Managing medical professional liability (MPL) lawsuits and accurately pricing MPL risk are issues the industry has been grappling with for years.
“Historically speaking, the premiums charged for doctors, physician groups and surgeons have been tied to three main metrics: A physician’s specialty, location of practice and the absence or prevalence of medical liability claims,” said Brian Kern, chief executive officer of Deep Risk Management, a company specializing in data-driven MPL and financial risk management and underwriting.
According to an American Medical Association analysis of claim frequency, the potential of being sued is a stark reality for many in the profession, with the study finding that the longer someone practices, the greater the risk.
The paper, which was published by José R. Guardado Ph.D. in May 2023, looked at data from the AMA’s 2016-2022 Physician Practice Benchmark Surveys, presenting estimates of claim frequency and exploring the role that factors such as age, gender and specialty played in overall risk.
Of note, in 2022, close to one-third (31.2%) of U.S. physicians reported being previously sued during their careers.
When broken down by age and gender, 46.8% of physicians over 54 had claims filed against them versus 9.5% of those under 40 and 36.8% of men and 23.8% of women were sued.
In addition, certain surgical areas presented the greatest risk, with about 62% of OB-GYNS and 59.3% of general surgeons reporting lawsuits.
Medical liability claims directly impact MPL insurance costs, but are they the only indicator of future claims?
What if insurance companies had access to other data points such as surgical infections, revision and readmission rates, or whether procedures were indicated or performed consistent with standards of care? Would it change the professional liability underwriting and risk management landscape?
As Kern explains such data exists, but there are obstacles to its widespread use.
“While a physician’s history of medical liability claims is easy to access and comprehend, that’s not the case with other data,” Kern said. “Although this data exists, it has to be assembled into a format that is understandable and streamlined.”
Additionally, he said there’s a need to raise awareness among underwriters and risk managers about the availability of the data and how it can be incorporated into overall risk modeling and management.
This potential data-driven revolution was the subject of a Crittenden Medical Liability panel last April moderated by Kern.
A licensed New Jersey attorney, Kern has helped build and grow several healthcare risk brokerages while studying law and risk management.
“New datasets can provide an entirely new perspective on how risk can be better managed, and better priced,” Kern said. “I’m not suggesting that underwriters and risk managers abandon their traditional approach, but I don’t think this new data can be ignored much longer. Does it make sense to offer the same rates to two surgeons who do hip replacements, if one has a much higher revision rate? This should be information that insurance companies use when determining the cost of a surgeon’s professional liability insurance.”
Incorporating data and analytics into the decision-making process is already underway at businesses such as Positive Physicians Insurance Company (PPIC), which now leverages the information to identify physicians and determine pricing based on that individual’s practice patterns.
PPIC’s President and CEO Michael Roque and Chief Strategy Officer Annie Matincheck, both participated in the panel at the Crittenden Medical Liability conference alongside Kern.
Their company recently partnered with Preverity Inc., a provider of clinical risk analytics and patient safety solutions, to better assess physician and surgeon risk factors.
“As Brian indicates, historical loss experience has been a key factor in determining pricing across the industry,” Matincheck said. “However, with ongoing changes in the healthcare sector encompassing both the delivery of care and advancements in medical practice, the risk profiles of physicians and practices are also evolving. As a result, we recognize we must also adapt our models to reflect these changes.”
Matincheck said in the past they were limited in their ability to make such dynamic adjustments.
“However, with access to new data sources such as those provided by Preverity, we can now leverage aggregated data from various sources to identify emerging trends more easily,” she said. “In addition, they are providing additional metrics and insights that we can use to provide a more comprehensive and transformative approach to how we measure, analyze and predict risk.”
See Part 2 of this story: Data-driven decision-making helps manage medical liability risk and improve patient outcomes
