Factoring in Bio-Psycho-Social Factors to Improve Patient Care Outcomes: A Conversation with Gretchen Alkema (November 4th)
While it appears obvious a person's health status is directly related to their life circumstances the health care industry has been slow to recognize an individual's bio-psycho-social factors or characteristics in planning and delivering an individual's care. This critcism is typically phrased as clinicians being over attentive to the "patient" and under attentive to the "person". For various reasons having in part to do with utilization/cost, reimbursement and population health concerns this is changing. That is the health care industry is developing a greater appreciation and more sophisticated understanding of the non medical predictors of health care risk.
During this 21 minute interview Dr. Alkema discusses why the health care industry has been slow to adopt socioeconomic factors in care planning and delivery, non-medical factors that correlate with higher care utilization, how these factors or characteristics can be used for predictive purposes and related related issues.
Dr. Gretchen Alkema currently serves as Vice President of Policy and Communications for The SCAN Foundation. Prior to joining SCAN Dr. Alkema was the 2008-09 John Heinz Health and Aging Policy Fellow serving in the office of Sen. Blanche Lincoln. Dr. Alkema earned her PhD at the University of Southern California’s Davis School of Gerontology and and completed her post-doctoral training at the VA Greater Los Angeles Health Services Research and Development Center of Excellence. Her academic research focused on evaluating innovative models of chronic care management and translating effective models into practice. She is a Licensed Clinical Social Worker and has practiced in government and non-profit settings including community mental health, care management, adult day health care, residential care and post-acute rehabilitation.
Listeners will recall in August 2013 Dr. Alkema discussed the relationship between Medicare utilization and cost and beneficiary (declining) functional status.
For more on predictive analytics related to high-risk Medicare beneficiaries see: http://www.thescanfoundation.org/sites/thescanfoundation.org/files/identifying_high_cost_benefits_fact_sheet_1_1.pdf