Previous studies demonstrate that male sex, being a neurosurgeon, having a high volume practice, and generating a large number of unsolicited patient complaints (UPCs), are associated with increased malpractice claims activity.1–6 In these studies, UPCs proved to be the best overall predictor.
Fortunately, targeted physician interventions reduce UPCs, and by extension, risk of lawsuits and associates costs of risk management. In fact, 60% to 80% of high-risk physicians, identified by having a large number of UPCs, improve after targeted interventions, with a recidivism rate of 3%.7–9 Such interventions can include informal discussions with colleagues, confidential data sharing in meetings with peer messengers, and more formal plans with senior leadership to increase resources that a physician may need to address personal issues, learn new skills, or run his or her practice effectively and efficiently. Fifteen percent to 20% of physicians do not improve on their own without assistance; 5% to 10% depart their organization before improvement occurs.
Ex ante studies to predict malpractice risk, based on UPCs, have been performed and validated for some surgical specialties,10,11 such as urology12 and trauma surgery,13 but not for plastic surgery. An examination of the distribution of complaints associated with plastic surgeons is important for several reasons. First, patients’ satisfaction with outcomes can be subjective and lead to both complaints and lawsuits. Second, lawsuits brought up against plastic surgeons are sufficiently common and expensive, that professional liability insurance rates are relatively high for all, so it is useful to examine whether all have similar risk. We therefore conducted an analysis of UPCs to determine whether complaints and associated malpractice risk are similarly distributed among plastic and reconstructive surgeons, compared to all physicians, all surgeons, and even dermatologists, whose scope of practice overlaps with that of plastic surgeons. The goals of this project were 3-fold: (1) to characterize the risk profiles of plastic surgeons, (2) to compare this risk profile to other related specialties, and (3) to determine if certain types plastic surgeons are at higher risk than others for UPCs and therefore increased malpractice claim activity.
We retrospectively examined the patient complaint profiles and risk scores of 4792 physicians (3935 surgeons, 338 plastic and reconstructive surgeons, and 519 dermatologists), affiliated with organizations using the Patient Advocacy Reporting System (PARS), a prospectively maintained registry of UPCs. These specialty groups’ data were compared with each other and with data aggregated over all physicians in the database (n = 31,077), who had active practices from 2009 to 2012. The PARS is administered by the Center for Professional and Patient Advocacy (CPPA) at the Vanderbilt University Medical Center.
Patient complaint reports were collected from 22 geographically diverse health care systems distributed across 10 states. Within each health care system’s hospitals and outpatient facilities, a department of patient relations (or its equivalent, henceforth DPR) gathers and records patients and family concerns about their patient care experience. Other sources of complaints transmitted to DPRs include communications from administrators, hospital staff coworkers, and billing office staff. When possible, the complaints are then assigned to the physician clearly associated with each complaint embedded in a report (e.g., 1 report may contain multiple complaints: “Dr X was 90 minutes late … did not answer my questions, and did not examine my wound …”). Of note, no attempts are made to evaluate the validity of the complaint, as complaints generate risk management activity and are linked to malpractice risk whether they are valid concerns or not. Multiple physicians may be complained about in 1 report; each must be clearly identified for the complaint to be assigned.
Participating medical centers securely transfer electronic reports containing physician files and complaint report files to the CPPA at Vanderbilt, where trained evaluators reliably code them into the following groups: communication, concern for the patient and family, medical care and treatment, access and availability, safety and environment, and billing issues associated with perceived failures of care and treatment. The distribution of UPCs is then established as a “complaint profile,” which assigns complaints to the various categories. Furthermore, a “risk score” is calculated for each physician. The risk score is a proprietary weighted-sum algorithm based on 4 years of data, with recent complaints weighted more heavily than those recorded in previous years. For purposes of the current analysis, we defined physicians with risk scores between 50 and 70 as having moderate risk for medical malpractice claims, and scores above 70 as high risk.
Within the PARS database at the CPPA, plastic surgeons are recorded as either “plastic” surgeons (n = 233) or “reconstructive” plastic surgeons (n = 41), categories selected by the home institution based on the type of practice they provide to their health care system. Only data from 2012 were used for this subgroup analysis, representing a slightly smaller cohort than the group from 2009 to 2012. Specific subspecialties, such as hand surgery, microsurgery, aesthetic surgery, or craniofacial surgery, are not reported to the CPPA. To determine if any differences existed between “plastic” and “reconstructive” plastic surgeons, these physicians were first confirmed to be in practice, as a plastic surgeon, by a single analyst (M.A.S.), who was blinded to their risk scores. This analyst then de-identified the files, so that the first author (C.S.H.) could gather information about the surgeons’ practices, from several data sources: administrative data from PARS, public information regarding hospital characteristics, and academic information from the American Council of Academic Plastic Surgeons and the American College of Surgeons.
The CPPA calculated a risk score for every physician included in this study. We compared the risk stratification curves of all physicians, all surgeons, all dermatologists, and all plastic surgeons to determine what percentage of our cohorts had risk scores higher than 50 and those with risk scores higher than 70. Data compiled for the comparison between “plastic” surgeons and “reconstructive” plastic surgeons included: duration of privileges at hospital, practice based at an academic medical center, number of hospital beds at primary institution, presence of American College of Surgeons-verified level 1 trauma center, presence of accredited plastic surgery residency program, and physician sex.
Distribution of physician risk scores for each cohort was compared graphically. Wilcoxon rank and χ2 analysis were used to determine differences in the risk profiles of these cohorts, using complaint scores higher than 50 and higher than 70 as indicators of moderate and higher risk. Student t test for continuous data and χ2 analysis for categorical data were used to assess differences between “plastic” and “reconstructive” plastic surgeons. P values less than 0.05 were assigned statistical significance.
Over this 4-year period between January 1, 2009, and December 31, 2012, the majority of plastic and reconstructive surgeons (50.8%) did not generate any patient complaints, but those who did elicit 1 or more UPCs received a mean of 9.8 complaints from 4.8 patients. “Reconstructive” plastic surgeons generated an average of 17.0 complaints from 7.5 patients, whereas “plastic” surgeons generated an average of 8.7 complaints from 4.3 patients.
Comparison With Other Cohorts
Plastic and reconstructive surgeons tended to have higher complaint indices than all physicians combined and lower complaint indices than the subset of all types of surgeons combined, but these differences did not reach statistical significance (Figs. 1 and 2). Overall, 2.0% of the entire database has a risk score higher than 70, compared to 4.1% of surgeons and 2.4% of plastic and reconstructive surgeons (Table 1). By contrast, 3.2% of dermatologists had a risk score higher than 50, which was significantly lower than the 6.9% of plastic and reconstructive surgeons who had a risk score higher than 50 (P = 0.016). This difference disappeared when only risk scores over 70 were considered: 1.4% of dermatologists compared to 2.4% of plastic and reconstructive surgeons (P = 0.267, NS). The risk score profiles, comparing plastic and reconstructive surgeons, dermatologists, and all physicians, are depicted in Figure 3.
Comparison of Risk Score by Surgeon Type
“Reconstructive” plastic surgeons (7.5%) had risk scores higher than 70, whereas 1.4% of “plastic” surgeons had risk scores higher than 70 (P = 0.004). “Reconstructive” plastic surgeons (15.0%) had risk scores higher than 50, compared to 5.3% of “plastic” surgeons. Although “reconstructive” plastic surgeons’ risk profile appears greater than dermatologists’ for scores higher than 70 (P < 0.0002), “plastic” surgeons and dermatologists had similar proportions of members with risk scores higher than 70 (Fig. 4).
Differences Between Types of Plastic Surgeons
As noted in Table 2, “reconstructive” plastic surgeons and “plastic” surgeons had similar duration of privileges at their hospitals. However, “reconstructive” surgeons were more likely to be based at an academic medical center (97.6% vs 63.9%, P < 0.0001), have a higher ratio of female to male surgeons (1:2.7 vs 1:6.1, P = 0.042), practice at a level 1 trauma center (97.6% vs 85.5%, P = 0.036), and be associated with an accredited plastic surgery residency (97.6% vs 52.4%).
Patient Complaint Profiles
Overall mix of patient complaints for plastic and reconstructive surgeons did not significantly differ from that of the cohort of all physicians: care and treatment, 49%; communication, 19%; accessibility and availability, 14%; money or payment issues, 9%; and concern for patient/family, 9% (Fig. 5). For the national cohort of all physicians, complaints were distributed as follows: care and treatment, 47%; communication, 21%; accessibility and availability, 15%; concern for patient/family, 11%; and money or payment issues, 6%. No patients complained their physician contributed to an unsafe environment.
Examination of a multisite database of patient complaints reliably linked to specific physicians demonstrated that plastic and reconstructive surgeons (n = 338) had risk profiles suggesting little or no risk for most, but high risk for small proportions of physicians. The overall distributions suggest slightly higher risk for plastic and reconstructive surgeons than all physicians (n = 31,077), and marginally lower than all surgeons (n = 3935). These differences did not reach statistical significance. Plastic and reconstructive surgeons were both associated with more UPCs than dermatologists. Furthermore, plastic surgeons identified as “reconstructive” by their health care system appear to be at higher risk for UPCs. The differences are meaningful because UPCs are a proxy for malpractice litigation and claims. In addition, UPCs offer opportunities for groups to learn patient/family concerns in their own words, provide meaningful service recovery, and identify unnecessary litigation risk.14–16
Although we were not able to determine the subspecialties of the plastic surgeons in this cohort, we did note that “reconstructive” plastic surgeons (n = 41), compared to “plastic” surgeons (n = 245), were more likely to practice at an academic medical center, with a level 1 trauma center and an accredited residency program in plastic surgery. In fact, 15.0% of the “reconstructive” plastic surgeons appeared to have moderate risk or greater, and 7.5% had high risk. This contrasts with lower rates for all physicians, 5.5% of whom had moderate risk and 2.0% high risk.
Because UPCs are a robust proxy for malpractice risk, targeted interventions to decrease patient complaints about plastic and reconstructive surgeons may reduce patient dissatisfaction and reduce malpractice claims. The PARS, which was designed by the CPPA group at Vanderbilt, serves as both a tool for identifying “high-risk” physicians, as well as a feedback system that provides a graduated program of interventions, designed to improve communication and professionalism.17,18 We have developed a professionalism curriculum for medical students, residents, and faculty members at our own institution,19–21 but the PARS process allows our health care system to identify high-risk physicians who can received targeted interventions, hopefully before malpractice claims accumulate.
The PARS process involves a series of interventions that begin with Department of Patient Relations representatives sharing individual patient/family concerns with physicians and helping the physicians resolve the issues. Level 1 “Awareness” interventions occur when an apparent pattern develops and the physician’s patient complaints reach a certain threshold for concern—usually at the 95th or greater percentile for UPCs. The PCMC Chair assigns a PCMC member to share a physician’s UPC data, which includes a personalized table of complaint types, plus graphical representations of where that person “falls on the curve” relative to other providers at his or her institution, as well as their multicenter peer group. These meetings are designed to be purely informational, nondirective, nonpunitive, and confidential.
For physicians whose risk scores do not improve or worsen after 2 to 3 years, an authority “Guided” intervention is performed by the Chair of the clinical department in which the physician has his or her appointment. The peer messenger and/or the chair of PCMC support the chair with data and recommendations, all of which the chair may accept or reject. These level 2 interventions are designed to result in specific plans, such as health-related evaluations, re-education in communication or practice management, or provision of clinical resources needed to address operational challenges. Level 3 interventions are “Disciplinary” in nature and may involve restrictions of privileges, mandatory physical, psychological, and/or psychiatric assessment and treatment, and increase in malpractice premiums. Fortunately, within the PARS model, physicians rarely go to a Level 3 intervention.
In addition to the documented success at Vanderbilt,1 PARS has been shown to be effective at other medical centers,5,10 in both academic and community settings, and with specific cohorts of physicians, such as trauma surgeons,13 urologists,12 and anesthesiologists.16 In addition to helping decrease the number of UPCs physicians may incur, the PARS model has multiple downstream effects. Not only has PARS been successful in reducing the number of UPCs generated by physicians receiving interventions—at both Vanderbilt and all other partner sites—but this program has also improved the risk scores of at least 64% of “high-risk” physicians, and it is associated with institutional savings and positive return on investment.22–27
This study has some limitations. Although UPCs generate increased activity for risk management and serve as a proxy for future litigation, this correlation applies to a population of physicians, not necessarily to a single physician. A reconstructive microsurgeon may have a low risk score but high incidence of lawsuits, with large payouts, or conversely, a hand surgeon with a high-risk score may have never been sued. However, as a group of physicians, plastic surgeons have their own unique complaint profile, distinct from other specialists, such as dermatologists.
Another limitation of PARS is that the quality of the data may vary from institution to institution, or may vary within an institution, depending upon the reporting lines of UPCs. Furthermore, 1 patient may generate multiple complaints, skewing the profile of a physician who may have had a series of less than optimal patient encounters. However, the data are all processed and analyzed by a central group at Vanderbilt that has experience analyzing over 640,000 complaint reports associated with more than 60,000 physicians who practiced since 1992. The power of the PARS analytics is that the databases are large enough that physicians can compare themselves to specialty-specific peer groups with statistical confidence—from their own and from nationally diverse institutions. Another limitation was the inability to make our analysis more granular with regard to subspecialization in plastic surgery. The 2 categories that a health care system uses to label plastic surgeons may be used with some discernment, but it is clear from our data that the 2 cohorts have different risk profiles.
Monitoring UPCs may permit early identification of and intervention in high-risk plastic and reconstructive surgeons, before malpractice claims accumulate. Furthermore, surgeons from academic medical centers appear to be at increased risk for UPCs, perhaps due to external forces that leave patients frustrated. These forces may or may not differ from those faced by physicians who practice in regional medical centers, but in our experience may include large teams with variable integration of members, multiple subspecialty consultants without a “captain of the ship,” ineffective transitions of care, and incomplete or rushed patient hand-offs. Fortunately, plastic and reconstructive surgeons are in a position to address idiosyncratic behaviors and contribute to system improvements, and foster a safety culture based on respect, patient-centeredness, and transparency. Physicians may become stuck in a moment that they can get out of, with the help of interventions like PARS, to restore professionalism and communication, 2 competencies essential to being an effective physician.
1. Hickson GB, Federspiel CF, Pichert JW, et al. Patient complaints
. 2002; 287: 2951–2957.
2. Hickson GB, Jenkins AD. Identifying and addressing communication failures as a means of reducing unnecessary malpractice
claims. N C Med J
. 2007; 68: 362–364.
3. Hickson GB, Entman SS. Physicians influence and the malpractice
problem. Obstet Gynecol
. 2010; 115: 682–686.
4. Hickson GB, Entman SS. Physician practice behavior and litigation risk: evidence and opportunity. Clin Obstet Gynecol
. 2008; 51: 688–699.
5. Hickson GB, Federspiel CF, Blackford J, et al. Patient complaints
risk in a regional healthcare center. South Med J
. 2007; 100: 791–796.
6. Hain PD, Pichert JW, Hickson GB, et al. Using risk management
files to identify and address causative factors associated with adverse events in pediatrics. Ther Clin Risk Manag
. 2007; 3: 625–631.
7. Pichert JW, Moore IN, Karrass J, et al. An intervention model that promotes accountability: peer messengers and patient/family complaints. Jt Comm J Qual Patient Saf
. 2013; 39: 435–446.
8. Martinez W, Pichert JW, Hickson GB, et al. Programs for promoting professionalism: questions to guide next steps. Jt Comm J Qual Patient Saf
. 2014; 40: 159–160.
9. Hickson GB, Pichert JW, Webb LE, et al. A complementary approach to promoting professionalism: identifying, measuring, and addressing unprofessional behaviors. Acad Med
. 2007; 82: 1040–1048.
10. Murff HJ, France DJ, Blackford J, et al. Relationship between patient complaints
and surgical complications. Qual Saf Health Care
. 2006; 15: 13–16.
11. Sanfey H, Darosa DA, Hickson GB, et al. Pursuing professional accountability: an evidence-based approach to addressing residents with behavioral problems. Arch Surg
. 2012; 147: 642–647.
12. Stimson CJ, Pichert JW, Moore IN, et al. Medical malpractice
claims risk in urology: an empirical analysis of patient complaint data. J Urol
. 2010; 183: 1971–1976.
13. Mukherjee K, Pichert JW, Cornett MB, et al. All trauma surgeons are not created equal: asymmetric distribution of malpractice
claims risk. J Trauma
. 2010; 69: 549–554;discussion 554–6.
14. Hayden AC, Pichert JW, Fawcett J, et al. Best practices for basic and advanced skills in health care service recovery: a case study of a re-admitted patient. Jt Comm J Qual Patient Saf
. 2010; 36: 310–318.
15. Martinez W, Hickson GB, Miller BM, et al. Role-modeling and medical error disclosure: a national survey of trainees. Acad Med
. 2014; 89: 482–489.
16. Kynes JM, Schildcrout JS, Hickson GB, et al. An analysis of risk factors for patient complaints
about ambulatory anesthesiology care. Anesth Analg
. 2013; 116: 1325–1332.
17. Pichert JW, Moore IN, Hickson GB. Professionals promoting professionalism. Jt Comm J Qual Patient Saf
. 2011; 37: 446.
18. Kauffmann RM, Landman MP, Shelton J, et al. The use of a multidisciplinary morbidity and mortality conference to incorporate ACGME general competencies. J Surg Educ
. 2011; 68: 303–308.
19. Wagner IJ, Hultman CS. Elevation: developing a mentorship model to raise the next generation of plastic surgery professionals. Ann Plast Surg
. 2013; 70: 606–612.
20. Hultman CS, Halvorson EG, Kaye D, et al. Sometimes you can’t make it on your own: the impact of a professionalism curriculum on the attitudes, knowledge, and behaviors of an academic plastic surgery practice. J Surg Res
. 2013; 180: 8–14.
21. Hultman CS, Connolly A, Halvorson EG, et al. Get on your boots: preparing fourth-year medical students for a career in surgery, using a focused curriculum to teach the competency of professionalism. J Surg Res
. 2012; 177: 217–223.
22. Keroack MA, Youngberg BJ, Cerese JL, et al. Organizational factors associated with high performance in quality and safety in academic medical centers. Acad Med
. 2007; 82: 1178–1186.
23. Hickson GB, Pichert JW. Identifying and addressing physicians at high risk for medical malpractice
claims. In: Youngberg B, ed. The Patient Safety Handbook
. 2nd ed. Burlington, MA: Jones & Bartlett Learning; 2012: 347–368.
24. Youngberg BJ. Event reporting: the value of a nonpunitive approach. Clin Obstet Gynecol
. 2008; 51: 647–655.
25. Youngberg BJ. Assessing your organization’s potential to become a high reliability organization. J Healthc Risk Manag
. 2004; 24: 13–19.
26. Youngberg BJ. Meeting the challenges of patient safety through the design of a new risk management
process. J Healthc Risk Manag
. 2001; 21: 5–11.
27. Kuhn AM, Youngberg BJ. The need for risk management
to evolve to assure a culture of safety. Qual Saf Health Care
. 2002; 11: 158–162.
Keywords:Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
patient complaints; malpractice; risk management