy between what patients report as their preferred place of death (most often home) and their actual place of death1220. Compared with people receiving patient-centred palliative care services at home, those who die in institutions such as acute care facilities have unmet needs for symptom control, physician communication, emotional support, and respectful treatment21,22.

The use of administrative health care data to evaluate quality indicators of eol care was originally developed in the United States through a combination of literature review, lay focus groups, and expert panels23. A similar panel of indicators has been developed for the Canadian setting24. An aggregate score of “aggressive care” has been described in both the United States and Canada10,11. Knowing which services patients receive before death offers insight into whether they are accessing resources meant to improve quality of death and dying25.

Since the early 2000s, the quality of eol care in Canada has been highly criticized in a series of federal and provincial reports2632. Those criticisms have included lack of expertise and of adequate home support services, lack of coordinated comprehensive programs, fragmentation of care, and inadequate caregiver support. Although eol care has been studied in several provinces14,22,3339, the quality of data for comparing eol care in cancer patients across Canada is poor.

In 2010, the Canadian Cancer Society reported on eol care as a special topic for their annual report. The authors concluded that comparisons between provinces are limited because of a lack of standard definitions and methods, and an inability to link data across provinces40. Ironically, more high-quality research has been published comparing eol care in Ontario and the United States than between provinces in Canada11,41. The purpose of the present project was to evaluate eol quality indicators in cancer patients from British Columbia, Alberta, Ontario, and Nova Scotia.


Study Design

This retrospective cohort study considered patients with a confirmed cancer cause of death between 1 April 2004 and 31 March 2009 in four Canadian provinces: British Columbia, Alberta, Ontario, and Nova Scotia. Patients less than 19 years of age at the time of death and those with an invalid provincial health card number were excluded.

Data Sources

Index cases of death from cancer were identified from the cancer registries of each participating province. All registries are population-based and capture at least 90% of all incident cancer cases4245. Encoded unique health card numbers were used to link cases to administrative health databases within each province so as to obtain information about health services received at eol. Data were not merged across provinces, but were analyzed independently.

The source databases included the Discharge Abstract Database maintained by the Canadian Institute for Health Information46,47, which contains diagnostic and procedure information about all acute care hospitalizations in Canada; the National Ambulatory Care Reporting System48, which, for Alberta and Ontario, contains information from hospital and community-based ambulatory care including day surgeries, outpatient clinics, and emergency departments (eds); physician billing claims databases from provincial health insurance plans (the Medical Services Plan in British Columbia49, Medical Services Insurance in Nova Scotia, and the Ontario Health Insurance Plan in Ontario), which provide information on reimbursement claims made by physicians for services provided to patients; databases available from provincial organizations overseeing home care services (Home and Community Care in British Columbia50, Continuing Care in Nova Scotia, and the Ontario Association of Community Care Access Centres in Ontario); and the BC Cancer Agency’s Systemic Therapy database for chemotherapy treatment information. Physician claims and home care data were not available for Alberta, and chemotherapy data were not complete for Nova Scotia.

Sociodemographic information was obtained from the cancer registries of all provinces except Ontario and British Columbia, where public health insurance registration records were used51,52. The Statistics Canada 2006 census profile was used to obtain neighbourhood income and community size information. Additionally, as a measure of baseline comorbidity, a Charlson–Deyo modified score was calculated using hospitalizations in the 6 months before death53. The score is calculated by summing the points for a predefined list of conditions, with the points for cancer excluded.

Health Service Quality Indicators

We examined health service quality indicators commonly used and previously identified as important to quality care at eol23,24, where eol is considered to be the time shortly before death. Indicators for which higher use is considered lower quality include ed use in both the last 2 weeks and the last 30 days of life, a new hospital admission in the last 30 days of life, intensive care unit (icu) admission in the last 30 days of life, chemotherapy use in the last 2 weeks of life, and death in an acute care hospital. Indicators for which higher use is considered higher quality include physician house calls in the last 2 weeks of life, and nursing and personal support worker visits at home in the 6 months before death. Because the icu admission date for one province was unknown, admissions to the icu were counted only if the hospital admission date was within 30 days of death. Because patients considered palliative are eligible for increased home care services, we also examined a separate indicator for palliative home care, defined as receiving a nursing or personal support worker visit at home in the 6 months before death, with a specific flag or indicator of the palliative intent of the care.

Aggregate measures of aggressive and supportive care combining selected indicators were also developed:

  • □ “Aggressive care” was defined as any one or a combination of ed visits (2 or more), a hospitalization, or an icu admission in last 30 days of life10,11. Although the earlier literature included chemotherapy use in the aggressive care measures, variation in the sources of chemotherapy data between the provinces studied here would limit their comparability, and thus chemotherapy was excluded.

  • □ “Supportive care” was defined as either or both of a physician house call in the 2 weeks before death and a palliative nursing or personal support worker visit at home (as already defined) in the 6 months before death. That aggregate measure was created specifically for the present study.

Table i details the indicator definitions and data sources.

TABLE I Indicator definitions and data sources from each province


Statistical Analysis

Baseline characteristics of each provincial study population were compared using descriptive statistics. Crude and standardized rates for each indicator were compared between provinces for fiscal years 2004–2008 and overall. Crude rates were calculated as the proportion of patients who met the indicator definition. Standardized rates were calculated using the direct method and the combined fiscal year 2004/2005 study populations from each province as the standard population.

For each province, two separate multivariable logistic regression models were used to examine factors associated with receipt of aggressive and supportive care. Factors included in the adjusted models were age, sex, score on the Charlson-Deyo comorbidity index53, cancer type, neighbourhood income quintile, community size, health service region, and fiscal year of death. Age was included in the model as a continuous variable. The remaining variables were categorical. Each province was checked for colinearity between community size and region using the variance inflation factor. No colinearity was found, and so both variables were included in the model. Odds ratios (ors) are reported with 95% confidence intervals (cis) and are considered statistically significant if the confidence interval does not include 1.00.

Because nursing and personal support worker home visits and physician house call data were not available from Alberta, analyses of those indicators and of supportive care were not performed for that province. Statistical analyses were performed using the SAS (version 9.3: SAS Institute, Cary, NC, U.S.A.) and R (version 3.0.1: The R Foundation, Vienna, Austria) software applications and Microsoft Excel 2010 (Redmond, WA, U.S.A.).

The study was approved by the Hamilton Health Sciences Research Ethics Board and by the research ethics boards of each participating provincial organization: the Capital Health Research Ethics Board in Nova Scotia; the Alberta Health Services Research Ethics Board; and the University of British Columbia—BC Cancer Agency Research Ethics Board. In Ontario, the study was conducted in accordance with the strict confidentiality and privacy policies of the Institute for Clinical Evaluative Sciences.


During the study period, 200,285 patients in the four provincial cancer registries who died from their cancer met the eligibility criteria for inclusion in the study (Table ii). Overall, mean age at death was 71.4 ± 12.9 years, and 47% were women. Demographics were similar across the provinces. Compared with the other provinces, British Columbia had a slightly lower proportion of cases with a score of least 1 on the Charlson-Deyo comorbidity index, and the Nova Scotia study population lived in smaller-sized communities.

TABLE II Socio-demographics of study populations overall, by province, 2004–2008


Table iii shows the crude and standardized quality indicator rates by province, for all years combined. Overall, 54% of patients died in a hospital, with British Columbia having the lowest standardized rate of such deaths at 50.2%. Patients hospitalized within 30 days of death varied from 49.2% in Nova Scotia to 60.7% in Ontario. Rates of admission to the icu were similar. Comparing ed visit data from the Discharge Abstract Database (ed visits captured from hospital admissions via the ed), Nova Scotia also had the lowest use of ed within both 2 weeks and 30 days of death (22.2% and 30.7% respectively); Ontario had the highest use (35.7% and 47.9%). Rates estimated using the National Ambulatory Care Reporting System and physicians claim data in Alberta and Ontario were 4%–10% higher than the rates estimated using hospitalization data, but relative use across provinces was unchanged. In Nova Scotia, rates estimated using claims were lower. Intravenous chemotherapy treatment in the last 2 weeks of life ranged from 2.4% in Alberta to 4.8% in British Columbia; however, this particular comparison must be interpreted with caution because of the varying types of data sources used to gather the information. Nova Scotia chemotherapy data were incomplete.

TABLE III Quality indicator ratesa by province, 2004–2008


With respect to the aggregate indicators, 8.7% of all patients received aggressive care, with rates being similar in all provinces. Supportive care was received by 46.3% of the study population. The highest rate of supportive care was observed in British Columbia (61.8%), and the lowest, in Nova Scotia (41.2%). Results across years were relatively stable.

In regression analyses, younger age, male sex, and residence in smaller-sized communities were all associated with an increased likelihood of receiving aggressive care (Table iv), an observation that was consistent for all provinces. In Ontario, living in a low-income neighbourhood or having a score of 1 or more on the Charlson-Deyo comorbidity index were also associated with receipt of aggressive care. Factors associated with an increased likelihood of supportive care receipt were younger age, female sex, no comorbidity, lung cancer, living in a higher-income neighbourhood and in a larger community, although some exceptions were observed (Table v). Notably, compared with people in the highest-income neighbourhoods, people living in the lowest-income neighbourhoods had a 0.73–0.87 likelihood of receiving supportive care.

TABLE IV Multivariable logistic regression model for aggressive carea


TABLE V Multivariable logistic regression model for supportive carea



We successfully used administrative health care data to create identically defined cohorts with commonly defined indicators in four Canadian provinces that include about 65% of the Canadian population. Moderate differences in the indicators were observed between provinces, but overall, more than half the cancer patients died in hospital and 2 in 5 visited the ed near the eol. Associations with explanatory covariates were similar in all the provinces, suggesting that observations from a single province are generalizable to others. One of the strongest associations observed was that patients living in poorer neighbourhoods were less likely to receive supportive care services.

The present work makes an important contribution to maturing the study of eol cancer care in Canada. It addresses some of the gaps previously identified by the Canadian Cancer Society—specifically, comparing identically defined cohorts during the same years, with indicators defined as identically as the data allow. This work is in keeping with priorities outlined by the U.S. Institute of Medicine’s recent report54, such as providing patients and families with eol care that consistent with their values and developing a national quality reporting program.

Strengths and Limitations

Our study has several strengths. Its population-based cohorts of cancer decedents were identified using a common method, and it examines care provided in the inpatient, ambulatory, and community settings. Earlier work was conducted primarily within single provinces14,3339. The provincial populations included in the present study account for more than half the Canadian population. Tremendous effort was taken to ensure that the indicators represent fair comparisons, despite the variety of data sources.

The Canadian Partnership Against Cancer is monitoring location of death across the country, but that variable is reported as an unadjusted value55. Interpretation is further limited because location of death is identified from the death certificate, and there are differences in death certificate reporting. The Canadian Institute for Health Information has released a national-level report on eol care, but its study included only patients who died in hospital and was able to examine only care delivered in an inpatient setting, thus excluding care delivered in the community56.

There are limitations to the present study. All of the methodology choices made prioritized assurance of an “apples to apples” comparison. In some cases, options were limited. For example, ed visits were not available for all provinces from either the National Ambulatory Care Reporting System (a data source that specifically captures ed visits) or physician claims data. For that reason, inpatient hospitalization data were used to identify patients admitted to hospital via the ed. As a result, ed visits that did not lead to hospitalization were not counted. In other cases, the data required to evaluate an indicator could not be obtained. For example, the custodians of home care data in Alberta did not release it for inclusion in the study. Although cause-of-death data are available for more recent years from some provinces, the availability of such data lags by 1–2 years in Ontario, such that all the cohorts included data only up to March 2009. Finally, the indicators themselves have limitations. For example, death in hospital might not reflect the location in which a patient spent most of his or her time at eol.

Comparison with Other Studies

The indicator values and associations reported here are in keeping with earlier Canadian results24,33. Notably, in all provinces studied, patients living in lower-income neighbourhoods were less likely to receive supportive care and, in Ontario, were more likely to receive aggressive care. In all provinces, people residing in smaller communities were more likely to receive aggressive care and less likely to receive supportive care. In contrast to earlier work using data from the early 2000s, an increase in aggressive care over time was not evident11. That discrepancy might be a result of our inability to include chemotherapy in the aggregate indicator of aggressive care, although the earlier work indicated that all types of aggressive care increased over time. Alternatively, aggressive eol care might be beginning to stabilize. Other countries have reported similar data. For example, Canadian in-hospital death rates seem to be higher than those in the United States, but similar to those in Taiwan41,57,58.


We successfully used administrative health care data to create identically defined cohorts with commonly defined indicators for four Canadian provinces. National reporting of quality of care improves the contextual understanding of variations in care. It facilitates a richer consideration of differences in the structures and processes of care that might contribute to the variations. The time and effort required to produce these results was, however, tremendous and raises feasibility issues with respect to ongoing surveillance in the absence of a more integrated national data platform. Future work in this arena would be facilitated by data-sharing arrangements at the national level.


This study was funded primarily by a grant (019789) from the Canadian Centre for Applied Research in Cancer Control (arcc). The Canadian Centre for arcc is funded by the Canadian Cancer Society Research Institute (ccsri). Additional support was provided by an operating grant from ccsri.

In Ontario, the study used databases maintained by the Institute for Clinical Evaluative Sciences, which receives funding from the Ontario Ministry of Health and Long-Term Care. The BC Cancer Agency and the British Columbia Ministry of Health approved access to and use of the data facilitated by Population Data BC for this study. Portions of the data used in this report were made available by the Nova Scotia Department of Health and Wellness and the Population Health Research Unit (now known as Health Data Nova Scotia) of Dalhousie University. Alberta Health Services provided access to Alberta data. The opinions, results, and conclusions in this paper are those of the authors and are independent from the sources of funding and data provision.

The authors acknowledge Dr. Stuart Peacock, who facilitated data access in British Columbia.

Earlier versions of this work were presented at the 2014 arcc Annual Scientific Meeting in Toronto and the 2014 American Society of Clinical Oncology Quality Symposium in Boston, MA, U.S.A.


We have read and understood Current Oncology’s policy on disclosing conflicts of interest and we declare that we have none.


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Correspondence to: Lisa Barbera, Department of Radiation Oncology, 2075 Bayview Avenue, Toronto, Ontario M4G 2R7. E-mail: lisa.barbera@sunnybrook.ca

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Current Oncology, VOLUME 22, NUMBER 5, October 2015

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