Validating, Standardizing, and Accelerating Healthcare Applications on Mayo Clinic Platform

The cornucopia of digital apps for healthcare administration, patient care, treatment, and optimization can be overwhelming, and the growth in AI raises questions of how far to trust each app. Mayo Clinic Platform has created a program to help health IT companies leverage Mayo Clinic Platform data, pursue clinical validation, and get their solutions deployed and adopted by healthcare organizations faster.

One of the early companies to start leveraging Mayo Clinic Platform was Dock Health.  We sat down for an interview with Dr. Michael Docktor, CEO at Dock Health, and Dr. Sonya Makhni, Medical Director at Mayo Clinic Platform, to learn more about the Platform and how it’s helping companies like Dock Health develop solutions more quickly to better serve healthcare customers.

Dock Health, developed originally at Boston Children’s Hospital, was created by a clinician to automate many of the administrative tasks that clinicians don’t want to spend their time doing.  Focused on managing “all the administrative and operational tasks of patient care,” Dock Health delivers a more efficient and streamlined administrative process for care teams.  The company has standardized workflows such as managing inbound referrals, augmented by AI and pursued qualificationusing Mayo Clinic Platform and its network of experts to ensure the solution is solving real clinical and administrative pain points.

In our interview, Docktor and Makhni list some of the challenges facing healthcare sites that want to benefit from the new generation of applications. Makhni says that clinicians at Mayo Clinic Platform evaluate a number of applications from different companies. Health systems must choose solutions that address their specific clinical and operational needs, patient populations, budgets, and resources. These solutions should seamlessly integrate into existing workflows, and appropriate change management measures should be followed to ensure success. Such measures include education, incentive alignment, and clinician champion resources. The availability of staff and their budgets limit the number of applications that can be chosen. A particular solution is not always appropriate for a given patient population.  Docktor adds that apps must fit doctors’ workflows, overcome resistance to change, and prove security compliance as well as accuracy.

Both interviewees repeatedly stress the role of validation. AI-driven apps have been proven to be mostly accurate, but can still suffer from occasional hallucinations, so we have to “preserve a bit of skepticism”. Docktor says their application does not try to offer clinical decision support, which would “need a higher level of scrutiny” than the operational and administrative tasks they perform.

Makhni explains that the complex nature of AI solutions can be challenging for some health systems to methodically assess to determine if a given AI solution is a suitable fit for their needs. To make this process easier and more transparent, Mayo Clinic Platform has developed a multidisciplinary process including expert clinicians, informaticians, statisticians, data scientists, and others known as Qualification. Qualification involves a rigorous review of a solutions performance, intended use, development, and outcomes. Mayo Clinic Platform communicates this information in a clear, standardized manner that is transparent and easy to digest by potential end users. Through this process, Mayo Clinic Platform hopes to improve responsible adoption of AI solutions in healthcare.

Watch the video for more details about Mayo Clinic Platform and how Dock Health’s use of the platform accelerates adoption and trust of their application.

Learn more about Mayo Clinic Platform: https://www.mayoclinicplatform.org/

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