Defense costs are the greatest expenditure for many medical professional liability (MPL) insurers. Employing big data analytics may help MPL insurers control their litigation expenses more effectively. Milliman consultant Chad Karls provides perspective in his article “Big data analytics: A practical application for MPL insurers.”
Here is an excerpt:
The new and rapidly advancing science of big data analytics offers MPL insurers the opportunity to absorb the massive amount of legal invoice data as it is being reported, take a deep dive into it, and – with the help of sophisticated algorithms – quickly derive valuable insights that can be used to better understand and manage the claims process.
The result is precise, actionable information that insurers can utilize to evaluate and manage their defense strategies – even as cases are progressing from discovery to depositions, from the expert witness prep phase to trial and beyond….
So, once this data has been properly prepared and constructed, an MPL insurer is in a position to investigate the efficacy of its claims-handing strategies. Rather than relying on just intuition and judgment, which are often biased by one’s outlier and/or most recent experiences, we can allow the data to inform our strategies. We can answer questions like these:
• Is it an effective strategy to file a motion for summary judgment (MSJ) in a particular venue or with a particular judge, given our historical success rate? How much does it cost to file an MSJ?
• What is the average cost of an expert deposition and are we taking more of them now, or has the average cost per deposition increased, or both?
• What is the optimal lag between preparing our defendant for his or her deposition and the deposition itself, if any?
• Do we tend to get a better outcome when the lead attorney’s hours represent at least X% of the total hours spent on the case?
• How much does it cost to have our defense firms comply with our 90-day claim summary report, and does the compliance rate correlate with the outcome of the claim?
• Can we develop a more cost-effective strategy for our record retrieval and court reporting costs?