Early Offers in Medical Malpractice Case Law

Transcription

1 Journal of Empirical Legal Studies Volume 6, Issue 4, , December 2009 The Effects of Early Offers in Medical Malpractice Cases: Evidence from Texasjels_ Bernard Black, David A. Hyman, and Charles Silver* Medical malpractice litigation is costly and time consuming. Professor Jeffrey O Connell, with various co-authors, has long advocated early offer rules that would encourage defendants to offer to settle for economic damages plus attorney fees, and punish plaintiffs who refuse such offers. Using detailed closed claims data from Texas for , we simulate the effects of these early offers. Under a base set of assumptions, early offers will sharply reduce payouts in cases with small economic damages (under $100,000, all amounts in 1988 dollars); will moderately reduce payouts in currently tried cases with economic damages from $100,000 $200,000 and would normally increase payouts (and therefore will not be made) in tried (settled) cases with economic damages over $200,000 ($100,000). Overall, we predict that early offers will be made in 72 percent of all cases, and will result in a 16 percent (20 percent) decline in payouts in tried (settled) cases. Almost all this effect comes from the sharp decline in payouts in cases with small economic damages. Defense costs will drop by roughly 60 percent (20 percent) in currently tried (settled) cases in which an early offer is made, and by about 13 percent overall. An early offer program will have very different effects on different types of plaintiffs, with especially large payout reductions for elderly and deceased plaintiffs. An early offer program also overlaps substantially in its effects with a statutory cap on noneconomic damages (which 26 states already have). Defendants in many of these states have already realized large reductions in payment of noneconomic damages; the additional reductions from an early offer program are modest and would often affect plaintiffs whose recoveries were already limited by damage caps. Our mixed results contrast sharply with dramatic claims by O Connell and co-authors, who predict 70 percent reductions in both payouts and defense costs. Their estimates reflect the compound effects of a series of unreasonable assumptions. I. Introduction Critics of medical malpractice (med mal) litigation assert that it is slow, expensive, and levies an unjustified tort tax on defendants. Similar criticisms apply to personal injury *Address correspondence to Bernard Black; [email protected]. Black is Hayden W. Head Regents Chair for Faculty Excellence, University of Texas Law School, and Professor of Finance, University of Texas, Red McCombs School of Business; Hyman is Richard and Marie Corman Professor of Law and Professor of Medicine, University of Illinois; Silver is McDonald Endowed Chair in Civil Procedure, University of Texas Law School. We thank Jill Horwitz and participants in the 2008 Conference on Empirical Legal Studies, 2008 Midwest Law and Economics Association Meeting, and workshops at Northwestern and University of Michigan Law Schools for helpful comments, and Hyun Kim for superb research assistance. 723

2 724 Black et al. litigation more generally. Because the overwhelming majority of cases settle, rules that encourage faster settlement are an obvious strategy for improving the performance of the tort system. In this article, we analyze one important early settlement proposal, first made by Professor Jeffrey O Connell in Under the current version of this early offer proposal, defendants can offer to settle for full economic damages plus attorney fees, possibly with a minimum damages offer in some cases. Plaintiffs who refuse the offer face a large stick in the form of a higher burden of proof; the defendants are making offers that can t be refused. 2 Recent studies by O Connell and co-authors estimate huge payout reductions from such a program on the order of a 70 percent drop in both payouts and defense costs. 3 We simulate the impact of an O Connell early offer program on payouts. We use a data set of all closed medical malpractice claims in Texas from with payouts over $25,000 (1988$). 4 We study both tried and settled cases, and find similar results for both sets of cases. All amounts in this article are in 1988 dollars; multiply by 1.82 to convert to 2008 dollars. Under a base set of assumptions, we estimate that an early offer program could produce a 16 percent overall decline in payouts in currently tried cases, and a 20 percent decline in settled cases. We explore sensitivity analyses how this estimate will vary depending on program details and one s assumptions. This decline in payouts will result primarily from large payout reductions for plaintiffs with limited or no economic damages ($0 $100,000). There will also be large variation in how an early offer program affects different plaintiff groups, with large payout declines for elderly and deceased plaintiffs, limited effects on employed adults in nondeath cases and on children, and almost no effect on baby cases. There is also substantial overlap between the cases in which an early offer program will reduce payouts and the cases in which a cap on noneconomic damages (adopted by 26 states) already does so. Defendants will make early offers only if they expect to gain by doing so. This means that early offers will be made principally in cases with small economic damages ($0 to $100,000). They may also be made in currently tried cases with economic damages from $100,000 $200,000, depending on likelihood of liability and other case characteristics. Early offers would generally produce higher payouts in tried (settled) cases if economic 1 O Connell (1982). 2 Hence the title of Professor O Connell s initial article, which begins Offers That Can t Be Refused. Id. 3 Hersch et al. (2007); O Connell and Born (2008); O Connell and Robinette (2008). 4 This article is one of a series using the Texas closed claims database to explore different aspects of medical malpractice and personal injury litigation. Other pieces of this project include Black et al. (2005) (trends in overall payouts); Hyman et al. (2007) (comparing jury verdicts with actual payouts); Zeiler et al. (2007) (physician policy limits and out-of-pocket payments); Black et al. (2008) (analyzing defense costs in medical malpractice claims); Hyman et al. (2009a) (estimating effect of various damages caps); and Hyman et al. (2009b) (analyzing effect of insurer duty to settle).

3 Early Offers in Medical Malpractice Cases 725 damages are over $200,000 ($100,000), and thus will normally not be made in these cases. Overall, we predict that early offers will be made in 72 percent of all cases, which represent about 42 percent of current payout. The 70 percent payout reductions estimated by O Connell and co-authors reflect the compound effects of a series of unreasonable assumptions. These include: (1) assuming no minimum damages offer in many cases; (2) assuming that two-thirds of paid damages are noneconomic (we estimate that noneconomic damages represent 40 percent (52 percent) of payout in tried (settled) cases); (3) assuming that current payouts include full payment of economic damages (they do not in many tried cases and are unlikely to in settled cases); (4) treating a fee of 10 percent of economic damages as a market-clearing price for the services of plaintiffs attorneys (it isn t close); (5) ignoring plaintiffs out-of-pocket costs; (6) ignoring the time value of money; and (7) assuming that liability is certain. Defense costs will decline moderately. We estimate that defense costs will drop by roughly 60 percent (20 percent) in currently tried (settled) cases that are resolved with an early offer, or about 13 percent across all cases. This contrasts with O Connell s assumption that defense costs will drop by 70 percent in both tried and settled cases. Our approach and data set have important limitations. Our data come from a single state, albeit a large one. Our simulations require a series of assumptions. For tried cases, these include assumptions about how to allocate payouts to different components of damages, equilibrium fee levels, and plaintiffs ex ante chances of winning at trial in cases that they actually win ex post. For settled cases, we also need to estimate the economic and noneconomic components of payouts. We believe, however, that our assumptions for both tried and settled cases are far more realistic than O Connell s. Our simulation approach ignores how an early offer program might affect which cases are brought, which are taken to trial, and how they are tried. Note, too, that any payout reductions from an early offer program are a wealth transfer, and not a direct social savings. We do not evaluate here the efficiency implications of a change in payouts. Section II provides background on the pretrial settlement process, and describes the Texas medical malpractice data set and our simulation methodology. Section III discusses our data set, and Section IV describes our simulation methodology for tried cases. Section V analyzes how an early offer program will affect tried cases. Section VI extends the analysis to settled cases. Section VII examines how an early offer program will affect different types of plaintiffs. Section VIII examines how such a program will affect defense costs, total defendant costs, plaintiff s net recovery, and system efficiency. Section IX compares our early offer results to those found by O Connell and co-authors. Section X discusses some implications of our findings. Section XI concludes. HOV reply to this article in the next volume of this journal, and we then respond to their reply. 5 We urge those interested in fully understanding the differences in assumptions and analysis that drive the differences in results to read those two articles, as well as this one and the original HOV article. In particular, our response contains a more extensive statement of our assumptions, and how they differ from HOV, than is offered below. 5 Hersch, O Connell & Viscusi (forthcoming); Black, Hyman & Silver (forthcoming).

4 726 Black et al. II. Background A. Settlement and the Pretrial Process In standard litigation models, cost savings and risk aversion drive the parties to settle most cases. Cases go to trial when the parties settlement ranges do not overlap because they disagree on the plaintiff s chances of prevailing, on expected damages, or both. Other factors can enter into the decision whether to settle, such as concern about showing weakness, conveying information about one s reservation amount by being the first to offer settlement, or concern with the implications of a settlement for other cases. 6 Several voluntary programs encourage early settlement. In 2004, the U.S. Department of Health & Human Services (HHS) began a program covering Federal Tort Claims Act claims against HHS. 7 Both sides have 90 days from claim filing to send a settlement offer to a neutral intermediary (the Settlement Depository). Neither side knows if the other side has submitted a settlement offer or the amount of that offer, unless the case is resolved through the program. No data on the results of this program are available. We are also aware of early offer/apology programs run by a major malpractice insurer in Colorado (COPIC), the Universities of Illinois and Michigan, and a Veterans Administration hospital in Lexington, Kentucky. There are reports suggesting that these programs are associated with reduced payouts. However, there has been no peer-reviewed study of these programs, and informal reports suggest that formal apologies alone, plus willingness to settle after admitting wrongdoing, can also reduce payouts (Sack 2008). In separate work, we explore the effect of insurer liability for unreasonable refusal to settle within policy limits on case duration and defense costs. 8 B. O Connell Early Offers In 1982, Professor Jeffrey O Connell proposed an early offer program in a law review article. 9 In the intervening years, in numerous venues, and with numerous co-authors, Professor O Connell has promoted the virtues of early offers. 10 Although the details of the proposal have evolved over time, the general idea is that defendants can offer to settle by paying full economic damages plus a statutorily determined attorney fee, computed as a percentage of economic damages. If no offer is made, the usual tort recovery rules apply. 6 Weise (2001) ( How many times have you heard from outside litigation counsel that... wecan t raise settlement now; it would show weakness. ). 7 Department of Health and Human Services (1994). Hyman is the Settlement Depository for this program. 8 Hyman et al. (2009b). 9 O Connell (1982). 10 O Connell and Robinette (2008) list the full series of articles.

5 Early Offers in Medical Malpractice Cases 727 If the plaintiff rejects an early offer, then to recover anything, the plaintiff must either receive an economic damages award at trial that exceeds the offer, 11 or else face both a higher burden of proof (either clear and convincing evidence or beyond a reasonable doubt) and a lower standard of care (such as gross negligence). 12 Most recently, O Connell, with Joni Hersch and W. Kip Viscusi (HOV), estimated huge payout reductions in medical malpractice cases from implementing his proposal roughly a 70 percent drop in total payouts and a similar drop in defense costs. 13 We discuss this paper in detail below. O Connell then wrote a second article (with Patricia Born) extending the empirical claims to other types of personal injury litigation, and a book (with Christopher Robinette) further developing the early offer proposal. 14 Because the O Connell and Born article and the book largely replicate and extend the analysis in HOV, we focus on HOV in this article. We know of no early offer programs in existence comparable to the O Connell proposal, nor of efforts by other researchers to estimate their effects. 15 III. Data on Medical Malpractice Claims Our data come from the Texas Closed Claims Database (TCCD), a publicly accessible database maintained by the Texas Department of Insurance (TDI). This database contains individual reports of closed personal injury claims covered by mono-line general liability, commercial auto liability, commercial multiperil, medical professional liability, and other professional liability insurance involving payouts by all defendants of more than $10,000 in nominal dollars, closed from 1988 on. When we completed work on this article, data were available through TDI checks the reports for internal consistency and reconciles them against aggregate annual reports filed by each insurer. 11 Or so we infer. Neither Hersch et al. (2007) nor O Connell and Robinette (2008) discuss what happens if the plaintiff can prove larger economic damages than the defendant s offer. O Connell and Robinette (2008) are also silent on this issue. O Connell, Kidd, and Stephenson (2005) state that the higher proof standard would not apply if the plaintiff can show economic damages that exceed the defendant s offer. O Connell has not explained how one would, in practice, handle a jury trial in which the burden of proof and degree of culpability depend on the level of damages. 12 Hersch et al. (2007) state that the plaintiff must show gross negligence beyond a reasonable doubt; O Connell and Robinette (2008:124) suggest that a legislature might choose a clear and convincing evidence standard instead. 13 Hersch et al. (2007). 14 O Connell and Robinette (2008); O Connell and Born (2008). 15 The early offer proposal also allows defendants to reduce their offers by the amount of any collateral source coverage (such as coverage of medical expenses through health insurance). O Connell and Robinette (2008:124). Neither we nor HOV examine this aspect of the proposal.

6 728 Black et al. A. Med Mal Data Set We construct a med mal data set, which includes the following cases. 16 Payout by all defendants is at least $25,000 in 1988 dollars (roughly $45,000 in 2008 dollars). We convert payouts to 1988 dollars using the Consumer Price Index for All Urban Consumers (CPI). 17 The claim meets two of the following three criteria: It was paid under medical professional liability insurance; It was against a physician, hospital, or nursing home; It involved injuries caused by complications or misadventures of medical or surgical care. 18 A claim is an incident causing bodily injury and resulting in a request to an insurer by a policyholder for coverage. An insurer must file a report with the Texas Department of Insurance (TDI) in the year a claim closes when the insurer has made all indemnity and expense payments on the claim. 19 Many med mal cases involve multiple defendants. We reviewed all claim reports to identify duplicate reports. When duplicate reports exist, we treat the last-filed report as the primary report. This report should capture any prior payouts by parties that were not required to file closed claim reports, such as self-insured hospitals. Our sample includes 15,038 distinct cases involving total payouts over of $4.81 billion. The sample includes 358 tried cases with plaintiff verdicts involving allowed verdicts (allowed damages after remittitur and applying damage caps, plus pre- and postjudgment interest) of $468 million and payouts of $255 million For a fuller discussion of the TCCD, the med mal data set, and data set limitations, see Black et al. (2005) (overall data set); Hyman et al. (2007) (jury verdict cases). The Texas Department of Insurance (TDI) Closed Claim Reporting Guide (2004) (containing reporting instructions), the long and short forms, summary Closed Claim Annual Reports, and the data on which we rely are available at 17 Cases with payout of at least $25,000 are reported on a Long Form, which contains the nature of the injury, which we require to classify a claim as involving medical malpractice. The reporting thresholds are not inflation adjusted. Thus, some claims that are reported on the Long Form in later years would have been reported in earlier years on the Short Form used for smaller claims. To address this bracket creep, we limit the sample to cases with payout of at least $25,000 in 1988 dollars. 18 Other types of health-care providers (e.g., nurses and free-standing medical clinics) are not separately listed in the Long Form. We also include cases that meet one of these three criteria and otherwise seem likely to involve medical malpractice. For example, we include cases against nursing homes that were paid under other professional liability rather than under medical professional liability insurance. We exclude cases that meet two of these criteria, but seem unlikely to involve medical malpractice. Thus, we exclude cases paid under automobile liability insurance even if they meet the other two criteria. In identifying duplicate reports, we sometimes exercised judgment when claim reports were similar but not identical. Insurers also make some reporting errors that TDI does not catch. In a few cases when both the error and the correction were apparent, we corrected the underlying data. Details on the procedure we used to identify duplicates, the data adjustments we made, and our inclusion rules are available from the authors on request. 19 TDI, Closed Claim Reporting Guide (2004:18). 20 Our data set also includes 51 cases with a defense verdict followed by a payout $25,000. Most of these payouts appear to reflect high-low agreements. See Hyman et al. (2007). We exclude defense verdict cases from our analysis, since there is no basis on which to allocate the payout to economic versus noneconomic damages.

7 Early Offers in Medical Malpractice Cases 729 B. General Data Set Limitations The TCCD includes only insured claims. We lack claims against pure self-insured providers (which do not rely on captives or risk pooling). Most physicians carry malpractice insurance, but many hospitals do not. We lack data on claims against the University of Texas (UT) hospital system and UT-employed physicians. Thus, our data set likely captures most trials in which physicians make payments, but a smaller and unknown fraction in which the payers are hospitals and other providers. We have data on plaintiff age, employment status, and county of injury, but not injury severity, gender, or county of residence. We lack data on cases with zero or small payout. We have data on tried cases with defense verdicts only when they result in a payout. IV. Simulation Methodology for Tried Cases We now turn to estimating the effects of the O Connell early offer program. Our basic approach is to simulate the effect by applying the early offer rules (payment of full economic damages and attorney fees, but not noneconomic or punitive damages) to the cases in our data set. For tried cases, we have many of the data we need to simulate the program s effect. Where we lack data, we make explicit assumptions, and then vary the assumptions to test the sensitivity of our results to those assumptions. For settled cases, we have fewer data and thus must make stronger assumptions. This simulation approach builds on a similar approach that we developed in prior work to estimate the effect of damages caps on payouts. 21 Texas had caps on punitive damages, and on the sum of economic damages, noneconomic damages, and prejudgment interest in death cases throughout our sample period. We refer to these caps, together with remittitur, as other caps. The payouts we observe, and thus our estimate of how an early offer program would affect payouts, are after the effect of these other caps. Our sample period largely precedes Texas s adoption of a cap on noneconomic damages (nonecon cap). We simulate below how the Texas nonecon cap would affect our results. Our data set includes 358 tried med mal cases with damage awards. The TCCD reports the amount awarded by the jury as economic, nonecon, and punitive damages, and the lump sum paid to resolve the case. To estimate the impact of an early offer program, we first determine for each case the allowed damages of each type, after other caps. We then gross-up the awarded and adjusted damages of each type by adding prejudgment and postjudgment interest to each. This approach treats interest as compensating for the time value of money, beginning as of the time when prejudgment interest begins to accrue, generally 180 days after suit is filed. We refer to the sum of awarded damages (allowed 21 Hyman et al. (2009a).

8 730 Black et al. Table 1: Allowed and Paid Damages in Tried Cases Economic Damages Nonecon Damages Punitive Damages Total Adjusted verdict $202,743 $283,384 $32,103 $518,230 Allowed verdict $198,974 $247,197 $22,207 $468,377 Payout (before payout bonus) $146,554 $102,638 $5,815 $255,006 Present value of allowed verdict $161,090 $192,241 $16,328 $369,660 Present value of payout $118,341 $80,784 $4,103 $203,228 Mean (median) PV of payout $398 ($78) $306 ($151) $256 ($113) $568 ($220) Column as % of total payout 58.2% 39.8% 2.0% 100% Payout as % of allowed verdict 73.5% 42.0% 25.1% 55.0% Note: Adjusted verdict, allowed verdict, and total payout for tried cases. Present value is measured at six months from date of suit. Data set is 358 nonduplicate cases with plaintiff verdicts included in the med mal data set of claims closed from with payout $25,000 in 1988 dollars. Allocation rules for payout are stated in the text. Total payout excludes payout bonus of $5.9 million (present value). Mean and median for each type of damages are for cases with nonzero awards of this type. Four outlier punitive awards are winsorized at level of next highest punitive award ($2.76 M). Amounts in thousands of 1988 dollars. damages), including the gross-up for interest, as the adjusted verdict ( allowed verdict ). We compute paid damages by allocating the payout to allowed damages as follows: 22 First, to allowed economic damages until payout is exhausted or these damages are fully paid (paid econ damages); Second, to allowed nonecon damages until payout is exhausted or these damages are fully paid (paid nonecon damages); Third, to allowed punitive damages until payout is exhausted or these damages are fully paid (paid punitive damages). 23 This approach assumes that the parties have lexical priorities in allocating payout to damages, with economic damages paid first, nonecon damages second, and punitive damages third. This assumed priority is consistent with the policy premises underlying the early offer concept, and with our interviews of plaintiff s attorneys. 22 About one-third of claim reports do not include prejudgment interest. For these cases, we estimate prejudgment interest based on the statutory rates in effect during different periods. For most of our sample time period, prejudgment interest was set by statute at 10 percent simple annual interest, postjudgment interest was 10 percent interest compounded annually, and there was no prejudgment interest on punitive damages. Under Texas law, prejudgment interest is generally computed from 180 days after the earlier of when the suit was filed or written notice of the claim was received. We lack information on when plaintiffs provide written notice to defendants, so use the lawsuit filing date as the starting date. For details on the Texas rules and how we computed pre- and postjudgment interest, see Hyman et al. (2007). Our data set includes nine cases tried to a judge, rather than a jury. In robustness checks, we obtain similar results if we exclude these cases. Four cases involve large punitive damage awards ($6.9 M, $7.3 M, $16 M, and $41 M), most of which exceeded the Texas cap on punitive damages, and none of which were paid. We winsorize the punitive damages in these cases at the level of the next largest punitive award ($2.76 M). 23 In some cases, defendants pay more than the adjusted verdict. We exclude this payout bonus from our analysis, since we cannot predict how an early offer program would affect it. There is a payout bonus in 37 cases, with a mean (median) of $161,000 (45,000).

9 Early Offers in Medical Malpractice Cases 731 Table 1 shows the results for the tried cases in our data set. Of the total payouts in tried cases, 58 percent reflect economic damages, 40 percent reflect nonecon damages, and 2 percent reflect punitive damages. On average, 73 percent of allowed economic damages are paid, but only 42 percent of allowed nonecon damages, and 25 percent of allowed punitive damages. We discuss the reasons for the gap between allowed and paid damages in prior work. 24 Our simulation approach holds constant the manner in which cases are chosen and brought and applies a hypothetical early offer program to cases that were brought without the program in place. An actual early offer program will affect plaintiff s lawyers choice of which cases to bring, which to take to trial, and how cases are developed and tried. We cannot address those effects. 25 We also do not study how an early offer program will affect total payouts in all cases, or insurance premiums. Those effects will depend in part on endogenous changes in case selection and handling. V. Early Offers in Tried Cases To determine the impact of an early offer program, we must specify its rules in a form that we can simulate with our data set. We assume that the program would work as follows. Plaintiffs and defendants agree on the level of economic damages. Defendants may make a settlement offer equal to 100 percent of economic damages plus a specified percentage meant to cover reasonable attorney fees and litigation-related expenses (we will refer to this loosely as the fee percentage ). The fee percentage must be enough to cover the value of the attorney s time and expenses, both in cases that result in a payout and those that do not. Below, we make various assumptions as to whether defendants will make qualifying offers in all cases, or only in specified subsets of cases. To address cases with zero or low economic damages, the program may require a minimum offer, regardless of the level of economic damages. If the defendant makes a qualifying offer, the plaintiff must either accept the offer or face a large penalty for rejecting the offer. That penalty could involve limits on collecting damages above the offer, a higher burden of proof for some or all damages, a fee-shifting rule, or other possibilities. We follow HOV in assuming that the stick is large enough so that the offer, if made, will be accepted. We also follow HOV in assuming offers will be made six months after suit is filed. The timing of offers is not critical to our analysis, as long as offers made later than this must include prejudgment interest. The starting place for analysis is to recognize that under the current system, defendants often pay less than the jury award, and do not pay the plaintiff s attorney fees Hyman et al. (2007). 25 In most states, jurors are not told of the existence of damage caps. If jurors were told of the existence of the O Connell early offer program, it is unclear how that would affect damage awards. 26 Id. See also Hyman et al. (2007).

10 732 Black et al. Whether an early offer program will affect payouts turns on whether fast payment of 100 percent of economic damages plus attorney fees is larger or smaller in present value than the status quo (slower payment of less than 100 percent of economic, noneconomic, and punitive damages). In algebraic terms, if paid economic (noneconomic) damages are E (NE), full economic damages are E full, and the fee percentage is y, an early offer is appealing to defendants if: ( E+ NE)> E full ( 1+ y ). A. Graphical Overview of Payout Changes Our base case assumes that the fee percentage is 30 percent of gross payout. 27 References to fee percentage are to percentage of gross payout, unless otherwise specified. This compares to a current norm of a one-third attorney fee plus out-of-pocket costs. Given typical out-of-pocket expenses, the current norm involves mean fees and expenses of about 36 percent. Thus, our base case assumes about a one-sixth reduction in plaintiff-side litigation costs. Below we discuss why a 30 percent fee is reasonable and examine how varying this percentage affects our results. We initially assume that liability is certain, but relax this assumption below. We discount all payouts back to present value as of six months after suit was filed, using the statutory rate for interest (both prejudgment and postjudgment) for these periods. This puts these actual payouts on the same time footing as early offers, which we assume (following HOV) occur six months after suit is filed. Suppose, for example, that the prejudgment interest rate is 10 percent simple interest, as it was for most of our sample period, a trial was held three years after suit, and a payout of $125,000 is made soon thereafter. We would discount this payment back to six months after suit. It would be equivalent in present value to an $100,000 early offer. In Figure 1, we show how the early offer program affects payouts, under different assumptions about the details of the program. Each bar includes stacked subbars, with each subbar reflecting payout components (i.e., economic, noneconomic, and punitive damages, minimum offers, and attorney fees). The first bar shows the actual payout in the 358 plaintiff verdict cases in our data set. The second bar, labeled no minimum offer, shows the expected payout under an early offer program, assuming (unrealistically) that there is no minimum amount for a qualifying offer; an offer is made in all cases; and liability is certain. Compared to the first bar, economic damages rise, to reflect full payout of these damages. A new area for attorney fees also appears, but noneconomic and punitive damages drop out. The rise in paid economic damages and the payout of attorney fees 27 If the fee as a fraction of gross payout is y, the fee will equal x = y/(1 - y) as a fraction of the plaintiff s net recovery after the fee. So, if the gross fee fraction is 0.30, percentage is 30 percent, the fee as a fraction of economic damages would be For example, if economic damages are $100,000, attorney fees plus expenses will be $42,857, the gross payout would be $142,857, and (fees + expenses)/gross payout will be $42,857/$142,857 = 30%.

11 Early Offers in Medical Malpractice Cases 733 Figure 1: Impact of early offer program on payout in tried cases. 120% 100% 80% 60% 40% 20% 0% Actual payout No minimum offer 50k minimum offer Punitive damages Nonecon damages Fees Minimum offer Economic damages 50k minimum, 50k minimum, no offer if no offer if econs > 200k econs > 200k, 75% plaintiff chances Note: Figure shows in percentage terms total actual payout (brought to present value as of six months from date of suit) in 358 nonduplicate med mal cases with plaintiff verdicts, closed from with payout $25,000 in 1988 dollars, and predicted payout under different variants of an early offer program. Second, third, and fourth bars assume an early offer is made in all cases. Second bar shows payout under early offer rule, with early offer = economic damages. Third bar also requires a minimum damages offer of $50,000. Fourth (fifth) bar assumes a $50,000 minimum damages offer and no early offer if economic damages > $200,000. All early offer variants assume attorney fees and expenses = 30% of gross payout. Amounts in 1988 dollars. more than offsets the elimination of noneconomic and punitive damages. Overall, payouts would increase by 11 percent, relative to the status quo. The next three bars of Figure 1 progressively introduce more realistic assumptions. First, a rule that lets defendants settle cases with zero or small economic damages for very low amounts ($0, for the 17 percent of cases with zero awarded economic damages) is not realistic. We cannot imagine any legislature deciding that a fair offer for negligently causing the painful death of a retired person, with no economic damages, is $0. In the third bar, we therefore assume a minimum damages offer of $50,000. Including the fee percentage, the minimum total offer would be $71,400. Of the 358 tried cases in our data set, about half (177) had $50,000 or less in paid economic damages. As the third bar reflects, payouts would then increase by 18 percent, relative to the status quo. (If we were to instead assume a minimum damages offer of $100,000 ($143,000 including the fee percentage), payouts would increase by 25 percent.) Below, we assume a $50,000 minimum damages offer, unless otherwise specified. Second, defendants will not make early offers in all cases. Early offers become progressively less attractive to defendants as economic damages increase. Table 2 shows how the change in expected payout from making early offers varies with the level of economic damages. Payouts drop by 77 percent for cases with zero economic damages (despite the $50,000 minimum damages offer); by 61 percent for economic damages between $1 and $100,000; and by 32 percent if economic damages are from $100,000

12 734 Black et al. Table 2: Early Offer Effect on Payout in Tried Cases, by Level of Economic Damages Allowed Economic Damages Range No. of Cases Allowed Econ Damages Total Payout Early Offer Payout Early Offer % Change in Payout $ ,689 4,357 14, % >$0 but <$100 k 153 5,065 30,346 11,951 18, % $100 k, but <$200 k 42 6,093 12,777 8,705 4, % All cases <$200 k ,159 61,812 25,014 36, % $200 k, but <$500 k 37 11,607 19,769 16,582 3, % $500 k, but <$1 M 30 20,401 22,476 29,145-6, % $1 M, but <$2.5 M 20 31,186 33,746 44,551-10, % $2.5 M 15 86,737 65, ,910-58, % All cases , , ,202-35, % Note: Total allowed economic damages, actual payout (brought to present value as of six months from date of suit), and early offer, for cases with allowed economic damages in indicated ranges, for 358 nonduplicate med mal cases with plaintiff verdicts, closed from with payout $25,000 in 1988 dollars. Early offer = (max(economic damages, $50,000)) + (attorney fees and expenses of 30% of gross payout). Amounts in thousands of 1988 dollars. $200,000. These cases account for 72 percent of tried cases, but only 7 percent of allowed economic damages and 30 percent of payouts. Predicted payouts also decline for cases with economic damages from $200,000 $500,000, but these payout reductions will vanish once we relax the assumption of 100 percent plaintiff chances of success (see Figure 2). Early offers will increase payouts for cases with economic damages over $500,000, dramatically so for cases with economic damages over $2.5 million. The fourth bar in Figure 1 assumes that early offers will be made only in cases with economic damages greater than $200,000. Total predicted payouts now decline by 18 percent. To the extent that defendants can do a more nuanced job of assessing which cases are likely to involve a high ratio of noneconomic to total damages, and hence may warrant early offers, this bar will underestimate the overall payout decline from an early offer program. We address the final bar in Figure 1 below. B. Varying Plaintiffs Chances of Winning at Trial We next relax the clearly false assumption that liability is certain. In fact, plaintiffs lose 75 percent of med mal trials 28 and, overall, about 80 percent of insurer claim files are closed without payment. 29 We have 358 cases with plaintiff verdicts in our sample, and therefore estimate that there were roughly 3 * 358 = 1,074 trials with defense verdicts over our sample period, mostly unobserved. A few of these cases may have gone to trial even though liability 28 We lack data on this proportion in Texas, but 75 percent defense wins is a reasonable national estimate. See Cohen (2004) (plaintiff win rates for 1992, 1996, and 2001; Bureau of Justice Statistics surveys ranged from percent, with mean of 27 percent); Studdert et al. (2006) (21 percent plaintiff win rate). 29 See Black et al. (2005).

13 Early Offers in Medical Malpractice Cases 735 Figure 2: Early offer programs and different plaintiff chances of winning. 75% 50% % change in payout 25% 0% -25% -50% -75% 100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% Plaintiff's chance of winning $0, but < $100k $100k, but < $200k $200k, but < $500k All cases, lesser of payout or early offer Note: Figure shows how percentage change in total payout from early offer program (brought to present value as of six months from date of suit) varies with ex ante plaintiff s chances of winning, for cases within indicated economic damage ranges, for 358 nonduplicate med mal cases with plaintiff verdicts, closed from with payout $25,000 in 1988 dollars. Early offer program includes a $50,000 minimum damages offer and (attorney fees + expenses) of 30 percent of gross payout. Heavy line assumes offers are made only in the payout ranges for which economic damages would decline (see text for details). Amounts in 1988 dollars. was certain or nearly so because the parties could not agree on damages, but more often, liability is uncertain as well. Uncertainty about liability will make early offers less attractive to defendants. Suppose, for example, that the defendant estimates economic damages of $500,000 and noneconomic damages of $300,000. If liability is certain, a $500,000 early offer plus a 30 percent fee ($714,000) reduces expected payout by $86,000. But if the defendant estimates a 75 percent (50 percent) chance of being found liable, the same early offer would instead increase expected payout by $102,000 ($289,000). Using the terms defined earlier, if paid economic (noneconomic) damages are E (NE), full economic damages are E full, and plaintiff chances of prevailing are z, the expected payout from going to trial is (E + NE) * z. If (fees + expenses) as a fraction of economic damages are y, then an early offer of E full *(1+ y) is attractive if: ( E+ NE)> E full ( 1+ y) z. An early offer thus becomes steadily less attractive as the plaintiff s chances decrease. We lack data on the ex ante odds of plaintiff success for the tried cases in our data set, which plaintiffs in fact won, viewed ex post. We address how these odds affect an early offer program using two approaches. First, we use a simple algebraic approach in which we assume that the cases in our data set that plaintiffs won ex post all had the same ex ante chances of plaintiff success. We assume the defendant knows the plaintiff s ex ante chances

14 736 Black et al. on average. We vary that plaintiff win probability from 100 percent down to 50 percent. Second, we use a simulation approach, in which we assume that the cases we observe are draws from a smooth distribution of cases with a specified mean chance of success, which varies from 100 percent to 50 percent, which we again assume the defendant knows. 30 We obtain similar results with both approaches, and present here the algebraic results. Details on how we implement each approach are in Appendix A. Figure 2 shows how the plaintiff s chances of success affect the overall change in payout from an early offer program. The top line in the figure shows the change in payout for cases with economic damages from $200,000 $500,000. Defendants can achieve small payout reductions in these cases if liability is certain. They will break even if there is a 85 percent probability of liability, and pay more if the probability of liability is 80 percent or less. However, as we discuss in Appendix A, it is difficult to construct plausible distributions in which the mean chances of plaintiff success, in cases which plaintiffs win ex post, are greater than 75 percent or, at the most, 80 percent. At a 75 percent success rate, payouts will increase by 12 percent. Thus, we would generally not expect defendants to make early offers in cases with economic damages from $200,000 $500,000. We accordingly so assume in this article, unless otherwise specified. The middle curved line in Figure 2 shows the change in payout for cases with economic damages from $100,000 $200,000. Once again, the percentage payout reduction falls as the plaintiff s chance of prevailing drops, from 32 percent if liability is certain, to about 9 percent if plaintiffs chances of prevailing are 75 percent. Predicted payouts will increase if plaintiffs chances are 65 percent or less. The bottom line in Figure 3 shows how the chances of liability affect expected change in payout for cases with economic damages of $0 to $100,000. Here, early offers are attractive to defendants across the full range of plaintiff chances. In many of these cases, the $50,000 minimum damages offer will exceed the expected value of the damages (which equals full economic damages/plaintiffs chances of prevailing), so plaintiffs chances of prevailing will not affect the expected payout. For such cases, the estimated payout reduction declines gently from 67 percent if liability is certain to 56 percent if plaintiffs mean chances are 50 percent. To summarize these results, we expect defendants will make early offers in all cases if economic damages are less than $100,000; and for plaintiff chances of 70 percent or higher if economic damages are from $100,000 $200,000; and only for plaintiff chances of percent if economic damages are $200,000 or higher. 31 The heavy line in Figure 3 shows how plaintiffs chances affect expected payouts, assuming that defendants will make early offers in all cases where expected payout is thereby reduced. The overall decline in payout varies gently from 20 percent (with 100 percent chance of liability) to 14 percent (with 50 percent chance of liability). 30 For both approaches, defendants will make early offers in some cases that we observe (do not observe) because the plaintiff won (lost) ex post. We also assume that the cases we observe are representative, in damages amounts, damages allocation, and payouts, of all cases in which early offers are made. 31 Most cases with economic damages over $200,000 will still settle, but for lower amounts than a qualifying early offer. The early offer option will not greatly affect settlement dynamics for these cases.

15 Early Offers in Medical Malpractice Cases 737 Figure 3: Fee percentage and payout changes for early offer program. 30% Change in total payout (%) 20% 10% 0% -10% -20% -30% 10% 15% 20% 25% 30% 35% Fee percentage no minumum offer 50k minimum, no offer if econs > 200k 50k minimum offer Note: Percentage change in total payout (brought to present value as of six months from date of suit) under different variants of an early offer program and varying (fee and expense) levels, as a percentage of gross payout, for 358 nonduplicate med mal cases with plaintiff verdicts, closed from with payout $25,000 in 1988 dollars. No minimum offer line shows change in payout for early offer = economic damages + indicated percentages of gross payout. 50 k minimum offer line requires a minimum damages offer of $50,000. Bottom line assumes $50,000 minimum damages offer and no early offer if economic damages exceed $200 k. Amounts in 1988 dollars. Returning to Figure 1, the final bar shows expected payout assuming a 75 percent chance of liability. Overall payout declines by 16 percent (compared to 18 percent if liability is certain). This decline comes almost entirely (96 percent) from cases with economic damages of $100,000 or less. In this scenario, early offers are made in 256/358 (72 percent) of currently tried cases. C. Varying the Fee Percentage Payouts under an early offer program are directly influenced by the fee percentage. Figure 3 shows how varying this percentage from 10 percent (close to the 9 percent level assumed by HOV) to 35 percent (close to current norms) influences payouts. We report results for the first three of the four variations developed in Figure 1; a line for the fourth variation would be very similar to, but slightly above, the third line. Figure 3 reports results for a broad range of fee percentages. However, as we discuss in Section VIII, fee percentages lower than 25 percent are not realistic as market rates. Not surprisingly, a higher fee percentage increases the payout from an early offer program. For the two upper lines in Figure 3 (no minimum offer and $50,000 minimum

16 738 Black et al. offer), each 5 percent increase in the fee percentage increases predicted payouts by 6 7 percent. As the bottom line reflects, the slope of the line is far lower if, as we expect, defendants generally will not make offers in cases with economic damages over $200,000. This is simple arithmetic: payouts in cases with early offers will be a small fraction of total payouts (about 15 percent of total payouts with a 30 percent fee percentage). The fee on these payouts is a small fraction of defendants total costs, whatever the fee percentage. D. Interaction with Caps on Noneconomic Damages We have thus far assumed no cap on noneconomic damages. However, 26 states cap noneconomic damages. An early offer program can be understood as a particular type of nonecon cap, available at the defendant s election. For example, if liability were certain, an early offer program with a $50,000 minimum offer and a 30 percent fee can be understood as similar to a cap on noneconomic damages at the greater of (1) ($71, percent of economic damages) or (2) 43 percent of economic damages, conditioned on full payment of economic damages. If a state directly caps noneconomic damages, the early offer program will often largely or entirely affect payment of damages that are already above the cap. This will reduce the impact of the early offer program. In deciding whether to make an early offer, defendants will take into account only the below-cap portion of an expected award of noneconomic damages. Texas adopted a nonecon cap toward the end of our sample period. This cap is not inflation adjusted, is $250,000 (nominal) for an institutional defendant or for one or more individual defendants, but can be as high as $750,000 (nominal) if there are both two liable institutional defendants and one or more liable individual defendants. In prior work examining the effect of this cap, we found that the Texas cap is roughly equivalent to a simple cap on noneconomic damages of $318,000 (nominal), regardless of number and type of defendants. 32 As in our previous work, we model the Texas cap by treating it as constant in real dollars at the equivalent of $250,000 in 2003 dollars for a single defendant (about $161,000 in the 1988 dollars we use in this article). We estimate how an early offer program will affect payouts if applied on top of the Texas nonecon cap by adjusting the methodology described above to include the cap. First, we estimate allowed damages after all caps by applying the nonecon cap to allowed damages after other caps. Second, we estimate paid noneconomic damages and total payout after all caps. Third, we estimate the effect of the early offer program on payouts. Figure 4 shows the results. The first bar shows payout after other caps. The second bar shows the effect of the Texas nonecon cap, which reduces total payout by 22 percent. The third bar in Figure 4 shows predicted payout with a nonecon cap plus an early offer program with a $50,000 minimum damages offer, offers not made if economic damages are greater than $200,000, and 100 percent plaintiff chances of success. Predicted payout with a $50,000 minimum offer declines by 9 percent (compared to 18 percent in Figure 1 without 32 Hyman et al. (2009a). The Texas cap affected none of the 358 plaintiff verdict cases in our data set (only three postcap cases had been closed by year-end 2005, and none involved an above-cap award of noneconomic damages), and applied to only 222 of the roughly 15,000 settled cases in our data set.

17 Early Offers in Medical Malpractice Cases 739 Figure 4: Interaction of nonecon cap and early offers. 100% 80% 60% 40% 20% 0% Actual Payout (after other caps) Predicted Payout (after all caps) 50k minimum, no offer if econs > 200k 50k minimum, no offer if econs > 100k, 75% plaintiff chances Punitive damages Nonecon damages Fees Minimum offer Economic damages Note: Figure shows in percentage terms total actual payout (brought to present value as of six months from date of suit) in 358 nonduplicate med mal cases with plaintiff verdicts, closed from with payout $25,000 in 1988 dollars, predicted payout after applying the Texas nonecon cap, and predicted payout after also applying variants of an early offer program. First bar shows actual payout; second bar shows payout with the nonecon cap; third bars show payout with nonecon cap, early offer equal to economic damages, $50,000 minimum damages offer, and no early offer if economic damages > $200,000 made in all cases. Fourth bar is same as third, except assumes 75 percent plaintiff chances of success and no early offer if economic damages > $100,000. All early offers include (attorney fees + expenses) at 30 percent of gross payout. Amounts in 1988 dollars. the nonecon cap). The final bar assumes a 75 percent chance of plaintiffs winning, and limits early offers to economic damages of $0 $100,000, which is the range over which early offers would reduce predicted payouts with a nonecon cap in place and these plaintiff chances. Predicted payouts decline by 7 percent (compared to 16 percent without a nonecon cap). Of course, the Texas nonecon cap is not the only type of nonecon cap. A more (less) restrictive nonecon cap would leave less (more) room for defendants to gain from making early offers. VI. Early Offers in Settled Cases Cases settled without a full trial (settled cases) represent 98 percent of cases and 95 percent of payouts, so it is important to assess the impact of an early offer program on these cases. In this part, we extend our results for tried cases to settled cases. Our central approach is to extrapolate from tried cases, to estimate the amount of paid economic and noneconomic damages in settled cases. We first divide cases into eight subgroups (Section VII provides details on the groups) with similar demographics (age, employment, and type of harm), but that differ in these ratios. For example, elderly death cases, on average, have a 16 percent

18 740 Black et al. Figure 5: Impact of early offer program on payout in settled cases. 120% 100% 80% 60% 40% 20% 0% Actual payout No minimum offer 50k minimum offer Punitive damages Nonecon damages Fees Minimum offer Economic damages 50k minimum, no offer if econs > 200k 50k minimum, no offer if econs > 100k, 75% plaintiff chances Note: Figure shows in percentage terms total actual payout (brought to present value as of six months from date of suit) in 14,680 nonduplicate med mal cases settled before verdict, closed from with payout > $25,000 in 1988 dollars, and predicted payout under different variants of an early offer program. Second, third, and fourth bars assume an early offer is made in all cases. Second bar shows payout under early offer rule, with early offer = economic damages. Third (fourth) bar also requires a minimum damages offer of $50,000 ($100,000). Fifth bar assumes a $50,000 minimum damages offer and no early offer if economic damages > $200,000. All early offer variants assume attorney fees and expenses = 30% of gross payout. Amounts in 1988 dollars. ratio of total paid economic damages/total payout, compared to 72 percent for baby cases. We then use a bootstrap approach, in which we assign ratios drawn from tried cases in the same subsample to settled cases, at random and with replacement. Appendix B provides details on our methodology and on robustness checks. We have less confidence in the results for settled cases, due to the need to make additional assumptions, including extrapolating from tried to settled cases, even though there are likely to be unobserved differences between tried and settled cases. In robustness checks, the simulated ratio of paid economic damages/total payout ranged from 46 percent (in our actual bootstrap approach) to 52 percent. This compares to 58 percent in tried cases. A lower ratio implies larger payout reductions from an early offer program. Our simulation results for settled cases are broadly similar to those for tried cases. Early offers will substantially reduce payouts in cases with small economic damages. They will have a more moderate impact on cases with economic damages from $100,000 $200,000. Early offers will normally not be made in cases with economic damages greater than $100,000 because payouts would rise if offers were made in these cases. Overall, early offers will be made in 72 percent of settled cases. Figure 5 has the same general format as Figure 1. The first bar shows the estimated breakdown of actual payouts in settled cases. Settled cases are more likely to involve plaintiff demographics that predict a high ratio of noneconomic/total damages, so the mean ratio of noneconomic/total damages is 52 percent in settled cases, compared to 40 percent in tried cases. The second bar shows the impact of an early offer program with no minimum

19 Early Offers in Medical Malpractice Cases 741 offer, a 30 percent fee, and an offer made in all cases. Paid economic damages increase because previously unpaid economic damages now must be paid in full. However, noneconomic and punitive damages drop out. Overall, predicted payouts now rise by 5 percent (vs. 13 percent for tried cases in Figure 1). The next three bars of Figure 5 progressively introduce more realistic assumptions. In the third bar, we assume a minimum damages offer of $50,000. Predicted payout increases by 17 percent (compared to 18 percent for tried cases). In the fourth bar, we also assume that an offer will be made only if estimated economic damages are less than $200,000. Appendix B, Table B-2 confirms that for settled cases, similar to Table 2 for tried cases, this is the damages range in which defendants will gain by making early offers. Predicted payout decreases by 25 percent (compared to 18 percent for tried cases). We also assessed which cases were likely to produce early offers if plaintiffs chances of prevailing are less than 100 percent. Most settled cases likely involve a significant ex ante chance that the plaintiff will lose at trial. This risk will be reflected in a settlement for less than full damages. An early offer, however, must include full economic damages. Thus, the lower the chances of plaintiff success, the less defendants stand to gain by making early offers. 33 Unless plaintiff chances of prevailing are 77 percent or greater, defendants will only make early offers in cases with economic damages less than $100,000. The final bar in Figure 5 assumes a 75 percent plaintiff chance of prevailing, and early offers made in cases with economic damages less than $100,000. Overall expected payouts now decline by 20 percent (vs. 16 percent in tried cases). Early offers will be made in 72 percent of settled cases; these cases represent 8 percent of economic damages and 42 percent of payout. Our results for settled cases are similar to those for tried cases. Overall payout declines somewhat more in settled cases because these cases tend to be smaller, and thus are more likely to involve economic damages in a range that makes early offers attractive to defendants. VII. Distributional Impact So far, we have focused on how an early offer program will affect payouts. We found large payout reductions in cases with small economic damages. In this section, we examine a related question: How will an early offer program affect different plaintiff groups? Prior studies have shown that nonecon caps disproportionately affect some groups, especially the elderly and the unemployed. 34 An early offer program also targets noneconomic damages, so is likely to disproportionately affect the same groups. We confirm that intuition below. 33 The (paid) settlement value of economic damages = full economic damages * chance of liability. Defendants who make early offers must pay full economic damages, which = (settlement value of economic damages)/(chance of liability). For tried cases, we know economic damages but not settlement value; for settled cases, we know settlement value but not economic damages. For both, the algebra is the same: the ratio of (early offer)/(ex ante expected payout) increases as the chance of liability declines by a factor of 1/(chance of liability). 34 Hyman et al. (2009a); Rubin and Shepherd (2007, 2008); Studdert et al. (2004).

20 742 Black et al. To assess how an early offer program will affect different plaintiff groups, we return to tried cases and divide our sample into eight subsamples based on plaintiff age, employment status, and nature of harm. Babies (age 0 1 month); Children (age 2 months 18 years); Adult nonelderly (age 19 64); divided into subsamples of employed plaintiff and nondeath outcome, unemployed nondeath, employed death, and unemployed death; Elderly (age 65+); divided into subsamples of death and nondeath. We chose the subsamples based on characteristics that, for tried cases, predict differences in the ratio of economic/total damages, while requiring a large enough subsample size to make it reasonable to draw conclusions about the subsample. In an earlier paper, we used the same subsamples to estimate the impact of a nonecon cap on payouts in tried and settled cases. 35 Table 3 shows results in tried cases for each group, assuming no offer if economic damages greater than $200,000; a 30 percent fee; and 100 percent plaintiff chances of success. The first part of Table 3 shows results for each subgroup. The second part shows results for different combinations of subgroups. The first three columns of Table 3 show plaintiff age and status and the number of plaintiff verdict cases for each group. The fourth column shows the ratio of total paid economic damages for all cases in a group to total paid damages for that group. This ratio varies widely, from 13 percent in elderly death cases to 75 percent in adult employed nondeath cases. These differences drive differences in how an early offer program affects aggregate payout for all cases within that group (fifth column). Baby cases are scarcely affected (4 percent decline in aggregate payout), but aggregate payouts to elderly deceased plaintiffs decline by 66 percent. More generally, early offers strongly affect death cases (45 percent aggregate payout reduction) compared to nondeath cases (12 percent aggregate reduction). The sixth column of Table 3 shows the mean of the per-case percentage change in payouts for the cases in each group. These percentages are smaller in magnitude than the percentage change in aggregate payout. Some are positive even when the aggregate percentage change is negative. If defendants can cherry-pick the cases in which they make early offers, the aggregate percentage decline in payout will be larger, and the mean of the per-case percentage changes will likely be negative. The final column shows a t test for differences in the means of the per-case fractional changes in payout, for selected pairs of groups. In general, payout reductions are larger in death cases versus nondeath cases; elderly cases versus adult nonelderly cases; and adult nonelderly unemployed cases versus employed cases. Thus, although the early offer program is facially neutral, its impact varies greatly depending on plaintiff demographics, employment status, and type of harm. 35 Hyman et al. (2009a).

21 Early Offers in Medical Malpractice Cases 743 Table 3: Impact of Early Offer Program on Payout Received by Different Plaintiff Groups Age Status Number of Cases Total Paid Econ Damages/ Total Payout % Change in Aggregate Payout Mean (Per-Case % Change in Payout) t Test Elderly Death % -65.8% -53.6% 2.47** Nondeath % -44.3% -6.6% Unemployed, death % -49.3% -44.6% 1.51 Unemployed, nondeath % -39.2% -11.5% Employed, death % -26.7% -46.1% 2.93*** Employed, nondeath % -10.1% 25.1% Children All % -8.6% -10.0% 0.06 Baby % -4.0% -7.8% All Death % -45.4% -48.1% 4.98*** Nondeath % -12.2% 10.2% Elderly All % -54.0% % 1.91* All % -22.3% 1.51% Unemployed % -43.3% % 2.84*** Employed % -12.9% 15.85% All All % -18.1% -5.03% Note: Percentage impact of early offer program on different plaintiff groups for 358 med mal cases with plaintiff verdicts, closed from with payout $25,000 in 1988 dollars. Early offer program is assumed to include $50,000 minimum damages offer, no offer if economic damages > $200,000; (fees + expenses) = 30% of gross payout; and 100 percent plaintiff chances of success. First three columns specify plaintiff characteristics and number of cases in each group. Next three columns show aggregate ratio of paid economic damages/total paid damages, percent change in aggregate payout, and the mean of the per-case percentage changes in payout in each group. Last column shows t test for differences in per-case mean change in payout for indicated pairs of groups (test based only on cases in which early offers would be made). * (**) (***) indicates significance at the 10 percent (5 percent) (1 percent) level. Amounts in 1988 dollars. VIII. Defense Costs, Total Costs, Plaintiff Net Recoveries, and System Efficiency Part of the argument for an early offer program is that it will speed settlement and reduce litigation costs. Our estimates above already reflect the time value of money faster payment of the same amount is worth more to plaintiffs, but costs more to defendants. We cannot directly assess any additional value to plaintiffs of faster settlement. We examine in this section how an early offer program will affect defense costs, defendants total costs, plaintiffs counsel fees, net payouts to plaintiffs after these fees, and what fraction of defendants total costs end up in plaintiffs pockets which is one measure of system efficiency. A. Defense Costs An early offer program will produce faster settlements and lower payouts in cases suitable for early offer. We confirm in earlier work the intuition that the sooner a malpractice case

22 744 Black et al. closes and the smaller the payout, the less the insurer spends on defense costs. 36 But by how much? Much defense spending is front-loaded the insurer needs to assess liability and economic damages, and must usually hire an expert. If a case is early offer suitable, the insurer can avoid estimating noneconomic damages, but this is likely to be a small portion of total cost. We estimate the impact of early offers on defense costs in two steps. First, using early offer suitable cases (economic damages < $200,000 for tried cases and < $100,000 for settled cases), we regress ln(defense costs) on ln(payout), ln(duration), resolution stage dummy variables, and other control variables. 37 Second, we use the regression coefficients to predict defense costs using early offer payout instead of actual payout, and early offer duration of six months instead of actual duration. The estimated decline in defense costs is 53 percent for tried cases and 15 percent for settled cases. The decline for tried cases comes largely from avoiding the cost of trial and appeal. Defense cost savings could be higher than our estimate in some cases. In particular, if economic damages are below the minimum offer, insurers may be able to invest less in determining economic damages because they will not affect the early offer amount. Below, we assume 60 percent (20 percent) savings in tried (settled) cases that receive early offers. We estimate that defense costs will decline by about 13 percent across all cases. B. Overall Impact of an Early Offer Program We assess in this section the impact of reduced litigation costs on defendants total costs (for both payouts and defense costs); on the fraction of defendants total cost that is consumed by defense costs, on plaintiffs net recoveries; and on the fraction of defendants total cost that ends up in plaintiffs pockets (after fees and expenses). As noted above, we assume an early offer program will reduce the market-clearing price for plaintiff-side representation (fees + expenses) from 36 percent to 30 percent of gross payout. On the defense side, we estimate that an early offer program will reduce defense costs (fees + expenses) by 60 percent (20 percent) in tried (settled) early offer suitable cases. Table 4 reports the resulting percentage changes in payout(assuming 75 percent plaintiff chances of prevailing), total spending by defendants, the net amount received by plaintiffs, and the amount received by plaintiffs lawyers. We break out the impact by range of economic damages. As Table 4 reflects, the overall percentage decline in total defendant cost in early offer suitable cases is a blend of the declines in payout and defense costs. Overall, payout drops by 48 percent in these cases, defense costs by 22 percent, and total cost to defendants 36 Black et al. (2008). 37 The regression includes county fixed effects and is: ln(defense cost, summed across duplicate reports relating to the same case) =a* constant +b 1 * ln(payout) +b 2 ln(duration) + g * [vector of control variables, including year settled, dummy variables for stage of resolution (suit filed, trial started, trial completed, and appeal (no suit filed is the omitted category)), type of defendant (physician, hospital, or nursing home ( other is the omitted category)), and presence of multiple defendants]. Results for settled cases are similar if we run a separate regression limited to these cases. Regression results are available from the authors on request.

23 Early Offers in Medical Malpractice Cases 745 Table 4: Impact of Early Offer Program on Defendants, Plaintiffs, and Plaintiffs Lawyers Percent Change In Economic Damages Range Payout Defense Costs Total Costs (Payout + Defense Costs) Plaintiff Net Recovery Amount Received by Plaintiff s Counsel Early offer suitable cases $0-72.3% -22.0% -66.0% -69.7% -77.0% $1 $99, % -21.8% -31.2% -27.1% -44.4% $100k $200k (tried cases only) -9.2% -60% -19.6% -0.6% -24.3% All early offer suitable cases -48.4% -22.2% -44.1% -43.6% -57.0% All cases -20.2% -13.4% -19.4% -18.2% -23.8% Note: Predicted percentage impact on payout, defendants total cost for payout and defense costs, plaintiff net recovery, and plaintiff s legal fees and expenses from an early offer program for cases with allowed economic damages in indicated ranges, for 358 tried med mal cases with plaintiff verdicts (256 early offer suitable, with economic damages < $200,000) and 14,680 settled cases (10,603 early offer suitable, with economic damages < $100,000), closed from with payout $25,000 in 1988 dollars. Early offer = (max(economic damages, $50,000)) + (attorney fees and expenses of 30% of gross payout). We assume 75 percent plaintiff chances of prevailing; a 60 percent (20 percent) decline in defense costs in tried (settled) early offer suitable cases, and plaintiffs (fees + expenses) without early offer = 36% of gross payout. Amounts in 1988 dollars. by 44 percent. Plaintiffs do somewhat better (and their lawyers somewhat worse) in an early offer program than suggested by the change in payout because legal fees and expenses decline. Thus, for example, for economic damages from $1 $99,999, payouts decline by 33 percent, but plaintiffs net recoveries decline by only 27 percent because fees paid to plaintiffs counsel drop by 44 percent. In Table 5, we address how an early offer program will affect two measures of the efficiency of medical malpractice litigation what fraction of defendants total cost goes to defense costs, and what fraction of defendants total cost ends up in plaintiffs pockets, net of the plaintiffs own legal fees and expenses. Overall, the changes in both measures are quite modest. In early offer suitable cases, the ratio of defense costs to total cost rises because payouts drop more than defense costs. The ratio of plaintiff net recovery to total cost is nearly unchanged because this decline is offset by a decline in plaintiff fees. Across all cases, the ratio of defense costs to total cost rises somewhat, but the ratio of plaintiff net recovery to total cost also rises somewhat. Overall, O Connell early offers do not materially affect the efficiency of medical malpractice litigation. IX. Comparing Our Results to HOV A. Overview It is time to compare our results to the radically different results found by HOV. Using basically the same Texas data set we use, HOV estimate that an early offer program will result in a 70 percent decline in both payouts and defense costs across all cases, both tried

24 746 Black et al. Table 5: Early Offers and System Efficiency Defense Cost/ Total Cost Plaintiff Net Recovery/ Total Cost Early offer suitable cases Current rules 16.1% 53.7% Early offer 22.9% 54.0% All cases Current rules 11.8% 56.4% Early offer in suitable cases 12.9% 57.2% Note: Predicted effect on defense cost/defendants total cost and plaintiff net recovery/defendants total cost from an early offer program for cases with allowed economic damages in indicated ranges, 358 tried med mal cases with plaintiff verdicts (256 early offer suitable, with economic damages < $200,000) and 14,680 settled cases (10,603 early offer suitable, with economic damages < $100,000), closed from with payout $25,000 in 1988 dollars. Early offer = (max(economic damages, $50,000)) + (attorney fees and expenses of 30% of gross payout). We assume 75 percent plaintiff chances of prevailing, a 60 percent (20 percent) decline in defense costs in tried (settled) early offer suitable cases, and plaintiffs (fees + expenses) without early offer = 36% of gross payout. Amounts in 1988 dollars. and settled. They also conclude that defendants will find it advantageous to make early offers in almost all cases. How is such a large difference possible? The short answer is that HOV make a series of extreme assumptions, some explicit, others implicit or hidden, all of which tilt their results toward larger gains to defendants. The principal assumptions that drive their results are: There is no minimum offer in (depending on which variant one examines) either all or about half of the cases; Two-thirds of paid damages are noneconomic; Current payouts include full payment of economic damages; A contingent fee of 10 percent of economic damages (9 percent of gross payout) is a market-clearing price for plaintiffs attorneys under an early offer regime; Out-of-pocket expenses incurred by plaintiffs counsel to bring cases are negligible; There is no time value of money (and thus no cost to defendants from making payouts sooner); Plaintiffs have a 100 percent chance of success; and Defense costs will decline by 70 percent. These assumptions are either wrong or unreasonable. HOV s flawed assumptions lead, not surprisingly, to flawed results. In the remainder of this section, we explore the principal differences between our analysis and theirs. B. Explaining the Differences (Implicit) Problematic Assumption 1: No minimum offer in roughly half of all cases. Better Approach: Some minimum offer is likely to be appropriate in all cases that pass a threshold measure of severity. An early offer of economic damages for cases with zero economic damages is a nonsequitur the offer would be $0. HOV address this issue by assuming various floors on an

25 Early Offers in Medical Malpractice Cases 747 acceptable early offer, ranging from $100,000 $500,000, for what they term serious cases (death, brain damage, spinal cord injury, amputation). For other cases, they effectively estimate savings assuming that $0 offers will be accepted in cases with zero economic damages. The 7,778 cases in our data set (52 percent of all cases) that they term nonserious include burns, poisoning, eye injury, respiratory condition, nervous condition, hearing loss, circulatory condition, multiple injuries, back injury, skin disorder, scarring, and other as the principal harm. 38 These cases include median paid economic (noneconomic) damages of $30,000 ($29,000). We can imagine a minimum offer that varies based on type and severity of harm, but a minimum offer of $0 seems implausible as a legislative judgment on fair compensation. Problematic Assumption 2: Two-thirds of paid damages are noneconomic. Better Estimate: Forty percent (52 percent) of paid damages in tried (settled) cases are noneconomic. HOV estimate the ratio of noneconomic to total paid damages as follows. For tried cases, the jury allocation is available. For settled cases, insurers are supposed to indicate whether they believe the settlement was influenced by a demand for or possible award of noneconomic [damages], [punitive] damages, or pre-judgment interest. If yes, the insurer must allocate the payout among damage types and prejudgment interest. Insurers allocate damages for only about 35 percent of claims. In cases with allocation, insurers estimated that economic (noneconomic) damages represented 30 percent (59 percent) of payouts. HOV use the insurer allocation where it is provided. Where it is not, instead of accepting the insurers allocation of 0 percent of the settlement to noneconomic damages, HOV rely on Florida data to impute percentages of noneconomic damages ranging from 64 percent to 85 percent, depending on the type of case and plaintiff demographics. HOV thus effectively assume that noneconomic damages, on average, are a larger fraction of damages where insurers allocate nothing to noneconomic damages than when insurers allocate a positive amount. This cannot be correct. It is also unlikely that the payout allocation in settled cases is so radically different than in tried cases. To be sure, settled cases are likely to be different than tried cases. Above, we adjust for differences in case mix when we extrapolate from tried to settled cases. Those differences lead us to estimate that noneconomic damages are 52 percent of total damages in settled cases versus 40 percent in tried cases. In robustness checks using different extrapolation approaches, this percentage ranges from percent. None of our approaches produces a percentage approaching HOV s estimate. HOV do not specify how they computed their Florida-based estimates, and we have not reviewed the Florida data. But we do know that the Florida data set does not include information on actual allocations by juries, and research by Neil Vidmar and co-authors 38 Cases with other causes of harm account for 5,407 cases, or 70 percent of the cases that HOV treat as nonserious.

26 748 Black et al. suggests that the allocation data it does include are highly suspect. 39 Finally, a recent review by Studdert and co-authors of all available studies of the proportion of noneconomic damages estimated that noneconomic damages are 40 percent of total damages. 40 Their estimate is consistent with our estimate for tried cases, below our estimate for settled cases, and far below HOV s estimate. (Implicit) Problematic Assumption 3: Current payouts include full payment of economic damages. Better Estimate: In tried (settled) cases, 74 percent (62 percent) of economic damages are paid. A significant fraction of jury awards go unpaid. In prior work, we find that overall, med mal plaintiffs receive less than half the amount the jury awards, with larger haircuts in larger cases. 41 We estimate above that even if one allocates payments first to economic damages, plaintiffs receive only 74 percent (62 percent) of awarded economic damages in tried (settled) cases. HOV ignore the fact that, on average, plaintiffs receive substantially less than full payment of economic damages. Problematic Assumption 4: A contingent fee of 9 percent of gross payout is a market-clearing wage for plaintiffs counsel. Better Estimate: A market fee percentage (excluding expenses for the moment) will be around 25 percent of gross payout. HOV would require defendants to pay a market-clearing fee for plaintiffs counsel. HOV assume that attorneys will receive a fee of 10 percent of the damages payment (9 percent of gross payout) in the cases they win, and (implicitly) 0 percent in the cases they lose. This is far below an appropriate market rate. As noted previously, plaintiffs lose most med mal cases. Plaintiffs counsel must earn enough in the cases they win to cover their costs in the cases they lose, including both the opportunity cost of their time and out-of-pocket expenses. In Defense Costs, we estimate, based on a variety of sources, that defense costs in cases with zero or very small payout are 45 percent of total defense costs. This percentage seems unlikely to be lower on the plaintiff side, since some cases involve plaintiff-side spending followed by abandonment of what turns out to be a weak case. If plaintiff side costs in zero or small payout cases are 45 percent of total plaintiff costs, then, assuming a 33 percent contingency fee, 45 percent of this amount, or 15 percent, compensates plaintiffs counsel for the cases that generate no fees. 39 See Vidmar et al. (2005:326) (among other weaknesses, the Florida data do not include jury trial outcomes; the allocations often do not sum to the total payment; insurer allocations that include both economic and noneconomic components are available in only 10 percent of cases; only 2 percent of reports estimate positive economic damages and zero noneconomic damages; while 50 percent of reports estimate zero economic damages and 100 percent noneconomic damages). 40 Studdert et al. (2007) (see online technical appendix). 41 Hyman et al. (2007).

27 Early Offers in Medical Malpractice Cases 749 Even if a 9 percent fee percentage were enough for the cases that plaintiffs win, the equilibrium fee percentage would only decline to about 24 percent. Another way to generate similar estimates is to suppose that we assume that an early offer program would reduce plaintiff s legal fees in cases with early offers by one-half (onethird). If plaintiffs counsel currently earn an 18 percent fee in the cases they win (after covering costs for the cases they lose), that percentage would decline to 9 percent (12 percent), which implies a total fee of 24 percent (27 percent). To be sure, in prior work, O Connell and Brickman have separately suggested that contingent fees are too high and are supported by a cartel among plaintiffs counsel. 42 But that claim is theoretically implausible and lacks empirical support, and HOV make no such claim. If there is collusion in the market for legal services, addressing that collusion could reduce tort system costs, but those savings would be independent of an early offer program. (Implicit) Problematic Assumption 5: Ignoring plaintiffs out-of-pocket expenses. Better Approach: Plaintiffs out-of-pocket expenses average 4 percent of gross payout. HOV do not take out-of-pocket expenses into account in their analysis. In a typical contingent-fee arrangement, if defendants make a payment, plaintiffs pay expenses out of the recovery. If there is no recovery, plaintiffs counsel pays these costs. In research in progress on plaintiff-side personal injury practice, we find that in cases with recoveries, expenses average around 3 5 percent of recoveries. 43 There should be some savings due to quicker settlement under an early offer program, but many expenses are incurred early on to obtain medical records, obtain an initial expert opinion, and depose the defendants. Taking these factors together, we believe that 4 percent of recovery is a reasonable estimate for plaintiffs out-of-pocket expenses under an early offer program. Adding 4 percent expenses to percent in legal fees gives a total fee percentage of percent; hence our general use above of a 30 percent fee. It is unlikely that the market-clearing fee percentage is less than 25 percent. As Figure 2 shows, for small economic damage cases, which is where we expect early offers to be made, overall payout is not materially affected by whether the fee percentage is 25 percent or 30 percent. (Implicit) Problematic Assumption 6: Ignoring the time value of money. Better Approach: Compare payments with and without an early offer program by bringing both to present value at the same time, relative to when the case is brought. HOV compare estimated early offer payouts with actual payouts, without adjusting for differences in when the payment is made. This implicitly ignores the time value of money. Actual payouts are made 1.15 years later, on average, than HOV predict they would be in an early offer program. To correctly estimate how an early offer program affects payouts, one needs to compare payouts under current rules with early offer payouts by bringing both to present value at the same date, relative to when a suit was filed. 42 O Connell et al. (2000); Brickman (2003a, 2003b). 43 Hyman et al. (2009c).

28 750 Black et al. This is an elementary mistake, and not a small one. Assume, for example, that a case has $500,000 in economic damages. If the fee percentage is 30 percent and the case closes in six months under an early offer program, the defendants will pay $500,000 * (1.43) = $714,000. If the same case were to close at the median time for our sample of 600 days after suit is filed, economic damages plus prejudgment interest (meant to compensate for the time value of money), plus the fee percentage, would be $714,000 * (1.12) = $798,000. Economically, these amounts are equivalent in present value terms, assuming that the prejudgment interest rate properly reflects the time value of money. Both defendants and plaintiffs should be roughly indifferent between these two outcomes. Yet HOV treat the difference between these two amounts as a payout reduction from an early offer program. (Implicit) Problematic Assumption 7: 100 percent plaintiff chance of success. Better Approach: Plaintiffs chances of success will be well below 100 percent in most cases. The lower the plaintiffs chances of success, the less defendants have to gain from early offers. HOV ignore this issue, and thus effectively assume that plaintiffs have a 100 percent chance of recovery in all cases, both settled and tried. This assumption has a limited impact on our estimates because for us most of the savings come from cases with small economic damages, which are affected more strongly by the minimum offer than by plaintiffs chances. But it would have a much larger effect on the HOV estimates. As Figure 3 shows, varying plaintiff chances of success has large effects on the change in payout in cases with significant economic damages. Realistic assumptions about plaintiff success rates also affect which cases will be early offer suitable. For tried cases, we estimate above that early offers would be made in cases with economic damages from $200,000 $500,000 if plaintiff success were certain, but will not be made if we assume, more realistically, a 75 percent plaintiff chance of success. For settled cases, early offers would be made in cases with economic damages from $100,000 $200,000 if plaintiff success were certain, but generally will not be made if we assume a 75 percent plaintiff chance of success. Problematic Assumption 8: A 70 percent drop in defense costs. Better Approach: Defense costs will decline by 60 percent (20 percent) in tried (settled) cases. HOV assume that a market-clearing plaintiff fee percentage under an early offer program is 10 percent of economic damages and that the current fee level is 33 percent. They then assume that defense costs will drop by a factor of 23/33 (70 percent) to mirror this assumed drop in plaintiff fees from 33 percent of payout to 10 percent of economic damages, in both tried and settled cases. They offer no other basis for this assumption. Above, we use data on defense costs to estimate by how much the reduction in duration and payout in early offer suitable cases, and the presumed elimination of trial expenses, would reduce defense costs in these cases. Our regression estimates are 53 percent (15 percent) defense cost savings in tried (settled) cases. Including likely savings in cases with economic damages below the minimum offer, which our regression analysis

29 Early Offers in Medical Malpractice Cases 751 Figure 6: Impact of HOV s assumptions. 120% 100% 80% 60% 40% 20% 0% Actual payout per HOV HOV early offer estimate 50k min for all injuries BHS estimate of econ/nonecon BHS estimate 30% fee vs. 10% Time value of of unpaid econs money Interest Punitive damages Nonecon damages Fees Minimum offer Economic damages Note: Figure shows, in percentage terms, actual payout in 14,680 nonduplicate med mal cases settled before verdicts, closed from with payout $25,000 in 1988 dollars, and predicted payout under different variants of an early offer program. First bar shows actual payout with HOV estimate of economic/total damages. Second bar shows payout under HOV early offer proposal. Remaining bars progressively change the HOV assumptions. Third adds $50,000 minimum damages offer. Fourth uses our (BHS) estimate of economic/total damages. Fifth adjusts for partial payment of economic damages. Sixth, 30 percent fee. Seventh brings payouts to present value at six months from date of suit. Seventh bar uses same assumptions as, and matches, third bar of Figure 5. Amounts in 1988 dollars. cannot capture, we estimate savings of 60 percent (20 percent) in tried (settled) cases. These estimates are rough. Still, they strongly suggest that HOV s assumed savings in settled cases are not realistic. C. Reconciling the HOV Payout Estimates with Ours Each of the HOV assumptions discussed in Section IX.B points in the direction of finding larger payout and defense cost reductions from an early offer program. Figure 6 quantifies the effect on payout of progressively correcting their assumptions, using our sample of settled cases. Once one does so, HOV s payout reduction estimates are consistent with ours. We obtain similar results in tried cases (results not reported). To generate Figure 6, we first attempt to reproduce HOV s results for the settled cases in their data set, which differs slightly from ours. We are able to almost perfectly replicate their results. 44 We then apply HOV s assumptions to the settled cases in our data set, and obtain very similar results. Thus, data set differences do not explain the differences between HOV and our results. The first bar in Figure 6 shows current payouts, but with 44 HOV end their sample with 2002 (we continue our sample through 2005); they define med mal cases based solely on type of insurance (we have a more nuanced definition); they include duplicate cases (we exclude them); they include all cases with payout > $10,000 (nominal), while we study cases with payout > $25,000 (in 1988 dollars); and they do not report results separately for tried and settled cases.

30 752 Black et al. HOV s estimates of the economic and noneconomic components of damages, instead of ours. The second bar adopts HOV s approach to estimating payout reductions. It takes their estimate of economic damages and adds 10 percent, which is their assumed attorney fee rate (as a percentage of plaintiff net recovery). Estimated payout declines by 70 percent. In the remainder of Figure 6, we progressively adjust the HOV assumptions to match ours. The order in which we change from HOV s assumptions to ours does not affect the results from a full switch to our assumptions, but can affect the change in predicted payout when we add a particular assumption. The third bar in Figure 6 assumes that a $50,000 minimum damages offer is required in all cases. The estimated payout reduction declines to 63 percent. The fourth bar changes from HOV s estimate of two-thirds noneconomic damages to our estimate of 46 percent. The overall payout reduction declines to 49 percent. The fifth bar adjusts for less than full payment of economic damages under current rules. The estimated payout reduction declines again, to 30 percent. The sixth bar in Figure 6 assumes a 30 percent fee, instead of the 9 percent assumed by HOV. The estimated payout reduction declines to 9 percent. The seventh bar completes the reconciliation by taking into account the time value of money earlier payments are more costly to defendants. Estimated payout now increases by 16 percent almost the same as the 17 percent in the third bar of Figure 5, which applies the same assumptions to a slightly different data set. D. In Which Cases Will Defendants Make Early Offers? BHS Versus HOV In this section, we approach the differences between the BHS and HOV analyses from a different perspective by focusing on the damages ranges in which defendants will make early offers. We assume (unrealistically, to be sure) that defendants can perfectly predict the economic and noneconomic damages that will be awarded and paid, taking into account policy limits and other sources of haircuts between awarded and paid damages. We then assess the combinations of paid economic and noneconomic damages where an early offer will reduce payouts. Figure 7 summarizes our results. It contains four panels, using different assumptions about how an early offer program will operate. For each panel, the shaded area(s) shows the damages space where an early offer will increase payout and hence will not be made. Panel 7(a) presents results for HOV s assumptions. Early offers will reduce payout, and therefore will be made, in all cases except a thin triangle at the bottom with a high ratio of economic to noneconomic damages. Panel 7(b) adds a second roughly triangular space above the HOV triangle, showing additional cases where early offers will not be made under a base set of BHS s assumptions (30 percent fee; $50,000 minimum damages offer; economic damages are not fully paid; and a 75 percent plaintiff chance of prevailing). 45 The region where no early offer will be made grows dramatically. Panel (c) of Figure 7 shows the additional impact of the Texas nonecon cap. The shaded area in the top left represents infeasible space payouts that will never occur, since 45 We estimate the ratio of paid economic damages to total damages based on a regression, using tried cases, of ln(allowed economic damages) on ln(paid economic damages) + constant term.

31 Early Offers in Medical Malpractice Cases 753 Figure 7: In which cases will early offers be made? Paid noneconomic damages ($ thousands) Paid noneconomic damages ($ thousands) 1, ,000 (a) , , (c) , ,000 Paid economic damages ($ thousands) (b) (d) nonecon cap BHS assumptions (75%) HOV assumptions nonecon cap ($161k) $321k policy limits $642k policy limits Note: Shading shows combinations of paid economic and noneconomic damages for which defendants would not make early offers because to do so would increase payout (early offer payouts > status quo). Panel (a) uses HOV s assumptions. Panel (b) shows HOV area plus additional no early offer area using BHS assumptions. Panel (c) adds shading for infeasible area due to the Texas nonecon cap. Panel (d) adds slanted lines indicating policy limits of $321 k and $643 k ($500 k and $1 M nominal); area above these lines is above policy limits. Full assumptions are stated in the text. Unshaded area shows remaining area where early offers will be made. All areas assume defendants can accurately predict awarded and paid damages. Amounts in 1988 dollars. the nonecon cap cuts off all payouts above the dashed line. Only a small amount of feasible space remains. Finally, the downward sloping lines in Panel 7(d) show how policy limits affect the feasible space, assuming (as we find in previous work) that defendants will not offer to settle for more than limits. 46 The two lines show limits of $321,000 and $643,000 ($500,000 and $1 million nominal). The area above and to the right of each line is above limits, and hence infeasible. Even without a nonecon cap, the only feasible area is the limited area outside the HOV and BHS shaded areas, and below and to the left of the applicable policy limits line. This is not nothing. This area, although a small portion of the damages space, includes a large number of cases we estimate that 72 percent of both 46 See Zeiler et al. (2007) (finding that coverage limits generally cap recovery even when there is an above-limits verdict).

32 754 Black et al. tried and settled cases are early offer suitable. But the early offer suitable area covers far less of the damages space than HOV s analysis suggests. In many instances, the defendant s decision not to make an early offer will be overdetermined. As Panel (d) of Figure 7 reflects, substantial portions of the damages space are unattractive or infeasible for more than one reason because it will increase expected payouts, would involve noneconomic damages exceeding the damages cap, or involve total payout exceeding policy limits. X. Discussion A. Payout Reductions Are Not Social Savings We have been careful to describe the changes in payouts from an O Connell early offer program as only that. An increase (decrease) in payouts is not, without more, a social cost (saving). A reduction in litigation costs is a social savings, and an early offer program will reduce legal costs, albeit not nearly as much as HOV assume. Yet, one should not seek to minimize legal costs in isolation from other goals. The social value question should instead be, as for the tort system generally, how do the benefits we obtain from med mal litigation in deterrence and in the social value of fair compensation for injury compare to litigation costs? That question needs to be asked at the margin. Answering that question is well beyond the scope of this article. We do not know the marginal effect of early offers on deterrence; whether the loss in deterrence will be partly offset by reduced health-care costs and therefore greater access to healthcare; or how to value the fairness of providing compensation for noneconomic losses due to negligently (or worse) inflicted medical injury. These issues need to be addressed before one can assess whether an early offer program is more fair or efficient than the current system. B. Complexities and Uncertainties of an Early Offer Program The O Connell early offer program is bold and appears simple. But complexity is lurking just beneath the surface. What is a market rate for attorney fees and out-of-pocket expenses? What should the minimum damages offer be? How should the minimum offer vary with severity of injury and plaintiff demographics? How will an early offer program affect payouts, both overall and for different plaintiff groups? How should the parties estimate the plaintiff s ex ante chances of success (which will affect whether an early offer is attractive to defendants)? How will policy limits, which effectively cap recoveries in many cases, affect which cases early offers are made in? What happens in cases where economic damages are uncertain? Consider, for example, the last issue. O Connell argues that the level of economic damages is statutorily set and therefore largely certain. 47 If only the world were that simple. Future medical expenses and lost income will be uncertain, sometimes highly so. 47 O Connell, Kidd, and Stephenson (2005:266).

33 Early Offers in Medical Malpractice Cases 755 For example, future medical expenses in bad baby and other catastrophic injury cases depend on life expectancy and future medical costs, both of which depend in part on future medical technology. 48 An early offer program therefore needs rules, as yet unspecified, to handle cases in which the level of economic damages is disputed. C. Are Early Offers Fair? Professor O Connell argues that his early offer proposal is fair to plaintiffs because it offers rapid compensation for economic losses. He titled his book A Recipe for Balanced Tort Reform (emphasis in original). 49 In fact, the early offer program is likely to encourage low-ball offers; make many cases nonviable for plaintiffs attorneys; and disproportionately reduce payouts to certain plaintiff groups. We discuss these issues in turn. 1. Low-Ball Offers and Plaintiff Risk Aversion The O Connell early offer program imposes a large penalty (relative to current rules) on a plaintiff who refuses an offer and then fails to beat the proffered level of economic damages at trial, yet imposes no penalty on defendants who make low-ball offers. Moreover, plaintiffs are undiversified and hence likely to be risk averse. This combination will predictably lead to (1) defendants making low-ball offers, which fall toward the low end of a plausible range within which economic damages are likely to fall; (2) many plaintiffs accepting these offers; and (3) zero payouts to some plaintiffs who suffer negligent medical care, reject what they consider to be low-ball offers, and cannot persuade the jury that economic damages were larger than the offered amount. An early offer program also imposes the risk of loss from rejecting a settlement offer on an undiversified plaintiff, instead of on a diversified insurer. 2. Viability for Plaintiffs Counsel The rhetoric of early offers is fast recovery of economic damages. The likely reality in many cases with limited economic damages will be no recovery of any damages, since the cases will no longer be brought. For these cases, expected recoveries will drop sharply. That will surely affect the willingness of plaintiffs counsel to bring these cases, even if the program includes a realistic fee percentage, such as 30 percent. The lower the fee percentage, the starker that result is likely to be. Suppose, for example, that a legislature adopted O Connell s proposed fee level (9 percent of gross payout) and bars plaintiffs and attorneys from contracting for an additional fee, to be paid 48 To be sure, early offers will not be made in bad baby cases because they involve large economic damages. However, these cases highlight the uncertainty potentially associated with determining even economic damages. O Connell and Robinette (2008) suggest that defendants can offer to pay future damages as incurred, with the amount to be determined later. However, this is unlikely to be attractive to defendants, who want to know their total exposure. It would also invite ongoing litigation, and seems counter to the spirit of the overall proposal, which seeks to reduce dispute resolution costs. 49 O Connell and Robinette (2008).

34 756 Black et al. out of damages. Holding payout constant, fees would decline by 73 percent. But payout will drop sharply as well. For cases with economic damages of $0 ($1 $100,000), the expected 76 percent (58 percent) drop in damages (see Table 2) would imply a 93 percent (88 percent) drop in allowable fees. This is a recipe for squelching suits in these cases altogether. 3. Disparate Impact As we have seen, an early offer program will have dramatically different effects, depending on age, employment status, and whether the plaintiff is deceased. These disparate impacts reflect wide variation in the fractions of paid economic and noneconomic damages across these demographic categories. A minimum offer reduces the disparate impact, but the differences are still stark. Legislators considering an early offer program should be prepared for opponents to charge that they are supporting kill granny cheap tort reform. 50 The disparate impact would likely increase if one took into account O Connell s proposal to bundle an early offer rule with a collateral source rule, so that defendants would not have to pay for economic damages that were paid by another source, such as medical expenses paid by health insurance. Without a meaningful minimum damages offer, kill granny cheap might become kill granny free. Medicare largely covers medical costs, and any remaining economic damages might well be too small to be worth suing for. D. Perverse Incentives Paradoxically, the O Connell proposal discourages strong suits more than weak ones. Plaintiffs with moderate economic damages but strong cases will be particularly hard hit by an early offer program because they will lose the potential recovery of noneconomic damages. Plaintiffs with weaker cases, in contrast, will be unaffected because defendants will not make early offers in these cases. This creates an incentive for plaintiffs counsel to persuade defense counsel that their case is weaker than it really is. Better to have or be seen by the defense to have a case with a chance of collecting both economic and noneconomic damages than a case with a 90 percent chance of winning, which might lead to collecting only economic damages plus attorney fees. This dynamic exacerbates the information asymmetry and strategic gamesmanship that can obstruct settlement and raise litigation costs. E. Overall Deterrence There is a consensus among medical malpractice researchers that med mal litigation substantially underdeters negligent medical care. 51 Most researchers would also agree that med mal litigation has some deterrent effect, even if only a modest one. These observations 50 For criticism of nonecon caps on similar grounds that they discriminate against women and the elderly see, e.g., Finley (2004), Zimmerman and Hallinan (2004), and Costello (2007). 51 See, e.g., Studdert et al. (2006); Baker (2005).

35 Early Offers in Medical Malpractice Cases 757 put a sharper edge on questions about whether the large payout reductions for early-offersensitive groups are good policy. Consider death cases. In general, as Table 3 shows, an early offer program substantially reduces payouts in death cases. Yet the current mean payout in death cases is only $524,000 ($263,000) in tried (settled) cases. These amounts are well below most estimates of the value of a statistical life. The tendency of juries to put a low value on life compounds the effects of other sources of underdeterrence. Cutting these (already far-too-low) payouts in half can only further reduce deterrence. 52 F. Toward an Improved Early Offer Program HOV assume that defendants need incentives to make early offers, and plaintiffs need sticks to force them to accept the offers. Yet incentives might often be the other way around. Many plaintiffs might happily settle early for economic damages plus a market-clearing fee percentage, while defendants might often resist paying at this level, even if liability is likely. If we want to improve on HOV s early offer program, we need to give both sides strong incentives to make early settlement offers, hit both with large sticks if they refuse a qualifying offer, and provide payment of full economic damages plus attorney fees in virtually all cases not just those where defendants would benefit. To make the idea concrete, imagine a two-sided early offer program that would combine: 1. Something similar to our variant of the O Connell program, with a substantial minimum damages offer, ideally one that depends on severity of harm, and a 30 percent fee; A less onerous stick to encourage plaintiff acceptance of a defendant offer; A plaintiff-side program, under which plaintiffs could offer to settle for economic damages plus the fee percentage, and defendants would face a reasonable stick if they refuse and the plaintiff then wins at trial and is awarded economic damages that equal or exceed the offer; 55 and 4. A requirement that defendants carry enough malpractice insurance to cover most expected payouts See also Cross and Silver (2006). 53 For example, one could set a minimum damages offer of $100,000 in current dollars, inflation adjusted, plus a multiplier (running say from 1 to 5) based on harm severity, using the NAICS severity measure. 54 The stick to encourage plaintiff acceptance of the offer could be denial of recovery of noneconomic damages, to the extent that they would bring total damages above the minimum offer, if awarded economic damages are less than, say, 95 percent of the defendant s damages offer. Unlike O Connell, we would not change the plaintiff s burden of proof. 55 For example, the defendant could be made liable for the fee percentage on all damages, not just economic damages. 56 For example, defendants could be required to carry insurance sufficient to pay full economic damages plus the fee percentage in 95 percent of cases. The minimum amount of insurance could be set by the state insurance department based on past jury awards against similar defendants, adjusted for inflation, say, over the past decade.

36 758 Black et al. An improved early offer program should also recognize that economic damages are often uncertain, and sometimes highly so. One might allow the trier of fact to impose no penalty on plaintiffs or defendants who refuse an offer if their estimate of economic damages is reasonable (even if not one the trier ultimately accepted). One might also impose penalties on defendants who make low-ball offers. 57 In separate work, we find a significant impact from the plaintiff-side incentives (and defendant sticks) created by the insurer s duty to settle. Cases that settle at limits do so faster and with lower defense costs than cases that settle below limits. 58 As we discuss there, one could build on that apparent success by strengthening defendants incentives to settle, and expanding the range of cases in which the duty to settle would apply. Overall payouts would be likely to rise under a two-sided program. Payouts in cases with small (large) economic damages would drop (rise), and presumably fewer (more) such cases would be brought. Cases would be handled more quickly and efficiently, given both sides incentives to settle early. The most severely injured plaintiffs would, for the first time, have a realistic expectation of recovering full economic damages, after paying their lawyers. Such a truly balanced reform should dominate the one-sided O Connell proposal in any policy debate. But we re not holding our breath waiting for it to be adopted. G. More Data, Less Rhetoric We have criticized HOV for major flaws in their analysis of the impact of an early offer rule. But there is an important positive aspect to their effort to empirically estimate that impact. Without empirical estimates, we are left with rhetoric and anecdotes to go on when making policy decisions. Both have been in ample supply in the tort reform debate. By offering empirical evidence, however flawed, HOV advanced our understanding of how procedural reform might affect tort litigation. Our article would not have been possible without their having taken a first step. So, too, for our related paper exploring how insurer duty to settle affects settlement. 59 We undertook that project only because studying early offers caused us to think about what other rules might promote faster settlement and lower litigation costs, and what might be testable using the TCCD. XI. Conclusion An O Connell early offer program: (1) will not produce the huge overall payout reductions that O Connell and co-authors predict; (2) will produce large payout reductions in cases 57 For example, if a plaintiff refuses a defendant s early offer and obtains larger damages at trial than a defendant offered, the defendant could be liable for economic damages (plus fee percentage) on awarded economic damages, plus a statutory penalty percentage on the amount by which awarded economic damages exceed the offer. Or the defendant could be made liable for the fee percentage on both economic and noneconomic damages. 58 Hyman et al. (2009b). 59 Hyman et al. (2009b).

37 Early Offers in Medical Malpractice Cases 759 with small economic and large noneconomic damages; (3) will have large differential effects on different plaintiff groups, including large payout reductions for elderly and unemployed plaintiffs; (4) will have little effect in cases with large economic damages because defendants will not make early offers in these cases; (5) will not change the current reality that most plaintiffs with large economic damages fail to recover even their economic damages; and (6) will have effects that depend greatly on its details. The combination of minimum damages offers in small cases, and money-losing (relative to the status quo) offers in cases with economic damages over $200,000, means that defendants will make early offers principally in cases where the damages are just right economic harm is not too large, expected noneconomic damages are not too small, and the likelihood of liability is high enough. That outcome might satisfy Goldilocks, but others ourselves included might doubt the merits of kill granny cheap (or free) tort reform. A more balanced early offer program would speed settlement and generate social savings without being unduly harsh to plaintiffs with grave harm but low economic damages. We have offered some ideas on what such a program might look like. References Baker, Tom (2005) The Medical Malpractice Myth. Chicago, IL: Univ. of Chicago Press. Black, Bernard, David Hyman, & Charles Silver (forthcoming) O Connell Early Offers: Toward Realistic Numbers, 7 J. of Empirical Legal Studies. Black, Bernard, David Hyman, Charles Silver, & William Sage (2008) Defense Costs in Medical Malpractice and Other Personal Injury Cases: Evidence from Texas, , 10 American Law & Economic Rev Black, Bernard, Charles Silver, David A. Hyman, & William M. Sage (2005) Stability, Not Crisis: Medical Malpractice Claim Outcomes in Texas, , 2 J. of Empirical Legal Studies 207. Brickman, Lester (2003a) Effective Hourly Rates of Contingency-Fee Lawyers: Competing Data and Non-Competitive Fees, 81(3) Washington Univ. Law Q (2003b) The Market for Contingent Fee Financed Tort Litigation: Is it Price Competitive, 25(1) Cardozo Law Rev. 65. Cohen, Thomas H. (2004) Medical Malpractice Trials and Verdicts in Large Counties, Bureau of Justice Statistics. Available at Costello, Daniel (2007) Lacking Lawyers, Justice is Denied, Los Angeles Times Dec. 29. Cross, Frank, & Charles Silver (2006) In Texas, Life is Cheap, 59(6) Vanderbilt Law Rev Department of Health and Human Services (1994) Thompson Launches Early Offers Pilot Program to Speed Compensation to Injured Patients, Help Reduce Medical Costs. Available at Farber, Henry S., & Michelle J. White (1994) A Comparison of Formal and Informal Dispute Resolution in Medical Malpractice, 23 J. of Legal Studies 777. Finley, Lucinda (2004) The Hidden Victims of Tort Reform: Women, Children, and the Elderly, 53 Emory Law J Hersch, Joni, Jeffrey O Connell, & W. Kip Viscusi (2007) An Empirical Assessment of Early Offer Reform for Medical Malpractice, 36 J. of Legal Studies s231. (forthcoming) Reply to the Effects of Early Offers in Medical Malpractice Cases: Evidence from Texas, 7 J. of Empirical Legal Studies. Hyman, David A., Bernard Black, & Charles Silver (2009b) The Impact of the Duty to Settle on Settlement Evidence from Texas. Working paper. Available at

38 760 Black et al. (2009c) Waiting for the Big One: The Economics of Plaintiff-Side Personal Injury Practice. Working paper. Hyman, David A., Bernard Black, Charles Silver, & William Sage (2009a) Estimating the Effect of Damage Caps in Medical Malpractice Cases: Evidence from Texas, 1 J. of Legal Analysis 355. Hyman, David A., Bernard Black, Kathryn Zeiler, Charles Silver, & William Sage (2007) Do Defendants Pay What Juries Award?: Post-Verdict Haircuts in Texas Medical Malpractice Cases, , 4 J. of Empirical Legal Studies 3. O Connell, Jeffrey (1982) Offers That Can t Be Refused: Foreclosure of Personal Injury Claims by Defendants Prompt Tender of Claimants Net Economic Losses, 77 Northwestern Univ. Law Rev O Connell, Jeffrey, & Patricia Born (2008) The Cost and Other Advantages of an Early Offer Reform for Personal Injury Claims Against Business, Including for Product Liability, 2008 Columbia Business Law Rev O Connell, Jeffrey, Carlos M. Brown, & Michael D. Smith (2000) Yellow Page Ads as Evidence of Widespread Overcharging by the Plaintiff s Personal Injury Bar, 6 Connecticut Insurance Law J O Connell, Jeffrey, Jeremy Kidd, & Evan Stephenson (2005) An Economic Model Costing Early Offers Medical Malpractice Reform: Trading Noneconomic Damages for Prompt Payment of Economic Damages, 35 New Mexico Law Rev O Connell, Jeffrey, & Christopher J. Robinette (2008) A Recipe for Balanced Tort Reform. Durham, NC: Carolina Academic Press. Rubin, Paul H., & Joanna M. Shepherd (2007) Tort Reform and Accidental Deaths, 50 J. of Law & Economics 221. (2008) The Demographics of Tort Reform, 4 Rev. of Law & Economics 591. Sack, Kevin (2008) Doctors Start to Say I m Sorry Long Before See You in Court, New York Times May 18. Studdert, David M., & Michelle M. Mello (2007) When Tort Resolutions Are Wrong : Predictors of Discordant Outcomes in Medical Malpractice Litigation, 36 J. of Legal Studies 47. Studdert, David M., Michelle M. Mello, Atul A. Gawande, Troyen A. Brennan, & Y. Claire Wang (2007) Disclosure of Medical Injury to Patients: An Improbable Risk Management Strategy, 26(1) Health Affairs 215. Studdert, David M., Michelle M. Mello, Atul A. Gawande, Tejal K. Gandhi, Allen Kachalia, Catherine Yoon, Ann Louise Puopolo, & Troyen A. Brennan (2006) Claims, Errors, and Compensation Payments in Medical Malpractice Litigation, 354 New England J. of Medicine Studdert, David M., Y. Tony Yang, & Michelle M. Mello (2004) Are Damages Caps Regressive? A Study of Jury Verdicts, 23(4) Health Affairs 54. Taragin, Mark I., Laura R. Willett, Adam P. Wilczek, Richard Trout, & Jeffrey L. Carson (1992) The Influence of Standard of Care and Severity of Injury on the Resolution of Medical Malpractice Claims, 117 Annals of Internal Medicine 780. Vidmar, Neil, Paul Lee, Kara MacKillop, Kieran McCarthy, & Gerald McGwin (2005) Seeking the Invisible Profile of Medical Malpractice Litigation: Insights from Florida, 54 DePaul Law Rev Weise, Richard H. (2001) Representing the Corporation: Strategies for Legal Counsel. New York: Aspen. Zeiler, Kathryn, Charles Silver, Bernard Black, David A. Hyman, & William M. Sage (2007) Physicians Insurance Limits and Malpractice Payments: Evidence from Texas Closed Claims, , 36 J. of Legal Studies 9. Zimmerman, Rachel, & Joseph T. Hallinan (2004) As Malpractice Caps Spread, Lawyers Turn Away Some Cases, Wall Street J. Oct. 8.

39 Early Offers in Medical Malpractice Cases 761 Appendix A: Algebraic and Simulation Methodologies for Likelihood of Prevailing We examine here some details of how plaintiffs less-than-100-percent chances of winning at trial affect how an early offer program will change expected payouts. We first discuss an algebraic approach, which forms the basis for the discussion in the text. We then discuss a simulation approach. The simulation approach produces results consistent with the simpler algebraic approach. 1. Proportion of Good Cases, and Plaintiffs Mean Chances in Those Cases We assume that, overall, defendants win 75 percent of trials. This assumption is consistent with the available data. We also assume that (1) cases are either good or bad ; (2) good cases have average plaintiff success probability of x percent (which we vary from 50 percent to 100 percent); (3) good cases are a fraction p good of all tried cases (which we vary from 20 percent to 30 percent); and (4) defendants and plaintiffs know which cases are good (bad). Table A1 shows how the fraction of plaintiff wins that comes from good cases and the plaintiff win probability y in bad cases, must vary with x and p good to produce defendant wins in 75 percent of all cases. 60 Table A1 highlights a tradeoff in estimating how many good cases there are and how good those cases are. The more cases are good, and the higher the plaintiffs chances in these cases, the worse the remaining cases must be. For example, if there are 25 percent good cases, with 80 percent chances of success, the remaining cases must have only a 5 percent chance of success. Yet it is unlikely that plaintiffs counsel often take to trial cases with such low odds of success. If we require that plaintiffs chances in bad cases be at least 10 percent, then if there are 25 percent good cases, plaintiffs chances can be at most 70 percent, and at least 30 percent of ex post plaintiff wins will come from bad cases, in which no early offer will be made. Plaintiff average chances in good cases above 80 percent seem unlikely because plaintiffs lose a nontrivial percentage of cases where medical error is clear. Across both trials and settled cases, Studdert, Mello, and co-authors report that where an independent review of insurers claim files finds virtually certain evidence of medical error, plaintiffs recover 84 percent of the time. 61 Taragin and co-authors report a 91 percent recovery rate in cases judged by an insurer to be indefensible. 62 In cases where medical error is merely probable, rather than almost certain, Studdert, Mello, and co-authors report a 67 percent chance of recovery. They also find that plaintiffs win only 43 percent of trials in which medical error is at least probable. Farber and White report a 66 percent chance of recovery 60 Table A1 is based on the formula (p good *x)+ [(1 - p good) *y]= 0.25 (plaintiffs average chances across all cases). 61 Studdert et al. (2006); Studdert and Mello (2007). 62 Taragin et al. (1992).

40 762 Black et al. Table A1: Plaintiff Trial Wins in Good Cases and Chances in Bad Cases Good Cases/ Total Cases 20% 25% 30% Plaintiff Win Prob. in Good Cases %of Plaintiff Wins from Good Cases Plaintiff Win Prob. in Bad Cases %of Plaintiff Wins from Good Cases Plaintiff Win Prob. in Bad Cases %of Plaintiff Wins from Good Cases Plaintiff Win Prob. in Bad Cases 50% 40% 18.8% 50% 16.7% 60% 14.3% 55% 44% 17.5% 55% 15.0% 66% 12.1% 60% 48% 16.3% 60% 13.3% 72% 10.0% 65% 52% 15.0% 65% 11.7% 78% 7.9% 70% 56% 13.8% 70% 10.0% 84% 5.7% 75% 60% 12.5% 75% 8.3% 90% 3.6% 80% 64% 11.3% 80% 6.7% 96% 1.4% 85% 68% 10.0% 85% 5.0% Not feasible; plaintiff win 90% 72% 8.8% 90% 3.3% prob. in bad cases is <0 95% 76% 7.5% 95% 1.7% 100% 80% 6.3% 100% 0.0% Note: Table shows percentage of plaintiff trial wins that come from good cases, and percentage of bad cases that plaintiffs win, for indicated plaintiff mean winning probability x in good cases and fraction p good of good cases. We assume that all cases are either good or bad and defendants win 75 percent of all cases. Shaded cells show combinations we consider plausible, with plaintiff win chances in good (bad) cases of 80 percent or less (10 percent or more). in meritorious cases. 63 The shaded cells in Table A1 show the combinations we consider plausible plaintiff win chances in good (bad) cases of 80 percent or less (10 percent or more). The same conclusion holds if we use the simulation method described below. We were unable to generate plausible probability distributions with means over 80 percent, unless good cases are rare (less than 20 percent of all tried cases). 2. Simulation Approach for Tried Cases In the algebraic approach above, we assumed that all good cases have the same expected win probability x. This is unrealistic. We therefore also developed a simulation-based model in which we (1) allow plaintiff chances of success to be distributed around a mean of x (y ) in good (bad) cases, subject to the constraint that plaintiffs win 25 percent of all cases. We also examined trimodal distributions with good, ok, and bad cases, with similar results. Consider a bimodal distribution with p good = 0.25, x = 0.70, and therefore y = 0.10, in which good (bad) cases are drawn from a beta distribution (a generalization of the binomial distribution) of the form b (0.7a, 0.3a) (b (0.1b, 0.9b)). We choose a and b to be small numbers to allow for greater dispersion in the probability of success in a particular case, but require that the probability of a case going to trial approach zero as the plaintiff win chances approach 0 or 1, on the grounds that these cases will rarely go to trial. Figure A1 63 Farber and White (1994) (66 percent of meritorious claims received compensation).

41 Early Offers in Medical Malpractice Cases 763 Figure A1: Bimodal beta distribution examples for p good = 0.25; x = 0.70; y = probability density (1) 0.25*beta(6, 2.57) *beta(1.5, 13.5) (2) 0.25*beta(3.5, 1.5) *beta(1.2, 10.8) x Note: Probability density for indicated bimodal beta distributions. Cases are either good or bad. Distributions are chosen so plaintiffs have 70 percent mean chances of winning good cases and 10 percent chances of winning bad cases; and so that probability density approaches zero as win chances approach 0 or 1. shows the distribution of plaintiff win chances for two plausible values of a and b. Lower values of a (b) will produce a distribution that peaks at 1 (0). Higher values will produce sharper peaks around the mean values of x and y. We then choose a distribution, but verify in robustness checks that our results are not sensitive to this choice. For example, we choose line 1 of Figure A1 as the basis for further analysis. We assume early offers will be made only in good cases. We sample repeatedly from the good portion of this distribution to generate cases with different plaintiff win chances. For each case, the sampling procedure provides both ex ante win chances and the ex post outcome (plaintiff win or not). We assume that the cases in our data set (with plaintiff wins ex post) are representative of all good cases. 64 Given (known) payout in the good cases that plaintiffs win ex post, and assumed known ex ante plaintiff chances of winning these cases, we can compute ex ante expected payout, and compare this expected payout to the early offer amount. However, simply summing payout changes for cases that plaintiffs win ex post will overstate changes in payout, since some ex post plaintiff wins will come in bad cases, in which no early offer 64 This simulation approach, in effect, flips the customary Bayesian problem on its head. Bayesian analysis is concerned with determining posterior probabilities, if prior probabilities are known. We instead simulate prior probabilities, given a known overall posterior mean and an assumed bimodal distribution.

42 764 Black et al. would have been made. A better estimate of the change in payout in tried cases from an early offer program is: ( payout change in cases with ex post wins) (% of wins which come from good cases). Results from the sampling approach were very similar to those for the algebraic approach. 65 Appendix B: Methodology for Settled Cases We develop here the additional assumptions needed to extend our analysis of tried cases to settled cases. The key assumptions involve allocating the settlement payout among economic, noneconomic, and punitive damages, including simulating the dispersion across cases in the ratio of economic damages to total payout, estimating what fraction of economic damages would be paid if liability were certain, and estimating how the plaintiff s ex ante chances of success at trial affect settlements. 1. Allocation Procedure for Settled Cases We estimate the allocation of payouts among different types of damages in settled cases by extrapolating from the outcomes in tried cases. We considered using, but rejected as unreliable, insurer allocations in claim reports, partly because these allocations are only available in about one-third of settled cases. 66 We allocated payouts by first dividing the cases into the eight plaintiff subsamples discussed in the text. For each tried case, we determined the ratio of paid economic damages/(total paid allowed damages). These ratios vary widely both within and across subsamples, with subsample means of per-case ratios ranging from 16 percent in elderly death cases to 72 percent in baby cases. 65 Simulation results are available from the authors on request. 66 As noted previously, the Closed Claim Reporting Guide asks insurers to indicate whether they believe the settlement was influenced by a demand for or possible award of non-economic [damages], [punitive] damages, or pre-judgment interest. (The Closed Claim Reporting Guide refers to punitive damages as exemplory damages. ) If the insurer judges that settlement was so influenced, it must allocate the payout among damage types and prejudgment interest, but is given no advice on how to do so. Insurers allocate damages for only about 35 percent of claims, but allocate some payout to noneconomic damages in 97 percent of these cases. In cases with allocation, insurers estimated that economic (noneconomic) damages represented 30 percent (59 percent) of payouts or, with interest allocated to damages, 32 percent (61 percent). If paid noneconomic damages were truly zero in the remaining settled cases, then economic (noneconomic) damages would represent 70 percent (25 percent) of payouts in all settled cases. This compares to our estimates in the text of 46 percent (52 percent). It seems unlikely that only 34 percent of settled cases were influenced by a demand for noneconomic or punitive damages. Noneconomic damages were awarded in 84 percent of tried cases. We would expect plaintiffs counsel to almost always seek noneconomic damages. These potential damages should have settlement value in most cases. We also doubt the reliability of allocations when an allocation is made. For tried cases, where the jury allocation of damages is known, TDI instructs insurers to allocate the payout among economic, noneconomic, and punitive damages. Insurer allocations are often inconsistent with the damage award.

43 Early Offers in Medical Malpractice Cases 765 Table B1: Allowed and Paid Damages in Settled Cases Economic Damages Nonecon Damages Punitive Damages Total Paid Damages Total payout $2,080,998 $2,396,958 $79,395 $4,557,351 Present value of payout $1,875,976 $2,139,580 $71,015 $4,086,571 Mean (median) PV of payout $156 ($47) $193 ($79) $95 ($32) $278 ($120) Column as % of total payout 45.9% 52.4% 1.9% 100.0% Payout as % of allowed damages 62.2% 35.6% 61.3% 38.3% Note: Total payout for 14,680 nonduplicate med mal cases settled before verdict, closed from with payout $25,000 in 1988 dollars. Present value is measured at six months from date of suit, or date claim reported to insurer if no suit was filed. Allocation rules for payout are stated in the text. Mean and median for each type of damages are for cases with nonzero awards of this type. Amounts in thousands of 1988 dollars. We used a bootstrap approach to assign ratios to individual settled cases. For each settled case i in subsample j, we assigned a ratio drawn at random, with replacement, from the pool of observed ratios for that subsample in tried cases. In tried cases, damages are not fully paid even after liability is established. The same would surely be true in settled cases. For each subsample, we determine for tried cases the ratio of (total allowed economic damages)/(total paid economic damages). This ratio ranges from essentially 1 for elderly cases to 1.41 for employed, nondeath cases. We then assume that for each settled case i in subsample j: allowed econ damagesi = ( allowed econ damages paid econ damages) j paid econ damages i. Table B1 summarizes our estimates of payout allocations in settled cases. The proportion of payout attributable to economic damages in settled cases is 46 percent versus 58 percent in tried cases. The lower percentage share of economic damages in settled cases arises because these cases are more likely to involve subsamples with low ratios of economic/total damages. We also estimate that 62 percent (37 percent) of economic (noneconomic) damages are paid, compared to 73 percent (42 percent) in tried cases. In robustness checks using a variety of approaches, we obtain estimates of (paid economic damages)/(total payout) ranging from percent. 67 Our approach assumes that: (1) within each subsample, settled cases and tried cases are similar in relevant attributes, including mean ratio of (paid economic damages)/(total 67 If we repeat the bootstrap sampling procedure, we obtain ratios of (paid economic damages)/(total payout) ranging from percent. In one alternate approach, we assigned to each case in each subsample a ratio equal to the (total paid economic damages/total paid damages) for tried cases in that subsample. This ratio, in contrast to the bootstrap approach, was constant for all cases in each subsample. In a second alternate approach, we first regressed (paid econ damages/total paid damages) for each tried case on subsample dummy variables, ln(payout), and constant term, and similarly for noneconomic and punitive damages, and used the regression coefficients to estimate paid economic, noneconomic, and punitive damages in each settled case. The estimates of (paid economic damages)/(total payout) from these two approaches were 52 percent and 50 percent, respectively.

44 766 Black et al. Table B2: Early Offer Effect on Payout in Settled Cases, by Level of Economic Damages Allowed Economic Damages Range No. of Cases Allowed Econ Damages Total Payout Early Offer Payout Early Offer % Change in Payout Plaintiff chances 100% 100% 100% 75% of success $0 2, , , , % -72.2% >$0, but <$100 k 7, ,588 1,047, , , % -32.7% $100 k, but 1, , , , , % 3.1% <$200 k $200 k, but 1, , , ,698-9, % 35.4% <$500 k $500 k, but , , , , % 74.5% <$1 M $1 M, but , , , , % 127% <$2.5 M $2.5 M 182 1,243, ,729 1,776,220-1,263, % 362% All early offer 12, ,130 2,171,037 1,158,355 1,012, % -48.3% suitable cases All cases 14,680 3,016,046 4,086,571 4,761, , % 50.6% Note: Total economic damages, actual payout (brought to present value as of six months from date of suit), and early offer, for cases with allowed economic damages in indicated ranges, for 14,680 nonduplicate med mal cases settled before verdict, closed from with payout $25,000 in 1988 dollars. Early offer = (max(economic damages, $50,000)) + (attorney fees and expenses of 30% of gross payout). Amounts in thousands of 1988 dollars. allowed paid damages), the dispersion of this ratio across cases, and the ratio of (paid economic damages)/(total allowed economic damages). These assumptions are likely false tried cases could well differ from settled cases in the nature of damages and how likely those damages are to be paid. They are simply the best we can do Change in Payout in Settled Cases by Range of Economic Damages Table B2 shows the change in expected payout in settled cases by level of economic damages, assuming 100 percent plaintiff chances of success. It is similar in format to Table 2, which examines tried cases. The shaded cells show the economic damages range in which defendants gain on average by making early offers. As with tried cases, defendants gain from making early offers principally for cases with low economic damages. With 75 percent plaintiff win chances, early offers will be made only in cases with economic damages of $100,000 or less. Within each economic damages range, the percentage decline in payout is smaller than for tried cases for example, 40 percent for settled cases with economic 68 Our approach implicitly assumes that the relevant case attributes do not depend on the level of payout. This can be tested for tried cases. A regression of (paid economic damages/total paid damages) on payout in $ millions, subsample dummies, and a constant term gives a positive coefficient on payout of (t = 3.94). However, a similar regression using ln(payout) instead of payout produces an insignificant coefficient of (t = 0.81). Moreover, over the limited range of economic damages for which early offers are likely to be made, the economic significance of any effect is small.

45 damages from $1 to $100,000 versus 61 percent for tried cases in this damages range. However, the overall payout decline is similar in tried and settled cases because smaller cases represent a larger portion of total payout in settled cases. 3. Plaintiff Win Chances in Settled Cases Early Offers in Medical Malpractice Cases 767 Most settled cases, similar to tried cases, result in zero payout. In Texas, only 18 percent of claim files opened by med mal insurers are closed with a payment to the plaintiff. To be sure, this low percentage partly reflects plaintiffs suing several defendants, and collecting from only some of them. Thus, plaintiff success rates are somewhat higher than this perhaps as high as 30 percent or so. Some claims involve virtually certain liability, but many do not. As with tried cases, it is implausible that plaintiffs bring many cases with very low ex ante chances of a payout. This implies that plaintiff chances of success are well below 100 percent in most settled cases. To assess plausible mean plaintiff chances, we use the simulation approach discussed in Appendix A for tried cases. We experiment with unimodal distributions, bimodal distributions (good and bad cases), and trimodal distributions (good, ok, and bad cases), assuming overall plaintiff success rates from percent. A unimodal distribution implies that there are very few cases with high ex ante plaintiff chances of success. The bimodal and trimodal distributions generate more ex ante good cases, but still suggest that plaintiff mean chances of success in the cases that produce payouts are unlikely to be more than percent.