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What Are the Variables That Are Associated with the Patient's Wish to Sue His Physician in Patients with Acute and Chronic Pain?

David A. Fishbain MD, FAPA, Daniel Bruns PsyD, John Mark Disorbio EdD, John E. Lewis PhD
DOI: http://dx.doi.org/10.1111/j.1526-4637.2008.00484.x 1130-1142 First published online: 1 November 2008

ABSTRACT

Objectives. Although there is limited research on patient attributes that may be related to reasons for launching a malpractice suit, no such research has been performed in acute pain patients (APPs) or chronic pain patients (CPPs). The objective of this study was then to develop some statistical models that would describe such patients' attributes.

Methods. A statement about having thoughts of suing a physician (sue medical doctor [MD]) is the focus of this study, and was contained within the Battery for Health Improvement (BHI) research version (BHI-R). The BHI-R was administered to 1,487 community subjects (1,329 healthy and 158 nonhealthy) and 777 patients in rehabilitation of whom 326 were APPs, 341 were CPPs, and 110 had no pain. In addition, descriptive data, such as whether the patient had an attorney for a worker's compensation claim, was collected. The sue MD Likert scale responses were dichotomized, and the relative risks for the sue MD wish were calculated for the aforementioned groups utilizing the healthy community group as the reference group. With APPs and CPPs, those patients responding alternatively affirmatively to the sue MD statement were compared with those patients responding negatively on all available categorical variables and BHI 2 scales via appropriate statistics. If a BHI 2 scale was statistically significant at P < 0.001, then all the questions from this scale were analyzed for significance by chi-square. Significant categorical variables (P < 0.001) and significant BHI 2 questions were then utilized as independent variables in a logistic regression model to assess the predictability of the independent variables for sue MD.

Setting. Variety of settings.

Result. The relative risks for affirming the sue MD statement relative to the healthy community sample for various groups were as follows in order of ascending risk: APPs in rehabilitation; nonhealthy community members; rehabilitation patients in general; rehabilitation patients without pain; CPPs in rehabilitation; and with the highest risk being rehabilitation patients with worker's compensation litigation. For APPs, the logistic regression model utilized three variables: trusting physicians (protected against sue MD); physicians appearing to be motivated by financial incentives; and being upset over one's health (depression variable). This model classified 96% of the patients correctly. For CPPs, the logistic regression model also utilized three variables: being in worker's compensation litigation; being coerced to see a distrusted physician; and being angry with the physician. This model classified 93% of the patients correctly.

Conclusions. CPPs are at a greater risk than patients without pain and APPs for harboring the sue MD wish. Some patient attributes and the referral/treatment situation appear to be important predictors for harboring the sue MD wish, but differ between APPs and CPPs.

  • Sue Physicians
  • Wish to Sue Physicians
  • Predictor Variables Wish to Sue Physicians
  • Battery for Health Improvement (BHI 2)
  • Doctor Dissatisfaction Scale (DDS)
  • Patient–Physician Interaction
  • Patients
  • Litigation
  • Malpractice
  • Patient Characteristics
  • Medicolegal
  • Lawsuits
  • Worker's Compensation
  • Depression
  • Trust

Introduction

Presently, litigation over malpractice adds huge costs to the overall health care costs in the United States. It has been estimated that in addition to 5 billion in malpractice premiums and uncounted billions in court costs, another 14 billion is spent on “defensive medicine” procedures in order to protect against malpractice suits [1]. It appears that there is evidence that physicians try to reduce medicolegal risk by ordering tests and procedures that are of marginal or no medical benefit [2]. Presently, there is a new medical malpractice crisis underway. This crisis is apparently the result of a staggering increase in the size of payout to successful plaintiffs, a substantial increase in the average administrative costs associated with defending claims, but a small increase in the frequency of claims [3]. Because of the increased payouts, the new malpractice crisis was thought to be associated with run-away juries. However, there is some evidence [4] that juries appear to treat physicians fairly: the stronger the plaintiff's evidence of negligence, the greater the likelihood of the plaintiff's verdict [4]. Plaintiffs win 10–20% of cases, but reviewers feel they should lose 20–30% of cases rated as toss-ups, and roughly 50% of the cases with strong evidence for negligence [4]. It is to be noted that these data do not include frivolous cases that may have been settled pretrial.

Besides the statistical data on malpractice suits briefly reviewed previously, research into malpractice suits can be broken down into four general areas of inquiry [5]: what are the specific attributes of the injury, is there negligence or not; what are the attributes of the physician involved; what was the nature of the patient–physician relationship before, during, and after the injury; and what are the attributes of the patient and how do these contribute to the malpractice allegations? Research on these four areas of inquiry can then be summarized as follows: in reference to negligence (attribute of the injury), it appears that negligence may not be the determining factor in whether a lawsuit is initiated. Negligence is poorly correlated with actual lawsuit incidence [6,7]. In one study of 100 medicolegal cases, clinical analysis found negligence to be an issue in only 56% [8]. In the other 44%, reasons for the lawsuit were the following: inability to come to terms with disease or end results (21%), lack of understanding of disease process (16%), and unreasonable medicolegal action (7%) [8]. In another recent study [9] of a review of 1,452 closed claims by trained physicians, it was found that for 3% of the claims, there was no justifiable medical injury, and in 37%, there was no medical error. These kinds of studies indicate that there may be other reasons besides negligence (attributes of the injury) for initiation of malpractice suits.

In reference to the physician attributes involved, there has only been limited research. Here, it appears that the number of lawsuits incurred does not relate to the quality of medicine practiced [10]. Personal attributes, such as stern tone of the presenter, appear to relate to malpractice history [11]. It is unclear why physician personal attributes, such as tone of voice, relate to malpractice history, but this could be because physician personal attributes relate to the strength of the physician–patient relationship.

With regard to the physician–patient relationship, there is significant evidence that a strong relationship may protect against malpractice suits [5,12–14]. Of 100 suit-prone patients, only 16% proceeded with litigation [15], and it is believed that this relates to the strength of the patient–physician relationship [15,16] and physician–patient communications [14,17]. Similar results are also available from malpractice insurance carriers. Here, of those patients having the ability to bring forward a malpractice suit for failure to act or acting inappropriately, only less than 10% did [16].

There is very little data regarding patient attribute associated with malpractice suits. However, some studies have suggested that being affluent [18], having a higher education [18], and being a woman [19] are associated with being more likely to bring forward such a suit. Little is known about the personality of the patient who wishes or has initiated a lawsuit [20]. However, on the basis of clinical observation, Virshup and others [21] and Hsia [22] have observed that patient anger is a factor.

The area of patient attributes is important because some authors [23] have postulated that in some lawsuits, the institution of a lawsuit may be secondary to patient attributes that the physician can neither anticipate nor control. These patients may have “low threshold” for filing a lawsuit [23,24].

There have been a number of case reports pertaining to the area of pain treatment and medical malpractice [25–29], but no systematic research. It is therefore the objective here to report on the results of a study that investigated a group of chronic pain patients (CPPs) and acute pain patients (APPs) who affirmed on a standardized questionnaire that they had a wish to sue one of their physicians. For these patients, their patient attributes and their patient–physician relationship were explored in relation to this wish. To the authors' knowledge, this is the first such study in the literature on relationship to pain patients.

Methods

A statement about having thoughts of suing a physician (sue medical doctor [MD]), which is the focus of this study, was one of the 600 questions/statements contained within the Battery for Health Improvement (BHI) research version (BHI-R) and the Battery for Health Improvement 2 (BHI 2) [30], which is a shorter version of the BHI-R. The BHI-R was administered to the subjects in this study, and the BHI 2 scales were scored from this.

The BHI 2 is a published, standardized, valid [30], and reliable [30] psychological test. It is intended for the psychological assessment of medical patients, and was based on a biopsychosocial theory [31]. The BHI 2 has been integrated into clinical protocols [32,33].

This test contains 18 scales: two validity scales (self-disclosure and defensiveness); four physical symptoms scales (somatic complaints, pain complaints, functional complaints, and muscular bracing); three affective scales (depression, anxiety, and hostility); five character scales (borderline, symptom dependency, chronic maladjustment, substance abuse, and perseverance); and four psychosocial scales (family dysfunction, survivor of violence, doctor dissatisfaction, and job dissatisfaction). The job dissatisfaction scale was not included in the analyses in the present study as many of the subjects were not in the workforce [30].

In the development of the BHI 2, the BHI-R was administered to 777 rehabilitation patients who were under treatment for pain or a physical injury and were from 30 states in all four geographical regions of the United States. They were recruited by posters or flyers provided to them by their providers, and were from a variety of settings: acute physical therapy, work hardening programs, chronic pain programs, physician offices, and vocational rehabilitation settings. These patients were also drawn from various payor systems (Medicare, private insurance, worker's compensation, and auto insurance), and their diagnoses included a range of orthopedic injuries, headache and head injuries, fibromyalgia, and complex regional pain syndrome. Any patient wishing to enter was allowed entrance into the study group. The only exclusion criteria were being less than 18 or over 65 and not able to read at the sixth grade level.

All 777 rehabilitation patients were administered with the BHI-R anonymously, and signed an informed consent indicating that the information would be used for research purposes only and that no results or feedback would be given. Patients were informed that the information would not influence the course of their clinical care.

Of these 777 rehabilitation patients, for the purposes of this study, 667 were first identified as being treated for pain if they reported that their lowest pain in the last month was greater than zero, indicating no episodes of being pain free. Of these pain patients, patients were selected as suffering from chronic pain (CPPs) if they had pain for greater than 90 days. Pain patients not fulfilling these criteria were then classified as having acute pain (APPs). The sample of rehabilitation patients who had no pain (N = 110) was utilized as a reference group for part of the analyses described further.

Community healthy and community nonhealthy control groups were also established by administering the BHI-R to 1,487 community subjects from 16 states in all four geographical areas of the United States. These subjects were recruited by newspaper advertisements and posters. They were stratified according to race, education, age, and gender, and the subjects were recruited to match these demographics. No subject was excluded on the basis of past or present medical or psychological diagnosis. All community subjects were asked if they had any serious medical conditions. Those who reported no serious medical conditions constituted the “healthy” (N = 1,329) subset of the community sample, leaving 158 nonhealthy community subjects. These categories were later utilized for the relative risk analysis described further. For a complete description of these subjects, please see Bruns and Disorbio [30].

Besides the completed BHI-R, additional data collected included the following: age, gender, highest level of education (less than high school graduate, high school graduate, some college, or college graduate or higher), ethnicity (non-white vs all others), worker's compensation status (yes vs no), litigation (whether the patient has an attorney for a worker's compensation claim) status (yes vs no), personal injury status (yes vs no), injury type (lower extremity, upper extremity, headache/head injury, neck injury, low back injury, and multiple injury), insurance type (Medicare/Medicaid, personal injury, private health insurance, or worker's compensation), and medical setting (acute physical therapy, pain program, or work hardening). Demographic data, except for age, were analyzed as categorical variables (described further).

Data Analysis

The sue MD statement about thoughts of suing a physician was scored on a Likert-scale format with the responses being strongly disagree, disagree, agree, and strongly agree being assigned scores 1 through 4, respectively. For the analyses described further, the sue MD item/variable was transformed to a dichotomy. Here, the subjects were classified as having a wish to sue their physician if they agreed or strongly agreed with the statement.

Data were analyzed using SPSS 14.0 software (SPSS Inc., Chicago, IL). Frequency and descriptive statistics were calculated to check all relevant characteristics of the data for each patient group. The relative risk for the wish to sue MD was calculated using the healthy community sample (N = 1,329) as the reference group, compared with the total community group (N = 1,487), community nonhealthy patients (N = 158), pain patients in rehabilitation with chronic pain (N = 341), patients in rehabilitation without pain (N = 110), patients in rehabilitation with chronic pain (N = 134), patients in rehabilitation with acute pain (N = 326), patients in rehabilitation with worker's compensation (N = 264), patients in rehabilitation with personal injury (N = 82), and patients in rehabilitation with worker's compensation litigation (N = 199). For patients in rehabilitation with worker's compensation, patients in rehabilitation with personal injury, patients in rehabilitation with worker's compensation litigation, patients in rehabilitation with worker's compensation and worker's compensation litigation (N = 84), and patients in rehabilitation with personal injury and worker's compensation litigation (N = 48), the relative risk values were calculated within each of these groupings for patients who had no pain, those who had acute pain, and those who had chronic pain in comparison with the healthy community reference group.

Student's t-tests were used to assess the age and the scales from the BHI 2 for each pain group separately, comparing those who responded affirmatively on the sue MD item with those who did not express this desire. If a BHI 2 scale was significantly different (P < 0.001), then the scale was subjected to further analysis. All of the items (questions) that were subsumed under this scale were then analyzed by chi-square to assess their individual significance as categorical variables. Other categorical demographic variables were also then analyzed by chi-square. Significant categorical variables (P ≤ 0.001) both from the significant BHI 2 scales and from other categorical variables, e.g., litigation, were then used as independent variables in a logistic regression model to assess the predictability for any of the independent variables on sue MD. The α = 0.001 level of significance was employed in this study because of the large number of analyses and the large sample size. Thus, we wanted to ensure that our type I error rate was minimized as much as possible and to rule out spurious findings.

Results

Table 1 displays the relative risk values for each respondent group for affirming that they had the wish to sue MD. The healthy community nonpatient sample was used as the reference group for calculating each relative risk. The highest relative risk for the wish to sue MD within each grouping was found for (Table 1) worker's compensation litigation (7.35) in the patients in rehabilitation group, without pain (5.54) in the patients in rehabilitation with worker's compensation group, chronic pain (3.59) in the patients in rehabilitation with personal injury group, chronic pain (8.05) in the patients in rehabilitation with worker's compensation litigation group, without pain (13.29) in the patients in rehabilitation with worker's compensation and worker's compensation litigation group, and chronic pain (5.11) in the patients in rehabilitation with personal injury and litigation groups.

View this table:
Table 1

Relative risk of respondent groups (total N = 2,264) for affirming that they would like to sue one of their physicians

CategoryTotal NPercent Wishing to Sue MDRelative Risk
Healthy community (reference group)1,329 1.50 1.00
Healthy community plus nonhealthy community1,487 1.88 1.25
Community nonhealthy  158 5.06 3.36
Patients in rehabilitation  777 5.41 3.59
Patients in rehabilitation without pain  110 5.45 3.62
Patients in rehabilitation with acute pain  326 3.99 2.65
Patients in rehabilitation with chronic pain  341 6.74 4.48
Patients in rehabilitation with worker's compensation  264 6.06 4.03
Patients in rehabilitation with personal injury   82 3.66 2.43
Patients in rehabilitation with worker's compensation litigation  19911.06 7.35
Patients in rehabilitation with worker's compensation
  Without pain   24 8.33 5.54
  With acute pain   86 4.65 3.03
  With chronic pain  154 6.49 4.31
Patients in rehabilitation with personal injury
  Without pain   6 0.00 0.00
  With acute pain   39 2.56 1.70
  With chronic pain   37 5.41 3.59
Patients in rehabilitation with worker's compensation litigation
  Without pain   16 6.25 4.15
  With acute pain   51 9.80 6.51
  With chronic pain  13212.12 8.05
Patients in rehabilitation with worker's compensation and worker's compensation litigation
  Without pain    520.0013.29
  With acute pain   1811.11 7.38
  With chronic pain   6113.11 8.71
Patients in rehabilitation with personal injury and litigation
  Without pain    4 0.00 0.00
  With acute pain   18 5.56 3.69
  With chronic pain   26 7.69 5.11

Demographic comparisons for the patients in rehabilitation without pain, with acute, and chronic pain are displayed in Table 2. Of the chronic pain sample, 6.7% (N = 23) affirmed the sue MD statement, while 4.0% (N = 13) of APPs and 5.5% (N = 6) of patients without pain affirmed the sue MD statement. These differences, however, were not statistically significant.

View this table:
Table 2

Demographic comparisons for rehabilitation patient subgroups (no pain, acute pain, and chronic pain)

VariableCategoryChronic Pain (N = 341)Acute Pain (N = 326)Patients with No Pain (N = 110)Statistic, P Value
Age*,†M = 39.8 (SD = 10.1) R = 19, 65M = 36.4 (SD = 11.5) R = 18, 65M = 40.9 (SD = 10.6) R = 18, 64F(2, 776) = 11.0, P < 0.001
GenderMale149 (43.7%)146 (44.8%)45 (40.9%)χ2(2) = 0.50, P = 0.78
Female192 (56.3%)180 (55.2%)65 (59.1%)
Highest level of educationLess than high school graduate55 (16.1%)32 (9.8%)16 (14.5%)χ2(6) = 21.3, P = 0.002
High school graduate94 (27.6%)88 (27.0%)31 (28.2%)
Some college or tech school142 (41.6%)117 (35.9%)43 (39.1%)
College graduate or more45 (13.2%)85 (26.1%)19 (17.3%)
Unknown5 (1.5%)4 (1.2%)1 (0.9%)
RaceWhite275 (80.6%)278 (85.3%)83 (75.5%)χ2(10) = 18.8, P = 0.042
Black25 (7.3%)19 (5.8%)14 (12.7%)
Asian1 (0.3%)3 (0.9%)3 (2.7%)
Native Americans13 (0.7%)6 (1.8%)1 (0.9%)
Hispanic21 (6.2%)14 (4.3%)6 (5.5%)
Other1 (0.3%)3 (0.9%)0
Unknown5 (1.5%)3 (0.9%)3 (2.7%)
Wish to sue MDNo318 (93.3)313 (96.0%)104 (94.5%)χ2(2) = 2.48, P = 0.29
Yes23 (6.7)13 (4.0%)6 (5.5%)
  • * Acute pain different from patients with no pain.

  • Chronic pain different from acute pain.

  • SD = standard deviation.

T-tests and Chi-Square Analyses for CPPs

Those CPPs who affirmed the wish to sue MD scored significantly higher on the BHI 2 doctor dissatisfaction scale compared with those CPPs who did not affirm a desire to sue MD (see Table 3). A higher proportion of those affirming the wish to sue MD was involved in worker's compensation litigation, which was the only significant demographic categorical variable (Table 4). A higher proportion of those affirming the desire to sue MD was 1) thinking that some MDs are stupid (doctor dissatisfaction), 2) coerced to see distrusted MD (doctor dissatisfaction), and 3) were angry with MDs (doctor dissatisfaction), compared with those not affirming the wish to sue MD (Table 4).

View this table:
Table 3

Battery for Health Improvement (BHI) 2 scale scores for chronic pain patients

BHI 2 Scale T ScoreNo sue MD (N = 318)Yes sue MD (N = 23)t Statistic (df)P Value
MeanSDMeanSD
Somatic complaints52.8110.4156.6212.261.7 (339)0.10
Pain complaints52.80 9.5056.4912.711.8 (339)0.08
Functional complaints54.7310.1655.57 9.380.4 (339)0.70
Muscular bracing52.59 9.2454.51 7.661.0 (339)0.33
Depression52.5810.1454.55 9.580.9 (339)0.37
Anxiety49.93 9.9050.81 6.490.4 (339)0.67
Hostility50.3510.5653.22 8.241.3 (339)0.20
Borderline50.42 9.9454.0810.421.7 (339)0.09
Symptom dependency52.1610.9053.50 8.650.6 (339)0.56
Chronic maladjustment49.7610.2450.56 9.280.4 (339)0.72
Substance abuse50.9210.2048.05 7.841.3 (339)0.19
Perseverance49.7810.4749.67 8.720.1 (339)0.96
Family dysfunction51.1710.0652.96 9.380.8 (339)0.41
Survivor of violence50.41 9.9352.66 9.351.1 (339)0.29
Doctor dissatisfaction50.7610.3159.7411.974.0 (339)0.001
  • SD = standard deviation.

View this table:
Table 4

Comparisons for significant categorical demographic and Battery for Health Improvement (BHI) 2 scale items

VariableVariable from which BHI 2 ScaleCategoryNo sue MDYes sue MDχ2 Statistic (df)P Value
Worker compensation litigation statusNot applicableNo202 (63.5%)7 (30.4%) 9.9 (1)0.001
Yes116 (36.5%)16 (69.6%)
Some of my MDs are stupidDoctor dissatisfactionNo202 (63.5%) 6 (26.1%)12.6 (1)0.001
Yes116 (36.5%)17 (73.9%)
Coerced to see mistrusted MDDoctor dissatisfactionNo295 (92.8%)17 (73.9%) 9.8 (1)0.001
Yes 23 (7.2%) 6 (26.1%)
Anger with MDsDoctor dissatisfactionNo272 (85.5%) 11 (47.8%)21.6 (1)0.001
Yes 46 (14.5%)12 (52.2%)

T-tests and Chi-Square Analyses for APPs

Tables 5 and 6 display the results of the significant scales of the BHI 2 and the BHI 2 individual items significant for APPs. Those patients who affirmed the wish to sue MD scored significantly higher on the BHI 2 scales of depression (P < 0.001) and doctor dissatisfaction (P < 0.001) compared with those patients who did not affirm the desire to sue MD (Table 5). Problems with functioning, somatic complaints, muscular bracing, hostility, borderline personality traits, family dysfunction, and being a survivor of violence were also significantly higher patients affirming a desire to sue MD, while the capacity for perseverance was significantly lower. However, none of these variables reached the P < 0.001 level of significance needed for further study.

View this table:
Table 5

Battery for Health Improvement (BHI) 2 scale scores for acute pain patients

BHI 2 Scale T ScoresNo sue MD (N = 313)Yes sue MD (N = 13)t Statistic (df)P Value
MeanSDMeanSD
Somatic complaints47.61 9.1855.04 10.04 2.8 (324)0.005
Pain complaints46.65 8.8747.75 9.790.44 (324)0.66
Functional complaints46.01 8.8652.6710.06 2.6 (324)0.01
Muscular bracing47.72 9.9953.80 8.72 2.0 (324)0.05
Depression47.15 9.4757.2410.17 3.8 (324)0.001
Anxiety49.00 9.5352.6511.46 1.3 (324)0.18
Hostility48.85 9.4954.8512.30 2.2 (324)0.03
Borderline48.70 9.9057.6311.44 3.2 (324)0.002
Symptom dependency47.43 9.4850.9212.00 1.3 (324)0.20
Chronic maladjustment49.31 9.9752.91 9.97 1.3 (324)0.20
Substance abuse49.20 9.9653.6610.26 1.6 (324)0.11
Perseverance50.95 9.7542.9113.70 2.9 (324)0.004
Family dysfunction48.8510.1654.87 8.22 2.1 (324)0.04
Survivor of violence49.21 9.6554.6310.66 2.0 (324)0.05
Doctor dissatisfaction48.45 9.3659.2613.31 4.0 (324)0.001
  • SD = standard deviation.

View this table:
Table 6

Comparisons for significant categorical Battery for Health Improvement (BHI) 2 scale items for acute pain patients

VariableVariable from which BHI 2 ScaleCategoryNo sue MDYes sue MDχ2 Statistic (df)P Value
Trust MDsDoctor dissatisfactionNo79 (25.2%) 9 (69.2%)12.3 (1)<0.001
Yes234 (74.8%) 4 (30.8%)
Coerced to see mistrusted MDDoctor dissatisfactionNo304 (97.1%) 9 (69.2%)25.4 (1)<0.001
Yes  9 (2.9%) 4 (30.8%)
Anger with MDsDoctor dissatisfactionNo290 (92.7%) 7 (53.8%)23.2 (1)<0.001
Yes 23 (7.3%) 6 (46.2%)
MDs motivated by financial interestsDoctor dissatisfactionNo297 (94.9%) 7 (53.8%)33.4 (1)<0.001
Yes 16 (5.1%) 6 (46.2%)
Depressed by medical conditionDepressionNo200 (63.9%) 2 (15.4%)12.5 (1)<0.001
Yes113 (36.1%11 (8.56%)
Upset with healthDepressionNo257 (82.1%) 4 (30.8%)20.6 (1)<0.001
Yes 56 (17.9%) 9 (69.2%)
Suicidal ideationDepressionNo298 (95.2%) 9 (69.2%)15.3 (1)<0.001
Yes 15 (4.8%) 4 (30.8%)

None of the categorical demographic variables were significantly different between those APPs affirming the sue MD wish and those not affirming the sue MD wish. A lower percentage of those affirming the sue MD wish said that they trusted MDs (doctor dissatisfaction), compared with those who did not affirm the sue MD wish. A greater percentage of those affirming the sue MD wish vs those not affirming the sue MD wish reported that 1) they feel coerced to see a distrusted MD (doctor dissatisfaction), 2) they are angry with their MDs (doctor dissatisfaction), 3) MDs are motivated primarily by financial incentives, 4) they have reacted to their medical condition with depression (depression), 5) they are very upset with their health (depression), and 6) they have had suicidal ideation (depression) (Table 6).

Logistic Regression for Significant Independent Variables with Sue-MD as the Dependent Variable for CPPs (Table 7)

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Table 7

Final model logistic regression results for prior significant independent variables with sue MD as the dependent variable for chronic pain patients

Step χ2 (df), P ValuePercentage of Cases Predicted Correctly by the ModelStep Nagelkerke R2VariableAssociated BHI 2 ScaleBWald, P ValueOdds RatioLower 95% CI for Odds RatioUpper 95% CI for Odds Ratio
16.3 (1), <0.00193.30.120Litigation statusNot applicable1.084.97, 0.0262.961.1407.670
6.3 (1), 0.01293.30.044Forced to see mistrusted MDDoctor dissatisfaction1.084.18, 0.0412.931.045 8.217
4.5 (1), 0.03593.30.032Anger with MDsDoctor dissatisfaction1.327.50, 0.0063.761.457 9.696
  • BHI = Battery for Health Improvement; CI = confidence interval.

A logistic regression was conducted with statistically significant variables from the prior analyses as the independent, and Sue-MD as the dependent variable for CPPs. The aforementioned signifi cant variables were entered into a sequential logistic regression model to test the individual contribution of each predictor in the final model. Table 7 includes the step χ2 and significance level, step Nagelkerke R2, and the final regression coefficient, Wald statistic and significance level, and odds ratio and 95% confidence intervals. The final model chi-square for the analysis was significant (χ2 = 27.06[3], P < 0.001). The model classified 93% of the subjects correctly.

Litigation status, feeling coerced to see a mistrusted MD, and anger with MDs were the significant predictors of the sue MD variable that were retained in the final model for CPPs. The odds of reporting the desire to sue MD were increased by almost three times for being involved in “litigation” and for feeling coerced to see a mistrusted MD, and by over 3.5 times for anger with MDs (Table 7). Other variables were insignificant and were not retained in the final model.

Logistic Regression for Significant Independent Variables with Sue MD as the Dependent Variable for APPs (Table 8)

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Table 8

Final model logistic regression results for prior significant independent variables with sue MD as the dependent variable for acute pain patients

Step χ2 (df), P ValuePercentage of Cases Predicted Correctly by the ModelStep Nagelkerke R2VariableAssociated BHI 2 ScaleBWald, P ValueOdds RatioLower 95% CI for Odds RatioUpper 95% CI for Odds Ratio
16.8 (1), <0.00196.00.177Trust MDsDoctor dissatisfaction−1.51 5.11, 0.0240.220.0600.818
11.4 (1), 0.00195.70.114MDs motivated by financial incentivesDoctor dissatisfaction 2.1910.42, 0.001 8.932.36333.75
 5.4 (1), 0.02096.30.053Upset with healthDepression 2.1210.29, 0.001 8.372.28530.64
  • BHI = Battery for Health Improvement; CI = confidence interval.

A logistic regression was conducted with statistically significant variables from the prior analyses as the independent, and sue MD as the dependent variable for APPs. The aforementioned significant variables were entered into a sequential logistic regression model to test the individual contribution of each predictor in the final model. Table 8 includes the step χ2 and significance level, step Nagelkerke R2, and the final regression coefficient, Wald statistic and significance level, and odds ratio and 95% confidence intervals. The final model chi-square for the analysis was significant (χ2 = 33.58[3], P < 0.001). The model classified 96% of the subjects correctly.

“Trust MDs,” “MDs motivated by financial incentives,” and “upset with health” were the significant predictors of the sue MD variable that were retained in the final model for APPs (Table 8). The odds of reporting the desire to sue MD were increased by over eight times for believing that MDs are motivated by financial incentives and being “upset with health.” The odds of wanting to sue MD were 78% less likely by trusting physicians. Other variables were insignificant and were not retained in the final model.

Discussion

To the authors' knowledge, this is the first study to explore the question of what are the characteristics of APPs and CPPs who harbor a wish to sue a physician (sue MD). A number of general observations can be made in reference to the results of this study. These are the following: 1) the risk of harboring a wish to sue MD is increased by being nonhealthy, being in rehabilitation, being inrehabilitation with chronic pain, and being in rehabilitation and having worker's compensation litigation (Table 1). It is also to be noted that within all the subcategories, e.g., patients in rehabilitation with personal injury, the risk for the sue MD wish was always greater for CPPs vs APPs (Table 1). 2) Patients with chronic pain tended to have fewer college graduates and had fewer white members than APPs (Table 2); 3) for CPPs, three major categorical variables were found to predict the sue MD wish: being in litigation over worker's compensation issues, being coerced to see a distrusted MD, and being angry with physicians (Table 7). This then is the picture of the CPP contemplating suing his/her physician. This model classified 93% of the patients correctly; and 4) for APPs, three major categorical variables predicted the sue MD wish: trusting physicians protected against this wish, physicians perceived as being motivated by financial incentives, and being upset with one's health (Table 8). These then are the characteristics of the APP who is contemplating suing his/her physician. This model was even better than the previous one, classifying 96% of the patients correctly. These observations will be discussed in detail further according to relevant previous literature.

As noted previously, patients with chronic pain were at greater risk than other rehabilitation patients and APPs for affirming the sue MD wish. There is no previous literature that has addressed this association. However, intuitively, this finding appears to be correct. CPPs would be exposed to a chronic condition (pain) for a longer period of time, during which time such a wish would be more likely to develop.

Previous or current litigation has also not previously been identified as a variable important to the physician litigation literature. However, again, this finding appears to be intuitively correct. Patients in litigation or having a history of litigation should be more familiar with the litigation process and intellectually more prepared to carry it through. Conversely, prior experience with the legal system might discourage them from considering suing. However, this was not our statistical finding.

There is also no previous physician litigation literature that has identified feeling coerced to see a distrusted MD as a potentially important variable in contemplating litigation. However, this variable has been described as being potentially important in the pain-violence literature. Here, it appears important for being a potential reason for contemplated violence against physicians [34,35]. Within the worker's compensation system, pain treatment often involves the carrier choosing the treating physician. The patient is precluded from seeing preferred physicians either by lack of insurance or because if this is done, the carrier may deny benefits. As such, the patient cannot leave the physician's care. These patients are usually involved in litigation with their carriers, and as such, may see the assigned (correctly or erroneously) physician as an agent of the carrier and thereby having a conflict of interest rather than being his/her physician. The patient therefore feels trapped/cornered/coerced [12]. Here, there is naturally a lack of a “therapeutic alliance”[20]. As noted previously, a strong patient–doctor relationship may protect against malpractice suits [5,12–14]. Consequently, the lack of a therapeutic alliance in these situations would naturally lead to a weak patient–doctor relationship that could then expose the physician to the contemplation of a lawsuit by the patient. The point here is that the nature of the referral-treatment situation exposes the physician to the patient contemplating a suit. Thus, the results of this study appear to be similar to some factors identified in the violence literature for potential pain patient violence.

There is a significant previous physician lawsuit literature [5,21,36], which indicates that patient anger at the physician is an important reason for the initiation of the lawsuit. Thus, our results support this literature, and in turn, this literature supports our results. However, these results do not necessarily mean that the patient is angry at the physician for perceived bad treatment or medical error. It is also possible that anger, which preexisted the bad treatment or medical error, predisposed the patient to the sue MD wish. There is some evidence for this possibility in the previous physician lawsuit literature. Here, in the only experimental study in this area of research, Linberg [37] took a number of test subjects and exposed them to sand in the university basement. He then had an alleged construction worker walk in and advise the subjects that the sand would damage their lungs. Those subjects who perceived danger and had the personality characteristic of anger contemplated a lawsuit [37]. Thus, our findings could be a function of inherent patient anger rather than a function of bad treatment or medical error.

There is obviously no previous physician litigation literature that has addressed the patient's perception that physicians are motivated by financial incentives as a factor in contemplated litigation. However, this variable could be closely related to patient anger and could possibly serve as a rationalization for the contemplated lawsuit.

There is also no previous physician lawsuit literature that has identified depression as a potential variable important to this issue. However, there are some data that indicate that patients sue when they are unable to come to terms with their disease or end result [8]. As “not coming to terms” may lead to depression, these previous data may indirectly support our findings of being “upset with health” (BHI 2 depression item).

Finally, it is to be noted that some of the results of this study are not compatible with previous physician lawsuit literature. Neither the CPP nor the APP model for sue MD included the sex or education variables. As noted in the Introduction, these variables have previously been shown to be associated with actual lawsuits. The fact that these variables were associated with actual lawsuits (suing) rather than the wish to sue may be the reason for the discrepancy between our results and those previous studies.

There are a number of potential weaknesses/confounders to this study. First, although the subjects were stratified to match the U.S. Census data, they were not randomly selected. Consequently, there could be an unknown selection bias. Second, it is possible that the anonymous nature of the study encouraged some patients to make extreme responses. To control for this, however, distributed among the BH1 Z items were items with extreme or bizarre content. The subjects endorsing more than one of these extreme items were excluded from the study. Third, in epidemiology research, there are static variables (those that do not change over time, e.g., age) and dynamic variables (those that can change with time, e.g., anger can ameliorate or be changed with therapy). Both static and dynamic variables were found to be predictive in the models for sue MD for both CPPs and APPs. As dynamic variables can change over time, the derived variables will have predictive validity over a short period of time only. Fourth, another potential confounder is that of the use of patient self-report to establish the sue MD wish. There is no previous literature on how reliable this process is in litigation research. As such, this issue could have confounded the results. Fifth, the relative risk values indicated that CPPs were at the greatest risk for the sue MD wish vs APPs, who were in turn at a greater risk than patients without pain. Yet, our chi-square analyses comparing these three groups for sue MD wish did not find a statistical difference. This appears to be incongruent. However, these are two different types of analyses that can be incongruent with each other. Thus, we are confident that CPPs are at a greater risk for the sue MD wish vs APPs, who in turn are at greater risk than patients without pain. The final and most important problem with this study is that of prediction validity. There is a difference between wishing to sue, having the intention to sue, or making a threat, and actually proceeding with the lawsuit. As indicated in the Introduction, only about 16% of suit-prone patients proceed with an actual suit [15]. We essentially have analyzed the variables of patients who harbor the wish to sue but have not yet proceeded with the lawsuit. As such, it is unclear if the derived variables will actually be predictive of an actual lawsuit. This type of validity can only be determined in a prospective long-term follow-up study. Nevertheless, as it is likely that suits would originate from a population that contemplates suing, our results may be helpful to this problem.

What then is the clinical utility of the aforementioned results? At the present time, there are two ways of attempting to predict any behavior: actuarial [18,19] and clinical [21,22]. Actuarial methods are statistical methods that attempt to predict the behavior by utilizing patient variables that in the past have been demonstrated to be associated with the behavior. Clinical predictors may or may not utilize the same variables, but here, the clinician makes an unaided clinical judgment. Actuarial methods have been shown to be more accurate than clinical prediction and to be subject to less bias. As this is a preliminary study, it may be too early to recommend our results to be included in any routine future actuarial analyses. However, the data presented here may be clinically useful. The portraits of the APPs and CPPs who contemplate suing presented earlier or identification of these patients by questionnaire could potentially alert the physician to these patients. The physician could then try to conscientiously work on establishing the patient–physician relationship. This could be carried out by transmitting a compassionate caring demeanor. Additionally, the physician should transmit that he is willing to spend time with the patient and that he is thorough in his approach to the patient's problem. Finally, the physician could open a discourse with the patient on the patient's relationship with his worker's compensation carrier and explore whether the patient is presenting to the physician's office voluntarily or because the carrier is sending him or her. If the patient does perceive that the physician is an agent of the carrier, the physician should make it clear that he would be fair in his appraisal of the patient's problem and will not act legally as an agent of either the patient or the carrier, but nevertheless, will always act in the best medical interest of the patient. With that understanding, the physician could then ask the patient whether he/she wishes to remain under his care in spite of the fact that the patient may feel that the physician is an agent of the carrier. It is to be noted that there is no evidence in the literature that such a discourse has any predictive validity for decreasing litigation propensity. However, the authors believe that such a discourse could improve the physician–patient relationship with patients who are angry at physicians.

Conclusions

APPs and CPPs are at a greater risk than patients without pain for harboring the sue MD wish. Some patient attributes and the referral-treatment situation appear to be important predictors for harboring this issue, but appear to differ in importance between APPs and CPPs. Future research may wish to test the validity of these variables in patient groups that have proceeded with lawsuits against physicians.

Disclosures

  • Funding/support: the present study was conducted without any external funding or support. This study reanalyzed data from a previous study funded and supported by Pearson Assessments. Dr. Bruns and Dr. Disorbio were involved in this study, but were not reimbursed for their participation.

  • Role of the sponsor: Pearson Assessments was involved in data collection and development of the BHI 2 test. However, Pearson Assessments had no role in the design or statistical analysis of the present study, which was discovered by the authors in a reanalysis of the data after the original study had been completed.

  • Financial disclosure: Dr. Bruns and Dr. Disorbio are compensated as BHI 2 authors.

  • Drs. Fishbain and Lewis were not compensated in any way for their reanalysis of the data and development of the manuscript, and are not stockholders of Pearson Assessments and are not compensated in any way through the BHI 2.

Footnotes

  • 1 Authors of the BHI 2 Test.

References

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