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Physician preparedness for resource allocation decisions under pandemic conditions: A cross-sectional survey of Canadian physicians, April 2020.

ABSTRACT: BACKGROUND:Under the pandemic conditions created by the novel coronavirus of 2019 (COVID-19), physicians have faced difficult choices allocating scarce resources, including but not limited to critical care beds and ventilators. Past experiences with severe acute respiratory syndrome (SARS) and current reports suggest that making these decisions carries a heavy emotional toll for physicians around the world. We sought to explore Canadian physicians' preparedness and attitudes regarding resource allocation decisions. METHODS:From April 3 to April 13, 2020, we conducted an 8-question online survey of physicians practicing in the region of Ottawa, Ontario, Canada, organized around 4 themes: physician preparedness for resource rationing, physician preparedness to offer palliative care, attitudes towards resource allocation policy, and approaches to resource allocation decision-making. RESULTS:We collected 219 responses, of which 165 were used for analysis. The majority (78%) of respondents felt "somewhat" or "a little prepared" to make resource allocation decisions, and 13% felt "not at all prepared." A majority of respondents (63%) expected the provision of palliative care to be "very" or "somewhat difficult." Most respondents (83%) either strongly or somewhat agreed that there should be policy to guide resource allocation. Physicians overwhelmingly agreed on certain factors that would be important in resource allocation, including whether patients were likely to survive, and whether they had dementia and other significant comorbidities. Respondents generally did not feel confident that they would have the social support they needed at the time of making resource allocation decisions. INTERPRETATION:This rapidly implemented survey suggests that a sample of Canadian physicians feel underprepared to make resource allocation decisions, and desire both more emotional support and clear, transparent, evidence-based policy.

SUBMITTER: Dewar B

PROVIDER: S-EPMC7580904 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Physician preparedness for resource allocation decisions under pandemic conditions: A cross-sectional survey of Canadian physicians, April 2020.

Dewar Brian B Anderson Joanna E JE Kwok Edmund S H ESH Ramsay Tim T Dowlatshahi Dar D Fahed Robert R Dyason Claire C Shamy Michel M

PloS one 20201022 10

<h4>Background</h4>Under the pandemic conditions created by the novel coronavirus of 2019 (COVID-19), physicians have faced difficult choices allocating scarce resources, including but not limited to critical care beds and ventilators. Past experiences with severe acute respiratory syndrome (SARS) and current reports suggest that making these decisions carries a heavy emotional toll for physicians around the world. We sought to explore Canadian physicians' preparedness and attitudes regarding re ...[more]

PMID: 33091015

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Project description:Cost-effectiveness analysis, routinely used in health care to inform funding decisions, can be extended to consider impact on health inequality. Distributional cost-effectiveness analysis (DCEA) incorporates socioeconomic differences in model parameters to capture how an intervention would affect both overall population health and differences in health between population groups. In DCEA, uncertainty analysis can consider the decision uncertainty around on both impacts (i.e., the probability that an intervention will increase overall health and the probability that it will reduce inequality). Using an illustrative example assessing smoking cessation interventions (2 active interventions and a "no-intervention" arm), we demonstrate how the uncertainty analysis could be conducted in DCEA to inform policy recommendations. We perform value of information (VOI) analysis and analysis of covariance (ANCOVA) to identify what additional evidence would add most value to the level of confidence in the DCEA results. The analyses were conducted for both national and local authority-level decisions to explore whether the conclusions about decision uncertainty based on the national-level estimates could inform local policy. For the comparisons between active interventions and "no intervention," there was no uncertainty that providing the smoking cessation intervention would increase overall health but increase inequality. However, there was uncertainty in the direction of both impacts when comparing between the 2 active interventions. VOI and ANCOVA show that uncertainty in socioeconomic differences in intervention effectiveness and uptake contributes most to the uncertainty in the DCEA results. This suggests potential value of collecting additional evidence on intervention-related inequalities for this evaluation. We also found different levels of decision uncertainty between settings, implying that different types and levels of additional evidence are required for decisions in different localities.

Project description:BackgroundImplementing evidence into clinical practice is a key focus of healthcare improvements to reduce unwarranted variation. Dissemination of evidence-based recommendations and knowledge brokering have emerged as potential strategies to achieve evidence implementation by influencing resource allocation decisions. The aim of this study was to determine the effectiveness of these two research implementation strategies to facilitate evidence-informed healthcare management decisions for the provision of inpatient weekend allied health services.Methods and findingsThis multicentre, single-blinded (data collection and analysis), three-group parallel cluster randomised controlled trial with concealed allocation was conducted in Australian and New Zealand hospitals between February 2018 and January 2020. Clustering and randomisation took place at the organisation level where weekend allied health staffing decisions were made (e.g., network of hospitals or single hospital). Hospital wards were nested within these decision-making structures. Three conditions were compared over a 12-month period: (1) usual practice waitlist control; (2) dissemination of written evidence-based practice recommendations; and (3) access to a webinar-based knowledge broker in addition to the recommendations. The primary outcome was the alignment of weekend allied health provision with practice recommendations at the cluster and ward levels, addressing the adoption, penetration, and fidelity to the recommendations. The secondary outcome was mean hospital length of stay at the ward level. Outcomes were collected at baseline and 12 months later. A total of 45 clusters (n = 833 wards) were randomised to either control (n = 15), recommendation (n = 16), or knowledge broker (n = 14) conditions. Four (9%) did not provide follow-up data, and no adverse events were recorded. No significant effect was found with either implementation strategy for the primary outcome at the cluster level (recommendation versus control β 18.11 [95% CI -8,721.81 to 8,758.02] p = 0.997; knowledge broker versus control β 1.24 [95% CI -6,992.60 to 6,995.07] p = 1.000; recommendation versus knowledge broker β -9.12 [95% CI -3,878.39 to 3,860.16] p = 0.996) or ward level (recommendation versus control β 0.01 [95% CI 0.74 to 0.75] p = 0.983; knowledge broker versus control β -0.12 [95% CI -0.54 to 0.30] p = 0.581; recommendation versus knowledge broker β -0.19 [-1.04 to 0.65] p = 0.651). There was no significant effect between strategies for the secondary outcome at ward level (recommendation versus control β 2.19 [95% CI -1.36 to 5.74] p = 0.219; knowledge broker versus control β -0.55 [95% CI -1.16 to 0.06] p = 0.075; recommendation versus knowledge broker β -3.75 [95% CI -8.33 to 0.82] p = 0.102). None of the control or knowledge broker clusters transitioned to partial or full alignment with the recommendations. Three (20%) of the clusters who only received the written recommendations transitioned from nonalignment to partial alignment. Limitations include underpowering at the cluster level sample due to the grouping of multiple geographically distinct hospitals to avoid contamination.ConclusionsOwing to a lack of power at the cluster level, this trial was unable to identify a difference between the knowledge broker strategy and dissemination of recommendations compared with usual practice for the promotion of evidence-informed resource allocation to inpatient weekend allied health services. Future research is needed to determine the interactions between different implementation strategies and healthcare contexts when translating evidence into healthcare practice.Trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12618000029291.

Project description:ImportancePhysicians must participate in end-of-life discussions, but they understand poorly their patients' end-of-life values and preferences. A better understanding of these preferences and the effect of baseline attitudes will improve end-of-life discussions.ObjectiveTo determine how baseline attitudes toward quality vs quantity of life affect end-of-life resource allocation.Design, setting, and participantsOtolaryngology-head and neck surgery (OHNS) physicians were recruited to use a validated online tool to create a Medicare health plan for advanced cancer patients. During the exercise, participants allocated a limited pool of resources among 15 benefit categories. These data were compared with preliminary data from patients with cancer and their caregivers obtained from a separate study using the same tool. Attitudes toward quality vs quantity of life were assessed for both physicians and patients and caregivers.InterventionsParticipation in online assessment exercise.Main outcomes and measuresMedicare resource allocation.ResultsOf 9120 OHNS physicians e-mailed, 767 participated. Data collected from this group were compared with data collected from 146 patients and 114 caregivers. Compared with patients and caregivers, OHNS physician allocations differed significantly in all 15 benefit categories except home care. When stratified by answers to 3 questions about baseline attitudes toward quality vs quantity of life, there were 3 categories in which allocations of patients and caregivers differed significantly from the group with the opposite attitude for at least 2 questions: other medical care (question 1, P < .001; question 2, P = .005), palliative care (question 1, P = .008; question 2, P = .006; question 3, P = .009), and treatment for cancer (questions 1 and 2, P < .001). In contrast, physician preferences showed significant differences in only 1, nonmatching category for each attitude question: cash (question 1, P = .02), drugs (question 2, P = .03), and home care (question 3, P = .048).Conclusions and relevancePatients with cancer and their caregivers have different preferences from physicians. These preferences are, for these patients and their caregivers, affected by their baseline health attitudes, but physician preferences are not. Understanding the effect of baseline attitudes is important for effective end-of-life discussions.

Dataset Information

Physician preparedness for resource allocation decisions under pandemic conditions: A cross-sectional survey of Canadian physicians, April 2020.

Publications

Physician preparedness for resource allocation decisions under pandemic conditions: A cross-sectional survey of Canadian physicians, April 2020.

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