The article from the Harvard Law School Forum on Corporate Governance, authored by Subodh Mishra of Institutional Shareholder Services Inc., discusses the emerging trend of AI governance in corporate settings, particularly in the S&P 500 companies. It highlights that only 15% of these companies disclosed some form of board oversight on AI, mainly within the information technology sector. With AI becoming increasingly material to business operations, there is a growing call for companies to not only reveal board members’ skills and oversight roles regarding AI but to also enhance these disclosures. The analysis reflects on the need for more comprehensive AI oversight mechanisms as investors and regulatory bodies begin to demand better management of AI-related risks and opportunities.

AI Governance Appears on Corporate Radar publication

The article from Health Affairs discusses the rising use of telemedicine since the COVID-19 pandemic, focusing on its effects on healthcare utilization, spending, and quality from 2019 to 2022. By comparing patient data from health systems with varying levels of telemedicine adoption, the study notes modest increases in visit frequencies and medication adherence, alongside a decline in emergency department visits for systems with higher telemedicine use. Despite these benefits, the associated increase in overall healthcare spending was a significant finding, suggesting that while telemedicine enhanced some aspects of patient care, it also led to higher costs. This analysis informs policymakers on the continued financial implications of telemedicine and underscores the need for further research to optimize its benefits while managing expenses.

The Impact Of Telemedicine On Utilization, Spending, And Quality, 2019–22 | Health Affairs Journal publication

Spencer Dorn discusses the complexity of evaluating healthcare AI, comparing it to the rigor of drug trials, and the need for similarly meticulous standards in AI measures. These discussions unmask the often misleading and overly simplistic metrics used to gauge AI effectiveness, highlighting a significant gap in meaningful, generalizable, and cost-effective AI evaluation within healthcare settings. As professionals grapple with these challenges, the article stresses the crucial distinction between trivial technological advancements and meaningful medical outcomes, emphasizing the high stakes involved in healthcare compared to other AI applications.

Spencer Dorn on LinkedIn: A.I. Has a Measurement Problem Publication

In the NEJM Catalyst event, "New Models, Measures & Money: Care Delivery Innovation," Amy Compton-Phillips, MD, discusses the urgent need to address the growing complexity in health care delivery which has led to widespread dissatisfaction among patients and providers alike. Highlighting the failure of current tactical solutions, Compton-Phillips advocates for a strategic overhaul based on Richard Rumelt’s approach, focusing on diagnosing the issue, establishing a guiding policy, and implementing coherent actions. She proposes a simplified health care model encapsulated in three key strategies—new models of care that prioritize human-centered and coordinated approaches, new measures that focus on the outcomes rather than inputs of care, and new financial models that incentivize desired outcomes. These strategies aim to make comprehensive, compassionate care both affordable and accessible to all, suggesting a significant shift towards simplification in the health care industry.

A Portfolio of Tactics to Simplify Health Care | NEJM Catalyst NEJM Catalyst