CARe Seminar 2005
Medical Malpractice:
Observations, Issues and Methodologies
June 7, 2005
Hamilton, Bermuda
Panelists:James D. Hurley, ACAS, MAAA
Kirk Bitu, FCAS, MAAA
Moderator: Anne Petrides, FCAS, MAAA
Towers Perrin
Willis Re
Meetinghouse LLC
Session Format
• Introductions
• Overview and Observations of the current
Medical Malpractice Environment including
current issues on Tort Reform
• Reinsurance Modeling techniques with
specific nuances to Medical Malpractice
• Discussion with Question and Answer
Opportunity
Casualty Actuaries in Reinsurance
Observations on Medical Malpractice
This document is incomplete without the accompanying discussion; it is confidential
and intended solely for the information and benefit of the immediate recipient hereof.
© 2005 Towers Perrin
Observations on Medical Malpractice
 Financial results
 Tort reform
 Insurance reform
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Occurrence
Direct
180.0
3,500,000
160.0
140.0
2,500,000
120.0
2,000,000
100.0
80.0
1,500,000
Loss Ratio
Premiums Earned (millions)
3,000,000
60.0
1,000,000
40.0
500,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Occurrence
Ceded
200.0
800,000
180.0
700,000
140.0
500,000
120.0
100.0
400,000
80.0
300,000
Loss Ratio
Premiums Earned (millions)
160.0
600,000
60.0
200,000
40.0
100,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Occurrence
Net
180.0
2,500,000
160.0
140.0
120.0
1,500,000
100.0
80.0
1,000,000
Loss Ratio
Premiums Earned (millions)
2,000,000
60.0
40.0
500,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Occurrence
Loss Ratios
200.0
180.0
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
1995
1996
1997
1998
2001
2000
1999
2002
2003
2004
Year
Direct
Ceded
Net
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Claims-Made
Direct
160.0
10,000,000
9,000,000
140.0
120.0
7,000,000
100.0
6,000,000
80.0
5,000,000
4,000,000
Loss Ratio
Premiums Earned (millions)
8,000,000
60.0
3,000,000
40.0
2,000,000
20.0
1,000,000
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Claims-Made
Ceded
180.0
3,500,000
160.0
140.0
2,500,000
120.0
2,000,000
100.0
1,500,000
80.0
Loss Ratio
Premiums Earned (millions)
3,000,000
60.0
1,000,000
40.0
500,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
7,000,000
160.0
6,000,000
140.0
120.0
5,000,000
100.0
4,000,000
80.0
3,000,000
Loss Ratio
Premiums Earned (millions)
Medical Malpractice - Claims-Made
Net
60.0
2,000,000
40.0
1,000,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Claims-Made
Loss Ratios
180.0
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
1995
1996
1997
1998
2001
2000
1999
2002
2003
2004
Year
Direct
Ceded
Net
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
14,000,000
160.0
12,000,000
140.0
120.0
10,000,000
100.0
8,000,000
80.0
6,000,000
Loss Ratio
Premiums Earned (millions)
Medical Malpractice - Occurrence & Claims-Made
Direct
60.0
4,000,000
40.0
2,000,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Occurrence & Claims-Made
Ceded
200.0
4,000,000
180.0
3,500,000
140.0
2,500,000
120.0
100.0
2,000,000
80.0
1,500,000
Loss Ratio
Premiums Earned (millions)
160.0
3,000,000
60.0
1,000,000
40.0
500,000
20.0
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
9,000,000
160.0
8,000,000
140.0
7,000,000
120.0
6,000,000
100.0
5,000,000
80.0
4,000,000
Loss Ratio
Premiums Earned (millions)
Medical Malpractice - Occurrence & Claims-Made
Net
60.0
3,000,000
40.0
2,000,000
20.0
1,000,000
0.0
0
1995
1996
1997
1998
2000
1999
2001
2002
2003
2004
Year
Premiums Earned
Loss Ratio
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Medical Malpractice - Occurrence & Claims-Made
Loss Ratios
200.0
180.0
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
1995
1996
1997
1998
2001
2000
1999
2002
2003
2004
Year
Direct
Ceded
Net
Source: Compilation of Best Data
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
 Financial results impacted by...
 1990’s
— modest loss trends
— favorable reserve development
— relatively high investment returns
— expansion
— slippage in pricing
 2000’s
— loss trends pick up
— unfavorable reserve development
— investment returns turn
— rates adjusted
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
180%
160%
140%
120%
100%
80%
60%
40%
20%
Combined
Investment Gain
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
0%
Operating
Source: A.M, Best’s Aggregates and Averages
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
Frequently discussed tort reforms
 Caps on non-economic loss
 Collateral source offsets
 Limitations on joint-and-several liability
 Punitive damage restrictions
 Periodic payments
 Frivolous suit penalties
 Limitations on attorneys’ fees
 Immunity statutes
Continued...
© 2005 Towers Perrin
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Observations on Medical Malpractice
Frequently discussed tort reforms (cont’d)
 Changes in pre-judgment interest
 Establishment of pre-trial hearing panels
 Establishment of state-operated funds to handle
certain claims
 Changes to the statute of limitation or statue of repose
 Mandatory mediation
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
 Tort reform
 Background – Federal
— HR5/HR4280
— MICRA-like
 Background – State
— many have discussed
— several have passed
— likely impacts
– e.g., Texas, Pennsylvania, Florida
Continued...
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
 Tort reform (cont’d)
 Issues/risks
—
—
—
—
limited data to evaluate
prospective credit?
interpreted as expected
upheld
Continued...
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
 Tort reform
 Issues/risks (cont’d)
— specifics
– non-economic limit: per defendant or per occurrence
– collateral source: jury disclosure or after award
– panels: admissible or not
– PCF: who defends?
– no-fault
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
 Insurance reform
 For example, Rhode Island proposal
— use ‘lowest factor’ of any state
— ‘rate formula’
– rate of return formula
– number of years for development, trend, ILF’s
– specific weights to each experience year
— class plan range limited to 500%
— use of RBC
– surplus exceeds RBC
– ‘unreasonably large’
– no rate increase/distribute ‘fairly allocable surplus’
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
Observations on Medical Malpractice
 Are we having fun yet?
© 2005 Towers Perrin
S:\People\hurlj\Presentations\050607 CARe.ppt
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Modeling: Approach
CARE Presentation
Modeling Technique
Typical Modeling exercise for Medical Malpractice
Find appropriate option for Med Mal book:
–
300,000 Per Occurrence Retention
–
500,000 Per Occurrence Retention
–
1,000,000 Per Occurrence Retention
–
ALAE treated pro-rata
Reasonable step process:
1.
Actuarial analyses: estimate ceded loss by retention
2.
Fit loss curve(s)
3.
Build model / Simulate loss
4.
Report results
Specific clash contracts and examples to follow
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Modeling Technique
Step 1 – Actuarial Analysis: Expected Loss By Layer
•Selected loss for each layer
•Experience Analysis
- trend analysis, loss development analysis
- Premium / exposures to current level
•Exposure Analysis
•Actuarial Judgment
Summary of Actuarial Analysis
Layer
Rentention
(A)
0
300,000
500,000
750,000
1,000,000
2,000,000
Limit
Experience
Rate
Exposure
Rate
Experience
Weight
Selected Loss
in Layer
(B)
300,000
200,000
250,000
250,000
1,000,000
1,000,000
(C)
53,142,464
17,564,162
10,440,632
6,097,199
6,942,335
1,200,000
(D)
53,142,464
25,077,247
22,625,780
9,908,166
14,923,142
2,998,391
(E)
100.00%
90.00%
80.00%
70.00%
60.00%
40.00%
(F)=(C),(D) wghtd
53,142,464
18,315,470
12,877,662
7,240,489
10,134,658
2,279,035
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Modeling Technique
Step 2 – Curve Fitting: Preliminaries
Common methods of fitting:
–
Maximum likelihood estimators
–
Method of moments
–
Percentile matching
–
Sum squared error
Inputs needed:
–
Data points (ultimate loss of the individual claims)
Medical Malpractice considerations:
–
Long-tailed - not all claims in data set are closed
–
Tort reform / changing social factors create non-homogeneous losses
–
Clash Losses
–
Pro-rata ALAE
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Modeling Technique
Step 2 – Curve Fitting: Addressing Med Mal Considerations
Long-tail business: Years with claims not closed?
•
Common Feedback:
– Do not use the ‘green’ years’ fit your curve
Tort Reform / Changing Social Factors: Older years have less predictive value
•
Common Feedback:
– Exclude older years in curve fitting / modeling
If we use this feedback, we are left with little data to fit to!
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Modeling Technique
Step 2 – Curve Fitting: Addressing Med Mal Considerations
Clash Losses: Modeling clash events
•
Common Feedback:
– Fit a distribution for number of claims per event
– Fit a distribution for individual claim severity correlated to claims in event
– Find distribution for claimi based on other claims in the event
Pro Rata ALAE: Addressing ALAE?
•
Common Feedback:
– Use regression analysis, correlation or fit a copula
While the feedback is sound in theory, is it practical or even necessary?
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Modeling Technique
Step 2 – Curve Fitting: Addressing Med Mal Considerations
Statistical complications:
– Adjustments for non-homogenous losses, open claims, etc.
– Variance-covariance matrix for the clash, in several dimensions
– ALAE: copula, regression analysis, correlation
• Difficult / impractical to implement
• Parameter and model error unavoidable
But these issues are implicitly addressed in the actuarial analysis!
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Modeling Technique
Step 2 – Curve Fitting: Alternative Approach – Using Actuarial Analyses
Fit directly to the output of our actuarial analyses
Summary of Actuarial Analysis
Layer
Rentention
(A)
0
300,000
500,000
750,000
1,000,000
2,000,000
Limit
(B)
300,000
200,000
250,000
250,000
1,000,000
1,000,000
Experience
Rate
(C)
53,142,464
17,564,162
10,440,632
6,097,199
6,942,335
1,200,000
Exposure
Rate
(D)
53,142,464
25,077,247
22,625,780
9,908,166
14,923,142
2,998,391
Experience
Selected Loss
Weight
in Layer
(E) (F) = wghtd (C),(D)
100.00%
53,142,464
90.00%
18,315,470
80.00%
12,877,662
70.00%
7,240,489
60.00%
10,134,658
40.00%
2,279,035
Fitted
Loss*
(G)
52,708,144
18,315,478
12,877,666
7,240,491
10,134,660
2,279,036
(G) Loss fit using SSE to Lognormal
Selected loss reflects terms of contract:
–
In this example: Selected Loss and Fitted Loss include ALAE pro rata
*In any curve fitting exercise, the analyst will also make necessary statistical considerations.
Examples: Non-parametric versus parametric estimators, # of parameter to use, spliced vs. mixed curves
vs. incorporating industry curves between nodes, accounting for clusters of points around limits, etc.
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Modeling Technique
Step 2 – Curve Fitting: Alternative Approach
Fitting to data points requires analysis of raw data twice:
RAW DATA
1) ACTUARIAL ANALYSIS
2) CURVE FITTING (data points)
3) SIMULATION
Alternative approach works from actuarial work already performed: Efficient!
RAW DATA
1) ACTUARIAL ANALYSIS
2) CURVE FITTING (actuarial analysis)
3) SIMULATION
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Modeling Technique
Step 3 – Simulation: Preparing Model
Use parameters found in curve fitting to simulate losses
Based on varying retentions, model impact on financial statements items
•
Summary of company underwriting assumptions:
Premium
125,000,000
Loss and ALAE
103,989,778
Loss and ALAE Ratio
83.2%
U/W Expense Ratio
12.0%
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Modeling Technique
Step 3 – Simulation: Options
Summary of retention options to model
Item
xs 1M
ALAE pro rata
xs 500K
ALAE pro rata
xs 300K
ALAE pro rata
Retention
$1M
$500K
$250K
Selected Loss Cost
9.93%
26.03%
40.68%
Reinsurance Rate
12.74%
31.67%
48.91%
ALAE coverage
Pro rata
Pro rata
Pro rata
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Modeling Technique
Step 4 – Report Model Results : Variability in Underwriting Result
Gross
xs 1M
ALAE pro rata
xs 500K
ALAE pro rata
xs 300K
ALAE pro rata
Average
6,272,638
2,804,298
-829,668
-4,129,742
Standard Dev.
39,471,857
24,560,844
16,394,465
10,812,028
Gross
xs 1M
ALAE pro rata
xs 500K
ALAE pro rata
xs 300K
ALAE pro rata
Conf. Level
Percentile
1 in 2
50.0%
14,103,742
6,215,023
1,076,202
1 in 10
10.0%
(38,916,169)
(29,008,083)
(22,159,918)
(18,207,299)
1 in 100
1.0%
(126,861,877)
(70,836,225)
(48,011,748)
(34,413,422)
1 in 250
0.40%
(170,471,132)
(86,736,496)
(57,444,760)
(40,179,523)
-3,035,565
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Modeling Technique
Step 4 – Report Model Results: Variability in Underwriting Result
100,000,000
50,000,000
Probability
Results
0
99.6%
75%
50%
(50,000,000)
25%
.4%
♦
(100,000,000)
(150,000,000)
(200,000,000)
Gross
xs 1M
xs 500K
xs 300K
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Avg
Modeling Technique
Clash: Coverage examples
Example 1:
Type: Per Occurrence retention
Modeling: Per occurrence
Example 2:
Type: Per Occurrence, Per Risk Cover (same retention)
Modeling: Per Occurrence
Allocate simulated occurrence losses to per-risk and clash components
Example 3:
Type: Clash Retention greater than Per Risk Cover
Modeling: Per-occurrence model for each per-risk retention
Simulate using two curves: Excess Per Risk, Clash
Requires correlation–two curves instead of many
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Modeling Technique
Handling Clash – Allocation of Losses
Use actuarial analysis to find per-risk loss in layer AND per-occurrence loss in layer
Clash Loss = Per-occurrence minus per-risk OR Model clash separately
Summary of Actuarial Analysis
Layer
Rentention
(A)
0
300,000
500,000
750,000
1,000,000
2,000,000
Limit
(B)
300,000
200,000
250,000
250,000
1,000,000
1,000,000
Selected Per
Occurence Loss
(C)
52,708,144
18,315,478
12,877,666
7,240,491
10,134,660
2,279,036
Selected Per
Risk Loss
(D)
60,096,712
16,234,915
11,505,562
6,834,184
9,131,489
0
Clash
Loss
(E) = (C) - (D)
2,080,563
3,452,667
3,858,975
4,862,145
7,141,181
Summary of Loss Allocation
Layer
Rentention
(A)
300,000
500,000
750,000
1,000,000
2,000,000
Limit
(B)
200,000
250,000
250,000
1,000,000
1,000,000
% of
Per Risk Loss
(C)
88.6%
89.3%
94.4%
90.1%
0.0%
% of
Clash Loss
(D)
11.4%
10.7%
5.6%
9.9%
100.0%
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