Worldwide Lead @ Microsoft for Startups | Driving Digital Health Innovation | Speaker | Author
Check out this insightful interview with Brian Hasselfeld, MD, from Johns Hopkins Medicine . Some key takeaways: 💡 ". . . technology has not yet done the thing that technology needs to do in healthcare, the thing it's done across many other industries, across the economy – inject productivity and efficiency gains to help bring into balance all of the demand for healthcare from our patients and the supply we have to offer, which arguably has been relatively fixed." 💡"If I could have a system, know the notes of your chart and understand what's been said about blood pressure, what's been said about weight, goals, what conditions you have, what medications you're on, and make that a precise layer of intelligence around that incoming data, such that we don't reproduce the inpatient alarm fatigue that already exists on the inpatient side, then I could take that to exponential scale on the outpatient side." Brad Holloman Dan Smith Mary Beth Chalk Derek Haynes #Healthcare #longitudinaldata #patientdata #innovation #AIinHealthcare #HealthcareonLinkedIn https://lnkd.in/e_NpCVEE
James Case
3mo
Great article Sally Ann Frank. There’s a lot of great insight in here about how AI can be used to enhance patient care and enhance the experience that our clinicans have in treating those patients.
HR & Marketing Manager at PangaeaData.AI
3moThank you for sharing Sally Ann Frank! Dr Brian Hasselfeld, MD makes some great points. It is critical for healthcare to utilize AI to not only improve patient outcomes earlier, but also reduce the healthcare burden on clinicians. Pangaea Data's product platform applies AI based on clinical guidelines to mimic a clinicians manual review of patient records (which currently takes over 40% of their workday) to find more untreated patients for 7,000 conditions. For example, this has demonstrated to find 6x more undiagnosed and miscoded cachectic cancer patients, COPD and at-risk CKD patients compared to ICD or generic NLP-based approaches. Being able to do so without the need for transacting data from the healthcare provider’s secure environment and ensuring zero disruption for clinicians and IT teams which is key for scalability and adoption.