Coming to a Hospital Near You : Fine-Tuning Predictive Demise

"In Canada, we don't like to talk about death and dying. We think patients have the right to their own information to tell them about what is going to happen to them."
"We still live in a paternalistic society where we don't think the patient can handle that information or don't think they should have this information."
"If you watch Netflix, it will tell you what Netflix thinks you like based on your previous choices. In health care, we are just figuring this out. These tools are to help patients make informed decisions."
"Too often,  you visit your doctor and your doctor has only [a] limited amount of time and limited information."
"We think patients have the right to know and seek out care that is appropriate to their needs. If a patient knows that they have a year to live, they should be receiving palliative care, supportive care, in order to stay at home."
"Clinicians don't do it enough, partly because we live in a death-denying society and partly because it is hard, especially if you don't have a terminal cancer diagnosis."
Dr. Peter Tanuseputro, investigator, Bruyere Research Institute, palliative care physician

So, then, if as a strong-minded individual with a positive outlook who has been given a diagnosis that includes the certainty that the dread disease you have been detected with will shorten your life much sooner than you might have thought conceivable, and you muster all the internal resources at your command to manage to defy the prognosis of an early death, this venture newly embarked upon by health care providers to assess and digitally calculate end-of-life certainty would identify you as an errant anomaly whose instinct would spurn the medical community's offer to know more precisely how long you have to live.

In the interests of conducting an aura of  'informed conversations' about death and all that it denotes to a family, researchers at a newly instituted National Centre for Individualized Health developed an algorithm predicting the months or years on the closure of their patients' lives and how best to treat those patients to ensure whatever is left to them represents quality of care, dependent on the results of this new predictive protocol. Dr. Tanuseptro who himself treats his palliative patients with house calls feels many elderly patients would wish to know exactly the time when they, in the vernacular would 'cash in their chips'.

Everyone, he asserts with the confidence of someone convinced he is serving the public interest, is deserving of the enabling courtesy to access such information which after all is based on their very own health information along with data that has been collected through the universal health care system, across the Province of Ontario The end-of-life calculator's results has the potential of leading care-givers to provide treatment seen as more appropriate to the patient's condition, itself leading to greater numbers of people taking benefit from palliative care services.

Data recently released from the Canadian Institute for Health Information indicates that 15 percent only of Canadians currently are recipients of palliative care during their end-of-life period of languishing, awaiting death. Among that 15 percent, stressed Dr. Tanuseputro, a substantial number receive that level of personal care at a too-late period in their decline toward death.

So RESPECT, the acronym by which the predictive algorithm is known (risk Evaluation for Support Predictions for Elder-life in the Community Tool for the End of Life), is used to calculate -- based on a series of 24 questions relating to the type of disease a patient has and how difficult they find it to care for themselves -- how long they have left to live. Ontario's health system's data was collected to help develop the algorithm.

RESPECT is being pilot-tested in the Windsor-Essex region as a tool to aid people whose condition is tenuous, to understand whether they might benefit from palliative care. With the use of big data, RESPECT is among a series of algorithms meant to help older people to reach a finer understanding whether palliative care would be of benefit to them. Needless to say, if the medical community feels that this new type of 'clarification' represents an improvement over the status quo that in itself tends to propel people under duress toward acceptance.

When the project is fully completed for release to the public the plan is to present it as an accessible tool to be used by individuals and family members on the projectbiglife.ca website. And that's when people will be able to ask themselves the critical questions: Do I really want to know? Of course, the medical community has already answered the question. But this is not a project to which everyone must sign on to, since it is as yet voluntary.

Researchers are in the throes of developing tools to help calculate how long it will take before an individual is poised to retreat to a nursing home, as well as their imminent risk of hospitalization. These predictive tools are viewed as assists to preventive measures that may help people remain longer in their own homes in some instances; alternately, to obtain care that seems most appropriate to their current condition.

Abstract

Introduction Older adults living in the community often have multiple, chronic conditions and functional impairments. A challenge for healthcare providers working in the community is the lack of a predictive tool that can be applied to the broad spectrum of mortality risks observed and may be used to inform care planning.

Objective To predict survival time for older adults in the home care setting. The final mortality risk algorithm will be implemented as a web-based calculator that can be used by older adults needing care and by their caregivers.

Design Open cohort study using the Resident Assessment Instrument for Home Care (RAI-HC) data in Ontario, Canada, from 1 January 2007 to 31 December 2013.

Participants The derivation cohort will consist of ∼437 000 older adults who had an RAI-HC assessment between 1 January 2007 and 31 December 2012. A split sample validation cohort will include ∼122 000 older adults with an RAI-HC assessment between 1 January and 31 December 2013.

Main outcome measures Predicted survival from the time of an RAI-HC assessment. All deaths (n≈245 000) will be ascertained through linkage to a population-based registry that is maintained by the Ministry of Health in Ontario.

Statistical analysis Proportional hazards regression will be estimated after assessment of assumptions. Predictors will include sociodemographic factors, social support, health conditions, functional status, cognition, symptoms of decline and prior healthcare use. Model performance will be evaluated for 6-month and 12-month predicted risks, including measures of calibration (eg, calibration plots) and discrimination (eg, c-statistics). The final algorithm will use combined development and validation data.

Ethics and dissemination Research ethics approval has been granted by the Sunnybrook Health Sciences Centre Review Board. Findings will be disseminated through presentations at conferences and in peer-reviewed journals.

Palliative care

Protocol

Algorithm for predicting death among older adults in the home care setting: study protocol for the Risk Evaluation for Support: Predictions for Elder-life in the Community Tool (RESPECT) BMJOpen