Health & Technology Journalism: AI-Assisted Care
Skills Demonstrated: Translating complex healthcare technology for general audiences, human-centered reporting on public health and AI, editorial clarity under tight word counts
Deliverable: Short-form explanatory journalism for a national health-technology publication.
Prescription medication adherence is a costly problem. The Centers for Disease Control and Prevention (CDC) notes “the costs of nonadherence to prescribed medications are high and place significant financial strains on the health care system as a whole.” For example, the CDC cites a study showing that higher adherence to prescribed medications lowered healthcare costs among people treated for congestive heart failure by an estimated $7,800 per person annually. For those managing blood pressure, the cost is around $3,900 each year, and about $1,250 annually for those controlling high cholesterol.
Employing AI in Underserved Communities
This problem is magnified in underserved areas—and becomes critical when a public health disease like tuberculosis (TB) is involved. TB treatment often requires Directly Observed Therapy (DOT), in which healthcare professionals observe patients taking their medications and monitor treatment response.TB disproportionately affects underserved communities. CDC data shows that about 88% of the TB cases reported in America occur among ethnic and racial minority groups.
Remote Care Via Video Devices
To reduce the number of healthcare professionals needed for in-person DOT, the CDC recommends telehealth technology with video-enabled devices that facilitate remote interactions between patients and healthcare workers. AI may help reduce that burden on healthcare workers even further. A recent study led by researchers at the University of Georgia shows that artificial intelligence can evaluate patient-submitted videos to verify medication adherence.
The study looked at TB treatment in low-resource communities in Uganda, where a program dubbed DOT Selfie generates thousands of videos of people taking their medications. But instead of healthcare workers watching all the videos, the study tasked AI-enabled programs with reviewing the videos.The best of the four AI models identified patients taking their medication 85% of the time, a percentage comparable to humans performing the same task.
Tech With a Human Touch
Though humans aren’t left out of the process entirely. University of Georgia researcher Juliet Sekandi says, “AI is really an accelerator of that process because then a nurse will not be worried that they have to watch all the 10,000 videos, but maybe watch only a few that need verification—say, 100 out of 10,000.” While the study only considered AI-assisted DOT among TB patients, it’s easy to see how this approach could extend to other treatments that rely on observed medication adherence.