[Skip to Content]
[Skip to Content Landing]
Place holder to copy figure label and caption
Figure 1.
Study Design

Time 0 indicates date of the operation.

Graphic Jump Location
Study Design
Place holder to copy figure label and caption
Figure 2.
Estimated Complication Rate According to the Operating Surgeon’s Reports by Coworkers About Unprofessional Behaviors in the 36 Months Preceding the Operation

Analyses are adjusted for total coworker reports, patient factors (age, sex, race/ethnicity, functional status, American Society of Anesthesiologists class), and operative characteristics (wound classification, long operative time [calculated as >75th percentile for each Current Procedural Terminology code]). Error bars indicate 95% CIs.

Graphic Jump Location
Estimated Complication Rate According to the Operating Surgeon’s Reports by Coworkers About Unprofessional Behaviors in the 36 Months Preceding the Operation
Table 1.
Characteristics of the Cohort Across Groups of the Operating Surgeon’s Coworker Reports About Unprofessional Behaviors in the 36 Months Preceding the Operation

Abbreviation: ASA, American Society of Anesthesiologists.

a Unless otherwise indicated, data are expressed as number (percentage) of patients. Percentages have been rounded and may not total 100.

b Calculated using Kruskal-Wallis test.

c Calculated using Pearson χ2 test.

Table 2.
Complications Across Groups of the Operating Surgeons’ Coworker Reports About Unprofessional Behavior in the 36 Months Preceding the Operation

a Calculated using Pearson χ2 test.

Table 3.
Sensitivity Analysesa

aP = .05 for association of reports in the multivariate regression model. P value was calculated from logistic regression results testing significance of surgeon report category after other covariates were included in the model.

b Reference group includes operations performed by surgeons with no coworker reports of surgeon’s unprofessional behavior in the 1095 days (36 months) preceding operation.

1.
Mitchell  P, Wynia  M, Golden  R,  et al. Core Principles and Values of Effective Team-Based Healthcare. Washington, DC: Institute of Medicine; 2012.
2.
Mazzocco  K, Petitti  DB, Fong  KT,  et al.  Surgical team behaviors and patient outcomes.  Am J Surg. 2009;197(5):678-685. doi:10.1016/j.amjsurg.2008.03.002PubMedGoogle ScholarCrossref
3.
Sexton  JB, Paine  LA, Manfuso  J,  et al.  A check-up for safety culture in “my patient care area”.  Jt Comm J Qual Patient Saf. 2007;33(11):699-703. doi:10.1016/S1553-7250(07)33081-XPubMedGoogle ScholarCrossref
4.
Makary  MA, Sexton  JB, Freischlag  JA,  et al.  Operating room teamwork among physicians and nurses: teamwork in the eye of the beholder.  J Am Coll Surg. 2006;202(5):746-752. doi:10.1016/j.jamcollsurg.2006.01.017PubMedGoogle ScholarCrossref
5.
Cooper  WO, Guillamondegui  O, Hines  OJ,  et al.  Use of unsolicited patient observations to identify surgeons with increased risk for postoperative complications.  JAMA Surg. 2017;152(6):522-529. doi:10.1001/jamasurg.2016.5703PubMedGoogle ScholarCrossref
6.
Hickson  GB, Moore  IN, Pichert  JW, Benegas  M  Jr. Balancing systems and individual accountability in a safety culture. In: Berman S, ed.  From the Front Office to the Front Line: Essential Issues for Healthcare Leaders. 2nd ed. Oakbrook Terrace, IL: Joint Commission Resources Inc; 2012:1-36.
7.
Moran  SK, Sicher  CM.  Interprofessional jousting and medical tragedies: strategies for enhancing professional relations.  AANA J. 1996;64(6):521-524.PubMedGoogle Scholar
8.
Joint Commission on Accreditation of Healthcare Organizations.  Sentinel Events: Behaviors That Undermine a Culture of Safety. Oakbrook Terrace, IL: Joint Commission on Accreditation of Healthcare Organizations; 2008.
9.
Mishra  A, Catchpole  K, Dale  T, McCulloch  P.  The influence of non-technical performance on technical outcome in laparoscopic cholecystectomy.  Surg Endosc. 2008;22(1):68-73. doi:10.1007/s00464-007-9346-1PubMedGoogle ScholarCrossref
10.
Shouhed  D, Gewertz  B, Wiegmann  D, Catchpole  K.  Integrating human factors research and surgery: a review.  Arch Surg. 2012;147(12):1141-1146. doi:10.1001/jamasurg.2013.596PubMedGoogle ScholarCrossref
11.
Allsop  J.  Two sides to every story: complainants’ and doctors’ perspectives in disputes about medical care in a general practice setting.  Law Policy. 1994;16:149-183. doi:10.1111/j.1467-9930.1994.tb00121.xGoogle ScholarCrossref
12.
Guillamondegui  OD, Gunter  OL, Hines  L,  et al.  Using the National Surgical Quality Improvement Program and the Tennessee Surgical Quality Collaborative to improve surgical outcomes.  J Am Coll Surg. 2012;214(4):709-714. doi:10.1016/j.jamcollsurg.2011.12.012PubMedGoogle ScholarCrossref
13.
Webb  LE, Dmochowski  RR, Moore  IN,  et al.  Using coworker observations to promote accountability for disrespectful and unsafe behaviors by physicians and advanced practice professionals.  Jt Comm J Qual Patient Saf. 2016;42(4):149-164. doi:10.1016/S1553-7250(16)42019-2PubMedGoogle ScholarCrossref
14.
Fathy  CA, Pichert  JW, Domenico  H, Kohanim  S, Sternberg  P, Cooper  WO.  Association between ophthalmologist age and unsolicited patient complaints.  JAMA Ophthalmol. 2018;136(1):61-67. doi:10.1001/jamaophthalmol.2017.5154PubMedGoogle ScholarCrossref
15.
American College of Surgeons. User guide for the 2012 ACS NSQIP Participant Use Data File. https://www.facs.org/~/media/files/quality%20programs/nsqip/ug12.ashx. Published October 2013. Accessed August 24, 2018.
16.
Martinez  W, Pichert  JW, Hickson  GB,  et al.  Qualitative content analysis of coworkers’ safety reports of unprofessional behavior by physicians and advanced practice professionals [published online March 15, 2018].  J Patient Saf. PubMedGoogle Scholar
17.
Kim  BD, Edelstein  AI, Hsu  WK, Lim  S, Kim  JY.  Spine surgeon specialty is not a risk factor for 30-day complication rates in single-level lumbar fusion: a propensity score-matched study of 2528 patients.  Spine (Phila Pa 1976). 2014;39(15):E919-E927. doi:10.1097/BRS.0000000000000394PubMedGoogle ScholarCrossref
18.
Roalfe  AK, Holder  RL, Wilson  S.  Standardisation of rates using logistic regression: a comparison with the direct method.  BMC Health Serv Res. 2008;8:275. doi:10.1186/1472-6963-8-275PubMedGoogle ScholarCrossref
19.
Catron  TF, Guillamondegui  OD, Karrass  J,  et al.  Patient complaints and adverse surgical outcomes.  Am J Med Qual. 2016;31(5):415-422. doi:10.1177/1062860615584158PubMedGoogle ScholarCrossref
20.
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(10):435-446. doi:10.1016/S1553-7250(13)39057-6PubMedGoogle ScholarCrossref
21.
Riskin  A, Erez  A, Foulk  TA,  et al.  The impact of rudeness on medical team performance: a randomized trial.  Pediatrics. 2015;136(3):487-495. doi:10.1542/peds.2015-1385PubMedGoogle ScholarCrossref
22.
Lagoo  J, Berry  WR, Miller  K,  et al.  Multisource evaluation of surgeon behavior is associated with malpractice claims [published online March 23, 2018].  Ann Surg. Google Scholar
23.
Hickson  G, Pichert  JW. Identifying and addressing physicians at high risk for medical malpractice claims. In: Youngberg  B, ed.  Principles of Risk Management and Patient Safety. Sudbury, MA: Jones and Bartlett Publishers, Inc; 2012:347-368.
24.
Hickson  GB, Federspiel  CF, Pichert  JW, Miller  CS, Gauld-Jaeger  J, Bost  P.  Patient complaints and malpractice risk.  JAMA. 2002;287(22):2951-2957. doi:10.1001/jama.287.22.2951PubMedGoogle ScholarCrossref
25.
Quinn  CM, Bilimoria  KY, Chung  JW, Ko  CY, Cohen  ME, Stulberg  JJ.  Creating individual surgeon performance assessments in a statewide hospital surgical quality improvement collaborative.  J Am Coll Surg. 2018;227(3):303-312.e3. doi:10.1016/j.jamcollsurg.2018.06.002PubMedGoogle ScholarCrossref
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    1 Comment for this article
    EXPAND ALL
    Poor outcomes could be linked to rudeness to patients
    Cecelia A Watson |
    As a long-time medical professional and the wife of a man who underwent 3 significant surgeries, I can say that a surgeon who is rude to co-workers often acts unprofessionally to patients as well, with predictable outcomes.

    During surgery, a patient is sedated or unconscious, powerless. He or she may very well be afraid to talk to a doctor who has that power and is unapproachable. Prior to surgery, a patient may be afraid to question, ask about or choose alternatives and thus may accept inappropriate surgery with negative outcomes. After surgery, more questions may arise, and if the
    patient is afraid to ask, or is answered rudely or not at all, a poor outcome is again more likely.

    The study makes perfect sense, but lacks a dimension
    CONFLICT OF INTEREST: None Reported
    READ MORE
    Views 25,975
    Citations 0
    Original Investigation
    June 19, 2019

    Association of Coworker Reports About Unprofessional Behavior by Surgeons With Surgical Complications in Their Patients

    Author Affiliations
    • 1Center for Patient and Professional Advocacy, Vanderbilt University Medical Center, Nashville, Tennessee
    • 2Department of Surgery, Stanford University, Stanford, California
    • 3Section of Surgical Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
    • 4Center for Surgery and Health Economics, Department of Surgery, Perelman School of Medicine, Philadelphia, Pennsylvania
    • 5Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
    • 6Department of Medicine, Stanford University, Stanford, California
    • 7Department of Clinical Effectiveness and Quality Improvement, University of Pennsylvania Health System, Philadelphia
    • 8Department of Urology, Vanderbilt University Medical Center, Nashville, Tennessee
    • 9Center for Quality, Safety and Risk Prevention, Vanderbilt University Medical Center, Nashville, Tennessee
    JAMA Surg. Published online June 19, 2019. doi:10.1001/jamasurg.2019.1738
    Key Points

    Question  Do patients of surgeons with a higher number of coworker reports about unprofessional behavior experience a higher rate of postoperative complications than patients whose surgeons have no such reports?

    Findings  Among 13 653 patients in this cohort study undergoing surgery performed by 202 surgeons, patients whose surgeons had a higher number of coworker reports had a significantly increased risk of surgical and medical complications.

    Meaning  Surgeons who model unprofessional behaviors may help to undermine a culture of safety, threaten teamwork, and thereby increase risk for medical errors and surgical complications.

    Abstract

    Importance  For surgical teams, high reliability and optimal performance depend on effective communication, mutual respect, and continuous situational awareness. Surgeons who model unprofessional behaviors may undermine a culture of safety, threaten teamwork, and thereby increase the risk for medical errors and surgical complications.

    Objective  To test the hypothesis that patients of surgeons with higher numbers of reports from coworkers about unprofessional behaviors are at greater risk for postoperative complications than patients whose surgeons generate fewer coworker reports.

    Design, Setting, and Participants  This retrospective cohort study assessed data from 2 geographically diverse academic medical centers that participated in the National Surgical Quality Improvement Program (NSQIP) and recorded and acted on electronic reports of safety events from coworkers describing unprofessional behavior by surgeons. Patients included in the NSQIP database who underwent inpatient or outpatient operations at 1 of the 2 participating sites from January 1, 2012, through December 31, 2016, were eligible. Patients were excluded if they were younger than 18 years on the date of the operation or if the attending surgeon had less than 36 months of monitoring for coworker reports preceding the date of the operation. Data were analyzed from August 8, 2018, through April 9, 2019.

    Exposures  Coworker reports about unprofessional behavior by the surgeon in the 36 months preceding the date of the operation.

    Main Outcomes and Measures  Postoperative surgical or medical complications, as defined by the NSQIP, within 30 days of the operation.

    Results  Among 13 653 patients in the cohort (54.0% [7368 ] female; mean [SD] age, 57 [16] years) who underwent operations performed by 202 surgeons (70.8% [143] male), 1583 (11.6%) experienced a complication, including 825 surgical (6.0%) and 1070 medical (7.8%) complications. Patients whose surgeons had more coworker reports were significantly more likely to experience any complication (0 reports, 954 of 8916 [10.7%]; ≥4 reports, 294 of 2087 [14.1%]; P < .001), any surgical complication (0 reports, 516 of 8916 [5.8%]; ≥4 reports, 159 of 2087 [7.6%]; P < .01), or any medical complication (0 reports, 634 of 8916 [7.1%]; ≥4 reports, 196 of 2087 [9.4%]; P < .001). The adjusted complication rate was 14.3% higher for patients whose surgeons had 1 to 3 reports and 11.9% higher for patients whose surgeons had 4 or more reports compared with patients whose surgeons had no coworker reports (P = .05).

    Conclusions and Relevance  Patients whose surgeons had higher numbers of coworker reports about unprofessional behavior in the 36 months before the patient’s operation appeared to be at increased risk of surgical and medical complications. These findings suggest that organizations interested in ensuring optimal patient outcomes should focus on addressing surgeons whose behavior toward other medical professionals may increase patients’ risk for adverse outcomes.

    Introduction

    In an era of increased attention to safety and quality, health care systems are placing greater emphasis on understanding, identifying, and addressing threats to delivery of reliable care. In many health care settings, particularly surgery, reliability depends on well-functioning teams with optimal communication, mutual respect, and continuous situational awareness.1-4 One factor that may affect surgical team performance is the level of professionalism displayed by all team members, but particularly the surgeon, whose role inherently requires team leadership.5 Unprofessional behaviors may contribute to undermining a culture of safety, threaten teamwork, and lead to medical errors and surgical complications.1,6-13

    Nurses and other health care team members are well positioned to observe surgeons’ behaviors and can address unprofessional behavior directly or convey concerns through their institution’s electronic event-reporting system.1-4,7-11 For example, a nurse who reports, “I asked for the procedure time out. Dr X said, ‘Look, we’re all on the same page here. Let’s get going without all this time out nonsense,’” might believe that Dr X is showing disrespect for and trivializing the system’s safety processes. A physician from another service who reports, “The patient was hypotensive and we started vasopressors. I told Dr Y (the surgeon) as soon as I started the infusion. Dr Y yelled at me for 5 minutes about not giving the necessary information,” might hesitate to speak up in future cases when a patient deteriorates.

    We hypothesized that patients of surgeons with a higher number of coworker reports describing unprofessional behaviors would experience surgical complications more often than patients of surgeons with fewer such coworker reports. Thus, we conducted a study using data from 2 large, geographically diverse academic health systems that participate in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP)12 and linked these data with electronic reports of coworker concerns about unprofessional behaviors.13

    Methods
    Setting and Data Sources

    We conducted a retrospective cohort study to investigate the association between prior coworker reports about a surgeon’s unprofessional behaviors and their patients’ risk for complications. Electronic event reports of coworker concerns about professionalism entered into each hospital’s electronic safety-reporting system were linked to data from the American College of Surgeons NSQIP. The study period for surgical cases (in the NSQIP) was January 1, 2012, through December 31, 2016; coworker reports from the 3 years (36 months) before the date of the operation for each case (ie, January 1, 2009 for earliest cases through December 30, 2016 for latest cases) were included in the analysis. Surgeon sex and years of experience (measured as years since medical school graduation) were identified from publicly available data from each study site’s website and online third-party physician review sites (eg, Healthgrades, Vitals.com, and Topnpi.com), which have been shown to be consistent with surgeon age 95.7% of the time in a large national study using similar approaches.14 The study was reviewed by the institutional review boards at Vanderbilt University Medical Center, Nashville, Tennessee, and Stanford University, Stanford, California, and qualified as nonhuman subjects research pursuant to CFR 46.102(f)(2) because the deidentified information on individuals in the cohort would not readily be ascertained by the investigators. The need for informed consent was therefore waived. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.

    The NSQIP files provided information for identifying the cohort, including the operation performed, patient characteristics, and operative characteristics that might be associated with surgical complications.5 The NSQIP data undergo rigorous audits and quality checks at the local site and at the central NSQIP site.15

    Coders trained for high interrater and intrarater reliability manually analyzed coworker reports of unprofessional behavior using a validated coding algorithm.16 Coders used qualitative analysis to identify the following 4 domains of unprofessional behaviors: concerns about poor or unsafe care (eg, “Dr ___ wiped the lens of the bronchoscopy scope on the bedsheets and then used the scope on the patient.”), clear and respectful communication (eg, “Dr ___ demanded, ‘Who’s the moron who has the patient in room 16?’”), integrity (eg, “Dr ___ instructed me to create false patients so it would look like the schedule was full.”), and responsibility (eg, “Dr ___ refused to enter the electronic order after I described the verbal orders policy.”).16

    The NSQIP data did not include patient identifiers. To protect physician confidentiality, a computer systems analyst not involved in conducting the research linked the study data sets using a probabilistic linkage algorithm based on physician identifiers included in both data sets. Once data files were linked, physician identifiers were stripped to create a file that could not be linked to an individual physician. The resulting files were used to conduct all analyses.

    Cohort and Follow-up

    The study cohort included patients in the NSQIP database who underwent an operation at a study site during the study period. Patients were excluded if they were younger than 18 years on the date of the operation, or if the attending surgeon had less than 36 months of monitoring for coworker reports preceding the date of the operation. Follow-up for each patient began on the date of the operation (defined as time 0) and continued through the next 30 days, to death, or to loss to follow-up (304 cases [2.2%]), whichever came first (Figure 1).5,17

    Outcomes

    The primary outcome was any complication during the 30-day postoperative period, including surgical and medical complications.5 Surgical complications included site infections (superficial surgical site infection, deep surgical site infection, organ or space surgical site infection) and wound disruption. Medical complications included pulmonary conditions (pneumonia, reintubation, mechanical ventilation), renal conditions (renal insufficiency, acute renal failure), central nervous system or nervous system complications (stroke), cardiovascular conditions (cardiac arrest, acute myocardial infarction), thromboembolic conditions (pulmonary embolism, deep venous thrombosis), and infectious conditions (sepsis or septic shock, urinary tract infections).17 Secondary outcomes included any surgical complication, any medical complication, 30-day mortality, readmissions, and reoperations.

    Statistical Analysis

    Data were analyzed from August 8, 2018, through April 9, 2019. Patient and surgeon covariates were compared across complaint groups using a Kruskal-Wallis test for continuous covariates or a Pearson χ2 test for categorical covariates. Means (SDs) or counts (percentages) were used to summarize continuous and categorical covariates, respectively, by complaint category. Multivariable logistic regression was used to model the association between the surgeon’s coworker reports in the 36 months (defined as 1095 days) preceding the date of the operation and the patient’s risk for any complication. Each patient had a unique surgeon- and time-dependent value created for their surgeon’s history of reports to the day preceding their operation. Regression models using the patient as the unit of analysis included variables believed to be the most important potential confounders. Models included total number of coworker reports, patient factors (age, sex, race/ethnicity, functional status, American Society of Anesthesiologists [ASA] class),15 operative characteristics (wound classification [ie, clean vs contaminated]), and long operative time to account for surgical complexity (defined as operative time >75th percentile for each Current Procedural Terminology code).5 Significance of the number of reports for multiple regression models reflected a comparison across all groups. Using this model, we calculated each patient’s estimated complication risk.18 We then compared complication risk by report groups using a Kruskal-Wallis test.

    We performed 3 sensitivity analyses. These included a model that added the surgeon’s years of experience to assess the possibility that surgeon experience (or inexperience) might be associated with unprofessional behavior and risk for complications. A second sensitivity analysis managed site as a fixed effect to account for possible cultural differences between the study sites in terms of willingness to report unprofessional behaviors and inherent site differences in outcomes. A third sensitivity analysis excluded the small number of cohort members with incomplete follow-up to assess the association of loss to follow-up with the study findings. We used R statistical software, version 3.2.3 (R Foundation for Statistical Computing) to perform all analyses. Two-sided P < .05 indicated significance.

    Results

    The cohort included 13 653 patients who underwent an operation during the study period (6285 [46.0%] male and 7368 [54.0%] female; mean [SD] age, 57 [16] years) performed by 202 unique surgeons (143 [70.8%] male, 58 [28.7%] female, and 1 [0.5%] unknown). Patients in the cohort underwent 10 462 general surgical (76.6%), 1104 orthopedic (8.1%), 851 vascular (6.2%), 164 gynecologic (1.2%), 31 plastic surgery (0.2%), 688 neurosurgical (5.0%), 2 otolaryngologic (0.01%), 148 urologic (1.1%), and 203 cardiothoracic (1.5%) operations. In the 36 months preceding the date of the operation, surgeons of cohort patients received a mean of 1.3 (2.4) coworker reports indicating unprofessional behavior (interquartile range, 0-2). Surgeons of patients in the group with the highest numbers of coworker reports had a mean of 6.1 (2.6) reports in the prior 36 months (Table 1). A greater percentage of surgeons for patients in the group whose surgeons had 0 reports were female (1716 [19.3%]) than in the other 2 groups (1-3 reports, 341 [12.9%]; ≥4 reports, 192 [9.2%] [P < .001]), suggesting that women were less likely to generate coworker concerns than men.

    Across groups of patients classified according to the number of surgeon’s coworker reports, patients were comparable in terms of age, sex, race/ethnicity, and functional status. Compared with patients whose surgeons had no reports, patients whose surgeons had a greater number of coworker reports were more likely to have higher ASA classification (ASA classification 3, 1159 of 2087 [55.5%] vs 4192 of 8916 [47.0%]; ASA classification 4, 90 of 2087 [4.3%] vs 309 of 8916 [3.5%]), were more likely to have contaminated wounds (247 of 2087 [11.8%] vs 866 of 8916 [9.7%]), and had longer mean operative times (164 [119] vs 154 [132] minutes) (Table 1).

    Among cohort patients, 1583 (11.6%) experienced a complication, including 825 (6.0%) who had a surgical complication and 1070 (7.8%) who had a medical complication (Table 2). Within 30 days, 140 patients (1.0%) died, 473 (3.5%) returned to the operating room, and 1053 (7.7%) were readmitted to the hospital.

    Patients whose surgeons had a greater number of coworker reports had a significantly increased rate of any complication (0 reports, 954 of 8916 patients [10.7%]; ≥4 reports, 294 of 2087 patients [14.1%]; P < .001), any surgical complications (0 reports, 516 of 8916 patients [5.8%]; ≥4 reports, 159 of 2087 patients [7.6%]; P < .01), and any medical complications (0 reports, 634 of 8916 patients [7.1%]; ≥4 reports, 196 of 2087 patients [9.4%]; P < .001). For surgical complications, surgical site infections were significantly more likely among patients whose surgeons had more coworker reports (0 reports, 477 of 8916 patients [5.3%]; ≥4 reports, 155 of 2087 patients [7.4%]; P < .001). For medical complications, pulmonary complications (0 reports, 234 of 8916 [2.6%]; ≥4 reports, 79 of 2087 [3.8%]), renal complications (0 reports, 60 of 8916 [0.7%]; ≥4 reports, 23 of 2087 [1.1%]), central nervous system complications (0 reports, 18 of 8916 [0.2%]; ≥4 reports, 2 of 2087 [0.1%]), and sepsis (0 reports, 249 of 8916 [2.8%]; ≥4 reports, 91 of 2087 [4.4%]) were more likely to occur in patients whose surgeons had greater numbers of coworker reports. No significant difference occurred between the study groups in the percentage who died, had reoperations, or who were readmitted within the 30-day postoperative period.

    In a logistic regression model adjusting for patient, surgeon, and operative characteristics, a surgeon’s prior reports by coworkers were significantly associated with the odds of a patient having any complication (logistic regression model testing significance of prior complaint category after other covariates included in model: Wald χ22 = 5.9; P = .05) (full model is shown in eTable 1 in the Supplement). The adjusted complication rate was 14.3% higher for patients whose surgeon had 1 to 3 reports and 11.9% higher for patients whose surgeon had 4 or more reports compared with patients whose surgeon had 0 reports. Patients whose surgeon had 1 to 3 reports were at 18.1% higher estimated risk of complication, and those whose surgeon had 4 or more reports were at 31.7% higher estimated mean risk of complication compared with patients whose surgeon had 0 reports (Figure 2). Findings from 3 sensitivity analyses (Table 3) that accounted for surgeons’ years of experience (odds ratio [OR] for 1-3 reports, 1.16 [95% CI, 1.01-1.34]; OR for ≥4 reports, 1.14 [95% CI, 0.98-1.32]; P = .05 for primary exposure coworker concern category) and the effect of the study site (OR for 1-3 reports, 1.17 [95% CI, 1.01-1.34]; OR for ≥4 reports, 1.13 [95% CI, 0.97-1.30]; P = .05) and excluded the small number of cohort members with incomplete follow-up (OR for 1-3 reports, 1.17 [95% CI, 1.02-1.35]; OR for ≥4 reports, 1.13 [95% CI, 0.97-1.31]; P = .05) were not materially different from findings in our primary models. Full models for sensitivity analyses are shown in eTables 2 to 4 in the Supplement.

    Discussion

    In this study of 13 653 patients and 202 surgeons from 2 academic medical centers in geographically distinct locations, patients whose surgeons had a higher number of coworker reports about unprofessional behavior in the 36 months before their operation were more likely to experience a surgical or medical complication than patients whose surgeons had no coworker reports. The differences remained significant in multivariable analyses controlling for patient, operative, and surgeon characteristics, as well as in 3 different sensitivity analyses. Although not demonstrating causality, the findings of this study are comparable to those of previous studies by Cooper et al5 and Catron et al19 that suggested a relationship between unprofessional behaviors and surgical complications. In those studies, the measure of unprofessional behavior was unsolicited patient complaint reports, which identify a small percentage (3%-5%) of surgeons who have multiple interactions in which patients perceive them as rude or disrespectful.20 In the studies of patient reports and surgical complications, patient reports were hypothesized to be a marker for surgeon behaviors that affect team performance.5,19 In the present study, we were able to measure reports of surgeon behaviors toward other team members more directly by identifying coworker descriptions of unprofessional interactions.

    This study provides additional evidence of the important association between unprofessional behaviors and team performance by directly measuring patient outcomes. A series of studies by Riskin et al21 measured the effect of unprofessional behaviors on neonatology team performance in simulations. Neonatal teams performed worse in diagnosing a condition and treating a complication when they were randomized to a condition of a rude consultant compared with teams not exposed to the condition.21 Lagoo et al22 recently described the effects of rude behaviors on surgical teams with a study identifying the association between negative behaviors and malpractice claims. The present study highlights the specific interactions, including disrespect, disregard for hospital policies, and lack of availability to answer questions, that might reasonably be expected to have a negative effect on team performance and increase the risk for complications. Although unprofessional behaviors by surgeons may occur in stressful environments with patients who have numerous comorbidities and critical illnesses, this study and the work by Riskin et al21 and Lagoo et al22 suggest that these are the environments in which surgeons have opportunities to promote and support optimal team function.

    Although the relative increase in rates of surgical complications represents a small absolute increase, the independent association of surgeons with more coworker reports and increased risk of complications suggests that the elevated odds are modifiable. Previous studies13,20,23 demonstrated that peer-delivered interventions effectively address physicians who generate a disproportionate share of patient or coworker reports of unprofessional behavior. Using a tiered escalation model with increasing consequences for failure to improve24 has been shown to decrease physicians’ reports by patients20 and coworkers,13 even for those with persistent patterns of unprofessional behavior. Future work should assess whether improved interactions with patients, families, and coworkers by surgeons who receive interventions for patterns of unprofessional behavior are also associated with improved surgical outcomes for their patients.

    Limitations

    Coworkers may have differing thresholds for reporting surgeon behavior, and the report of the observed behavior may be subjective in nature. However, the surgeons for patients in this study practiced in 1 of 2 academic medical centers, so presumably had similar opportunities to have reports filed by the same coworkers. In addition, many unprofessional behaviors by surgeons may go unreported, leading to some misclassification of our primary exposure. Even with a large cohort population (>13 500), the study had a relatively limited sample size. We included several patient, surgeon, and operative variables in our models, but other unmeasured factors related to surgeons who care for sicker patients may have influenced the results, although we included the primary variables hypothesized as likely to be associated with risk based on prior work.5 Because of the sampling strategy used in the NSQIP, we could not account for individual surgeon volume or case mix.25 The NSQIP data represent a purposive sampling of a surgeon’s cases during a year-long audit period. Thus, the cases selected at random might not represent all the cases for that surgeon. Finally, the study was conducted at 2 large academic medical centers; whether the findings extend to other academic centers or nonacademic centers is unknown.

    Conclusions

    Patients whose surgeons had an increased number of coworker reports about unprofessional behavior in the 36 months before the patient’s operation appeared to be at increased risk of surgical and medical complications. It would seem that organizations interested in ensuring optimal patient outcomes should focus on addressing surgeons whose behavior toward other medical professionals may increase their patients’ risk for adverse outcomes.

    Back to top
    Article Information

    Accepted for Publication: April 15, 2019.

    Corresponding Author: William O. Cooper, MD, MPH, Center for Patient and Professional Advocacy, Vanderbilt University School of Medicine, 2135 Blakemore Ave, Nashville, TN 37212 (william.cooper@vumc.org).

    Published Online: June 19, 2019. doi:10.1001/jamasurg.2019.1738

    Author Contributions: Dr Cooper and Mr Domenico had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Cooper, Spain, Guillamondegui, Kelz, Hopkins, Catron, Dmochowski, Hickson.

    Acquisition, analysis, or interpretation of data: Cooper, Spain, Guillamondegui, Domenico, Hopkins, Sullivan, Moore, Pichert, Webb, Dmochowski.

    Drafting of the manuscript: Cooper, Guillamondegui, Domenico, Dmochowski, Hickson.

    Critical revision of the manuscript for important intellectual content: Cooper, Spain, Guillamondegui, Kelz, Domenico, Hopkins, Sullivan, Moore, Pichert, Catron, Webb, Hickson.

    Statistical analysis: Cooper, Domenico.

    Administrative, technical, or material support: Cooper, Spain, Guillamondegui, Sullivan, Moore, Pichert, Catron, Dmochowski, Hickson.

    Supervision: Cooper, Spain.

    Conflict of Interest Disclosures: None reported.

    Funding/Support: This study was supported by the Vanderbilt Center for Patient and Professional Advocacy.

    Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Additional Contributions: We thank the NSQIP teams at Vanderbilt Medical Center, Nashville, Tennessee, and Stanford University, Stanford, California. Judith A. Dudley, BS, Vanderbilt University Medical Center, performed data set linkages; Barbara Martin, MBA, RN, Vanderbilt University Medical Center, facilitated NSQIP data downloads and variable definitions; Shannon Stratton, BS, Vanderbilt University Medical Center, served as research coordinator. None of the contributors were compensated beyond their salaries.

    References
    References
    1.
    Mitchell  P, Wynia  M, Golden  R,  et al. Core Principles and Values of Effective Team-Based Healthcare. Washington, DC: Institute of Medicine; 2012.
    2.
    Mazzocco  K, Petitti  DB, Fong  KT,  et al.  Surgical team behaviors and patient outcomes.  Am J Surg. 2009;197(5):678-685. doi:10.1016/j.amjsurg.2008.03.002PubMedGoogle ScholarCrossref
    3.
    Sexton  JB, Paine  LA, Manfuso  J,  et al.  A check-up for safety culture in “my patient care area”.  Jt Comm J Qual Patient Saf. 2007;33(11):699-703. doi:10.1016/S1553-7250(07)33081-XPubMedGoogle ScholarCrossref
    4.
    Makary  MA, Sexton  JB, Freischlag  JA,  et al.  Operating room teamwork among physicians and nurses: teamwork in the eye of the beholder.  J Am Coll Surg. 2006;202(5):746-752. doi:10.1016/j.jamcollsurg.2006.01.017PubMedGoogle ScholarCrossref
    5.
    Cooper  WO, Guillamondegui  O, Hines  OJ,  et al.  Use of unsolicited patient observations to identify surgeons with increased risk for postoperative complications.  JAMA Surg. 2017;152(6):522-529. doi:10.1001/jamasurg.2016.5703PubMedGoogle ScholarCrossref
    6.
    Hickson  GB, Moore  IN, Pichert  JW, Benegas  M  Jr. Balancing systems and individual accountability in a safety culture. In: Berman S, ed.  From the Front Office to the Front Line: Essential Issues for Healthcare Leaders. 2nd ed. Oakbrook Terrace, IL: Joint Commission Resources Inc; 2012:1-36.
    7.
    Moran  SK, Sicher  CM.  Interprofessional jousting and medical tragedies: strategies for enhancing professional relations.  AANA J. 1996;64(6):521-524.PubMedGoogle Scholar
    8.
    Joint Commission on Accreditation of Healthcare Organizations.  Sentinel Events: Behaviors That Undermine a Culture of Safety. Oakbrook Terrace, IL: Joint Commission on Accreditation of Healthcare Organizations; 2008.
    9.
    Mishra  A, Catchpole  K, Dale  T, McCulloch  P.  The influence of non-technical performance on technical outcome in laparoscopic cholecystectomy.  Surg Endosc. 2008;22(1):68-73. doi:10.1007/s00464-007-9346-1PubMedGoogle ScholarCrossref
    10.
    Shouhed  D, Gewertz  B, Wiegmann  D, Catchpole  K.  Integrating human factors research and surgery: a review.  Arch Surg. 2012;147(12):1141-1146. doi:10.1001/jamasurg.2013.596PubMedGoogle ScholarCrossref
    11.
    Allsop  J.  Two sides to every story: complainants’ and doctors’ perspectives in disputes about medical care in a general practice setting.  Law Policy. 1994;16:149-183. doi:10.1111/j.1467-9930.1994.tb00121.xGoogle ScholarCrossref
    12.
    Guillamondegui  OD, Gunter  OL, Hines  L,  et al.  Using the National Surgical Quality Improvement Program and the Tennessee Surgical Quality Collaborative to improve surgical outcomes.  J Am Coll Surg. 2012;214(4):709-714. doi:10.1016/j.jamcollsurg.2011.12.012PubMedGoogle ScholarCrossref
    13.
    Webb  LE, Dmochowski  RR, Moore  IN,  et al.  Using coworker observations to promote accountability for disrespectful and unsafe behaviors by physicians and advanced practice professionals.  Jt Comm J Qual Patient Saf. 2016;42(4):149-164. doi:10.1016/S1553-7250(16)42019-2PubMedGoogle ScholarCrossref
    14.
    Fathy  CA, Pichert  JW, Domenico  H, Kohanim  S, Sternberg  P, Cooper  WO.  Association between ophthalmologist age and unsolicited patient complaints.  JAMA Ophthalmol. 2018;136(1):61-67. doi:10.1001/jamaophthalmol.2017.5154PubMedGoogle ScholarCrossref
    15.
    American College of Surgeons. User guide for the 2012 ACS NSQIP Participant Use Data File. https://www.facs.org/~/media/files/quality%20programs/nsqip/ug12.ashx. Published October 2013. Accessed August 24, 2018.
    16.
    Martinez  W, Pichert  JW, Hickson  GB,  et al.  Qualitative content analysis of coworkers’ safety reports of unprofessional behavior by physicians and advanced practice professionals [published online March 15, 2018].  J Patient Saf. PubMedGoogle Scholar
    17.
    Kim  BD, Edelstein  AI, Hsu  WK, Lim  S, Kim  JY.  Spine surgeon specialty is not a risk factor for 30-day complication rates in single-level lumbar fusion: a propensity score-matched study of 2528 patients.  Spine (Phila Pa 1976). 2014;39(15):E919-E927. doi:10.1097/BRS.0000000000000394PubMedGoogle ScholarCrossref
    18.
    Roalfe  AK, Holder  RL, Wilson  S.  Standardisation of rates using logistic regression: a comparison with the direct method.  BMC Health Serv Res. 2008;8:275. doi:10.1186/1472-6963-8-275PubMedGoogle ScholarCrossref
    19.
    Catron  TF, Guillamondegui  OD, Karrass  J,  et al.  Patient complaints and adverse surgical outcomes.  Am J Med Qual. 2016;31(5):415-422. doi:10.1177/1062860615584158PubMedGoogle ScholarCrossref
    20.
    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(10):435-446. doi:10.1016/S1553-7250(13)39057-6PubMedGoogle ScholarCrossref
    21.
    Riskin  A, Erez  A, Foulk  TA,  et al.  The impact of rudeness on medical team performance: a randomized trial.  Pediatrics. 2015;136(3):487-495. doi:10.1542/peds.2015-1385PubMedGoogle ScholarCrossref
    22.
    Lagoo  J, Berry  WR, Miller  K,  et al.  Multisource evaluation of surgeon behavior is associated with malpractice claims [published online March 23, 2018].  Ann Surg. Google Scholar
    23.
    Hickson  G, Pichert  JW. Identifying and addressing physicians at high risk for medical malpractice claims. In: Youngberg  B, ed.  Principles of Risk Management and Patient Safety. Sudbury, MA: Jones and Bartlett Publishers, Inc; 2012:347-368.
    24.
    Hickson  GB, Federspiel  CF, Pichert  JW, Miller  CS, Gauld-Jaeger  J, Bost  P.  Patient complaints and malpractice risk.  JAMA. 2002;287(22):2951-2957. doi:10.1001/jama.287.22.2951PubMedGoogle ScholarCrossref
    25.
    Quinn  CM, Bilimoria  KY, Chung  JW, Ko  CY, Cohen  ME, Stulberg  JJ.  Creating individual surgeon performance assessments in a statewide hospital surgical quality improvement collaborative.  J Am Coll Surg. 2018;227(3):303-312.e3. doi:10.1016/j.jamcollsurg.2018.06.002PubMedGoogle ScholarCrossref
    ×