Kim McGrail

Does Increasing Home Care Nursing Reduce Emergency Department Visits at the End of Life? A Population-Based Cohort Study of Cancer Decedents

CONTEXT Despite being commonplace in health care systems, little research has described home care nursings effectiveness to reduce acute care use at the end of life. OBJECTIVES To examine the temporal association between home care nursing rate on emergency department (ED) visit rate in the subsequent week during the last six months of life. METHODS We conducted a retrospective cohort study of end-of-life cancer decedents in Ontario, Canada, from 2004 to 2009 by linking administrative databases. We examined the association between home care nursing rate of one week with the ED rate in the subsequent week closer to death, controlling for covariates and repeated measures among decedents. Nursing was dichotomized into standard and end-of-life care intent. RESULTS Our cohort included 54,576 decedents who used home care nursing services in the last six months before death, where 85% had an ED visit and 68% received end-of-life home care nursing. Patients receiving end-of-life nursing at any week had a significantly reduced ED rate in the subsequent week of 31% (relative rate [RR] 0.69; 95% confidence interval [CI] 0.68, 0.71) compared with standard nursing. In the last month of life, receiving end-of-life nursing and standard nursing rate of more than five hours/week was associated with a decreased ED rate of 41% (RR 0.59, 95% CI 0.58, 0.61) and 32% (RR 0.68, 95% CI 0.66, 0.70), respectively, compared with standard nursing of one hour/week. CONCLUSION Our study showed a temporal association between receiving end-of-life nursing in a given week during the last six months of life, and of more standard nursing in the last month of life, with a reduced ED rate in the subsequent week.

Quality Indicators of End-of-Life Care in Patients With Cancer: What Rate Is Right?

PURPOSE To develop data-driven and achievable benchmark rates for end-of-life quality indicators using administrative data from four provinces in Canada. METHODS Indicators 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 regions age- and sex-adjusted indicator rates along with the overall rate and 95% confidence limits. RESULTS Rates 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. CONCLUSION There is significant variation in end-of-life quality indicators across regions in four provinces in Canada. Using this studys 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 studys methods can support quality improvement by decreasing variation and striving for a target.

Classifying physician practice style: a new approach using administrative data in British Columbia.

Background:Primary medical care is changing—more female providers, desire for better work-life balance, and increasing availability of walk-in clinics have altered service delivery. There is no uniform physician practice style, and understanding service availability and delivery requires analysis of family physicians’ practice patterns, rather than just physician counts. Methods:This paper offers a new approach for describing the practice habits of primary care physicians. We use administrative data to identify activities associated with acting as “most responsible” physicians. We used British Columbia’s administrative health care data from 2007/2008 to 2011/2012 to derive information regarding physicians, patients, and service delivery. We developed 5 variables to describe practice style: referrals, oversight, screening, initial prescribing for long-term medications, and repeat visits. Cluster analysis revealed 3 distinct groups of physicians. Results:Only 24% of the primary care physicians were assigned to the high-responsibility group, whereas 36% and 39% were in the low-responsibility and mixed-practice groups, respectively. All cluster variables follow a similar pattern, with the high-responsibility and low-responsibility physicians many multiples apart on the means and the mixed group falling in between. Several forms of sensitivity analysis confirmed the robustness of these results. Conclusions:Physician practice patterns influence the effective supply of primary care. The fact that more than one third of British Columbia physicians are identified as “low responsibility” has implications for the delivery of primary care, both in ensuring that people have access to regular care and in insuring high-quality and comprehensive care.

Temporal association between home nursing and hospital costs at end of life in three provinces

BACKGROUND Research has demonstrated that increases in palliative homecare nursing are associated with a reduction in the rate of subsequent hospitalizations. However, little evidence is available about the cost-savings potential of palliative nursing when accounting for both increased nursing costs and potentially reduced hospital costs. METHODS Our retrospective cohort study included cancer decedents from British Columbia, Ontario, and Nova Scotia who received any palliative nursing in the last 6 months of life. A Poisson regression analysis was used to determine the association of increased nursing costs (in 2-week blocks) on the relative average hospital costs in the subsequent 2-week block and on the overall total cost (hospital costs plus nursing costs in the preceding 2-week block). RESULTS The cohort included 58,022 cancer decedents. Results of the analysis for the last month of life showed an association between increased nursing costs and decreased relative hospital costs in comparisons with a reference group (>0 to 1 hour nursing in the block): the maximum decrease was 55% for Ontario, 31% for British Columbia, and 38% for Nova Scotia. Also, increased nursing costs in the last month were almost always associated with lower total costs in comparison with the reference. For example, cost savings per person-block ranged from

The impact of the 2008/2009 financial crisis on specialist physician activity in Canada

376 (>10 nursing hours) to

Measuring Patient Experiences: Is It Meaningful and Actionable?

1,124 (>4 to 6 nursing hours) in British Columbia. CONCLUSIONS In the last month of life, increased palliative nursing costs (compared with costs for >0 to 1 hour of nursing in the block) were associated with lower relative hospital costs and a lower total cost in a subsequent block. Our research suggests a cost-savings potential associated with increased community-based palliative nursing.

Does access to end-of-life homecare nursing differ by province and community size?: A population-based cohort study of cancer decedents across Canada

Fee-for-service physicians are responsible for planning for their retirements, and there is no mandated retirement age. Changes in financial markets may influence how long they remain in practice and how much they choose to work. The 2008 crisis provides a natural experiment to analyze elasticity in physician service supply in response to dramatic financial market changes. We examined quarterly fee-for-service data for specialist physicians over the period from 1999/2000 to 2013/2014 in Canada. We used segmented regression to estimate changes in the number of physicians receiving payments, per-physician service counts, and per-physician payments following the 2008 financial crisis and explored whether patterns differed by physician age. The number of specialist physicians increased more rapidly in the period since 2008 than in earlier years, but increases were largest within the youngest age group, and we observed no evidence of delayed retirement among older physicians. Where changes in service volume and payments were observed, they occurred across all ages and not immediately following the 2008 financial crisis. We conclude that any response to the financial crisis was small compared with demographic shifts in the physician population and changes in payments per service over the same time period.

Choosing Your Partner for the PROM: A Review of Evidence on Patient-Reported Outcome Measures for Use in Primary and Community Care

Performance measurement must be meaningful to those being asked to contribute data and to the clinicians who are collecting the information. It must be actionable if performance measurement and reporting is to influence health system transformation. To date, measuring patient experiences in all parts of the healthcare system in Canada lags behind other countries. More attention needs to be paid to capturing patients with complex intersecting health and social problems that result from inequitable distribution of wealth and/or underlying structural inequities related to systemic issues such as racism and discrimination, colonialism and patriarchy. Efforts to better capture the experiences of patients who do not regularly access care and who speak English or French as a second language are also needed. Before investing heavily into collecting patient experience data as part of a performance measurement system the following ought to be considered: (1) ensuring value for and buy-in from clinicians who are being asked to collect the data and/or act on the results; (2) investment in the infrastructure to administer iterative, cost-effective patient/family experience data collection, analysis and reporting (e.g., automated software tools) and (3) incorporating practice support (e.g., facilitation) and health system opportunities to integrate the findings from patient experience surveys into policy and practice. Investment into the infrastructure of measuring, reporting and engaging clinicians in improving practice is needed for patient/caregiver experiences to be acted upon.

Public views and recommendations on the use of linked data for research: preliminary results from a public deliberation engagement

BACKGROUND Studies have demonstrated the strong association between increased end-of-life homecare nursing use and reduced acute care utilization. However, little research has described the utilization patterns of end-of-life homecare nursing and how this differs by region and community size. METHODS A retrospective population-based cohort study of cancer decedents from Ontario, British Columbia, and Nova Scotia was conducted between 2004 and 2009. Provinces linked administrative databases which provide data about homecare nursing use for the last 6 months of life for each cancer decedent. Among weekly users of homecare nursing in their last six months of life, we describe the proportion of patients receiving end-of-life homecare nursing by province and community size. RESULTS Our cohort included 83,746 cancer decedents across 3 provinces. Patients receiving end-of-life nursing among homecare nursing users increased from weeks -26 to -1 before death by: 78% to 93% in British Columbia, 40% to 81% in Ontario, and 52% to 91% in Nova Scotia. In all 3 provinces, the smallest community size had the lowest proportion of patients using end-of-life nursing compared to the second largest community size, which had the highest proportion. CONCLUSIONS Differences in end-of-life homecare nursing use are much larger between provinces than between community sizes.