In 2010, Milliman created a medical professional liability database. This includes professional liability for hospitals, nursing homes, and long-term care facilities using data gathered from Milliman offices throughout the country. We update the database biannually. The following key findings are compiled from our 2023 analysis based on data collected in 2022.
Our latest update contains over $22 billion in incurred losses for the most recent evaluation date. In addition to loss data, we collect other important details such as claim state, specialty, and hospital exposures. Part of our analysis includes creating industry loss development factors and increased limit factors. These factors become especially critical in cases where a hospital’s data is not credible on its own. Using other specific claim details collected, we can develop industry patterns tailored to specific characteristics of the program. The other part of our analysis includes analyzing other industry trends—which we have summarized in this report.
Severity trends
The medical professional liability (MPL) market has seen an uptick in severity in recent years. Using roughly 30,000 closed claims between 2012 and 2021, Figure 1 shows average severity for unlimited losses and those limited to $5 million. It is shown that unlimited average severity has increased at a faster pace than losses limited to $5 million. We conclude that the unlimited severity is heavily impacted by increased frequency of large loss claims (above $5 million). This conclusion is further supported by Figures 2 through 4. We selected severity trends of 4.5% on an unlimited basis and 4.0% limited to $5 million per claim.
Figure 1: Average loss and ALAE severity by close year
Large claims
As shown in Figure 2, the percentage of claims closed with an indemnity payment of $1 million or more was relatively flat between 2008 and 2013, but thereafter has gradually increased. There is an even more significant increase in the percentage of claims that closed with an indemnity payment of $5 million or more (Figure 3). The dramatic increase in third-party litigation funding (TPLF) is a possible driver of the increase in large claims.
Figure 2: Percentage of closed claims with indemnity payment of $1 million or more
Figure 3: Percentage of closed claims with indemnity payment of $5 million or more
Figure 4: Percentage of closed claims with indemnity payment at higher limits ($10 million and $15 million)
Severity by state group
Figure 5 shows closed claim severity by specialty, including both loss and allocated loss adjustment expenses (ALAE). Claims have been trended from their close dates to 2022 by 4.5% per year and organized by state groups with similar loss characteristics. For example, Group 4 contains the states with the highest average severities (Illinois, Florida, New York, etc.).
Figure 5: Severity by state group
There are clear differences across the state groups. Being able to break the data from similar states into groups, we can provide credible and relevant benchmarking factors for hospitals countrywide. Our database also contains more granular data (e.g., Cook County) so that we can use finer break-outs in our client work.
State loss cost map
Figure 6 displays each state’s cost per exposure relative to California’s cost per exposure. Darker states imply higher costs. In order to collect consistent hospital exposure information, we utilize the American Hospital Association (“AHA”) hospital database.
Figure 6: Relative cost by state
Severity by specialty
Figure 7 shows the closed claim severity by specialty, including both loss and ALAE. Claims have been trended from their close dates to 2022 by 4.5% per year. The green line is the average severity across all specialties.
Figure 7: Trended average severity by specialty
Loss expense ratio
As expected with increasing indemnity payments, the expense to indemnity ratio has been dropping in recent years, relatively steeply from what we saw in 2017 and prior. Figure 8 shows the ratio of expense to unlimited indemnity payments by close year.
Figure 8: Loss expense ratio
Expense versus indemnity payment
Figure 9 summarizes the amount of expense payments for claims closed in the last 10 years based on the size of the indemnity payment. As expected, the average expenses increase along with the size of the indemnity payments. The box represents the 25th to 75th percentile, with the line in the box being the median. The top and bottom bars extend to the 90th and 10th percentiles, respectively.
Figure 9: Amount of expense payments for claims closed in the last 10 years
Lag by claim size
We have analyzed the lag periods, both from occurrence date to report date and from report date to close date based on the indemnity payment amount. As anticipated, the lag from report date to close date increases as the amount of the indemnity payment increases. Interestingly, the occurrence-to-report lag is not positively correlated with the indemnity payment size. Claims that end up closing without an indemnity payment typically take longer to be reported than those with indemnity payments less than $1 million. One possible reason is that more of these claims without indemnity payments are reported as the statute of limitations is expiring. It is also interesting that claims that end up with $10 million or greater indemnity payments are reported more quickly than those with indemnity payments between $1 million and $10 million. In some of these more severe cases, it may be more evident to the hospital that a significant incident has occurred and it is reported faster. See Figure 10.
Figure 10: Average lag (in years)
| INDEMNITY PAYMENT SIZE | OCCURRENCE-TO-REPORT LAG | REPORT-TO-CLOSE LAG |
|---|---|---|
| $0 | 1.283 | 1.967 |
| < $1M | 0.866 | 2.458 |
| $1M < $5M | 1.395 | 3.785 |
| $5M < $10M | 1.518 | 4.206 |
| $10M + | 0.742 | 3.365 |
Discount summary
The interest rates used by the clients in this study to discount their reserves are summarized in Figure 11. We express no opinion on the appropriateness of the interest rates.
Figure 11: Discount rates used by clients
Percentile booked
The percentiles used by the clients in this study to book their reserves are shown in Figure 12. Thirty-nine percent of the clients in our analysis book reserves at the Actuarial Central Estimate (ACE). We express no opinion on the appropriateness of the percentiles used.
Figure 12: Percentiles booked
Retention
Figure 13 summarizes the retentions of the clients within the database organized by hospital or system size. Small systems are those with inpatient days per 365 days less than 250. Medium systems are between 250 and 600. Large systems are greater than 600 inpatient days. The median retentions for small, medium, and large systems are $1 million, $2 million, and $6 million, respectively. Out of the 95 clients we had retention statistics for in both 2020 and 2022 data:
- 1 had a retention decrease
- 77 had no changes in retention
- 17 had retention increases
