433
Articles
Predicting Risk for Medical Malpractice Claims Using Quality-of-Care Characteristics SARA C. CHARLES, MD, and ROBERT D. GIBBONS, PhD, Chicago, Illinois; PAUL R. FRISCH, JD, CAE, Portland, Oregon; CHARLENE E. PYSKOTY, MA, MPH; DONALD HEDEKER, PhD; and NAVNEET K. SINGHA, Chicago, Illinois
The current fault-based tort system assumes that claims made against physicians are inversely related to the quality of care they provide. In this study we identified physician characteristics associated with elements of medical care that make physicians vulnerable to malpractice claims. A sample of physicians (n=248) thought to be at high or low risk for claims was surveyed on various personal and professional characteristics. Statistical analysis showed that 9 characteristics predicted risk group. High risk was associated with increased age, surgical specialty, emergency department coverage, increased days away from practice, and the feeling that the litigation climate was "unfair:" Low risk was associated with scheduling enough time to talk with patients, answering patients' telephone calls directly, feeling "satisfied" with practice arrangements, and acknowledging greater emotional distress. Prediction was more accurate for physicians in practice 15 years or less. We conclude that a relationship exists between a history of malpractice claims and selected physician
characteristics. (Charles SC, Gibbons RD, Frisch PR, Pyskoty CE, Hedeker D, Singha NK: Predicting risk for medical malpractice claims using quality-of-care characteristics. West J Med 1992 Oct; 157:433-439) edical malpractice litigation is complex, and other factors besides negligence contribute to the initiation of malpractice claims against physicians. These include characteristics of the physician and the patient, health care systems, and the medical industrial system in which drugs, technology, and equipment are developed and distributed.' It is suggested that a large number of malpractice claims are generated by a few negligent physicians. If this were so, such physicians could be identified and rehabilitated or eliminated from medical practice.2 Negligence charges, however, are waged against a wide range of physicians, and those in certain specialties are at higher risk for malpractice claims than others.3'4 In most claims, negligence is not found.4-6 Nonetheless, certain physicians may possess specific characM
teristics that render them more "suit prone" than others.7 The "fault-based" tort system assumes the history of claims made against physicians is inversely related to the quality of care provided.8 Actual medical negligence is not
easily assessed,8 9 and evaluating physician-patient interaction is difficult. Characteristics associated with quality health care delivery have been identified, however.'0
Attributes of Quality Health Care Donabedian's classic work, which indirectly assesses quality of care in terms of structure, process, and outcome, is the theoretic framework for this study.'0 We structured a spectrum of physician characteristics, distinguishing stable characteristics, such as age and specialty, from modifiable characteristics, such as risk-management behaviors. Structure Health care structure consists of relatively stable characteristics of professionals, tools, and resources and the physi-
cal and organizational settings in which they work. 10 Attributes affecting a physician's contribution to quality of care are training, experience, specialization,"I length and school appropriateness of training,s2.13 international medical graduation, 14 volume of similar cases treated, I board certification,13 and organization of the hospital or clinic.'4 Some studies that equated chronologic age with increased experience showed an inverse relationship between increased age and a higher quality of care."5-7 Rhee noted a curvilinear relationship between years in practice and quality of care, with peak performance occurring from 11 to 15 years in practice. 12
Structural characteristics linked to a physician's increased claims history include specialty'8 and board certiflcation'8"19 but not international medical graduation."'8'9 Physicians in the 45- to 54-year age group, presumably in practice about 15 years, were found to be those most likely to lose their malpractice insurance because of their claims history.20 In a Florida study, claims experience was not observed to be a valid indicator of physician quality as measured by credentials, disciplinary history, specialty change, or retirement. 18 Process The process of care includes interrelated and overlapping activities within and between practitioners and patients.'o It encompasses the degree of physician competence that patients tend to expect21 22 and characteristics of the physicianpatient interaction.23 It might be assumed that technical competence is lacking for claims to occur, but competence is not easily measured objectively,24 and an award payment to a plaintiff is not a direct indicator that medical malpractice has occurred.25'p42724'
and From the Department of Psychiatry, School of Medicine (Drs Charles, Gibbons, and Hedeker) and the School of Public Health (Ms Pyskoty), University of Illinois, Chicago; of Medicine, the Department of Medical-Legal Affairs (Dr Frisch), Oregon Medical Association, Portland. Ms Singha is a fourth-year medical student, University of Illinois College Chicago. This study was done with the support of the Doctor's Company, Napa, Califomia, and the Oregon Medical Association, Portland, Oregon. 60612. Reprint requests to Sara C. Charles, MD, Dept of Psychiatry (M/C 913), University of Illinois at Chicago, 912 S Wood St, Chicago, IL
MEDICAL MALPRACTICE CLAIMS RISK
434
TABLE 1.-Physician Demographics by Individual Risk Group' Demographic
Age (mean), yr .................... Sex, 0 male ...................... Specialty, 0h Family practice ........... ....... Internal medicine ......... .......
Control Group-Low Risk Group 0 Group 1 (n=71) (n=49)
Sample Group-High Risk Group 2 Group 3 Group 4 (n= 16) (n=30) (n=82)
(n=248)
Total
46.11 91.3
48.35 87.8
49.63 96.6
52.66 97.6
53.56 100.0
49.64 93.9
8.6 27.1
20.4 24.5 10.2 4.1 22.4 2.0 6.1 6.1 4.1 30.6
24.1 31.0 10.3
6.4 11.5 19.2
7.7 15.4 30.8
24.1 3.4 6.9 --
55.1
46.2
69.0
1.3 1.3 5.1 22.0 87.8 7.3 1.3 79.0
---100.0 6.3 6.3 75.0
12.1 21.8 12.1 2.5 36.0 4.2 4.2 2.1 4.2 29.4 86.3 6.5 2.4 69.7
41.3 23.9 34.8
35.7 46.4 17.9
46.2 26.9 26.9
68.8 31.3 --
46.2
43.5 28.3
48.3 13.8 37.9 ----
50.0 18.5 28.4 1.2 2.5 --
50.0 --
48.3 15.8
43.8 ----
31.3 1.7 6.2 1.2
Obstetrics-gynecology ............ 2.9 Psychiatry ...................... 5.7 Surgery ........................ 27.1 Pediatrics ......................
11.4 Radiology ...................... 5.7 Ophthalmology .................. 1.4 Anesthesiology .................. 5.7 Additional postresidency training, . ... 39.4 Board certification, %0./...0 ...........85.9 International medical graduation ...... -Current licensure restriction, % ....... 2.8 Emergency department coverage, / ... 62.3 Geographic location, 0/ Urban ......................... 48.5 Rural .......................... 25.0 Suburban ...................... 26.5 Practice type, 0/ Single-specialty group ....... ..... 49.3 Multispecialty group ............. 8.8 Solo .......................... 30.9 Health maintenance organizations. . . 1.5 Hospital-based .................. 13.0 4.3 University ......................
81.6 2.0
4.1 63.0
28.3 4.3 8.7 --
--
40.0 83.3 3.3 --
28.4 25.4
Group O= no claims; group 1 - c3 claims, nopayments; group 2- a single lossof a $100,000; group 3 = 3 claims, with possible payoutsof
3 claims, with at least 1 payout of >$100,000.
Although a good physician-patient relationship has been suggested as the most effective method of preventing malstudies have not effectively practice claims, 26,27 empiric-stde demonstrated this.28 In a study that failed to account for the final disposition of claims, sued physicians and suing patients differed significantly in their perceptions of the relationship quality before the filing of a claim.29 Outcome The outcome of care as a measure of quality involves not only the success of treatment or improved health status judged by patient and physician, but also the level of satisfaction perceived by both."0 A patient's perception that medical injury has occurred probably plays a major role in whether or not a claim is brought. Physicians' personalities, behavior patterns, general health, and professional satisfaction influence quality of caret0 and may contribute to claims history. For example, a group of Oregon physicians disciplined for inappropriate prescribing were found to have significantly more malpractice claims than a control group.30 There are no studies linking physician impairment to claims history.2
Study Rationale Surgical specialty,'8'31 board certification,18'19 and emergency department coverage,1 all structural attributes of care, bear strong relationships to claims history. A recent study that attempted to identify physicians with distinct error profiles found only specialty consistently associated with error
type.31 Our study was designed to assess further the relationship between the physicians' claims history, whether or not legal settlement was reached or negligence was assessed, and the selected physician characteristics associated with quality care. We identified the characteristics associated with increased or decreased risk for claim and the possibility of modification or change in the identified characteristic. Method The sample consisted of physicians identified as "high risk" from a list generated by mandated reports of medical malpractice claims (from 1972 to 1988) to the Oregon Department of Insurance and Finance. A claim was defined as a written demand for compensation or services, irrespective of associated litigation. Physicians were defined as high risk who had a single loss of $ 100,000 or more (group 2), three or more claims that, in some cases, resulted in payouts of as much as $100,000 (group 3), or three or more claims with payouts of more than $100,000 (group 4). We randomly selected 236 of the 315 physicians identified. A control group of 219 physicians was randomly selected (every 14th name) from the balance (3,075) of the Oregon Medical Association membership list. Using basic survey methods,32 a refinement of an instrument employed in previous studies33'34 was mailed to both groups; confidentiality was assured, and responses were coded. Because some physicians in the control group acknowledged previous claims, the control group was further divided into two groups: group 0, those who had never had a
THE WESTERN JOURNAL OF MEDICINE
OCTOBER 1992
o
*
JOURNAL THE WESTERN
157
435
4
o
claim, and group 1, those who had a claim but did not meet high-risk criteria (Table 1).
Instrument An 11-page self-report questionnaire examining areas of physicians' personal and professional characteristics was used. Questions were grouped according to Donabedian's framework for assessing quality of care.10 Some of these characteristics encompassed two categories, that is, process and outcome,'0 but for the purposes of analysis, we assigned an item to only one category. We classified survey items as follows: structure of care: demographic data, credentials, practice characteristics including patient contact hours (patient volume), and hours of professionally related non-patient activities; process of care: practice-related behaviors and procedures, often defined under the rubric of risk management, including aspects of the physician-patient interaction; and outcome of care: measures of physician satisfaction, attitudes toward practice and profession, and a list of physical and emotional symptoms, including a standardized assessment of alcohol history,35 reflecting the health status of the physician. Sections were included on the claims history and an inventory of coping strategies that physicians used during litigation.
Statistical Methods In a preliminary data analysis, responses of five groups of physicians were compared using x2 statistics for categoric variables and one-way analysis of variance for continuous variables, and individual pairwise group differences were computed using Duncan's multiple range test. Variables used in the second stage of analysis were empirically derived based on a statistical consideration of the exploratory analysis that is theoretically consistent with Donabedian's framework (Table 2). The sample was analyzed to test the prediction of low risk (groups 0 and 1) and high risk (groups 2, 3, and 4). Owing to the composition of this study population, variables such as sex (n = 15 women), international medical school graduation (n = 16), and license restrictions (n = 6) were excluded because of low numbers.
435~~~~~~~~
Age and specialty defined as medical (family practice, internal medicine, pediatrics, and psychiatry) and surgical (obstetrics and gynecology, surgery, ophthalmology, radiology, and anesthesiology) were included in each analysis. Each of the remaining 34 variables relating to a component of Donabedian's framework was tested in a series of five logistic regression equations (one for each of the five listed in Table 2). For the physician attitude and emotion subarea (see Table 2), the five attitudinal measures were derived from a factor analysis of 24 attitudes toward practice (Table 3).36 Variables found significant in individual logistic regressions within each Donabedian component area were combined into a single logistic regression analysis. (For individual paired between-group comparisons, only variables for which significant overall group main effects were found were further analyzed [see Table 5].) After the parameter estimation phase, physicians were classified as low or high risk based on the estimated logistic regression model, testing accuracy in the classification of the logistic regression model. To determine generalizability of the estimated model, a random sample of two thirds of the physicians was used in the estimation phase; the remaining third was used during the classification phase only. Thus, the estimated model was not influenced by the data of the smaller subsample. Classification of this subsample provided an index of how well the estimated model predicted risk in an independent sample of physicians.
Results There were 248 completed surveys (54.1% response rate). Response rates above 50% were considered acceptable given the nature of the survey population and the content and length of the questionnaire.4'32 Demographics and practice characteristics ofthe study group are shown in Table 1. Comparison with nonrespondents, physician population in the same state, and physician population in the nation is shown in Table 4. Although nonrespondents' board-certification data were not available, they are similar to study group members on other demographic characteristics. The study group appears to have fewer women but a higher proportion of board-
TABLE 2.-Physician Characteristics Using Donabedian's Framework Outcome
Demogrophics
Age
Specialty Sex Postresidency training Board certified International medical graduate License restriction Marital status
Physician Attitude
Process
Structure Practice Characteristic
Practice Related Behoviors
Practice Procedures
and Emotions
Location Practice-type Emergency department coverage Patient-care hours Nonpatient hours No. of times changed location
Risk management education Risk management behaviors Days ill Days out
Allows patient input Schedules enough time Follow-up procedures Calls served by clerk Calls served by nurse Calls served by MD Office record documentation Informed consent: charted Informed consent: signed by
Conflicted attitude Satisfied attitude Naive attitude Unfair attitude Needy attitude Emotional symptoms
patient Informed consent: verbal
Sign out to same specialty Sign out to other specialty Sign out to nurse Sign out, beeper or telephone Accepts any patient Screens patients 'From Donabedian.11
436
MEDICAL MALPRACTICE CLAIMS RISK RISK
MEDICAL MALPRACTICE
436
CLAIMS
TABLE 3.-Factor Analytically Derived Scales Reflecting Attitudes Toward Practice Conflicted
Satisfied
Medicine is different from 5 years ago Patients expect too much I practice defensively
Eigen value* Variance, /
Unfair
With referral options
With coverage arrangements With backup from staff
Difficult to uphold ideals With backup from peers 3.766 2.348 15.7 9.8
......
......
Most claims are unjustified Claims do not represent malpractice
Physicians not guilty
Naive
Less experienced get sued Less knowledgeable get sued
still get sued 2.094 8.7
1.566 6.5
Needy
Important to be liked Claims are part of job Want my patients to like me 1.342 5.1
'From Harman.36
certified physicians than expected compared with state and national data. International medical graduate representation in the study sample is comparable to the same state sample but is lower than the US physician population in general. In all four populations, internists and family practitioners constitute approximately a third of the physician population. The study group is comparable to state and national physician populations and does not contraindicate generalizability of the results.
Preliminary and Intermediate Analyses Individual risk groups differed from one another on a list of characteristics and attitudes for which an overall significant main effect of a group was found at the 5% level (Table 5). The table construction indicates a direction so that the horizontal group designation represents a significantly TABLE 4.-Comparison of Sample, Nonrespondents, State, and United States Physicians ResponIndependent Variables
dents (n=248)
Age (mean), yr 49.64 Sex, Male .93.9 Female .6.1 Specialty, % Family practice 12.1 Internal medicine 21.8 Obstetrics12.1 gynecology Psychiatry .2.5
Surgery.36.0 Pediatrics .4.2
Radiology .4.2 2.1 Ophthalmology. 4.2 Anesthesiology Board certification, 9 . . 86.3 International medical graduation,
6.5
Oregon
Nonrespondents fn=207)
Medicol Society
Statistics
50.42
45.9
44.0
91.3 8.7
86.8 13.2
85.4 14.6
20.3 13.0
18.5 14.5
12.1 16.4
8.7 1.9 30.9 3.9 4.8 1.4 8.2
5.6 6.2 20.5 5.1 4.3 3.4 5.5
State
US
--
--
5.6 6.2 23.2 6.4 1.8 2.7 4.0 53.4
7.8
7.4
21.5
"more likely" or "greater" function than the vertical group designation. For example, physicians in group 3 were significantly more likely than groups 0, 1, and 2 to be in a surgical specialty. Separate logistic regression analyses were done for measures in each Donabedian component with risk group (low or high) as the dependent variable. Age and specialty were included in each analysis and were statistically significant, with increased age and surgical specialty predictive of high
risk. Additional significant results served as the basis for the final analysis. Final Analysis A logistic regression equation was developed based on the 11 variables that most accurately (73.9%) classified subjects into risk group (Table 6). Significant predictors of the high-risk group include increasing age, surgical specialty, emergency department coverage, increased number of days away from practice for vacation or out-of-town meetings, or both, and feeling that the current climate of litigation is "unfair." Low-risk group membership is predicted by a greater degree of current emotional symptoms, routinely scheduling time for patients to talk about their concerns and taking patients' calls directly, and feeling satisfied with practice arrangements.
To test the generalizability of our model, parameters were estimated on a two-thirds random subsample (n = 128) and applied to the remaining third (n = 71), resulting in a correct classification of 77.5% of the remaining third sample, with a false-positive rate of 21.4% and a false-negative rate of 24.1% Sensitivity ofthe measure was 82.5% and specificity was 71%. Prediction of Risk Group: Years in Practice Increasing age emerged as the strongest predictor of being in the high-risk group. Because previous research on quality of care suggested that peak physician performance occurred at about 15 years in practice, predictive accuracies were calculated for physicians who had been in practice 15 years or less and those who had been in practice more than 15 years, based on the previously estimated function for the two-thirds sample and applied to the third that was not used in estimating the weights. Predictive accuracy for those in practice 15 years or less was 90.9% (false-positive rate of 6.7% and false-negative rate of 1 1. 1%). We were able to predict accurately the risk group of 66.7% of the physicians in practice more than 15 years (false-positive rate 29.6%, false-negative rate 41.7%). To explain the greater predictive accuracy of the 15 years or less group, the relationship between years in practice and each of our predictor variables was examined. As expected, those physicians who had been in practice a shorter time were significantly younger than those in practice more than 15 years (t = 16.9, df = 238, P < .001). They also spent more time in direct patient care (t = 2.5, df = 239, P < .01) and in non-patient-related professional activities (t = 1.82, df = 237, P < .10) and reported more satisfaction with their practice arrangements than their older colleagues (t = 2.9, df = 229, P < .01). The over-15 years group was more likely .
WESTERN JOURNAL OF MEDICINE THEWFSL tHF
R
JORA
OFMDCN-
*
OCTOBER 1992 COER19
o
157
o
437
4
work, or both, have been found to have higher rates of claims but not necessarily higher rates of negligence.8 Why might this be so? The work itself may explain surgeons' claim vulnerability. Patients' expectations may differ for surgical, in contrast to medical, interventions. The amount of risk increases in complicated, often traumatic surgical situations in which unexpected adverse events are capable of producing serious injury or death. The fact that in our study surgeons in practice more than 15 years who also had desirable practice behaviors, especially those associated with good risk management, are at greatest risk suggests that surgical work stands alone as a significant risk factor. A claim in many of these instances may represent an unusual occurrence, an untoward outcome, or a single deviation from a physician's usual practice of otherwise high-quality care. Our study confirms Brennan and co-workers' assessment that efforts to identify "bad physicians" by a review of malpractice claims appears to be unproductive.8 Brennan and associates found in their review of paid claims that, aside from specialty, no other physician characteristics were associated with particular error profiles.8 Our study, using both paid and unpaid claims, although confirming strength of specialty as a predictor, also found another structural characteristic, that of increasing age, as important to the risk stratification process. We found that risk-for-claims differences are a function
to have taken a risk-management course (X2 = 2.75, df = 1, P < .10) and to take patients' calls directly rather than have them served by office personnel (X2 = 7.00, df = 1, P < .01). The groups did not differ significantly on the remaining predictor variables. The relationship between years in practice and ability to classify physicians correctly into high- and low-risk groups was contrasted on predictor variables for those in practice 15 years or less and more than 15 years. As noted, predictive characteristics for low- and high-risk grouping for those in practice less than 15 years resemble those for the full sample but differ from those in practice more than 15 years (Table 7).
Discussion Nine characteristics, representative of three components of Donabedian's framework to assess quality of care, were associated with a physician being at low or high risk for malpractice claims. Cross validation in an independent sample of physicians (one-third random sample) revealed these findings were not due to chance association produced by looking at a larger number of variables. Of the nine characteristics, surgical specialty is the strongest predictor for being at high risk for claims. This finding coincides with insurers' underwriting experience and with recent literature about malpractice litigation,"8'31 including the fact that surgeons engaged in high-risk or invasive
TABLE 5.-Comparative Profile of Individual Risk Groups t Independent Variables
Group 0
Age ...................... 3.14t Specialty (surgical vs medical) ........ 3§ Location ...................... -Emergency department coverage ...... 3t No. of times changed practice ........ 1t Schedules enough time ........-....... Informed consent charted ........... 211 Informed consent signed by patient.... -Informed consent verbal ............. --
Sign out to nurse ....................-Conflicted attitude ................. -Unfair attitude .................... 3t Needy attitude .................... 3,t1:t Risk-management education ......... 3§ Days ill ...................... 2t Days out ...................... 4t Emotional symptoms ...............-Being sued is an occupational hazard .. -Satisfied with career in medicine ........-Difficult to uphold ideals ........ .... -Patients' expectations are too high ... 1t Patients get higher quality of care than 5 years ago .....................-Plans to retire early ................ 3§ Risk management helps prevent losses . -Experienced death of a parent ........ 3§ Experienced death of own child ....... 311 Marital status Married ...................... 311 Divorced ...................... -Sex, male ...................... --
Group I Group 2
3t 31
Group 3
Group 4
Overall, P
Articles
Predicting Risk for Medical Malpractice Claims Using Quality-of-Care Characteristics SARA C. CHARLES, MD, and ROBERT D. GIBBONS, PhD, Chicago, Illinois; PAUL R. FRISCH, JD, CAE, Portland, Oregon; CHARLENE E. PYSKOTY, MA, MPH; DONALD HEDEKER, PhD; and NAVNEET K. SINGHA, Chicago, Illinois
The current fault-based tort system assumes that claims made against physicians are inversely related to the quality of care they provide. In this study we identified physician characteristics associated with elements of medical care that make physicians vulnerable to malpractice claims. A sample of physicians (n=248) thought to be at high or low risk for claims was surveyed on various personal and professional characteristics. Statistical analysis showed that 9 characteristics predicted risk group. High risk was associated with increased age, surgical specialty, emergency department coverage, increased days away from practice, and the feeling that the litigation climate was "unfair:" Low risk was associated with scheduling enough time to talk with patients, answering patients' telephone calls directly, feeling "satisfied" with practice arrangements, and acknowledging greater emotional distress. Prediction was more accurate for physicians in practice 15 years or less. We conclude that a relationship exists between a history of malpractice claims and selected physician
characteristics. (Charles SC, Gibbons RD, Frisch PR, Pyskoty CE, Hedeker D, Singha NK: Predicting risk for medical malpractice claims using quality-of-care characteristics. West J Med 1992 Oct; 157:433-439) edical malpractice litigation is complex, and other factors besides negligence contribute to the initiation of malpractice claims against physicians. These include characteristics of the physician and the patient, health care systems, and the medical industrial system in which drugs, technology, and equipment are developed and distributed.' It is suggested that a large number of malpractice claims are generated by a few negligent physicians. If this were so, such physicians could be identified and rehabilitated or eliminated from medical practice.2 Negligence charges, however, are waged against a wide range of physicians, and those in certain specialties are at higher risk for malpractice claims than others.3'4 In most claims, negligence is not found.4-6 Nonetheless, certain physicians may possess specific characM
teristics that render them more "suit prone" than others.7 The "fault-based" tort system assumes the history of claims made against physicians is inversely related to the quality of care provided.8 Actual medical negligence is not
easily assessed,8 9 and evaluating physician-patient interaction is difficult. Characteristics associated with quality health care delivery have been identified, however.'0
Attributes of Quality Health Care Donabedian's classic work, which indirectly assesses quality of care in terms of structure, process, and outcome, is the theoretic framework for this study.'0 We structured a spectrum of physician characteristics, distinguishing stable characteristics, such as age and specialty, from modifiable characteristics, such as risk-management behaviors. Structure Health care structure consists of relatively stable characteristics of professionals, tools, and resources and the physi-
cal and organizational settings in which they work. 10 Attributes affecting a physician's contribution to quality of care are training, experience, specialization,"I length and school appropriateness of training,s2.13 international medical graduation, 14 volume of similar cases treated, I board certification,13 and organization of the hospital or clinic.'4 Some studies that equated chronologic age with increased experience showed an inverse relationship between increased age and a higher quality of care."5-7 Rhee noted a curvilinear relationship between years in practice and quality of care, with peak performance occurring from 11 to 15 years in practice. 12
Structural characteristics linked to a physician's increased claims history include specialty'8 and board certiflcation'8"19 but not international medical graduation."'8'9 Physicians in the 45- to 54-year age group, presumably in practice about 15 years, were found to be those most likely to lose their malpractice insurance because of their claims history.20 In a Florida study, claims experience was not observed to be a valid indicator of physician quality as measured by credentials, disciplinary history, specialty change, or retirement. 18 Process The process of care includes interrelated and overlapping activities within and between practitioners and patients.'o It encompasses the degree of physician competence that patients tend to expect21 22 and characteristics of the physicianpatient interaction.23 It might be assumed that technical competence is lacking for claims to occur, but competence is not easily measured objectively,24 and an award payment to a plaintiff is not a direct indicator that medical malpractice has occurred.25'p42724'
and From the Department of Psychiatry, School of Medicine (Drs Charles, Gibbons, and Hedeker) and the School of Public Health (Ms Pyskoty), University of Illinois, Chicago; of Medicine, the Department of Medical-Legal Affairs (Dr Frisch), Oregon Medical Association, Portland. Ms Singha is a fourth-year medical student, University of Illinois College Chicago. This study was done with the support of the Doctor's Company, Napa, Califomia, and the Oregon Medical Association, Portland, Oregon. 60612. Reprint requests to Sara C. Charles, MD, Dept of Psychiatry (M/C 913), University of Illinois at Chicago, 912 S Wood St, Chicago, IL
MEDICAL MALPRACTICE CLAIMS RISK
434
TABLE 1.-Physician Demographics by Individual Risk Group' Demographic
Age (mean), yr .................... Sex, 0 male ...................... Specialty, 0h Family practice ........... ....... Internal medicine ......... .......
Control Group-Low Risk Group 0 Group 1 (n=71) (n=49)
Sample Group-High Risk Group 2 Group 3 Group 4 (n= 16) (n=30) (n=82)
(n=248)
Total
46.11 91.3
48.35 87.8
49.63 96.6
52.66 97.6
53.56 100.0
49.64 93.9
8.6 27.1
20.4 24.5 10.2 4.1 22.4 2.0 6.1 6.1 4.1 30.6
24.1 31.0 10.3
6.4 11.5 19.2
7.7 15.4 30.8
24.1 3.4 6.9 --
55.1
46.2
69.0
1.3 1.3 5.1 22.0 87.8 7.3 1.3 79.0
---100.0 6.3 6.3 75.0
12.1 21.8 12.1 2.5 36.0 4.2 4.2 2.1 4.2 29.4 86.3 6.5 2.4 69.7
41.3 23.9 34.8
35.7 46.4 17.9
46.2 26.9 26.9
68.8 31.3 --
46.2
43.5 28.3
48.3 13.8 37.9 ----
50.0 18.5 28.4 1.2 2.5 --
50.0 --
48.3 15.8
43.8 ----
31.3 1.7 6.2 1.2
Obstetrics-gynecology ............ 2.9 Psychiatry ...................... 5.7 Surgery ........................ 27.1 Pediatrics ......................
11.4 Radiology ...................... 5.7 Ophthalmology .................. 1.4 Anesthesiology .................. 5.7 Additional postresidency training, . ... 39.4 Board certification, %0./...0 ...........85.9 International medical graduation ...... -Current licensure restriction, % ....... 2.8 Emergency department coverage, / ... 62.3 Geographic location, 0/ Urban ......................... 48.5 Rural .......................... 25.0 Suburban ...................... 26.5 Practice type, 0/ Single-specialty group ....... ..... 49.3 Multispecialty group ............. 8.8 Solo .......................... 30.9 Health maintenance organizations. . . 1.5 Hospital-based .................. 13.0 4.3 University ......................
81.6 2.0
4.1 63.0
28.3 4.3 8.7 --
--
40.0 83.3 3.3 --
28.4 25.4
Group O= no claims; group 1 - c3 claims, nopayments; group 2- a single lossof a $100,000; group 3 = 3 claims, with possible payoutsof
3 claims, with at least 1 payout of >$100,000.
Although a good physician-patient relationship has been suggested as the most effective method of preventing malstudies have not effectively practice claims, 26,27 empiric-stde demonstrated this.28 In a study that failed to account for the final disposition of claims, sued physicians and suing patients differed significantly in their perceptions of the relationship quality before the filing of a claim.29 Outcome The outcome of care as a measure of quality involves not only the success of treatment or improved health status judged by patient and physician, but also the level of satisfaction perceived by both."0 A patient's perception that medical injury has occurred probably plays a major role in whether or not a claim is brought. Physicians' personalities, behavior patterns, general health, and professional satisfaction influence quality of caret0 and may contribute to claims history. For example, a group of Oregon physicians disciplined for inappropriate prescribing were found to have significantly more malpractice claims than a control group.30 There are no studies linking physician impairment to claims history.2
Study Rationale Surgical specialty,'8'31 board certification,18'19 and emergency department coverage,1 all structural attributes of care, bear strong relationships to claims history. A recent study that attempted to identify physicians with distinct error profiles found only specialty consistently associated with error
type.31 Our study was designed to assess further the relationship between the physicians' claims history, whether or not legal settlement was reached or negligence was assessed, and the selected physician characteristics associated with quality care. We identified the characteristics associated with increased or decreased risk for claim and the possibility of modification or change in the identified characteristic. Method The sample consisted of physicians identified as "high risk" from a list generated by mandated reports of medical malpractice claims (from 1972 to 1988) to the Oregon Department of Insurance and Finance. A claim was defined as a written demand for compensation or services, irrespective of associated litigation. Physicians were defined as high risk who had a single loss of $ 100,000 or more (group 2), three or more claims that, in some cases, resulted in payouts of as much as $100,000 (group 3), or three or more claims with payouts of more than $100,000 (group 4). We randomly selected 236 of the 315 physicians identified. A control group of 219 physicians was randomly selected (every 14th name) from the balance (3,075) of the Oregon Medical Association membership list. Using basic survey methods,32 a refinement of an instrument employed in previous studies33'34 was mailed to both groups; confidentiality was assured, and responses were coded. Because some physicians in the control group acknowledged previous claims, the control group was further divided into two groups: group 0, those who had never had a
THE WESTERN JOURNAL OF MEDICINE
OCTOBER 1992
o
*
JOURNAL THE WESTERN
157
435
4
o
claim, and group 1, those who had a claim but did not meet high-risk criteria (Table 1).
Instrument An 11-page self-report questionnaire examining areas of physicians' personal and professional characteristics was used. Questions were grouped according to Donabedian's framework for assessing quality of care.10 Some of these characteristics encompassed two categories, that is, process and outcome,'0 but for the purposes of analysis, we assigned an item to only one category. We classified survey items as follows: structure of care: demographic data, credentials, practice characteristics including patient contact hours (patient volume), and hours of professionally related non-patient activities; process of care: practice-related behaviors and procedures, often defined under the rubric of risk management, including aspects of the physician-patient interaction; and outcome of care: measures of physician satisfaction, attitudes toward practice and profession, and a list of physical and emotional symptoms, including a standardized assessment of alcohol history,35 reflecting the health status of the physician. Sections were included on the claims history and an inventory of coping strategies that physicians used during litigation.
Statistical Methods In a preliminary data analysis, responses of five groups of physicians were compared using x2 statistics for categoric variables and one-way analysis of variance for continuous variables, and individual pairwise group differences were computed using Duncan's multiple range test. Variables used in the second stage of analysis were empirically derived based on a statistical consideration of the exploratory analysis that is theoretically consistent with Donabedian's framework (Table 2). The sample was analyzed to test the prediction of low risk (groups 0 and 1) and high risk (groups 2, 3, and 4). Owing to the composition of this study population, variables such as sex (n = 15 women), international medical school graduation (n = 16), and license restrictions (n = 6) were excluded because of low numbers.
435~~~~~~~~
Age and specialty defined as medical (family practice, internal medicine, pediatrics, and psychiatry) and surgical (obstetrics and gynecology, surgery, ophthalmology, radiology, and anesthesiology) were included in each analysis. Each of the remaining 34 variables relating to a component of Donabedian's framework was tested in a series of five logistic regression equations (one for each of the five listed in Table 2). For the physician attitude and emotion subarea (see Table 2), the five attitudinal measures were derived from a factor analysis of 24 attitudes toward practice (Table 3).36 Variables found significant in individual logistic regressions within each Donabedian component area were combined into a single logistic regression analysis. (For individual paired between-group comparisons, only variables for which significant overall group main effects were found were further analyzed [see Table 5].) After the parameter estimation phase, physicians were classified as low or high risk based on the estimated logistic regression model, testing accuracy in the classification of the logistic regression model. To determine generalizability of the estimated model, a random sample of two thirds of the physicians was used in the estimation phase; the remaining third was used during the classification phase only. Thus, the estimated model was not influenced by the data of the smaller subsample. Classification of this subsample provided an index of how well the estimated model predicted risk in an independent sample of physicians.
Results There were 248 completed surveys (54.1% response rate). Response rates above 50% were considered acceptable given the nature of the survey population and the content and length of the questionnaire.4'32 Demographics and practice characteristics ofthe study group are shown in Table 1. Comparison with nonrespondents, physician population in the same state, and physician population in the nation is shown in Table 4. Although nonrespondents' board-certification data were not available, they are similar to study group members on other demographic characteristics. The study group appears to have fewer women but a higher proportion of board-
TABLE 2.-Physician Characteristics Using Donabedian's Framework Outcome
Demogrophics
Age
Specialty Sex Postresidency training Board certified International medical graduate License restriction Marital status
Physician Attitude
Process
Structure Practice Characteristic
Practice Related Behoviors
Practice Procedures
and Emotions
Location Practice-type Emergency department coverage Patient-care hours Nonpatient hours No. of times changed location
Risk management education Risk management behaviors Days ill Days out
Allows patient input Schedules enough time Follow-up procedures Calls served by clerk Calls served by nurse Calls served by MD Office record documentation Informed consent: charted Informed consent: signed by
Conflicted attitude Satisfied attitude Naive attitude Unfair attitude Needy attitude Emotional symptoms
patient Informed consent: verbal
Sign out to same specialty Sign out to other specialty Sign out to nurse Sign out, beeper or telephone Accepts any patient Screens patients 'From Donabedian.11
436
MEDICAL MALPRACTICE CLAIMS RISK RISK
MEDICAL MALPRACTICE
436
CLAIMS
TABLE 3.-Factor Analytically Derived Scales Reflecting Attitudes Toward Practice Conflicted
Satisfied
Medicine is different from 5 years ago Patients expect too much I practice defensively
Eigen value* Variance, /
Unfair
With referral options
With coverage arrangements With backup from staff
Difficult to uphold ideals With backup from peers 3.766 2.348 15.7 9.8
......
......
Most claims are unjustified Claims do not represent malpractice
Physicians not guilty
Naive
Less experienced get sued Less knowledgeable get sued
still get sued 2.094 8.7
1.566 6.5
Needy
Important to be liked Claims are part of job Want my patients to like me 1.342 5.1
'From Harman.36
certified physicians than expected compared with state and national data. International medical graduate representation in the study sample is comparable to the same state sample but is lower than the US physician population in general. In all four populations, internists and family practitioners constitute approximately a third of the physician population. The study group is comparable to state and national physician populations and does not contraindicate generalizability of the results.
Preliminary and Intermediate Analyses Individual risk groups differed from one another on a list of characteristics and attitudes for which an overall significant main effect of a group was found at the 5% level (Table 5). The table construction indicates a direction so that the horizontal group designation represents a significantly TABLE 4.-Comparison of Sample, Nonrespondents, State, and United States Physicians ResponIndependent Variables
dents (n=248)
Age (mean), yr 49.64 Sex, Male .93.9 Female .6.1 Specialty, % Family practice 12.1 Internal medicine 21.8 Obstetrics12.1 gynecology Psychiatry .2.5
Surgery.36.0 Pediatrics .4.2
Radiology .4.2 2.1 Ophthalmology. 4.2 Anesthesiology Board certification, 9 . . 86.3 International medical graduation,
6.5
Oregon
Nonrespondents fn=207)
Medicol Society
Statistics
50.42
45.9
44.0
91.3 8.7
86.8 13.2
85.4 14.6
20.3 13.0
18.5 14.5
12.1 16.4
8.7 1.9 30.9 3.9 4.8 1.4 8.2
5.6 6.2 20.5 5.1 4.3 3.4 5.5
State
US
--
--
5.6 6.2 23.2 6.4 1.8 2.7 4.0 53.4
7.8
7.4
21.5
"more likely" or "greater" function than the vertical group designation. For example, physicians in group 3 were significantly more likely than groups 0, 1, and 2 to be in a surgical specialty. Separate logistic regression analyses were done for measures in each Donabedian component with risk group (low or high) as the dependent variable. Age and specialty were included in each analysis and were statistically significant, with increased age and surgical specialty predictive of high
risk. Additional significant results served as the basis for the final analysis. Final Analysis A logistic regression equation was developed based on the 11 variables that most accurately (73.9%) classified subjects into risk group (Table 6). Significant predictors of the high-risk group include increasing age, surgical specialty, emergency department coverage, increased number of days away from practice for vacation or out-of-town meetings, or both, and feeling that the current climate of litigation is "unfair." Low-risk group membership is predicted by a greater degree of current emotional symptoms, routinely scheduling time for patients to talk about their concerns and taking patients' calls directly, and feeling satisfied with practice arrangements.
To test the generalizability of our model, parameters were estimated on a two-thirds random subsample (n = 128) and applied to the remaining third (n = 71), resulting in a correct classification of 77.5% of the remaining third sample, with a false-positive rate of 21.4% and a false-negative rate of 24.1% Sensitivity ofthe measure was 82.5% and specificity was 71%. Prediction of Risk Group: Years in Practice Increasing age emerged as the strongest predictor of being in the high-risk group. Because previous research on quality of care suggested that peak physician performance occurred at about 15 years in practice, predictive accuracies were calculated for physicians who had been in practice 15 years or less and those who had been in practice more than 15 years, based on the previously estimated function for the two-thirds sample and applied to the third that was not used in estimating the weights. Predictive accuracy for those in practice 15 years or less was 90.9% (false-positive rate of 6.7% and false-negative rate of 1 1. 1%). We were able to predict accurately the risk group of 66.7% of the physicians in practice more than 15 years (false-positive rate 29.6%, false-negative rate 41.7%). To explain the greater predictive accuracy of the 15 years or less group, the relationship between years in practice and each of our predictor variables was examined. As expected, those physicians who had been in practice a shorter time were significantly younger than those in practice more than 15 years (t = 16.9, df = 238, P < .001). They also spent more time in direct patient care (t = 2.5, df = 239, P < .01) and in non-patient-related professional activities (t = 1.82, df = 237, P < .10) and reported more satisfaction with their practice arrangements than their older colleagues (t = 2.9, df = 229, P < .01). The over-15 years group was more likely .
WESTERN JOURNAL OF MEDICINE THEWFSL tHF
R
JORA
OFMDCN-
*
OCTOBER 1992 COER19
o
157
o
437
4
work, or both, have been found to have higher rates of claims but not necessarily higher rates of negligence.8 Why might this be so? The work itself may explain surgeons' claim vulnerability. Patients' expectations may differ for surgical, in contrast to medical, interventions. The amount of risk increases in complicated, often traumatic surgical situations in which unexpected adverse events are capable of producing serious injury or death. The fact that in our study surgeons in practice more than 15 years who also had desirable practice behaviors, especially those associated with good risk management, are at greatest risk suggests that surgical work stands alone as a significant risk factor. A claim in many of these instances may represent an unusual occurrence, an untoward outcome, or a single deviation from a physician's usual practice of otherwise high-quality care. Our study confirms Brennan and co-workers' assessment that efforts to identify "bad physicians" by a review of malpractice claims appears to be unproductive.8 Brennan and associates found in their review of paid claims that, aside from specialty, no other physician characteristics were associated with particular error profiles.8 Our study, using both paid and unpaid claims, although confirming strength of specialty as a predictor, also found another structural characteristic, that of increasing age, as important to the risk stratification process. We found that risk-for-claims differences are a function
to have taken a risk-management course (X2 = 2.75, df = 1, P < .10) and to take patients' calls directly rather than have them served by office personnel (X2 = 7.00, df = 1, P < .01). The groups did not differ significantly on the remaining predictor variables. The relationship between years in practice and ability to classify physicians correctly into high- and low-risk groups was contrasted on predictor variables for those in practice 15 years or less and more than 15 years. As noted, predictive characteristics for low- and high-risk grouping for those in practice less than 15 years resemble those for the full sample but differ from those in practice more than 15 years (Table 7).
Discussion Nine characteristics, representative of three components of Donabedian's framework to assess quality of care, were associated with a physician being at low or high risk for malpractice claims. Cross validation in an independent sample of physicians (one-third random sample) revealed these findings were not due to chance association produced by looking at a larger number of variables. Of the nine characteristics, surgical specialty is the strongest predictor for being at high risk for claims. This finding coincides with insurers' underwriting experience and with recent literature about malpractice litigation,"8'31 including the fact that surgeons engaged in high-risk or invasive
TABLE 5.-Comparative Profile of Individual Risk Groups t Independent Variables
Group 0
Age ...................... 3.14t Specialty (surgical vs medical) ........ 3§ Location ...................... -Emergency department coverage ...... 3t No. of times changed practice ........ 1t Schedules enough time ........-....... Informed consent charted ........... 211 Informed consent signed by patient.... -Informed consent verbal ............. --
Sign out to nurse ....................-Conflicted attitude ................. -Unfair attitude .................... 3t Needy attitude .................... 3,t1:t Risk-management education ......... 3§ Days ill ...................... 2t Days out ...................... 4t Emotional symptoms ...............-Being sued is an occupational hazard .. -Satisfied with career in medicine ........-Difficult to uphold ideals ........ .... -Patients' expectations are too high ... 1t Patients get higher quality of care than 5 years ago .....................-Plans to retire early ................ 3§ Risk management helps prevent losses . -Experienced death of a parent ........ 3§ Experienced death of own child ....... 311 Marital status Married ...................... 311 Divorced ...................... -Sex, male ...................... --
Group I Group 2
3t 31
Group 3
Group 4
Overall, P
