AHRQ convenes national web conferences to highlight recent developments and disseminate the impact of innovative digital healthcare research. In 2020, the AHRQ Digital Healthcare Research Program convened two conferences.
Go to the Events page to see the most recent Health IT Web Conferences.
A National Web Conference on the Role of Telehealth to Increase Access to Care and Improve Healthcare Quality
Participants learned how telehealth can increase access to care and improve healthcare quality in real-world settings, and how evidence supports the use of telehealth during public health emergencies.
The June 9, 2020, web conference featured the following:
- Dr. Glen Xiong presented study results on the effectiveness of using telehealth for psychiatric services for people with mental illness who live in skilled nursing facilities. The team found that two modalities of virtual psychiatric consultations for these patients—real-time video conferencing, universally known as synchronous telepsychiatry (STP) and video-recorded interviews later sent to a psychiatrist for review and guidance—improved outcomes.
- Dr. Elizabeth D. Ferucci showcased study results where she compared disease symptoms and the quality of care for patients who receive rheumatology care through telemedicine to patients who receive only in-person rheumatology care. The team found that telemedicine and in-person appointments provide comparable care, which is great news when access to care is an issue for patients.
- Dr. Kenneth McConnochie discussed the Health-e-Access (HeA) telemedicine network in Rochester, NY, used to manage childhood illness, highlighting the value of this type of care to the community. In cases where children may need to be seen quickly, use of the HeA telemedicine network allows children to be seen quicker than an in-person visit as well as receive medication and antibiotics faster.
A National Web Conference on Applying Advanced Analytics in Clinical Care
Participants gained knowledge on how machine learning and natural language processing techniques can effectively analyze unstructured data and process information from multiple sources that identify patients who would benefit from treatments or interventions.
The October 14, 2020, web conference, featured the following research:
- Dr. Alexander Turchin highlighted research that showed inclusion of information from free-text notes into risk-of-death prediction models significantly improves the ability to predict the probability of death. This research reflects the potential for clinicians to incorporate life expectancy into shared decision making about medical interventions.
- Dr. Judith Dexheimer’s research showed that an EHR-integrated machine learning algorithm can aid clinicians in identifying patients with epilepsy who could benefit from surgery. Use of this algorithm has the potential to decrease time from diagnosis to surgical evaluation, with a resulting improvement in quality of life for patients and caregivers, reduction in suffering, and a decrease in treatment cost.
- Dr. Michael Avidan presented work on developing and evaluating an air traffic control-like command center for operating rooms. The research relied on data mining and machine learning to forecast adverse patient outcomes. Dr. Avidan found that these algorithms can predict postoperative adverse outcomes with a high degree of accuracy, leading to better outcomes for the highest-risk patients.
Access the October 2020 Web Conference Materials and Recording