AI and machine learning make sense of healthcare data →

By Lia Novotny | athenahealth | January 15, 2019

The healthcare industry has never produced or had access to more information – but how do physicians, patients, and communities make sense of all the data in a way that leads to better outcomes and improved health? Allen Gee, M.D., a neurologist at Frontier NeuroHealth in Cody, Wyoming, and a pioneer in technology adoption, sat down with athenaInsight to discuss how medicine can solve the challenge of information overload and put data in the service of better patient care.

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Healthcare Leaders Say the Next Phase of Connectivity Is a Transition From Data Collection to Information Curation →

By Chris Hayhurst | athenahealth | June 14, 2022

One possibility for increasing patient-provider communication without overloading clinicians, Gee said, is to better leverage wearable devices and software solutions designed to send out automated behavioral reminders. These tools allow providers to connect with patients without necessarily increasing their clinical workloads, he explains. “It’s a way to give patients medical knowledge and wisdom so they can do more for themselves.”

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Democratizing Resilient Aging Behavior Code & AI Nudge Theory Governance

WHILL | Oct 2016

Population aging is one of the most important social trends of the 21st century and in the United States, the number of people aged ≥65 is projected to increase by nearly 50% in the next 15 years. Most biomedical and public health efforts have focused on reducing harmful risk factors when targeting chronic disease—an approach that has contributed greatly to prevention and treatment programs. However, evidence suggests that the number of years lost to disability is increasing and historic gains we have made in life expectancy are eroding, and even reversing in some groups. As our society ages and grapples with these issues, expanding the focus to include resilience, as well as psychosocial assets in our prevention and treatment programs might help inform the multidisciplinary response effort we need. Traditional medical practices and relationships are changing given the widespread adoption of AI-driven technologies across the various domains of health and healthcare. In many cases, these new technologies are not specific to the field of healthcare. Still, they are existent, ubiquitous, and commercially available systems upskilled to integrate these novel care practices. Given the widespread adoption, coupled with the dramatic changes in practices, new ethical and social issues emerge due to how these systems nudge users into making decisions and changing behaviors. These AI-driven systems pose particular ethical challenges with regard to nudging. Nudging is a continually growing practice within the domain of health care, technology, and their intersection. However, given the potentially deleterious consequences of recalcitrant nudging, as well as its potential boons if employed responsibly, it makes sense that responsible innovation of AI-driven nudging technologies in the field of healthcare to be aligned with a design approach that is principled on similar commitments to avoid harm and actively contribute to doing good.

The effects of AI-driven nudging technologies within the healthcare field are thus not merely visible on an individual level; they are equally effective and persistent on a collective level and need a justification on the values they underpin and promote. Digitization of medicine brings with it a host of boons such as increased efficiency and accessibility. However, with these benefits may also emerge public concerns due to the specific capabilities of AI-driven systems and the possible sources of AI influences on stakeholders and environments. The WHILL, Linux Foundation Public Health, and Secours.io are exploring how the democratization of resilient aging code and nudge theory governance can successfully evolve within a foundation of digital ethics and governance protocols.