On this episode of Managed Care Cast, we interview the lead author of a paper in the Health IT issue of The American Journal of Managed Care.
In recent years, predictive models in medicine have become increasingly popular what with the continued integration of artificial intelligence and data technology into health care. However, these models can carry the risk of bias depending on which individuals make up the data sets.
The close relationship between health care and technology also raises a myriad of questions when it comes to regulation, accountability, and model implementation.
In this month’s Health Information Technology special issue of The American Journal of Managed Care®, Paige Nong, a PhD candidate in public health at the University of Michigan, and colleagues present research on facilitating informed decision-making and communicating equity issues when integrating predictive models into care.
On this episode of Managed Care Cast, Nong outlines how the researchers carried out their study, the ethical challenges of combining computer science with health, and next steps for combatting bias in predictive models.
Listen above or through one of these podcast services:
Disparities in Telehealth Access Undermine Adoption Among Patients With Schizophrenia
January 16th 2025The COVID-19 pandemic accelerated the widespread adoption of telemental health care, and new research indicates significant racial and ethnic disparities in access to this technology among Medicaid beneficiaries with schizophrenia.
Read More
Study Suggests Postdischarge Care Needs Targeted, Multifaceted Approaches
January 15th 2025The findings challenge the effectiveness of these widely used transitional care interventions and suggest a need for more targeted, multifaceted approaches to address the needs of higher-risk patients.
Read More