A Review and Considerations on Palliative Care Improvements for African Americans With Cancer

Inequities in access to palliative and end-of-life care in the black population in Canada: a scoping review

BACKGROUND

Improving equity and early access to palliative care for underserved populations in Canada is a priority. Little is known regarding access to palliative and end-of-life care in the Black population.

METHODS

We undertook a scoping review using the framework by Arksey and O'Malley to identify knowledge, access gaps, and experiences of palliative and end-of-life care among Blacks living with life-limiting illnesses in Canada. Primary studies, discussion papers, books, and reports were considered eligible. We followed a comprehensive search strategy developed by an information scientist. Searches were performed in the following bibliographic databases: Medline, EMBASE, PsycINFO via OVID, CINAHL via EBSCOhost, Scopus and Cochrane Library via Wiley. The search strategy was derived from three main concepts: (1) Black people; (2) Canada and Canadian provinces; (3) Palliative, hospice, or end-of-life care. No publication date or language limits were applied. Titles and abstracts were screened for eligibility by one reviewer and full text by two independent reviewers.

RESULTS

The search yielded 233 articles. Nineteen articles were selected for full-text review, and 7 articles met the inclusion criteria. These studies were published between 2010 and 2021, and conducted in the provinces of Ontario and Nova Scotia only. Studies used both quantitative and qualitative methods and included cancer decedents, next of kin, family caregivers and religious leaders. Sample sizes in various studies ranged from 6 - 2,606 participants. Included studies reported a general lack of understanding about palliative and end-of-life care, positive and negative experiences, and limited access to palliative and end-of-life care for Blacks, across all care settings.

CONCLUSION

Findings suggest limited knowledge of palliative care and inequities in access to palliative and end-of-life care for Blacks living with life-limiting illnesses in 2 Canadian provinces. There is an urgent need for research to inform tailored and culturally acceptable strategies to improve understanding and access to palliative care and end-of-life care among Blacks in Canada.

Power calculation for detecting interaction effect in cross-sectional stepped-wedge cluster randomized trials: an important tool for disparity research

BACKGROUND

The stepped-wedge cluster randomized trial (SW-CRT) design has become popular in healthcare research. It is an appealing alternative to traditional cluster randomized trials (CRTs) since the burden of logistical issues and ethical problems can be reduced. Several approaches for sample size determination for the overall treatment effect in the SW-CRT have been proposed. However, in certain situations we are interested in examining the heterogeneity in treatment effect (HTE) between groups instead. This is equivalent to testing the interaction effect. An important example includes the aim to reduce racial disparities through healthcare delivery interventions, where the focus is the interaction between the intervention and race. Sample size determination and power calculation for detecting an interaction effect between the intervention status variable and a key covariate in the SW-CRT study has not been proposed yet for binary outcomes.

METHODS

We utilize the generalized estimating equation (GEE) method for detecting the heterogeneity in treatment effect (HTE). The variance of the estimated interaction effect is approximated based on the GEE method for the marginal models. The power is calculated based on the two-sided Wald test. The Kauermann and Carroll (KC) and the Mancl and DeRouen (MD) methods along with GEE (GEE-KC and GEE-MD) are considered as bias-correction methods.

RESULTS

Among three approaches, GEE has the largest simulated power and GEE-MD has the smallest simulated power. Given cluster size of 120, GEE has over 80% statistical power. When we have a balanced binary covariate (50%), simulated power increases compared to an unbalanced binary covariate (30%). With intermediate effect size of HTE, only cluster sizes of 100 and 120 have more than 80% power using GEE for both correlation structures. With large effect size of HTE, when cluster size is at least 60, all three approaches have more than 80% power. When we compare an increase in cluster size and increase in the number of clusters based on simulated power, the latter has a slight gain in power. When the cluster size changes from 20 to 40 with 20 clusters, power increases from 53.1% to 82.1% for GEE; 50.6% to 79.7% for GEE-KC; and 48.1% to 77.1% for GEE-MD. When the number of clusters changes from 20 to 40 with cluster size of 20, power increases from 53.1% to 82.1% for GEE; 50.6% to 81% for GEE-KC; and 48.1% to 79.8% for GEE-MD.

CONCLUSIONS

We propose three approaches for cluster size determination given the number of clusters for detecting the interaction effect in SW-CRT. GEE and GEE-KC have reasonable operating characteristics for both intermediate and large effect size of HTE.

Telemedicine Utilization in the Ambulatory Palliative Care Setting: Are There Disparities?

CONTEXT

Given a shortage of specialty palliative care clinicians and geographic variation in availability, telemedicine has been proposed as one way to improve access to palliative care services for patients with cancer. However, the enduring digital divide raises questions about whether unequal access will exacerbate healthcare disparities.

OBJECTIVES

To examine factors associated with utilization of telemedicine as compared to in-person visits by patients with cancer in the ambulatory palliative care setting.

METHODS

We collected data on patients seen in Supportive Oncology clinic by palliative care clinicians with an in-person or telemedicine visit from March 1 to December 30, 2020. A logistic regression with generalized estimating equation was fit to assess the association between visit type and patient characteristics.

RESULTS

A total of 491 patients and 1783 visits were identified, including 1061 (60%) in-person visits and 722 (40%) telemedicine visits. Female patients were significantly more likely to utilize telemedicine than male patients (OR 1.46; 95% CI 1.11-1.90). Spanish-speaking patients (OR 0.32, 95% CI 0.17-0.61), those without insurance (OR 0.28, 95% CI 0.15-0.52), and those without an activated patient portal (Inactivated: OR 0.46, 95% CI 0.26-0.82; Pending Activation: OR 0.29, 95% CI 0.18-0.48) were less likely to utilize telemedicine.

CONCLUSION

Our study reveals disparities in telemedicine utilization in the ambulatory palliative care setting for patients with cancer who are male, Spanish-speaking, uninsured, or do not have an activated patient portal. In the wake of the COVID-19 pandemic, we can better meet the palliative care needs of patients with cancer through telemedicine only if equity is kept at the forefront of our discussions.

Access to Palliative Care Consultation for Hospitalized Adults with COVID-19 in an Urban Health System: Were There Disparities at the Peak of the Pandemic?

Background: Palliative care (PC) services expanded rapidly to meet the needs of coronavirus disease 2019 (COVID-19) patients, yet little is known about which patients were referred for PC consultation during the pandemic. Objective: Examine factors predictive of PC consultation for COVID-19 patients. Design: Retrospective cohort study of COVID-19 patients discharged from four hospitals (March 1-June 30, 2020). Exposures: Patient demographic, socioeconomic, and clinical factors and hospital-level characteristics. Outcome Measurement: Inpatient PC consultation. Results: Of 4319 hospitalized COVID-19 patients, 581 (14%) received PC consultation. Increasing age, serious illness (cancer, chronic obstructive pulmonary disease, and dementia), greater illness severity, and admission to the quaternary hospital were associated with receipt of PC consultation. There was no association between PC consultation and race/ethnicity, household crowding, insurance status, or hospital-factors, including inpatient, emergency department, and intensive care unit census. Conclusions: Although site variation existed, the highest acuity patients were most likely to receive PC consultation without racial/ethnic or socioeconomic disparities.