
@ShahidNShah
The behavioral health landscape faces several significant challenges, primarily stemming from a severe shortage of providers and increasing demand for services. As has been seen in recent years, there's been a surge in behavioral health needs across all demographics.This mismatch between supply and demand has led to long wait times, difficulty accessing care, and, in some cases, patients going without necessary treatment.Andy Flanagan is CEO of Iris Telehealth, a telepsychiatry technology and services provider. He holds a Master of Science in Health Informatics from the Feinberg School of Medicine at Northwestern University. His prior experience includes being a three-time CEO, as well as founding an SaaS company and holding senior-level positions at Siemens Healthcare, SAP and Xerox.
AI risk modeling in behavioral health involves analyzing a wide range of patient data to assess clinical urgency and care needs, including factors such as previous diagnoses, medication history, frequency of healthcare utilization, social determinants of health, and even real-time data from wearable devices or patient-reported outcomes.AI can streamline the entire virtual care workflow – from patient intake to follow-up care coordination – allowing providers to focus more on direct patient care and potentially see more patients in a given time frame.AI-driven predictive analytics identify trends in patient demand, treatment outcomes and operational metrics to help guide strategic planning, resource allocation and service expansion. Telehealth providers could leverage this capability to identify underserved markets or optimal times to offer certain services, leading to increased market share and revenue growth
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