Predict End of Life

Patients in the last days of life can experience unrelieved physical suffering as well as significant emotional, spiritual, and social distress. Unfortunately, they are frequently not recognized as dying. More than one in three patients that prefer palliative care do not receive it, and these patients incur 1.4x the costs of patients who receive end-of-life care consistent with their wishes.

Size of the Problem

• More than one in three end-of-life stage patients that prefer palliative care do not receive it (3).
• 20% of all Medicare spending occurs in the last 12 months of life (5).
• Roughly 70% of adults do not have an advance directive on record (7).
• $365 Billion was spent on end-of-life care in 2018 (6).

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Patients in the last days of life can experience unrelieved physical suffering as well as significant emotional, spiritual, and social distress. Unfortunately, defining when this phase begins is not always straightforward. Patients at the end of life are frequently not recognized as dying. As a result, suffering may not be properly appreciated or managed, and the patient’s overall condition may even be exacerbated by the continuation of standard medical care. Despite the fact that more than 80% of Medicare beneficiaries aged 65 and over would want to die at home, in 2013, one-third of deaths among older adults occurred in the hospital (1). Even among terminally ill patients, fewer than 50% have an advance directive in their medical record, and between 65% and 76% of practitioners whose patients had an advance directive were not aware that it existed (2).

This disparity in care preference and actual treatment can lead to unnecessary suffering and dramatic economic costs. More than one in three patients that prefer palliative care do not receive it, and these patients incur 1.4 times the costs of patients who receive end-of-life care consistent with their wishes (3). In 2014, inpatient hospital spending among decedents was seven times higher than among survivors on average, and in 2015, decedents accounted for over 20% of all Medicare spending (4,5).

Organizations must ensure patients the quality of life they desire in their final days, and AI-based models are ideal for identifying patients at high risk of mortality in the coming year. Predictive analytics can empower practitioners with the insights they need to start difficult conversations about beginning palliative care and can ultimately help to identify and support the best possible outcome for patients and their families.

• Electronic Health Records: EHR data with comprehensive patient histories of vital signs and symptoms, problem lists and chief complaints, tests results, diagnoses and procedures, and prescriptions.
• Medical Claims: Data extracted from health insurance medical claims with details about dates and place of service, diagnosis codes, key procedures, use of medical equipment, and provider specialties.
• Social Needs Assessments: Self-reported data that identify an individual's specific needs and the acute social and economic challenges they are experiencing.