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

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.

Trajectories at the end of life: A controlled investigation of longitudinal Health Services Consumption data

BACKGROUND

Knowledge of individual-level trajectories of Health Services Consumption (HSC) at End-of-Life (EoL) is scarce. Such research is needed for understanding and planning health expenditures.

OBJECTIVE

To explore individual-level EoL trajectories in the Israeli population. This approach differs from past studies which aggregated across populations or disease groups.

DATA SOURCES

We used HMO (Health Maintenance Organization) longitudinal data for HSC of persons ages 65-90 who died during 2010-2011 (n=35,887) and of an age by sex matched sample of persons who were alive by mid-2012 (n=48,560).

DESIGN

HSC per quarter was calculated for each individual. Trajectory-types of HSC were described through k-means cluster analysis.

EXTRACTION METHODS

Data were extracted from computerized HMO files. HSC was computed as a standardized function of HMO costs for each individual.

RESULTS

In both samples, low HSC trajectories were the most common. However, among the deceased, all trajectories had higher HSC than those who were alive; the low HSC trajectory cluster represented a smaller percentage of the sample; and all relevant trajectories included a HSC peak. In contrast, the most common trajectory among the living was a flat low HSC. Clusters differed significantly by sex, disease status, and age.

CONCLUSION

This methodology shows the utility of individual-level analysis of HSC at end-of-life and should inform future research and current debates concerning EoL care and resource distribution.

Correlates and Predictors of Changes in Dyspnea Symptoms Over Time Among Community-Dwelling Palliative Home Care Clients

CONTEXT

Dyspnea is a frequently reported and highly distressing symptom for persons nearing end of life, affecting the quality of living and dying.

OBJECTIVES

This study described health and clinical characteristics of persons experiencing dyspnea who receive palliative home care services and identified factors affecting change in dyspnea over time.

METHODS

Anonymized assessments (N = 6655 baseline; 959 follow-up) from the interRAI palliative care assessment instrument (interRAI PC) were collected during pilot implementation (2006-2011). Triggering of the interRAI PC dyspnea clinical assessment protocol was used to indicate presence of dyspnea. Bivariate and logistic regression analyses described risk and protective factors for developing new dyspnea and for recovery from dyspnea at follow-up.

RESULTS

At baseline, 44.9% of persons exhibited dyspnea. Dyspnea was more prevalent among older adults, males, persons with shortened prognoses, and persons without cancer. Persons with dyspnea were more likely to experience functional impairment, moderate cognitive impairment, fatigue, weight loss, and urinary incontinence. Among persons with dyspnea at baseline, 31.5% recovered from dyspnea at follow-up. In contrast, 31% of persons without dyspnea at baseline reported new dyspnea at follow-up. Risk factors for developing new dyspnea included smoking, fatigue, and receiving oxygen therapy.

CONCLUSION

Results highlight that dyspnea is not inevitable as persons progress toward death. Accordingly, dyspnea should be identified and prioritized during the care planning process. Integrated approaches using the interRAI PC dyspnea clinical assessment protocol may assist clinicians to make informed decisions addressing dyspnea at the person-level and thereby improve quality of life at the end of life.

Predictors of hospital stay and home care services use: a population-based, retrospective cohort study in stage IV gastric cancer

BACKGROUND

Home care services use has been proposed as a means of reducing costs in palliative care by decreasing hospital stay without impacting quality of clinical care; however, little is known about utilization of these services in the time following a terminal cancer diagnosis.

AIM

To examine disease, patient and healthcare system predictors of hospital stay, and home care services use in metastatic gastric cancer patients.

DESIGN

This is a population-based, retrospective cohort study. Chart review and administrative data were linked, using a 26-month time horizon to collect health services data.

PARTICIPANTS

All patients diagnosed with metastatic gastric cancer in the province of Ontario between 2005 and 2008 were included in the study (n = 1433).

RESULTS

Age, comorbidity, tumor location, and burden of metastatic disease were identified as predictors of hospital stay and receipt of home care services. Individuals who received home care services spent fewer days in hospital than individuals who did not (relative risk: 0.44; 95% confidence interval: 0.38-0.51). Patients who interacted with a high-volume oncology specialist had shorter cumulative hospital stay (relative risk: 0.62; 95% confidence interval: 0.54-0.71) and were less likely to receive home care services (relative risk: 0.80; 95% confidence interval: 0.72-0.88) than those who did not.

CONCLUSION

Examining how differences in hospital stay and home care services use impact clinical outcomes and how policies may reduce costs to the healthcare system is necessary.