Rhiannon L. Roberts, MScPH1, Christina Milani, MSc2, Colleen Webber, PhD1,2, Shirley H. Bush, MBBS, PgDip, Pall Med1,2,3, Kaitlyn Boese, MD1,3, Jessica E. Simon, MB, ChB4, James Downar, MD, MHSc1,2,3, Amit Arya, MD5,6, Peter Tanuseputro, MD, MHSc1,2,3, Sarina R. Isenberg, PhD, MA3,2,5,7
1Ottawa Hospital Research Institute, Ottawa, ON
2Bruyère Research Institute, Ottawa, ON
3Department of Medicine, Division of Palliative Care, University of Ottawa, Ottawa, ON
4Department of Oncology, Medicine and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB
5Department of Family and Community Medicine, University of Toronto, Toronto, ON
6Kensington Research Institute, Toronto, ON
7School of Epidemiology and Public Health, Faculty of Medicine, Ottawa, ONDOI: https://doi.org/10.5770/cgj.27.712
ABSTRACT
Background
At the end of life, individuals may experience physical symptoms such as pain, and guidelines recommend medications to manage these symptoms. Yet, little is known about the symptom management long-term care (LTC) residents receive at the end of life. Our research team developed a metric—whether residents receive one or more prescriptions for an end-of-life symptom management medication in their last two weeks—to explore end-of-life care for LTC residents. This qualitative study aimed to inform the refinement of the end-of-life prescribing metric, including the acceptability and applicability to assess the quality of a resident’s symptom management at end-of-life.
Methods
We conducted 14 semi-structured interviews with Ontario health-care providers (physicians and nurses) who work in LTC homes and family caregivers of residents who died in LTC. Interviews were conducted virtually between February 2021 and December 2022, and were analyzed using thematic analysis.
Results
We identified three major themes relating to perceptions of the metric: 1) appropriateness, 2) health-care provider applicability, and 3) caregiver applicability. Participants noted that the metric may be appropriate to assess end-of-life care, but noted important nuances. Regarding applicability, health-care providers found value in the metric and that it could inform their practice. Conversely, caregivers found limited value in the metric.
Conclusion
The proposed metric captures a very specific aspect of end-of-life care—whether end-of-life medications were prescribed or not. Participants deemed that the metric may reflect whether LTC homes have processes to manage a resident’s end-of-life symptoms with medication. However, participants thought the metric could not provide a complete picture of end-of-life care and its quality.
KEYWORDS: qualitative, thematic analyses, end-of-life, long-term care, medications, metric
Palliative care is a holistic approach aiming to achieve the best quality of life and comfort for a person with a life-limiting illness and their family caregivers; this care can occur during, but is not limited to, the end of life.(1) Holistic palliative care is an iterative process requiring ongoing assessments and adjustments to an individual’s care plan by health-care professionals to address the physical, psychological, social, spiritual, and practical needs of the person and their caregivers.(2) Quality end-of-life care involves a palliative approach to care. At the end of life, individuals may experience physical symptoms such as pain, shortness of breath, and agitated delirium, which can be distressing to both the individual and their caregivers. To address these symptoms, individuals and their caregivers often prioritize comfort care, including the use of medications to control these distressing symptoms.(3–5) Individuals who do not receive comfort care measures, including the use medications, may experience inadequate symptom control which could impact their care during the dying process.
Palliative care is an essential aspect of care that long-term care (LTC) homes are expected to provide. LTC homes provide personal and medical care to individuals unable to live in their own homes due to illness or disability. In Ontario, Canada—where an estimated 79,000 residents live in more than 600 LTC homes—the median survival after LTC admission is 18 months, and 80% of LTC residents have LTC as their place of death.(6–8) Therefore, LTC homes must be able to manage residents’ end-of-life and death to minimize residents and their families from experiencing unnecessary distress and poor quality care at the end of life.
Canada uses quality indicators (e.g., restraint use in LTC, location of death) to monitor and improve the quality of care LTC homes provide. Quality indicators are not an absolute measure of quality, but reflect desired or undesired care.(9) In Canada, trends show the LTC sector generally improves its performance on reported quality indicators over time.(9–11) While Canada collects and reports on several LTC quality indicators, none provide insight into end-of-life care supports. To address this gap, our team developed a potential metric to explore symptom management for LTC residents’ end of life.
The metric was developed using available administrative health data sets (i.e., via prescription claims data). The metric measures whether residents receive one or more prescriptions for an end-of-life symptom management medication in their last two weeks of life.(8) The list of symptom management medications was created by the research team and revised by palliative care specialists across Ontario. Palliative care specialists were palliative care physicians who work with LTC homes (within the home or as a consultant). The list comprises medications that are commonly recommended to alleviate residents’ end-of-life symptoms, such as pain, anxiety, agitated delirium, shortness of breath, and nausea.(12–15) To date, we have used this metric in research studies to describe end-of-life symptom management prescribing in LTC homes in Ontario before and during the COVID-19 pandemic.(8) Our overall project aim is to use the metric to monitor the quality of end-of-life palliative care provided in LTC.
This qualitative study aimed to understand and inform the use of the end-of-life prescribing metric. Specifically, we aimed to determine the acceptability and applicability of the metric to assess the quality of residents’ end-of-life care. We interviewed LTC physicians, nurses, and bereaved caregivers of LTC residents to understand their perceptions of this metric.
This qualitative study is part of a larger multi-methods research project to evaluate end-of-life care in LTC. For the quantitative analyses, the team conducted retrospective cross-sectional studies. For each LTC home in Ontario, the team calculated the metric—the proportion of residents prescribed medication in the last two weeks of life. Homes were then grouped into quintiles based on the metric; in the top prescribing quintile, 83% of residents were, on average, prescribed an end-of-life symptom management medication, while in the lowest prescribing quintile, only 38% of residents were prescribed an end-of-life symptom management medication.(8) The analysis was conducted twice, evaluating a period before COVID (January 17, 2017 to March 17, 2020) and during COVID (March 18, 2020 to March 17, 2021). The quantitative analyses are being replicated in Alberta.
In this qualitative study, we conducted semi-structured interviews with health-care providers (physicians and nurses) who work in LTC homes and family caregivers of residents who died in LTC. Participants were from Ontario and Alberta. Recruitment and interviews occurred from February 2021 to December 2022.
Post-positivism informed our underlying epistemological assumptions, which combine positivism and interpretivism. Post-positivism focuses on the experiences of the majority and asserts there is no universal truth and that multi-dimensional evidence can be inferred by perceived data (e.g., interviews).(16)
We used a phased recruitment approach. The intention of Phase 1 was to retrospectively understand LTC practice before COVID-19 (e.g., residents who died before COVID-19). The intention of Phase 2 was to understand LTC practice during COVID-19 and the large variations in prescribing practices seen in the quantitative study. In both Phase 1 and 2, we also intended to evaluate the acceptability and applicability of the metric to assess the quality of residents’ end-of-life care.
In Phase 1, we recruited participants from a single LTC home (February to March 2021). In Phase 2, we started by recruiting participants from homes with the highest and lowest prescribing rates as identified through our quantitative analyses (June to August 2021). However, due to low response rates, we expanded our recruitment to all Ontario LTC homes and to Alberta LTC homes where the research team had professional connections (August 2021 to November 2022). A further description of our recruitment strategy is in Appendix A.
The core research team responsible for recruitment, data collection, and analysis consisted of an experienced qualitative researcher and the principal investigator of the study (S.R.I.), two research coordinators (C.M., R.L.R.), and a research associate (C.W.), who met weekly (core research team). A larger co-investigator team supported this core team (A.A., K.B., S.B., J.D., D.L., J.S.). The entire team met monthly to discuss study design, recruitment, analysis, and interpretation.
S.R.I., C.M. and R.L.R. conducted interviews using Zoom.(17) Interviewer details are included in Appendix B. S.R.I. provided training to the other interviewers on how to effectively conduct an interview. The interviewer obtained verbal consent from participants and administered a demographics survey.
The core researcher team collaborated to create the first iteration of the interview guides. Pilot interviews were conducted with D.L. (caregiving experience) and K.B. (health-care provider experience), representing our two population subgroups. The development of the interview guides was iterative; we modified the guiding questions after each pilot and the first six interviews (which spanned Phases 1 and 2). Guiding questions were similar for our health-care providers, physicians and nurses, with some addressing potentially different roles and perspectives. Guiding questions for family caregivers were unique to the caregiving perspective. Interview guides were not provided to participants. The final interview guides are in Appendix C. Interviews were audio-recorded, transcribed verbatim, and de-identified. Interviewers made field notes following the interviews. Transcripts were not provided to interviewees for correction.
We analyzed transcripts using a coding reliability approach and thematic analysis.(18,19) All analysis stages were completed collectively by the core research team). S.R.I. trained C.M., C.W., and R.L.R. in effective coding and ensuring consistency across coders. First, the core team conducted close readings of transcripts to understand the interviews thoroughly. Second, the core team identified and arranged preliminary codes into a coding frame. The codebook evolved as new interviews were transcribed and read. Once no new codes were developed, the core team determined that thematic saturation had been reached.(20) They inserted the finalized codebook (Appendix D) into qualitative analysis software (MAXQDA),(21) along with the interview transcripts. The core team established reliability and accuracy of thematic coding through group and consensus coding. The core team group-coded three randomly chosen transcripts. The core team then separately coded a randomly selected transcript and merged the coded transcripts into one working document using MAXQDA. The core team then consensus-coded this merged transcript, discussed their coding rationale, and adjusted the coding frame to accommodate newly emerging patterns. The remaining ten transcripts were double- coded by the core team, who ensured agreement between coders through discussion and comparison. The core team then reviewed the coded segments and explored preliminary patterns before identifying core themes that we developed from the data. The core team then refined, defined, and named our themes, and found exemplary quotations. Interviewees were not consulted on the feedback.
We received approval from the Bruyère Research Ethics Board (REB) (December 7, 2020, #M16-20-060) and the Ottawa Health Science Network REB (April 1, 2021, #20210207-01H).
We interviewed 15 participants, 14 from Ontario and one from Alberta. We excluded the single Alberta transcript from our analysis as the interview suggested differences in practice across provinces. We determined we could not fully capture those differences with only one interview. Of the Ontario transcripts, there were six physicians, five nurses, and three family caregivers from seven of Ontario’s 626 LTC homes. Of the Ontarian participants, half (n=7, 50%) were female, and a third (n=5, 36%) were aged 60 to 69. Half (n=7, 50%) were from private not-for-profit LTC homes, and the majority (n=10, 71%) were from non-religious LTC homes. Of the health-care providers (n=11), the majority (n=9, 81%) had previous palliative care training (e.g., residency program or professional development courses) and were in a managerial or leadership role within their home (n=7, 64%). Participant demographics are in Table 1. The average interview length was 40 minutes (24 to 51 minutes).
Table 1 Caregiver and healthcare provider participants’ sociodemographic characteristics and healthcare provider professional characteristics
We identified three major themes relating to perceptions of the metric: 1) appropriateness, 2) healthcare provider applicability, and 3) caregiver applicability. Exemplary quotes for all themes are in Table 2.
Both types of participants, health-care providers and caregivers, commented that the metric might be appropriate to assess end-of-life care. Appropriateness is the perceived fit of the innovation to address a particular issue or problem.(22) Participants generally agreed that the metric was promising as a measure of end-of-life care in LTC, but noted nuances.
For many, they emphasized that the metric is necessary but not sufficient to assess end-of-life care. Participants flagged that some aspects of end-of-life care do not require medications (e.g., spiritual care and mouth, eye, and skin care). Participants felt that these types of care are as important at the end of life as medications and are not captured by the metric. Additionally, they noted that the metric only captures prescribed and not administered medications because the data were obtained from administrative health databases (i.e., via prescription claims data). Participants flagged instances when a medication was prescribed but not administered, even when the need was present (e.g., the resident died before the pharmacy filled the prescription). Additionally, they flagged instances where the resident had a medication prescribed, but it was not administered because it was no longer needed (e.g., a prescriber ordered an entire end-of-life order set in preparation for symptoms that did not materialize). The metric cannot differentiate between these two scenarios.
Participants also noted that the metric does not reflect whether the prescribed medication aligns with the resident’s preferences and addresses the resident’s symptom(s). Some caregivers shared that they preferred not to use medications until all other avenues had been exhausted. Caregivers also expressed their desire to balance their family member’s comfort achieved via getting medications with the compromised levels of alertness that can result from certain medications. In each of these cases, knowing that a resident received a prescription for a medication does not provide information on whether that medication aligned with the resident’s or caregiver’s preferences nor whether it sufficiently addressed the resident’s symptoms.
Applicability relates to the relevance and usefulness of applying the metric to assess end-of-life care.(23) Health-care providers thought they would use the metric at both the home and individual provider levels. At the LTC home level, health-care providers described using the metric at quarterly staff meetings to assess performance and gauge areas for improvement, similar to other LTC quality indicators. At the individual provider level, some health-care providers stated that they would compare their prescribing rates to the average and “high-performers” to learn how to improve their practice. In contrast, other health-care providers stated they would not use the metric as they perceived that they would be penalized if their prescribing rate for end-of-life medications was higher than the average. Importantly, health-care providers and caregivers thought the metric’s goal should be to improve the services provided to LTC residents (e.g., use of the metric as an educational tool), rather than a tool to be used for punitive purposes.
Health-care providers stated that to use the metric, they would need a defined prescribing range or threshold that indicates “good” practice. However, none of the participants could ascertain or estimate the right range or threshold to indicate quality end-of-life care. Interviewees said that, while they use medications to manage residents’ symptoms, they felt that a situation wherein 100% of LTC residents were prescribed an end-of-life symptom management medication before death would not be ideal. They shared instances where medication is not—and should not—be prescribed as some residents die suddenly, some do not experience symptoms which require medications, and in other circumstances, the medications do not align with the patient or caregivers’ preferences.
Family caregivers expressed that the metric does not reflect the residents’ or caregivers’ experience. For each caregiver, although their family member received an end-of-life symptom management medication, there were moments of great distress when medications were not started in a timely fashion or not given frequently enough, especially in the case of pro re nata (PRN) or “as needed” medications. As is, caregivers saw little value in using the metric as a tool to support decision-making in selecting an LTC home for their family member. Many other considerations (e.g., geography, friends’ experiences, staff with palliative care training) were more important in their decision-making than this metric.
Caregivers and health-care providers advocated for other metrics that included caregivers’ perspectives on residents’ end-of-life experiences. Participants suggested ways to collect these experiences (e.g., exit surveys), the types of questions that should be included (e.g., Do you feel your family member was comfortable at the end-of-life), and other metrics (e.g., evaluating the process of shared decision-making between caregivers and the medical team). However, some participants acknowledged the challenges in scaling these strategies, including the logistic challenges in obtaining caregiver experiences across multiple institutions across the province.
In this study, we interviewed LTC health-care providers and caregivers of deceased LTC residents to determine the acceptability and applicability of an end-of-life prescribing metric. This study identified three themes for considering this metric’s potential use and ability to assess end-of-life care within LTC. First, the metric can identify some aspects of end-of-life care but is not an absolute measure. Second, the metric can be used by health-care providers or LTC homes to compare their practice to others, but it is necessary to define and establish an acceptable range or threshold. Finally, the metric does not sufficiently reflect the caregiver’s experience, and caregivers offered suggestions for more meaningful metrics.
End-of-life care is complex and involves various types of care (e.g., spiritual, relational, mouth, eye, and skin care, medications) to address residents’ physical, psychological, social, spiritual, and practical needs. End-of-life care cannot be captured through a single global measure, but individual measures may reflect aspects of end-of-life care.
The proposed metric is only specific to whether a prescriber prescribes a subcutaneous end-of-life symptom management medication for a resident in the two weeks before their death. Using the Donabedian Framework(24) to categorize health-care indicators, resident health outcomes (e.g., pressure ulcers), processes within an LTC home (e.g., use of restraints), or the structure of LTC (e.g., staffing ratios; training), the proposed metric aligns with process indicators. Process indicators measure the program’s activities and outputs (direct products/deliverables of the activities), and together they indicate whether the program is implemented as planned.(24,25) Before a prescriber prescribes an end-of-life medication, LTC staff must correctly identify that residents are approaching the end of life and identify end-of-life symptoms, be comfortable in managing (prescribing and administering) end-of-life symptoms, and communicate effectively with families (e.g., how to manage symptoms in a way that aligns with the goals of care). These issues of identification, management, and communication at the end-of-life have been highlighted in previous studies exploring optimal end-of-life care in LTC.(26–30) The proposed metric may be a proxy for this process (identification, management, and communication of end-of-life) and indicate whether LTC homes and prescribers have processes to manage a resident’s end of life. We hypothesize that differences across these steps (e.g., identification, comfort, and communication) may contribute to differences in prescribing rates.
Nationally, Canada uses 14 LTC quality indicators.(31,32) Like these LTC quality indicators, our metric also uses administrative data, which reduces the operational burden on LTC staff to collect data. However, with the proposed metric and other indicators, it is difficult to capture resident-centred care only using only administrative data. Resident-centred care is respectful of, and responsive to, individual resident preferences, needs, and values, and ensures that resident values guide all clinical decisions.(21) Unfortunately, resident and caregiver values are collected through multiple avenues (e.g., a one-off clinical note or home-specific goals of care form either attached to a physical chart or integrated with the electronic medical record), if collected at all, making this information difficult to access on a systematic scale.(33) Like other quality indicators, LTC homes or prescribers could also use the metric to understand how their practice compares to others. However, before they can use the metric, we recommend defining a range or threshold of appropriate prescribing. Without such a range or threshold, the metric may be inconsistently interpreted. As reflected through the interviews, some health-care providers perceived high prescribing rates as the goal, albeit recognizing that the ideal prescribing rate is not 100%. Other providers thought they would be penalized if their prescribing rates were higher than average. We hypothesize that those who thought they would be penalized for high prescribing interpreted the metric similarly to commonly used metrics, such as measures of potentially inappropriate prescribing of antipsychotics in LTC, where a lower prescribing rate is the goal. Additionally, we recommend that decision-makers determine how they might want the indicator to be used, which can help guide determining a range or threshold.
Compared to existing indicators, this metric is specific to end-of-life (measured medication use during the last two weeks of life). Dying residents can experience symptoms that are distressing to them and their families. Therefore, comfort care (including medications to address these symptoms) is important to quality end-of-life care. In the preliminary quantitative study evaluating the metric, there was a two-fold difference in prescribing rates across Ontario’s LTC homes, indicating a large range in prescribing practice across Ontario.
There is an appetite to strengthen the delivery and evidence of palliative care in Canada. In 2017, the Government of Canada passed the Framework on Palliative Care in Canada Act (Bill C-277).(34) In its accompanying report, one of the five strategic objectives is to support health system quality improvement through enhanced data collection and research. Additionally, reports reflecting on the impact of the COVID-19 pandemic on LTC homes emphasize the need for end-of-life palliative care.(35) The proposed metric could be one way to measure and potentially improve end-of-life palliative care in LTC.
However, we would need to refine the metric further before it could be used across provinces. First, to further understand the appropriateness of the metric, we propose partnering with LTC homes to review medication charts to understand how often prescribed medications are administered. In such a partnership, we could also review advance care plans or goals of care forms to understand if the prescribed medications align with resident and caregiver preferences. Second, we must define a range or threshold to mark a “good” care standard. We would need to partner with LTC homes and staff to help define this standard.
Additional work is required to support the implementation of the refined metric. First, additional metrics should be developed and packaged together to create a more comprehensive assessment of end-of-life care. Most importantly, resources to support LTC staff, residents, and caregivers are required for LTC homes to have the opportunity, capability, and motivation to provide quality end-of-life care, including (but not exhaustive) how to identify an individual approaching end-of-life, and managing symptoms with medications appropriately.
Finally, future development of indicators needs to include the resident and caregiver perspective. Although there has been a consensus to involve individuals and their caregivers in indicator development, in practice, very few do.(36) One systematic review that assessed quality indicator development, regardless of sector, found limited indicators (n=11) included individuals or their caregivers.(36) Residents and caregivers (e.g., the resident is comfortable during the dying process) must select topics for future indicators. Specifically for end-of-life, residents and caregivers have reported that they most value quality communication with health-care providers (i.e., frequent, accessible, timely, clear, comprehensive, consistent, compassionate, and realistic) and shared decision-making about care decisions.(29,30) Individuals and caregivers are also guiding researchers in understanding the utility of indicators. This study evaluated the utility of this metric from a caregiver perspective—a novel approach in the existing literature.
Our study’s findings may have limited transferability to other jurisdictions due to Ontario’s organization, structure, and culture within LTC homes. Further, data collection occurred during the COVID-19 pandemic, when there was extensive strain on the LTC sector in Ontario and other areas. Our team had difficulty with data collection and had to expand our collection timeframe and sampling strategy to maximize the number of potential participants. It is possible that the few who agreed to participate were less affected by the pandemic (i.e., were from LTC homes with few to no outbreaks), and thus had more availability for, and interest in, participating. We cannot ascertain how the pandemic and its associated challenges may have influenced participants’ responses. Finally, of the health-care provider participants, the majority had previous palliative care training and a leadership position within their LTC home. These health-care provider participants may have different views on end-of-life prescribing and the potential use of the metric than other staff within the home.
In this study, we interviewed LTC health-care providers and caregivers of deceased LTC residents to determine the acceptability and applicability of the refinement of the end-of-life prescribing metric. The proposed metric captures a small aspect of end-of-life palliative care—whether end-of-life medications are prescribed. Participants deemed that the metric reflects whether LTC homes have processes to manage a resident’s end-of-life symptoms with medication. However, participants thought the metric could not provide a complete picture of end-of-life care and its quality.
We would like to thank Denyse Lynch who provided invaluable insight into her caregiving experience. DL was instrumental in the project’s development and analyses.
We have read and understood the Canadian Geriatrics Journal’s policy on conflicts of interest disclosure and declare there are none. Three of the authors of this paper had prior professional or personal relationships with four participants. To mitigate bias, interviewers did not interview participants with whom they had relationships. Additionally, nine authors helped develop the indicator. The indicator was used in the quantitative phase of the overarching research program.
This study received funding from the College of Family Physicians of Canada COVID-19 Pandemic Response and Impact Grant Program. The opinions, results and conclusions reported in this paper are those of the authors and are independent from the funding sources. PT is supported by PSI Graham Farquharson Knowledge Translation Fellowship. SHB receives an Academic Protected Time Award from the Department of Medicine, University of Ottawa, Ottawa, Canada. The funders had no influence in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
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The following three individuals conducted the interviewsa. Their characteristics reflect those at the time of the interviews.
Today we are going to be talking about your experiences in delivering end of life care in LTC, and specifically the prescribing of symptom management medications at the end of life. We recognize that this past year has been very difficult on all healthcare providers, and that LTC has been particularly hard hit. We want to get a better understanding of how EOL care is provided in your home, and how it changed during the pandemic
We appreciate that there are many components of end-of-life care. However, we are specifically looking at medications given at the end-of-life for symptom management. We are going to ask you questions about these medications.
[For Physicians]
[For RNs and RPNs]
It is often said that you can’t improve what you can’t measure. Quality indicators are things we can measure and help us assess how well a health care service is working.
We are proposing a new quality indicator to assess the delivery of end-of-life care provided at long-term care homes. The new quality indicator could help identify homes that need additional support for end-of-life care.
This new quality indicator will measure the percentage of residents in their last two weeks of life that are prescribed at least one symptom management medication – focusing on subcutaneous medications that are given when residents lose their ability to swallow near the end of life. We think this indicator is a proxy to palliative care delivery as these medications are prescribed only when a prescriber has thought about the end-of-life needs of residents. Unlike any other potential indicators of the quality of palliative care in LTC, the data required to measure this indicator is readily available and can be immediately used to identify homes and physicians with high and low rates of prescribing.
For this interview, we are going to refrain from using the name of your [insert relationship] to make it easier to de-identify the interview. We will instead be describing the person as [insert relationship].
There are many aspects to good end of life care. However, we are specifically looking at medications given at the end-of-life for symptom management. We are going to ask you questions about these medications.
It is often said that you can’t improve what you can’t measure. Quality indicators are things we can measure and help us assess how well a health care service is working.
We are interested in using a new quality indicator to identify long-term care homes that may need support delivering palliative care and end-of-life care. One measure we are exploring is the percentage of residents that are prescribed medicines to help manage symptoms during their last two weeks of life. For example, we can measure if a pain killer like morphine was prescribed in the final weeks of life. [Unlike any other indicators of palliative care, this data is readily available for all LTC residents and can be immediately used to identify homes and prescribers with high and low rates.]
Correspondence to: Rhiannon L. Roberts, Ottawa Hospital—Civic Campus, 1053 Carling Ave., Box 693, M-07 Admin Services Building, Ottawa ON K1Y 4E9, E-mail: rhroberts@ohri.ca
COPYRIGHT
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial No-Derivative license (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits unrestricted non-commercial use and distribution, provided the original work is properly cited.
Canadian Geriatrics Journal, Vol. 27, No. 1, MARCH 2024