Removing Data Bias from AI and Machine Learning Tools in Healthcare
Healthcare is rapidly growing and evolving to become a data science, using data to make decisions and guide clinical care at every opportunity.
Healthcare is rapidly growing and evolving to become a data science, using data to make decisions and guide clinical care at every opportunity.
Healthcare has a customer experience problem. What if technology could solve this, and ensure that individuals consistently receive the right care for them, at the right place and at the right time?
The environment a person lives in, their socioeconomic status, lifestyle, wealth and cultural/ethnic background all affect that person's health status in far more significant ways than was previously understood.
Efficiently enabling clinicians to provide the right care, to the right patient, at the right time and in the right place
A global pandemic on health systems
Improving Healthcare Outcomes and Containing Costs with Machine Learning and Virtual Care
Data from any connected healthcare entity, such as hospitals, clinics, doctors, pharmacies and laboratories, helps care teams provide more informed recommendations based on the longitudinal healthcare history of the patient.
The healthcare system is undergoing a transformation to a value-based funding model, which has concrete benefits for all stakeholders, including providers and patients.
In the community-based model of care, healthcare professionals treat their patients outside of the traditional boundaries of healthcare facilities, and care coordinators interact with patients and multiple provider groups over the phone or in their patients’ homes.