TORONTO, ON – Oct. 21st, 2015: AlayaCare, a home healthcare software company for community care providers, and We Care, a home health care provider that is part of CBI Health Group, have collaborated and released a white paper that applies machine learning to clinical data to help reduce hospital readmissions and emergency room visits by predicting negative health events from patient remote monitoring data. The study highlights the potential positive impact of applying machine learning powered remote patient monitoring to the home health care industry.
Regarding the release of the white paper, Jonathan Vallee, the Director of AlayaLabs (the research and development arm of AlayaCare software) states, “The transformational potential of machine learning in home healthcare is very promising. With the help of We Care, we have the ability to improve patient outcomes by analyzing incoming patient vitals and referencing against We Care data. This means we can predict negative health events [e.g. hospital readmissions & ER visits] with tremendous accuracy. This white paper is just the beginning—we’re taking home healthcare software to the next level.”
Anthony Milonas, Chief Operating Officer of Home Health with CBI Health Group goes on to say “With increasing demands on the healthcare system and constrained resources, providers like We Care need to find ways to improve the efficiency of home care services. Combining the clinical judgement of our healthcare professionals with the information provided by our remote monitoring service already improves client outcomes and our ability to serve remote communities. By adding machine learning algorithms with predictive ability, we can reduce negative health events even further. This technology has the potential to dramatically change home healthcare”.
As more data becomes available, algorithms will be able to learn more complex patterns and continuously improve their predictions. Home health care is an underserved market, and the hope is that the We Care/AlayaCare relationship will help establish the required foundation for better technologies to transform the industry.
The research revealed machine learning could improve event predictions by 11% while reducing over-diagnosis by 54%. Moreover, machine learning in combination with ‘Big Data’ can deliver the following capabilities:
- Risk scoring, which informs and provides insight to clinicians of possible adverse events such as falls, episodes, events and hospitalization (emergency) visits.
- More accurate prediction of events.
- Reduction of over diagnoses.
- Patients can remain at home longer with machine learning.
Download the AlayaCare/We Care machine learning white paper here: Alayacare / We Care Machine Learning White Paper.
The white paper marks the start of this flourishing partnership as We Care plans to launch the Clinical Documentation module of the AlayaCare software.
AlayaCare is a provider of revolutionary cloud-based home healthcare software. With Clinical Documentation, Home Health Scheduling, Client and Family Portals, Remote Patient Monitoring and Telehealth, Electronic Visit Verification and Nurse Schedule App, AlayaCare offers a platform for agencies to propel towards innovation and home care of the future.
We Care Home Health Services is a leading national provider of home healthcare and support services and is part of the CBI Health Group (CBI) network. Founded in 1974, CBI employs almost 10,000 clinical and support staff that deliver comprehensive healthcare services through more than 225 facilities. Our services include: community and hospital based rehabilitation centres, home health, neurodevelopmental treatment, assessments and medical services on behalf of individuals, third party funders and governments. Our purpose is to improve the health of Canadians by shaping standards and driving innovation in community care. For more information, visit www.CBI.ca.