Improving Interoperability to Address the Physician Shortage

Dr. Zhuqi Miao OSU-Tulsa; Sahee Abdelmomin, TIL
September 20, 2021

Excessive administrative tasks are one of the biggest burdens on the US healthcare systems. Nationwide, physicians spend between 30% and 50%  time  on clerical tasks that infringe time needed to provide direct patient care. This burden is a major contributor to physician burnout and the growing physician shortage - especially among rural populations.

Alleviating the current primary care physician shortage would save 7,000 American lives annually.  Unfortunately, the U.S. demand for physicians in every specialty has outpaced supply since 2018, and this deficit is expected to worsen over the next few years. In December 2020, Congress took a step toward addressing the physician shortage by adding 1,000 new Medicare-funded Graduate Medical Education spots, the first increase in the number of federally appointed residency spots since 1997. Despite this effort, studies still show that our country will experience a severe physician shortage. As a result, the medical community is now looking to health data technologies for solutions. Today, most health data capture is driven by billing purposes. However, ballooning healthcare demand and the precipitous physician shortage are forcing healthcare systems to turn to data-driven solutions such as Artificial Intelligence (AI) and Machine Learning (ML) for help. Realizing AI/ML’s potential to improve workflow efficiency and physician satisfaction, healthcare systems are starting to think of ways to enhance interoperability—or timely health data collection, exchange and use.

Tulsa Innovation Lab’s first white paper, “Improving Interoperability to Address the Physician Shortage", takes a closer look at the opportunity to apply artificial intelligence and machine learning to ethically and effectively improve healthcare for both workers and patients.  

The report synthesizes and analyzes insight from health data experts, physician interviews and primary literature to explore how data-driven technologies can help alleviate the effects of the physician shortage. To navigate this complex challenge, the report will discuss:

1. The Causes and Effects of the Physician Shortage

2. AI, ML, DL Alphabet Soup: What Does It Mean and How Can It Help?

3. Examples of How AI Can Reduce Physician Burnout and Critical Care Overload

4. Navigating Barriers To Widespread Adoption of Health AI Technologies

Additionally, the report includes a project spotlight that provides a peek into the future of health AI/ML technologies.

A huge thank you to Dr. Zhuqi Miao and WILLIAM PAIVA from OKLAHOMA STATE UNIVERSITY-TULSA and all of our expert contributors for their contributions to this whitepaper.

read the full article here