Closing the Mental Health Access Gap Through Novel Analytics

Depression and anxiety are associated with substantial morbidity, including physical deterioration. Connecting individuals to timely care improves outcomes. Unfortunately, significant gaps remain between the demand for behavioral healthcare and the supply of care. Further, estimates of demand are based on retrospective and/or non-localized measures, which impedes planning. This poses an opportunity to rethink how to close this gap. Health systems are better positioned than ever to do so, given novel technologies, data, and community integration. By developing more localized, real-time models of depression and anxiety demand and healthcare supply, health systems can better prioritize resource deployment and partnerships to proactively meet patient needs.