Milliman maintains a medical professional liability database that covers hospitals, nursing homes, and long-term care facilities using data collected from across the firm. The latest biannual update contains over $26 billion in incurred losses through 2023. This paper discusses key findings compiled from our analysis of this data.
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 (ILFs). 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 loss development patterns and ILFs 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 hospital professional liability (HPL) market has seen an uptick in severity in recent years. Using roughly 40,000 closed claims between 2014 and 2023, Figure 1 shows average severity for unlimited loss and allocated loss adjustment expenses (ALAE) 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 5.0% on an unlimited basis and 4.5% limited to $5 million per claim. Each trend reflects a 0.5% increase compared to our review in 2023.
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 2010 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). Social inflation and the dramatic increase in third-party litigation funding (TPLF) are possible drivers of the increase in large claims. According to this Milliman article, the TPLF market grew by 44% in the U.S between 2019 and 2022.
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 state group, including both loss and ALAE. Claims have been trended from their close dates to 2024 by 5.0% 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
Loss cost distribution by facility
Figure 7 displays each facility’s cost per exposure relative to the average cost of all facilities. This graph provides benchmarking information for our clients to show how their cost per exposure compares to other hospitals. This analysis also utilizes the American Hospital Association (“AHA”) hospital database to ensure consistent exposure information.
Figure 7: Relative cost by facility
Severity by specialty
Figure 8 shows loss and ALAE claim severity for key specialties. We include claims that have closed within the last fifteen years. Claims have been trended from their close dates to 2024 by 5.0% per year. Since our prior database update, both cardiology and cardiovascular surgery have increased in severity ranking. Most other specialties’ ranks are consistent.
Figure 8: Trended average severity by specialty
Loss expense ratio
The expense to indemnity ratio has been dropping since 2017, implying that indemnity payments have been increasing at a faster pace than defense expense costs. Figure 9 shows the ratio of expense to unlimited indemnity payments by close year.
Figure 9: Loss expense ratio
Expense versus indemnity payment
Figure 10 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 10: 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 11.
Figure 11: Average lag (in years)
| Indemnity payment size | Occurrence-to-report lag | Report-to-close lag |
|---|---|---|
| $0 | 1.296 | 2.006 |
| < $1M | 0.905 | 2.604 |
| $1M < $5M | 1.359 | 3.801 |
| $5M < $10M | 1.371 | 4.306 |
| $10M + | 0.947 | 3.358 |
Figure 12: Occurrence to report lag (in months)
On a similar note, we have graphed the occurrence to report lag (in months) in Figure 12. It is evident that the statute of limitations, often two years, is a significant driver of reporting patterns.
Discount summary
The interest rates used by the clients in this study to discount their reserves are summarized in Figure 13. We express no opinion on the appropriateness of the interest rates. As expected, the average discount rate has increased approximately 0.5% since our analysis two years ago.
Figure 13: Discount rates booked by clients
Retention
Figure 14 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 500. Large systems are greater than 500 inpatient days. The median retentions for small, medium, and large systems are $1 million, $3 million, and $6 million, respectively. Out of the clients we had retention statistics for in both 2022 and 2024 data:
- 2% had a retention decrease
- 56% had no changes in retention
- 42% had retention increases
Figure 14: Retention survey
