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Insights
Large Losses in Workers Compensation - Claims Above $1M
Large Losses in Workers Compensation - Claims Above $1M
NCCI Page Content Two
InsightsResearch & Briefs
ByJim Davis and Ryan VollMarch 31, 2020



Page Content

OVERVIEW

The workers compensation (WC) line of business has experienced a long-term decline in overall claim frequency that has spanned several decades. Despite this positive trend, serious accidents continue to occur and take their toll on injured workers and their families. In these instances, the WC industry rallies to the well-being of the injured worker to ensure the best possible outcome. These claims have received considerable attention in recent years.

The costs associated with serious accidents for medical treatment and lost-wage benefits can rise into the multi-million-dollar range. In this article, we examine the frequency of claims with incurred losses above $1M in all NCCI states combined over the most recent fifteen years.1 We also examine various characteristics of these claims (e.g., part of body, cause of injury) as well as how they have emerged over time.

KEY FINDINGS

  • Claims above $1M account for 10% of losses, but less than 0.2% of all lost-time2 claim counts
  • The cumulative change in frequency was approximately the same for claims above $1M versus below $1M over the period studied
  • In recent years, WC insurers have been utilizing a variety of new techniques to provide an early notice of claims that may have the potential to develop into large losses (referred to as adverse development)
  • The frequency of claims above $1M was significantly impacted by the Great Recession
  • Claims involving multiple body part injuries represent the highest share of claims above $1M
  • Motor vehicle accidents along with slips and falls are the cause of about half of all claims above $1M

INTRODUCTION

Analyzing the occurrence of large claims over time poses several challenges. For example, it may be several years before the full cost of a claim is known, changes in claims management can impact reserving patterns, and inflation may cause more claims to exceed a fixed-dollar threshold each year. To address these challenges, we compared accident years over time at the same age of maturity. We also adjusted the value of all historical claims to the current level of inflation.3 This allowed us to estimate how many claims in each historical year would have exceeded the $1M threshold in 2016 dollars.

LARGE CLAIM VOLUME

The limited number of large claims makes it challenging to identify a true frequency trend versus random fluctuation over time.

The table below displays the distribution of claims by size for Accident Year 2016 as of 2nd report.4 Claims above $1M accounted for less than 0.2% of all lost-time claims and approximately 10% of losses. Similar shares were observed for Accident Years 2002 through 2015.

Chart 1

FREQUENCY

We examined the frequency5 of claims above $1M, with each year measured at 2nd and 5th report.6
Note the following two key observations:

1. Claim Count Development—The emergence of large claims after 2nd report has slowed considerably in the more recent years. For example, the number of claims above $1M increased by 82% from 2nd report to 5th report for 2002, but by only 41% for 2013.

Chart 2

2. Claim Frequency—There has been a sharper decline in the frequency of claims above $1M when measured at 5th report versus 2nd report. Over the period 2002 to 2013, the average annual change in frequency for claims above $1M is -2.7% at 5th report and -1.0% at 2nd report.

Chart 3

CONSIDERATIONS

What might be driving these observations?

In some instances, WC insurers can identify large claims very quickly. Examples include claims involving brain injuries, paralysis, and other significant injuries, where the potential for extensive medical treatment is recognized immediately. In these instances, claims adjusters may establish a substantial case reserve very early in the life of the claim. However, other claims that may not initially appear to be serious, may develop adversely over time. For example, an unsuccessful surgery may have adverse consequences for the injured worker. One study estimated that two thirds of claims over $1M started out as “fairly routine.”7

In recent years, WC insurers have been using a variety of new techniques (e.g., predictive modeling and analytics) to provide an early notice of claims with the potential to develop adversely into large losses.8 Such earlier identification may have a two-fold effect:

  • Allows WC insurers to more quickly triage these claims with the proper resources to ensure the most effective care and best possible outcomes for injured workers. If successful, this may reduce the number of claims that develop into large losses and explain the general observation that fewer large claims have emerged at later ages of maturity for the more recent accident years.
  • Leads to the establishment of higher case reserves at an earlier point in time in recent years. This may explain the observation that the frequency of claims above $1M is relatively flat when measured at 2nd report but decreasing at 5th report.

GREAT RECESSION IMPACT

The graph below shows the indexed frequency of lost-time claims above, versus below, $1M. The cumulative declines through 2013 are similar when measured at 5th report. However, there is a notable divergence in the year-to-year rates of change. Specifically, the frequency of claims above $1M rose sharply up to and into the early stages of the Great Recession,9 and then declined dramatically during the recession.

Chart 4

Given the construction industry has historically had the highest frequency of large claims in any of NCCI’s five major industry groups, the growth and decline in construction industry employment may explain the divergence in the observed frequency changes for claims above and below $1M between 2005 and 2010. The graph below, which displays construction versus total employment indexed to 2002,10 shows that the pattern of construction industry employment was similar to the one observed above for claims exceeding $1M.

Chart 5

LARGE LOSS CHARACTERISTICS

The chart below displays the distribution of claims above $1M by NCCI’s major part-of-body groupings for years 2014 through 2016 combined. The largest category of claims exceeding $1M involve multiple body part injuries, while injuries to the head/brain represent the second largest grouping. For comparison, the distribution of all lost-time claims is also provided.

Chart 6

The chart below displays the distribution of claims above $1M by NCCI’s major cause-of-injury groupings for years 2014 through 2016 combined. Claims involving slips and falls, and motor vehicle accidents,11 account for more than half of all claims above $1M. For comparison, the distribution of all lost-time claims is also provided.

Chart 7

CLOSING REMARKS

Many factors have influenced the occurrence and cost of large claims, including:

  • Medical advances have increased the chances of surviving a serious accident and have improved the quality and duration of life for those that sustain catastrophic injuries
  • Motor vehicle accidents, which can result in very severe injuries, have been on the rise12
  • National attention to the opioid crisis has led to diminished opioid use resulting from significant changes in opioid prescription practices13
  • The frequency of large losses has been heavily influenced by the construction industry share of total employment

Going forward, NCCI will continue to monitor the emergence of large losses and share our findings.

​This article is provided solely as a reference tool to be used for informational purposes only. The information in this article shall not be construed or interpreted as providing legal or any other advice. Use of this article for any purpose other than as set forth herein is strictly prohibited.

1Large deductible policies are included in order to maximize the number of claims under review.
2 Lost-time claims for this analysis represent claims with an indemnity payment or reserve.
3 The reported indemnity portion (paid losses plus case reserve) of each claim was adjusted for changes in average weekly wages by state (US Bureau of Labor Statistics: Quarterly Census of Employment and Wages) and the reported medical portion (paid losses plus case reserve) was adjusted for changes in medical inflation (Personal Health Care Chain-Weighted Price Index).
4 For Statistical Plan data, first report for each policy is 18 months from the policy effective date, second report at 30 months, third report at 42 months, etc. At the time of this study, second report data was available for approximately 95% of 2016 policies.
5 Frequency—Reported, undeveloped lost-time claims at the specified report per $1M of earned premium, on-leveled to NCCI approved pure loss cost level by state and adjusted for changes in average weekly wages by state. Earned premium is on an “exposure year” basis and is on-leveled by extending payroll by the approved NCCI pure loss costs by state and class.
6 AY 2013 is the latest year currently available at 5th report.
7 Source: Property Casualty 360; “Top Causes of High-dollar Workers’ Comp Claims,” June 19, 2018, by Mark Walls and Stephen Peacock.
8 The Power of Predictive Models in Workers’ Compensation Claims Handling, November 2015, Advisen; Understanding Predictive Analytics for Workers’ Compensation Data Analysis, February 2018, by Mike Bishop; and Courtney Chandler; The Expanding Use of Predictive Analytics in Claims Management, May 2018, by Bill Lentz
9 The Great Recession spanned December 2007 through June 2009, according to the National Bureau of Economic Research.
10 Source: Bureau of Labor Statistics, Quarterly Census of Employment and Wages.
11 Motor vehicle accident claims as defined here include accidents involving cars, trucks, buses, motorcycles, trains, watercraft, and aircraft, but exclude accidents involving individuals being struck by a vehicle.
12 Source: Motor Vehicle Accidents in Workers Compensation, by Jim Davis and Delano Brown
13 Source: Medical Outlook, Quarterly Economics Briefing—2019 Q3, by Delano Brown and Raji Chadarevian




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