Aspen Policy Academy

Projects on Improving Healthcare and Health Data Privacy

  • Article Published January 31, 2022

San Francisco, CA – It is our pleasure to introduce the first set of projects from our 2021 Fellowship class.

The projects, focused on Improving Healthcare and Health Data Privacy, propose creative solutions for prior authorization delays, insecure medical devices, and improving healthcare procurement. We released the projects today at our webinar, and you can view the recording here

We invite you to read about the projects below and to check them out on the projects page of our website. Please also join us at our next webinar, February 15 at 9am PT to see the second set of our projects, focused on Empowering Marginalized Workers and Voters.

Improving Medication Access with Better Prior Authorization

by Lucy He and Christine Keung

Prior authorization (PA) refers to the process of getting an insurer’s approval before a physician provides a treatment, and can dangerously delay access to medication and care. Real-time benefit tools (RTBTs), a software product physicians consult before finalizing a prescription, can decrease the burden of PAs or help physicians avoid them altogether. This project proposes that the the New York State Department of Health (DOH) adopt a statewide standard to make RTBTs more usable and reliable and therefore decrease the burden of PAs. 

“Smart” but Insecure: Improving Medical Device Cybersecurity

by Daniel Bardenstein

As “smart” medical devices continue to proliferate across the healthcare sector, healthcare organizations have been increasingly targeted by ransomware and other debilitating cyber attacks. These devices are often vulnerable to attacks, potentially allowing malicious hackers to steal patient data, modify medical exam results, or disrupt life-supporting machines. This project proposes that the Food and Drug Administration establish a clear list of cybersecurity requirements for medical devices to receive FDA approval, including the use of Device Query interfaces.

Mitigating Algorithmic Bias in Government Healthcare AI Procurement

by Matthew Zhou

As digital tools become more common in medical decision-making, healthcare providers may risk exposing patient data or inadvertently using a tool that leads to racially biased outcomes. By building language into contracts that mandates data transparency, privacy protection, and bias prevention, government procurement offices can set their own responsible AI standards for private sector vendors. This project recommends a procurement request for proposal (RFP) generator tool that government procurement officials can use to incorporate and customize best practices for health tech governance into their RFPs and contractors.

Learn more about these and other projects here.

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