Surgical Malpractice in the United States, 1990 –2006 Ryan K Orosco, MD, Jonathan Talamini, JD, David C Chang, MPH, MBA, PhD, Mark A Talamini, MD, FACS Information about national trends and predictors of malpractice payments can constructively add to the hotly debated topic of medical malpractice. We sought to evaluate predictors of surgical malpractice payments and to explore national trends. STUDY DESIGN: Retrospective analysis of surgery-related malpractice payments using the National Practitioner Data Bank from 1990 to 2006. Payments were adjusted to 2006 dollars. We evaluated predictors of payment size and large payments (defined as those ⬎$1 million). Statutory law in the states demonstrating significant predictive values was analyzed. RESULTS: In total, 58,518 surgical malpractice payments met inclusion criteria. Patients were predominantly female (62%) and inpatient (63%), with a mean age of 42 years. The number of payments decreased and payment sums increased during the study period. Median payment was $132,915 (95th percentile $983,263). Claims most frequently cited improper performance (42%). Patient outcomes were the strongest predictor of both payment size and likelihood of a large payment. Children younger than 10 years old were 70% more likely to receive a large payment (p ⫽ 0.005); and patients older than 70 years were 80% less likely (p ⬍ 0.0005). Large variations across states were seen for both payment size and likelihood of large payment. The likelihood of reaching out-of-court settlement did not appear to be correlated with known factors. CONCLUSIONS: Nationwide, surgical malpractice claims show rising payment amounts. Patient outcomes are the strongest predictor of payment size. Considerable variation in payment size between states suggests a profound impact from local legal environments. (J Am Coll Surg 2012;215: 480–488. © 2012 by the American College of Surgeons) BACKGROUND:
and (4) the injury was caused in fact and proximately caused by the substandard conduct. The burden of proving these elements is on the plaintiff in a malpractice lawsuit. Importantly, whether or not these elements are met, claimants can receive settlement payments outside of court judgment. It has been reported that 1 in 4 malpractice cases end in nonmeritorious awards (ie, payments are made to claims without merit, or claims with merit do not receive compensation).1,2 Across medical and surgical specialties, Deshpande and Deshpande found that surgeons had the highest perceived threat of malpractice suits.3 Kane reported that 42% of US physicians have been sued for malpractice during the course of their careers, and 90% of surgeons aged 55 years and older have been sued. General surgeons and obstetricians experienced twice the overall average claims rate, followed closely by surgical subspecialists.4 In a survey of surgical oncologists at a major cancer center, 71% of respondents had been named in a medical malpractice suit. More than half of those surgeons who had been sued classified the experience as highly stressful, and stress from
Medical malpractice is hotly debated, especially among the recently heightening discussion of health care reform. Claims captured in the National Practitioner Data Bank (NPDB) can be used to learn more about surgical malpractice in the United States. Medical malpractice is a tort (civil crime) of negligence. A person who alleges negligent medical malpractice must prove 4 elements: (1) a duty of care was owed by the physician; (2) the physician violated the applicable standard of care; (3) the person suffered a compensable injury; Disclosure Information: Nothing to disclose. Abstract presented at the American College of Surgeons 97th Annual Clinical Congress, Surgical Forum, San Francisco, CA, October 2011. Received February 19, 2012; Revised April 16, 2012; Accepted April 30, 2012. From the Department of Surgery, University of California San Diego, San Diego, CA (Orosco, Chang, MA Talamini) and Practicing attorney, New York, NY (J Talamini). Correspondence address: Ryan K Orosco, MD, Department of Surgery, Division of Otolaryngology-Head and Neck Surgery, University of California San Diego, 200 W Arbor Dr, San Diego, CA 92103. email:
[email protected]
© 2012 by the American College of Surgeons Published by Elsevier Inc.
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lawsuit ranked higher than all of the other financial and professional factors assessed.5 In a large national survey of American surgeons, approximately 9% reported they had made a major medical error in the last 3 months, and there was a strong relationship between surgeon distress and perceived medical errors.6 Medical malpractice suits are common among US surgeons, and carry potentially profound personal consequences. A study of US surgeons by Balch and colleagues reported that recent malpractice suits were strongly related to burnout and depression, work schedule/hours, subspecialty, and practice setting.7 Many physicians experience considerable emotional distress and job-related stress after serious medical errors and near-misses. Interestingly, only 10% of physicians believed they were adequately supported by their employer health care organization after the incident.8 Fear of malpractice suit can also lead to defensive medicine practices. A survey of physicians and surgeons in Pennsylvania, a state with high liability insurance premiums, reported that ⬎90% of respondents admitted to practicing defensive medicine.9 The economic impact of medical liability reaches beyond indemnity payments to include these defensive medicine costs and administrative expenses, among others. Mello and colleagues estimated these combined costs to account for 2.4% of health care expenditures, approximately $55.6 billion annually.10 Congress passed the Health Care Quality Improvement Act of 1986 in an attempt to identify medical practitioners who provide incompetent care and to keep them from changing locations without revealing previous medical malpractice payment or disciplinary actions brought against them. The NPDB was subsequently created by the US Department of Health and Human Services as a mandatory reporting system of medical malpractice payments and adverse actions related to limitations on licensure, clinical privileges, professional society membership, and participation in federal programs. The NPDB contains data reported by malpractice carriers, hospitals, professional societies, and state licensing boards since 1990. Payments made directly by practitioners themselves, and not from insurance or other organization, are not required to be reported to the NPDB. Additionally, surgical malpractice cases in which no payment was made are not included in the dataset. Since the NPDB began data collection in 1990, an analysis of surgical malpractice claims has not been reported. The purpose of this study was to discover patterns and predictors of surgical malpractice payments. Specifically, we sought to evaluate predictors of cases ending in a large payment.
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Table 1. Most Commonly Cited Malpractice Allegations Frequency Malpractice allegation
Improper performance Allegation, not otherwise classified Retained foreign body Improper management Wrong body part Unnecessary procedure Improper technique Failure or lack of informed consent Failure to recognize a complication Delay in performance Failure to perform procedure Patient positioning problem Total
n
%
24,464 14,356 3,528 3,486 1,878 1,761 1,390 1,339 1,186 871 699 553 55,511
41.81 24.53 6.03 5.96 3.21 3.01 2.38 2.29 2.03 1.49 1.19 0.95 95
METHODS The NPDB was queried for surgery-related malpractice payments from 1990 to 2006 involving physicians or residents practicing in the United States. The study interval was chosen after review of the number of annual malpractice entries in the NPDB, as a long time span with large case volumes for analysis. For all statistical work, malpractice payments were adjusted to 2006 dollars using The Federal Reserve Bank of Minneapolis, Consumer Price Index Calculator.11 Payments exceeding $1 million were defined as a large payment because this sum was close to the 95th percentile for payment amounts. Case characteristics and payment trends were analyzed over time and across states. The main outcomes variables were malpractice payment amount and large payment, defined as those ⬎$1 million. The number of malpractice payments, median and mean payment amount, malpractice allegation, patient outcomes, and settlement outside of court judgment served as secondary outcomes. The main independent variables were patient age, sex, and state (50 states and Washington, DC). Standard methods were used to calculate the number, percentage, and mean and median payment amounts. Linear regressions for payment size and number of payments per year were performed. The likelihood of settlement outside of court was compared across states using logistic regression. Multivariate linear regression evaluated the relative contribution of each covariate toward payment size. Multivariate logistic regression evaluated predictors of having a large payment (⬎$1 million). Covariates for both multivariate models included patient sex and age, inpatient status, malpractice allegation, alleged patient outcomes, and state. Fixed effects for patient age, allegation, patient outcomes, and state were used. Reference points in both analyses in-
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Table 2. Alleged Patient Outcomes Frequency Alleged outcomes
Minor permanent injury Significant permanent injury Major temporary injury Minor temporary injury Death Major permanent injury Insignificant injury Quadriplegic, brain damage, lifelong care Cannot be determined Emotional injury only Total
n
%
3,584 3,318 3,184 2,909 2,768 1,518 401 243 173 113 18,211
19.68 18.22 17.48 15.97 15.2 8.34 2.2 1.33 0.95 0.62 100
cluded patient aged 20 to 69 years, malpractice allegations not listed in Table 1, patient outcomes of minor temporary injury, and the state of Ohio. Patient age groupings of younger than 10, 10 to 19, 20 to 69, and 70⫹ years were chosen to explore the contribution of age at each end of the spectrum. Ohio was chosen as a reference because it had an average payment close to the national mean, and represented a significant percentage of claims in relation to other states with similar payments. Coefficients and odds ratios for each state are given in graphical form and in tabular form for the other covariates. All analyses were performed using STATA SE 64-bit, version 11.1 (Stata Corp). Statistical significance was assessed using 2-sided tests, with statistical significance defined as p ⬍ 0.05. Current statutory law in the states demonstrating the highest positive and negative predictive values was analyzed.
RESULTS From ⬎750,000 entries in the NPDB, 11% represented surgery-related malpractice claims. Eighty-nine percent of surgical claims involved US physicians or residents. In total, 58,518 surgical malpractice payments met inclusion criteria. Patients were predominantly female (62%) and were inpatients (63%) with a mean age of 42 years (data available for 18,178 and 17,331 of the total 58,518 cases, respectively). Most claims cited a physician with an MD degree (95%); 4% involved physician with a DO degree, and the rest involved residents. Most cases were paid out with a single named practitioner (95.8%). Mean practitioner age was 44 years. With adjustment for inflation to 2006 dollars, mean payment was $262,727 and median payment amount was $132,915, with a 95th percentile of $983,263. A total of 2,772 claims had payment amounts ⬎$1 million. During the study period, the annual number of claims decreased by
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154 per year, and individual case payments increased by $3,200 per year (p ⬍ 0.0005 for both). Malpractice allegations most frequently cited improper performance (41.8%). Other allegations included retained foreign body (6%), improper management (6%), wrong body part (3.2%), and unnecessary procedure (3%) (Table 1). Alleged malpractice injury (patient outcomes) ranged from death to emotional injuries (Table 2). The most common alleged outcomes were minor permanent injuries (19.7%), significant permanent injuries (18.2%), major and minor temporary injuries (17.5% and 16%), and death (15.2%). Most payments were made by an insurance company or self-insured payment (96%), with the remainder paid by state funds. Most claims were settled outside of court (95%), with only 4% proceeding to a formal court judgment. Significant variability in the likelihood of case settlement outside of the formal court system was seen among states (Fig. 1). States where claims were more likely to be settled in court included NY, AZ, MI, TN, FL, MA, GA, MS, HI, OR, VT, RI, MN, NM, and NV. Cases in WI, IN, SD, LA, WA, AR, CO, VA, NC, KY, NJ, CT, AL, DE, NH, and MD were less likely to reach a formal court judgment. Multivariate analysis: payment size
Patient outcomes were the strongest predictor of payment size. Tragic outcomes of quadriplegia cost $806,000 more, relative to the reference group of minor temporary injuries. Major permanent injuries were $497,000 extra, and cases involving death added $294,000 (all p ⬍ 0.0005). Insignificant injury was the only result associated with a decreased payment of $50,000 (p ⫽ 0.039) (Table 3). Malpractice allegation had varying predictive value for payment size. Compared with less frequently cited allegations (those not listed in Table 1), cases citing retained foreign body were predicted to have $67,000 lower payments (p ⬍ 0.0005); and unnecessary procedure, improper technique, and improper performance predicted an extra $51,000 (p ⫽ 0.017), $31,000 (p ⫽ 0.033), and $28,000 (p ⫽ 0.003), respectively. Cases involving children younger than 10 years old added $61,000 (p ⫽ 0.005); and claims involving patients older than 70 years were associated with smaller payments by $128,000 (p ⬍ 0.0005). Settlements for inpatients had a relative payment increase of $55,000 (p ⬍ 0.0005). Patient sex did not predict payment size. With controlling for multiple covariates discussed here, payments were higher in IL, CT, DE, WI, MA, NY, DC, MN, and GA (Fig. 2). The 3 states with the highest predicted payments were Illinois, ⫹$243,000; Connecticut, ⫹$236,000; and Delaware, ⫹$188,000 (all p ⬍ 0.002). Payments were considerably lower in MI, KS, SC, TX,
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5
4.5
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Odds Rao of selement outside of court
3.5
3
2.5
2
1.5
1
0
* MI KS SC TX * NM NE * LA CA IA * VT UT MT ND * MS * FL WV * SD OK * AL * IN * CO ID * NH * KY MO PA ME * WA * TN * OR * NV * AZ * NC * MD * VA WY AK * NJ * AR * GA * RI * HI * MN DC * NY * MA * WI * DE * CT IL
0.5
State
Figure 1. Odds ratios for likelihood of settling malpractice claim outside of court, by state. *p ⬍ 0.05.
NM, NE, LA, and CA. The 3 states with the lowest predicted payments were Michigan, ⫺$155,000; Kansas, ⫺$152,000; South Carolina, ⫺$130,000 (all p ⬍ 0.0005). A total of 15,945 observations were used for this multivariate analysis. Multivariate analysis: large payment (>$1 million)
Similarly, as seen in payment-size trends, patient outcomes were the strongest predictor of large malpractice settlement (defined as those ⬎$1 million). Outcomes of severe disability (eg, quadriplegia/brain damage/life-long care) (odds ratio [OR] ⫽ 142), major permanent injury (OR ⫽ 66), death (OR ⫽ 28), and significant permanent injury (OR ⫽ 23) increased the likelihood of large payment when compared with minor temporary injuries (p ⬍ 0.0005 for each) (Table 4). Delay in performance was the only malpractice allegation reaching statistical significance in predicting a large payment (OR ⫽ 1.7; p ⫽ 0.04). When compared with 20 to 59-year-olds, claims involving children younger than 10 years old were 1.7 times more likely to receive a large payment (p ⫽ 0.005); and patients older than 70 years were 80% less likely to receive a large payment (p ⬍ 0.0005). Inpatient procedures also positively predicted a large payment (OR ⫽ 1.7; p ⬍ 0.0005). Patient sex was not a significant factor. As with payment size, much variability was observed at the state level (Fig. 3). Claims in IL, CT, WI, RI, NY, MA, and GA were more likely to have a large payment. The 3
states with the highest predictive likelihood of a large payment were Illinois (OR ⫽ 4.6; p ⬍ 0.0005), Connecticut (OR ⫽ 4.3; p ⬍ 0.0005), and Wisconsin (OR ⫽ 3.4; p ⫽ 0.002). Claims in KS, TX, MI, and PA were less likely to have a large payment. The 3 states with the highest negative predictive power for large payment were Kansas (OR ⫽ 0.1; p ⫽ 0.015), Texas (OR ⫽ 0.2; p ⬍ 0.0005), and Michigan (OR ⫽ 0.3; p ⫽ 0.002). A total of 15,496 observations were used for this multivariate analysis.
DISCUSSION A recent analysis of inpatient and outpatient malpractice claims using the NPDB from 2005 to 2009 found the number of overall claims to be decreasing and payment amounts to be stable. Inpatient adverse events were most commonly surgery related.12 In our study, surgical malpractice claims decreased in number but increased in payment amount. Notably, the denominator of number of surgeons and number of total surgical malpractice claims (paid and those not ending in any payment) is not known. Therefore, this yearly decrease in number of paid claims is difficult to interpret. Other studies have shown different rates of change across medical specialties.13,14 As previously reported in an analysis of all medical malpractice claims in the NPDB, we observed considerable variation in payment size among states.15 Not surprisingly, states with higher mean malpractice payments tended to have correspondingly high likelihoods of a large payment
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Table 3. Multivariate Analysis with Outcomes of Adjusted Payment Size Covariate
Inpatient Female Age, y Younger than 10 10 to 19 20 to 69 70 or older Alleged malpractice All other allegations Unnecessary procedure Improper technique Improper performance Delay in performance Failure to recognize a complication Failure to perform procedure Improper management Failure to obtain consent or lack of informed consent Wrong body part Patient positioning problem Surgical or other foreign body retained Alleged outcomes Minor temporary injury Quadriplegic, brain damage, lifelong care Major permanent injury Death Significant permanent injury Major temporary injury Minor permanent injury Emotional injury only Insignificant injury
Coefficient ($)
p Value
55,113 ⫺12,155
⬍0.0005 0.085
95% CI
61,508 ⫺24,562 Reference ⫺128,195
0.005 0.216 — ⬍0.0005
18,472 to 104,545 ⫺63,431 to 14,307 — ⫺150,899 to ⫺105,490
Reference 50,870 30,810 28,217 23,979 19,090 10,424 ⫺11,840 ⫺12,646 ⫺37,408 ⫺52,011 ⫺67,355
— 0.017 0.035 0.003 0.454 0.214 0.694 0.521 0.633 0.097 0.266 ⬍0.0005
— 9,205 to 92,535 2,192 to 59,429 9,622 to 46,811 ⫺38,737 to 86,694 ⫺11,043 to 49,223 ⫺41,473 to 62,321 ⫺48,040 to 24,361 ⫺64,565 to 39,273 ⫺81,577 to 6,762 ⫺143,668 to 39,645 ⫺101,326 to ⫺33,384
Reference 805,729 497,063 294,063 288,361 102,173 94,170 2,521 ⫺50,405
— ⬍0.0005 ⬍0.0005 ⬍0.0005 ⬍0.0005 ⬍0.0005 ⬍0.0005 0.954 0.038
— 744,914 to 866,543 468,189 to 525,937 268,878 to 319,248 264,912 to 311,810 79,183 to 125,163 79,183 to 125,163 ⫺82,575 to 87,617 ⫺98,138 to ⫺2,672
40,989 to 69,236 ⫺25,981 to 1,671
For each state, see Figure 2.
(ie, ⬎$1 million) (Figs. 2 and 3). Interestingly, the likelihood of settlement outside of court does not appear to correlate with state payment size (Fig. 1). It is estimated that only 2% to 3% of patients who suffer harm due to negligence file claims, and that only about half of claimants recover damages.1,2 In a recent study of malpractice risk according to physician specialty, 78% of claims did not result in payments and substantial variation in malpractice payment amounts was seen across specialties.16 Our data show that an overwhelming majority of surgery-related malpractice payments are settled without a formal court judgment, making the individual effect of local legal environments difficult to ascertain. Earlier case series have found patient outcomes to be a strong prognosticator of payment to the plaintiff.17 In our study, patient outcomes were the variable most strongly associated with payment size and with likelihood of having a large payment (ie, ⬎$1 million). Conversely, the mal-
practice allegation against the practitioner was not as strong a predictor. Of the allegations of surgeon misconduct, a large percentage (54%) related to technical performance (eg, improper performance, retained foreign body, wrong body part, improper technique, patient positioning problem). Other types of allegations dealt more with decision-making and judgment (eg, improper management, unnecessary procedure, failure to obtain consent, failure to recognize complication, delay in performance, failure to perform procedure). Negligent events such as retained foreign body, wrong site, and wrong procedures are rare but preventable contributors to surgical malpractice claims. They accounted for 9% of claims in this dataset. Several risk factors for such events have been reported.18,19 A surgical safety checklist has been proposed as a means of avoiding a considerable portion of these types of surgical malpractice claims.20
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2 250000
Coefficient of payment size
1 150000
50000
-50000
-1 150000
* MI * KS * SC * TX * NM * NE * LA * CA IA VT UT MT ND MS FL WV SD OK AL IN CO ID NH KY MO PA ME WA TN OR NV AZ NC MD VA WY AK NJ AR * GA RI HI * MN * DC * NY * MA * WI * DE * CT * IL
-2 250000
State
Figure 2. Payment size coefficients (arrows) and 95% confidence intervals (bars) by state (extension of Table 3 data). *p ⬍ 0.05.
Apart from technical error, many other system-related factors contribute to surgical adverse events and malpractice claims.21,22 Some studies have found that adverse events during surgery are less likely to be caused by negligence than nonsurgical ones.23 It is widely held that most medical and surgical errors are preventable. Medical decision making is as important as technical aspects of surgery. Although technical errors are frequently associated with complicated surgical factors, work to improve decision making and performance in routine procedures might reflexively benefit technical errors.24 When errors in judgment and decision making occur, they are generally due to flawed behavioral practices instead of lack of knowledge.25 Physician–patient communication has been correlated with nonsurgical malpractice claims,26 and it is likely that effective communication similarly improves surgical practices. Substantial variation in payments across states suggests a profound impact from local legal environments, although quantifying the effect of specific tort-reform tactics is difficult. Local malpractice regulations, laws, and legal precedence can extend to settlement decisions made outside of courthouse walls. A recent review of tort-reform publications from medical, economics, and law journals examined 8 of the most widely adopted state tort reforms.27,28 The main tactics used by states to affect malpractice litigation include damage caps, pretrial screening tools, and limiting attorney fees. Proponents of malpractice system reform aim to smooth
payment inconsistencies, improve the culture of medicine, and reduce medical errors.29 Currently, none of the 3 highest payment states (ie, IL, CT, DE) have statutory limits on noneconomic damages for malpractice cases. In fact, the Illinois Supreme Court has held that limitations on noneconomic damages violate the Illinois Constitution. In contrast, all of the 3 lowest payment states (ie, MI, KS, SC) have enacted some form of statutory limitation on noneconomic damages in medical malpractice cases.30 Interestingly, Wisconsin, in the top 3 for likelihood of having a million dollar claim during the study period, enacted a damage cap of $750,000 in April 2006. Kachalia and Mello reported considerable savings in mean indemnity costs, but mixed effects on claims frequency with these caps.31 Stewart and colleagues reported a considerable decrease in the prevalence and cost of surgical malpractice lawsuits in one academic medical center in Texas after the implementation of a noneconomic damage cap and other comprehensive tort reform.32 Among the 3 lowest payment states, there are no formal caps on attorney fees that are specific to medical malpractice cases. In the 3 highest payment states, however, each has enacted a complicated regimen for limiting the percentage of a judgment that attorneys can take as a fee in medical malpractice cases. These reforms have not been shown to substantially impact claims frequency or payment amounts.31 Pretrial screening generally takes the form of required mediation or settlement conferences before trials begin.
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Table 4. Multivariate Analysis with Outcomes of Large Payment (⬎$1 Million) Covariate
Inpatient Female Age, y Younger than 10 10 to 19 20 to 69 70 or older Alleged malpractice All other allegations Delay in performance Failure to perform procedure Failure to recognize a complication Improper technique Improper performance Failure to obtain consent or lack of informed consent Unnecessary procedure Improper management Wrong body part Patient positioning problem Surgical or other foreign body retained Alleged outcomes Minor temporary injury Quadriplegic, brain damage, lifelong care Major permanent injury Death Significant permanent injury Minor permanent injury Major temporary injury Emotional injury only Insignificant injury
Odds ratio
p Value
95% CI
⬍0.0005 0.223
1.5–2.1 0.8–1.1
1.7 0.9 Reference 0.2
0.005 0.566 — ⬍0.0005
1.2–2.4 0.6–1.4 — 0.1–0.3
Reference 1.6 1.6 1.2 1.2 1.2 1.1 1.1 1.0 0.9 0.7 0.5
— 0.042 0.085 0.229 0.324 0.141 0.663 0.652 0.981 0.81 0.533 0.083
— 1.0–2.7 0.9–2.6 0.9–1.6 0.8–1.6 1.0–1.4 0.6–2.1 0.7–1.8 0.7–1.5 0.5–1.8 0.2–2.3 0.2–1.1
Reference 142.2 66.1 27.8 23.1 7.2 5.6 Omitted Omitted
— ⬍0.0005 ⬍0.0005 ⬍0.0005 ⬍0.0005 ⬍0.0005 ⬍0.0005 — —
— 69.8–289.6 34.7–125.8 14.6–53.0 12.1–43.8 3.7–13.9 2.9–11.0 — —
1.7 0.9
For each state, see Figure 3.
Certificates of merit are an additional tool intended to reduce the number of superfluous claims. Two of the three lowest payment states require pretrial screening in the form of mediation (ie, MI and SC), and the third requires a settlement conference (ie, KS). Among the 3 highest payment states, only 1 requires a pretrial review panel (ie, DE). However, there is no clear reason why these pretrial requirements would have a systematic impact on payment size, and pretrial screening has failed to demonstrate an effect on indemnity costs, claims frequency, or malpractice premiums.31 These correlations with state-to-state malpractice reforms should be interpreted as associations and are in no way meant to be construed as causal relationships. Far too many factors surround medical malpractice decisions than can be fully addressed in this analysis. Our study has several limitations, in addition to the fact that it relies on the quality of data contained in the NPDB. The study time period was chosen to reflect large case num-
bers for analysis and is subject to reporting and data recording variations. Reporting to the NPDB is not required for being named in a malpractice suit that does not end in a payment, or if any payment is made directly from a physician’s own personal funds. Therefore, we cannot compare cases that ended in payments with cases that were dismissed or ended in no payment at all. For this study, there is also no way to determine the rate of malpractice claims across specific surgical subspecialties or with regard to type or surgical encounter.
CONCLUSIONS Nationwide, surgical malpractice claims demonstrated rising payment amounts. Patient outcomes are the strongest predictor of payment size. Considerable variation in payment size exists between states, suggesting a profound impact from the local legal environments. Studies of surgical
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1 10
9
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of Million dollar payment
7
6
5
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4
3
2
1
* MI * KS SC * TX NM NE LA CA IA VT UT MT ND MS FL WV SD OK AL IN CO ID NH KY MO * PA ME WA TN OR NV AZ NC MD VA WY AK NJ AR * GA * RI HI MN DC * NY * MA * WI DE * CT * IL
0
State
Figure 3. Odds ratios for likelihood of large payment by state (extension of Table 4 data). *p ⬍ 0.05.
malpractice payments add valuable perspective to the discussion of health care reform. These data can alert the medical community to areas for improvement, both in individual practices and across entire health care systems. Hopefully, this information will aid in pushing toward the goal of providing safer, higher-quality medical care, and justly reimbursing those harmed by divergence from such practice. Author Contributions
Study conception and design: Orosco, Chang, MA Talamini Acquisition of data: Orosco, Chang Analysis and interpretation of data: Orosco, J Talamini, Chang Drafting of manuscript: Orosco, J Talamini, Chang Critical revision: Chang, MA Talamini
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