How long will a loved one live? It’s difficult to hear, but harder not to know

Even for an experienced health-care professional, estimating the life expectancy of a patient with a serious illness is challenging. (Shutterstock)

Planning for the future is difficult for people living with a life-limiting illness. Clinicians, based on their experience, can offer broad estimates of survival — in days to weeks, weeks to months, or months to years. However, patients and their care partners often want greater precision when arranging or making decisions about their care.

An accurate prediction of survival can enable earlier conversations about preferences and wishes at the end of life, and earlier introduction of palliative care.

However, even for an experienced clinician, estimating the life expectancy of a patient with a serious illness is challenging. It requires large amounts of data and an understanding of the relationship between the patient’s baseline health, the complexity of their medical condition and how they respond to or progress with treatment. This is where predictive algorithms could help.

A tool for timely conversations and planning

RESPECT (Risk Evaluation for Support: Predictions for Elder life in their Communities Tool) is a risk communication tool powered by prediction algorithms that estimate individuals’ survival — that is, how long someone will live. It was developed by the Project Big Life Research Team and validated using health-care data collected on nearly one million older adults who received home and community care or nursing home care in Ontario.

RESPECT is intended to help people plan for palliative and end-of-life care.

RESPECT was designed with patients’ information needs in mind, and with the intention of empowering patients and their care partners. By providing patients with data on the survival and experiences of other individuals who had similar disease journeys, the tool can help patients understand their own illness trajectory, have earlier conversations about their preferences and wishes, and advocate for the support they need.

A tool for patients, care partners and clinicians

RESPECT launched publicly on ProjectBigLife.ca in July 2021. ProjectBigLife.ca is home to several health calculators developed by the research team as a means of translating data and evidence into tools that can help Canadians think about their health and plan for their care.

Using the responses to 17 questions about their health and ability to care for themselves, RESPECT provides an estimate of a person’s survival based on information gathered on people who have similar characteristics. Older adults, their care partners and health care professionals who are uncertain about the life expectancy of someone living with a critical illness can use the calculator to gain a better understanding of their decline.

Beyond life expectancy, RESPECT reports measures of functional decline — for example, whether the patient is able to get around their house and engage in activities of daily living, like bathing and cooking, without any assistance.

A patient can use this information to discuss their care needs with their care partners and health-care providers. Similarly, health-care providers can use this tool to discuss with their patient what can be expected as the patient approaches the end of life, and plan for the supports that their patient may need.

RESPECT is also actively used in Ontario’s retirement homes and nursing homes. Many residents in these settings have a life expectancy of less than two years. Earlier conversations about the older person’s goals and wishes for their remaining life can enable the care team to provide the best quality of life and care for the individuals under their care.

Sustainable infrastructure

One of the goals of RESPECT is to provide sustainable infrastructure to study, learn and improve how we use predictive algorithms for end-of-life care.

Despite the benefits that are emerging from the early uses of RESPECT, many questions remain about when and how it can be most appropriately used. For example, poor numerical literacy — that is, a person’s understanding of numbers, mathematics and statistics — could lead to misinterpreting the estimate provided by RESPECT. While the resources supporting RESPECT were co-developed with patients and their care partners, more research is still needed to reduce such potential harms.

To ensure we optimize the benefits that can be gained from prediction algorithms like RESPECT, clinical epidemiologists Douglas Manuel and Justin Presseau, along with the co-authors of this article, have created the RESPECT Learning Health System — a network of care partners, researchers and health-care professionals collaborating to address these challenges. We combine research and practice to sustainably study, learn and improve end-of-life care and experience through predictive algorithms.

Identification is just the first step

Only 58 per cent of people who die in Canada receive some form of palliative care prior to death. Few (13 per cent) are able to die at home with the support of palliative home care.

In deepening our understanding of frailty and decline, RESPECT may help clinicians, patients and their care partners be prepared for a poor prognosis and help develop a personalized plan for their care.

However, to improve end-of-life care delivery in Canada and enable Canadians to die with dignity, more investment is still needed within our formal health-care system to meet the need of individuals at the end of life.

Lysanne Lessard receives funding from Canadian Institutes of Health Research for research related to the RESPECT Learning Health System.

Lessard is a member of the University of Ottawa's LIFE Research Institute.

Amy T. Hsu receives funding from the Canadian Institutes of Health Research for research related to the RESPECT Calculator.

Peter Tanuseputro receives funding from the Canadian Institutes of Health Research for research related to the RESPECT calculator.

Sampath Bemgal does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.