We need data driven medical student and resident analytics

One sick care executive top of mind problem is how to recruit, train and retain workers. Many have suggested ways to do that, including the use of people artificial intelligence products for human resource management,

Medical school and graduate resident training program directors should have the same concerns. Given the changing premedical, medical student and resident personas, and the anxieties they have, we need to rethink how we fill and train the doctor pipeline.

Career dissatisfaction, burnout and the high costs of dropping out is sometimes the result of poor job fit and the lack of an adequate job preview. When it comes to the present system of medical education and training, they are self-inflicted wounds.

The use of AI in HR has exploded in recent years. 

The increasing interest in this technology is in line with its broader adoption within organizations at large. Even following the onset of the COVID-19 pandemic, 42% of companies continued investing in AI at the same rate as before, and 24% increased their investment, according to Gartner research. Even in tense economic circumstances, companies were willing to bet on AI. 

Where are the opportunities and use cases?

AI serves two primary functions in HR:

• Automating simple tasks: AI can be used to speed up repetitive tasks that drain a lot of the HR department’s time, like sorting through resumes.
• Providing insights: AI can generate trends and insights to help you better understand your workforce, allowing you to make people decisions with greater confidence.

A data driven medical student analytics platform would solve problems with:

Recruitment:

Problem: How do we do improve medical student and resident selection

Onboarding

Problem: Preparing medical students and residents for success

Performance Management

Problem: Monitoring performance and complying with accreditation requirements

Internal Mobility

Problem: Identifying at risk students

Career planning and residency selection

Problem: Increasing residency match targets and satisfaction

Outplacement services

Problem: Providing students and residents who decide to leave with appropriate exit ramps

Learning and Development

Problem: Monitoring and measuring requisite knowledge, skills, abilities, and competencies

Engagement and Retention

Problem: Mitigating burnout and career dissatisfaction

Workforce Analytics

Problem: Filling workforce education and training gaps

Using AI in HR comes with problems including privacy, bias and poor use of resources and misinterpretation of the findings.

It's time for medical schools and residency training programs to hire a data analytics officer, report meaningful results, and impact the next time US News wants you to participate in their ratings issue.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs