Using AI-Powered Nutritional Analytics to Improve Outcomes and Efficiencies in Long-Term Care
Improving patient nutrition and reducing food waste with AI.
Project Overview
Updated June 11, 2024.
The Problem
Worldwide, malnutrition affects 30-60% of older adults living in long-term care (LTC).1 Despite food also being the second highest cost in LTC, documenting and analyzing dietary intake and detecting early malnutrition are shockingly underdeveloped. Staff often lack the time and tools to objectively and accurately assess the quantity and types of food consumed, further limiting appropriate dietician guidance.
Good nutrition is paramount for maintaining patient health and preventing frailty, weight loss and other nutritional deficiencies. However, without accurate information, nutritional assessments are limited creating risk to residents.
How We Are Solving It
This project will incorporate RxFood’s clinically proven AI-powered nutritional assessment technology with PointClickCare’s leading healthcare technology platform for LTC to improve patient nutrition and reduce food waste. The consortium will pilot the solution in Partners Community Health’s Wellbrook Place Long Term Care Homes in Mississauga, Ontario, with additional collaboration from the Institute for Better Health at Trillium Health Partners to evaluate the potential of the solution for acute care.
User functionality will be for LTC staff to simply take a photo of food trays using tablets or smartphones after a resident/patient is done eating. RxFood’s AI-powered technology will then identify the contents of the tray and estimate the volume of each food item remaining, how much was consumed, and the corresponding caloric and nutritional value. The output is a nutritional assessment report much like a report that someone would get after having blood work done.
The resulting nutritional analysis will be incorporated into the resident/patient’s EHR for ongoing monitoring and to better support proactive dietitian assessment and recommendations. Clinical flags will also be generated to provide earlier warnings on potential frailty that can precede significant weight loss, frailty, or other negative clinical outcomes. In addition to assisting LTC facilities in estimating actual food consumption for cost and waste management, RxFood’s ability to detect ethnic foods will support the increasing diversity of populations being supported by LTC.
This project’s potential to concurrently improve patient health, manage costs in LTC facilities and reduce systemic food waste represents a multi-faceted opportunity of leveraging AI in health care settings.
