Using machine learning to improve end-of-life care for advanced cancer patients
Patients with incurable advanced cancer should have access to high-value, compassionate care with a focus on improving quality of life, as aggressive treatments may have limited ability to meaningfully extend life at this stage and may cause more harm than help.
Can technology solutions improve end-of-life care to avoid unplanned hospitalizations and maximize use of supportive care? To seek out answers, my colleagues and I at Hitachi R&D partnered with the University of Utah and Huntsman Cancer Institute. Our diverse, interprofessional team of experts included an oncologist and palliative care physician, a clinical pharmacist, nursing, and data scientists. We started by mapping out the clinical process around care nearing the end of life, trying to understand how machine learning could improve patient support at this stage.
