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Record W3212630148 · doi:10.1002/gps.5654

Invited letter: Integrated palliative care in a geriatric mental health setting during the COVID‐19 pandemic

2021· letter· en· W3212630148 on OpenAlexaffabout
Cristina de Lasa, Eric E. Brown, Rebecca E. Colman, Tarek K. Rajji, Sarah Colman

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2021
Typeletter
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsToronto Dementia Research AllianceSinai Health SystemUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPalliative carePandemicMedicineDementiaQuality of life (healthcare)Mental healthHealth carePopulationDiseasePsychiatryGerontologyNursingCoronavirus disease 2019 (COVID-19)Environmental healthInfectious disease (medical specialty)

Abstract

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The COVID-19 pandemic has disproportionately impacted the elderly residents of congregate settings with respect to morbidity and mortality. The high rate of severe illness in this population necessitates timely and quality access to palliative care. There are a number of challenges facing teams working in geriatric mental health settings during the COVID-19 pandemic with respect to palliative care. We outline our experience as an example of changes made to improve the provision of pandemic palliative care on site in a geriatric mental health inpatient unit. Improving palliative care can help to increase the quality of care for patients beyond the pandemic, can increase the skill set of staff members, and help to prevent staff burnout. In Canada, like other jurisdictions, the majority of residents in LTC have major neurocognitive disorder, or dementia, a progressive, disabling, irreversible and ultimately fatal disease.6 Reported 6-month mortality rate among people with advanced dementia is 25%. There have been longstanding calls to expand palliative care to include advanced dementia.7 The culture in some Canadian LTC and inpatient geriatric psychiatric settings is to defer management of acute medical issues and palliation.8-10 Patients with dementia may have challenges expressing their wishes. As a result, patients are often sent to medical hospitals, at times against their best interests, with increased risk of nosocomial infection and functional decline, and at a high cost to the medical system.9 The COVID-19 pandemic has challenged healthcare systems internationally due to threatened and actual resource scarcity. Faced with the potential need to ration critical care resources, clear advance directives with respect to life-sustaining care are necessary. Defaulting to intensive life-sustaining therapy (e.g., CPR) to all patients without their truly informed consent may be harmful. The ethical principle of non-maleficence demands that we protect such vulnerable people from dying in this uncomfortable way.5 Given these considerations, along with changes in the risk–benefit ratio during this pandemic, many institutions have had to pivot to be able to provide dignified death within their walls. Here we report our local experience in hopes that it will be useful for others in international settings, given the global context of the pandemic and universal ethical principles involved. Our setting is the 48-bed geriatric mental health unit at the Centre for Addiction and Mental Health, an academic mental health hospital in Toronto, Canada. Our patient population resembles LTC homes, with approximately half of patients admitted for behavioural symptoms of dementia, many being residents of LTC or retirement homes. Lengths of stay are months to years, mirroring LTC homes rather than general psychiatry inpatient units. As of September 2021, we have had 111 COVID-19-positive cases within the hospital. Six of these occurred on our unit in April 2020. Of these six, one required ICU admission. Another was provided comfort-based care on site consistent with the substitute decision-maker's (SDM) decisions and died within 3 weeks of symptom onset. At the time, there were concerns about lack of medical hospital space. This led to a broader acceptance of the idea that patients may die at our facility, accelerating our efforts upskill capacity to integrate palliative care in our setting. We integrated a clinical frailty scale in goals of care discussions to assist families in deciding between life-prolonging treatments and comfort-based approaches.11, 12 Using elements of the palliative care pandemic framework set out by Arya et al.13 we developed a plan to address 'stuff, staff, space and systems', the need for sedation and communication, with minimal additional expenses. We developed an electronic order set to standardize the provision of palliative care for those not frequently using those skills (Table 1). We reviewed local hospital palliative order sets and elicited interdisciplinary feedback. We collaborated with our pharmacists to ensure an adequate supply of medications and obtained specialized equipment such as butterflies for subcutaneous medication administration. We developed a collaborative, working relationship with a local palliative care team for virtual support to our front-line physicians. A medical mobile team of two nurses with palliative care expertise provided nursing staff with bedside support. Palliative care staff training was provided by nurse educators. Our hospital's Resuscitation Status for Inpatients Policy helped guide our clinicians in addressing relevant clinical, legal and ethical issues whereby different levels of medical care could be clearly requested by the patient or, if incapable, the SDM. Discussions about goals of care were held with patients, family and SDMs following the principles of shared decision-making. We set up the conversation and shared information and prognosis. We explored goals, fears, and strengths and provided a summary. We documented the conversation and resuscitation status in the electronic medical record. We increased communication among the clinical team through daily 'huddles' to discuss concerns and ensure proper provision of palliation. During hospital-wide grand rounds, we shared our experiences to promote a more palliative-friendly culture. The COVID-19 pandemic brought to the forefront institutional gaps in palliative care, such as insufficient goals of care discussions and lack of skill to provide palliative care on site. The acute need threatened by the pandemic served as a 'burning platform' to accelerate change in hospital culture. We realized that the risk of sending some patients to medical hospital may outweigh benefits. We acknowledged that death on the unit may be a preferred outcome by some patients and families. We adapted quickly to increase our comfort in managing end-of-life treatment. The issues facing our LTC homes and psychiatric hospitals in Canada were similar internationally.2 As the COVID-19 pandemic continues to impact residents in our inpatient setting, as in LTC and other congregate settings in which people with dementia reside, integrated palliative care services will be needed. Failing to properly address patients' goals of care and to provide effective palliation will compound the tragedy of this pandemic. By upskilling and adapting, we will be better prepared for future pandemics or new cycles of the present one. Our experience attests to the feasibility of rising to this mission. This research received no specific grant from any funding agency, commercial or not-for-profit sectors. The authors declare no conflict of interests. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.004
Open science0.0020.001
Research integrity0.0230.018
Insufficient payload (model declined to judge)0.0140.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.397
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations5
Published2021
Admission routes2
Has abstractyes

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