Surgeon Gender-Related Differences in Operative Coding in Plastic Surgery : Plastic and Reconstructive Surgery

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Surgeon Gender-Related Differences in Operative Coding in Plastic Surgery

Kalliainen, Loree K. M.D., M.A.; Chambers, Alison B. Ph.D.; Crozier, Joseph M.A.; Conrad, Heidi B.S.; Iozzio, Mary Jo Ph.D.; Lipa, Joan E. M.D., M.Sc.; Johnson, Debra M.D.; Hansen, Juliana E. M.D.

Author Information
Plastic and Reconstructive Surgery: November 2022 - Volume 150 - Issue 5 - p 1095e-1103e
doi: 10.1097/PRS.0000000000009609
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Abstract

Numerous studies in the medical and surgical literature have discussed the income gap between male and female physicians. Gender differences in practice characteristics, salary negotiations, academic levels, hours worked, leadership tasks, external employment, and maternity leave have been posited as partial explanations for inequity, yet none adequately account for observed income disparities.1–12 The possibility of sex-related billing and coding differences must also be entertained.

Among cardiologists,8 ophthalmologists,5 and orthopedists,13 practice composition seems to account for significant differences in annual earnings between male and female surgeons. The combination of male surgeons performing higher-reimbursing interventional procedures and working longer hours accounted for significant differences in annual earnings. Although male and female surgeons were reimbursed similarly for similar procedures, annual claim volume was three times greater for male surgeons than for female surgeons.5,13 Differences in case volumes may reflect individual preference but may also reflect institutional or regional referral patterns, and bias for referral to male surgeons may be ingrained within systems.14 Few economic analyses in plastic surgery have been conducted, but in a study of practice differences by Lafer et al., 67 percent of female facial plastic surgeons earned less than $400,000 annually, whereas 60 percent of men earned more than $400,000.15 Economic studies of plastic surgery practices to date have not routinely included breakdown of data by gender.16–18

Overall compensation may be related not only to case volume but to productivity based on work relative value units. The relative value unit system was developed in 1989 as a standardized method to value physician work by comparing time; mental, physical, and technical effort; judgment; and patient risk of procedures and services relative to each other across specialties. The relative value unit is composed of the work relative value unit, the practice expense relative value unit, and malpractice relative value unit. For the purposes of this study, we are looking only at the procedural component, the work relative value unit.19,20 Although case volume and its relationship to gender-based income disparity has been studied, the relationship of work relative value unit generation to income remains unexamined in plastic surgery. We hypothesized that gender differences might be responsible for differential generation of work relative value units in a practice.

The average annual compensation for a plastic surgeon in the United States in the 2019 Doximity survey was $433,000.21 Gender-based differences are noted, with an average income of $438,000 for men and $389,000 for women, a difference of $49,000 (11 percent). This result is consistent with a 2018 Merritt Hawkins White Paper showing a compensation range of $387,100 to $587,746.22 A report by the Urban Institute and SullivanCotter found that the median compensation-to–work relative value unit ratio was $65.45 for surgical subspecialists.23 For the purpose of the investigation, we assumed that all income was based on work relative value unit generation. An income difference of $49,000 at $65.45 per work relative value unit would translate to a difference of 749 work relative value units/year, or a modest coding difference of 14.4 work relative value units per week.

We explored the possibility of gender-based differences on work relative value unit generation using data available from the case list submissions to the American Board of Plastic Surgery. We hypothesized a priori that work relative value units, average codes per case, major cases, and minor cases would be at least 10 percent higher for male than for female physicians. We anticipated that such differences would be less prevalent among employed plastic surgeons in large multispecialty groups or accountable care organizations.

METHODS

Data Source and Processing

Deidentified data sets were provided by the American Board of Plastic Surgery for 1093 candidate surgeons who submitted 9-month case lists over a 5-year period (2014 to 2018). No candidates had requested that their data be withheld from research use. The data set was aggregated by physician (assigned a random number by the American Board of Plastic Surgery) for the following outcome variables: total work relative value units, work relative value units per case, number of CPT codes per case, total number of cases, number of major cases, number of minor cases, surgeon sex, primary state or country of residence, and surgical sites (hospitals, surgery centers, office settings). CPT cases were converted to work relative value units using the 2019 National Physician Fee Schedule Relative Value File January Release.24 Codes from earlier in the data collection period, which had been deleted by December of 2018, were converted to the most similar current code.

The per-case work relative value unit was calculated by dividing total work relative value units by total number of cases. Percentage differences are calculated as follows: (female-male/male).

Fifty-seven surgeons were not included in data assessment because they practiced outside the continental United States/Alaska/Hawaii (21 from Canada, three from Puerto Rico) or their location of practice could not be determined from the data set (n = 33). The final database used for analysis included 1036 surgeons.

A list of operative sites included by each candidate—unlinked from the candidate surgeon’s original code number—was provided to the authors. Sites were then subclassified by the authors as academic, independent academic medical center, military, private, and not able to assess. Some operative sites had names that were not definitively associated with an academic center; however, a surgeon who operated at an academic center was classified as an academic surgeon. If the institution was classified as an independent academic medical center, the surgeon was listed as independent. Those who operated solely at military settings were classified as military. If they operated at Veterans Health Administration hospitals and academic centers, they were classified as academic. Surgeons who worked at community hospitals, surgery centers, and office-based centers with no academic, independent academic, or military affiliations were listed as private. If the surgical site could not be definitively stratified as academic, independent, military, or private, it was listed as not able to assess (e.g., clinic and procedure room). Once the sites had been defined as one of the above five categories, the data sheet was returned to the American Board of Plastic Surgery. The original coded list of surgeons was then returned with the added worksite classification column.

Physician Level Data (Aggregate)

Average work relative value units, work relative value units per case, and number of codes per case were modeled by gender using a generalized linear model for log-normal distributions. Total cases, major cases, and minor cases were modeled by gender using a generalized linear model for negative binomial distributions. The p values for main effect differences were reported.

The outcome variables (work relative value units total, work relative value units per case, number of CPT codes per case, number of total cases, and numbers of major and minor cases) were also modeled by gender and category of institution. An interaction term was included in the models to determine whether differences between male and female surgeons were dependent on or influenced by category of institution, and to allow for comparisons between sexes within category of institution. Mean values with 95 percent confidence interval for sex by type of institution were reported, as were p values for the comparisons of sex within each category of institution.

All statistical analyses were run using Proc Glimmix, allowing for fitting of generalized linear models (log-normal and negative binomial), and deriving main effect and interaction p values for hypothesis tests or p values for estimated mean comparisons (SAS version 9.2; SAS Institute, Inc., Cary, N.C.). Classic sandwich estimation was used to adjust for any model misspecification. Familywise alpha was maintained at 0.05 using the Holm adjustment for multiple comparisons. Means with 95 percent confidence intervals are reported. Percentage difference in outcome means between male and female surgeons were also calculated. A 10 percent minimum difference was set a priori as statistically significant. Adjusted p values are reported unless otherwise stated.

RESULTS

Global Case Data

The number of cases in the 9-month case submission period submitted by all 1036 surgeons ranged from 41 to 986, with a median of 103 cases. The median number of CPT codes per case was 1.82. The range of major cases for all surgeons was 15 to 818, with a median of 72; the range of minor cases was 0 to 374, with a median of 29. The total value of work relative value units ranged from 435 to 51,037 with a median of 2973.

Surgeon Level Data

Of the 1036 surgeons, 277 were female and 759 were male. There were at least twice as many men as women in the academic, private, and independent settings (Table 1). More women were in academic or independent academic settings than in private practice.

Table 1. - Practice Setting
Category of Institution Total Men (%) Women (%)
Academic 497 347 (69.8) 150 (30.2)
Independent 41 30 (73.2) 11 (26.8)
Military 22 17 (77.3) 5 (22.7)
NA 12 10 (83.3) 2 (16.7)
Private 464 355 (76.5) 109 (23.5)
Total 1036 759 (73.3) 277(26.7)
NA, not able to assess.

The number of CPT codes billed per case per surgeon were significantly higher for male surgeons [1.86 (95 percent CI, 1.84 to 1.89)] than for female surgeons [1.78 (95 percent CI, 1.74 to 1.82); p = 0.001], a 4.49 percent difference (Table 2). This metric (CPT codes billed per case) helps normalizes CPT codes per case load and implies that gender differences hold true for surgeons with similar caseloads.

Table 2. - Sex-Based Billing and Coding Comparisons
Value (95% CI) Difference (%) p
Total wRVUs
 Female 2624.1 (2435.2–2829.6) 19.3 <0.0001
 Male 3253.2 (3090.5–3425.8)
Mean wRVUs per case
 Female 25.8 (24.3–27.4) 10.7 0.0013
 Male 28.9 (27.9–29.9)
Mean no. of CPT codes per case
 Female 1.78 (1.74–1.82) 4.5 0.001
 Male 1.86 (1.84–1.89)
Mean no. of cases
 Female 116.4 (109–124.4) 9.9 0.0106
 Male 129.2 (123.6–135.2)
Mean no. of major cases
 Female 77.6 (72.7–82.7) 14.3 0.0002
 Male 90.5 (86.3–4.9)
Mean no. of minor cases
 Female 38.6 (34.5–43.2) −2.0 0.7591
 Male 37.9 (35.5–40.4)
wRVUs, work relative value units.

Table 2 displays comparisons between sex-based billing and coding. The average values of total work relative value units, work relative value units per case, number of CPT codes per case, number of all cases, and number of major cases were all significantly higher for male surgeons than for female surgeons (Table 2). The average total work relative value units for male surgeons was significantly higher than for female surgeons [3253.2 (95 percent CI, 3090.5 to 3425.8) versus 2624.1 (95 percent CI, 2435.2 to 2829.6), a 19.34 percent difference; p < 0.0001]. Total work relative value units, work relative value units per case, and number of major cases all reached the a priori percentage difference between male and female surgeons of at least 10 percent. The total number of cases was close at 9.90 percent difference. The average number of minor cases was not found to be significantly different between male and female surgeons.

Gender Comparisons within Category of Institution

Male surgeons billed significantly more work relative value units than female surgeons for academic, independent, and private practice (21.4, 33.0, and 20.1 percent difference, respectively) (Table 3).

Table 3. - Total and Per-Case Work Relative Value Units Compared by Practice Setting
Category Total wRVUs wRVUs per Case
Mean (95% CI) % Difference p Adjusted p Mean (95% CI) % Difference p Adjusted p
Academic
 Female 2909.7 (2619.9–3235.7) 21.4 0.0002
 0.0008
 28.5 (26.2–31) 11.7 0.0123 0.0368

 Male 3700.4 (3457.5–3962) 32.3 (30.8–33.8)
Independent
 Female 1794.2 (1389.5–2337.9) 33 0.019
 0.0375
 20.5 (16.6–25.5) 8.5 0.5574 1
 Male 2679.8 (2185.7–3303.7) 22.4 (18.3–27.6)
Military
 Female 2092.5 (1259.4–3604.4) −10.6 0.727
 0.7272
 19.2 (13.8–27.9) 9.5
 0.6232 1
 Male 1891.5 (1518.4–2371.6) 21.2 (17.9–25.4)
Private
 Female 2390.4 (2143.1–2670.2) 20.1
 0.001
 0.004
 23.3 (21.5–25.4) 13.3
 0.005
 0.0199
 Male 2992.6 (2761.7–3245.4) 26.9 (25.6–28.4)
wRVUs, work relative value units.

Male surgeons billed more work relative value units per case than female surgeons in academic and private practices (11.7 percent and 13.3 percent difference, respectively; all adjusted p < 0.0368) (Table 3). Male surgeons billed more CPT codes per case than female surgeons for academic and private practice settings [1.87 (95 percent CI, 1.82 to 1.91) versus 1.74 (95 percent CI, 1.69 to 1.8), a 6.1 percent difference; adjusted p = 0.0129] (Table 4 and Fig. 1). No significant differences were detected between male and female surgeon coding per case for the other categories of practice types.

Table 4. - CPT Codes per Case Distributed by Practice Setting and Sex
Category Mean Codes/Case (95% CI) Difference (%) p Adjusted p
Academic
 Female 1.84 (1.78–1.9) 3.478075 0.0688 0.275
 Male 1.9 (1.86–1.94)
Independent
 Female 1.51 (1.39–1.68) 6.133817 0.3176 0.9529
 Male 1.61 (1.5–1.75)
Military
 Female 1.58 (1.47–1.74) 2.254204 0.6896 1
 Male 1.62 (1.52–1.74)
NA
 Female 1.6 (1.4–1.94) 5.644441 0.536 1
 Male 1.7 (1.58–1.85)
Private
 Female 1.74 (1.69–1.8) 6.086872 0.0026 0.0129
 Male 1.87 (1.82–1.91)
NA, not able to assess.

F1
Fig. 1.:
CPT codes per case related to practice setting and sex. NA, not able to assess.

The number of operative cases reported was used as one of the investigation’s outcomes indicators, assessed by different practice types (academic, independent, military, private, and not able to assess), and classified by gender (Table 5). The global gender-based case differences detected in the work relative value units and CPT codes were no longer present, signifying that practice type alone is not a prime determinant of differences between male and female surgeons regarding case numbers. No significant differences were found between male and female surgeons in different practice environments regarding the number of minor cases performed (Table 6). However, when the total case volume was assessed by major and minor cases, male surgeons in academia significantly outperformed their female surgeon counterparts in the number of major cases (Table 7 and Fig. 2).

Table 5. - Surgical Cases Distributed by Practice Setting and Sex
Category Mean Cases (95% CI) Difference (%) p Adjusted p
Academic
 Female 103.21 (95.84–111.3) 9.316975 0.0878 0.2635
 Male 113.82 (108.54–119.4)
Independent
 Female 87.68 (71.49–108.58) 28.11389 0.0154 0.0615
 Male 119.85 (103.72–139.09)
Military
 Female 108.95 (82.09–147.26) −18.4913 0.386 0.386
 Male 88.04 (72.83–107.33)
NA
 Female 63.72 (56.04–72.75) 51.8797 <0.0001 <0.0001
 Male 123.98 (97.82–159.06)
Private
 Female 103.53 (94.31–113.86) 9.807183 0.1334 0.2668
 Male 110.28 (104.24–116.73)
NA, not able to assess.

Table 6. - Minor Cases Distributed by Practice Setting and Sex
Category Mean Minor Cases (95% CI) Difference (%) p Adjusted p
Academic
 Female 40.4 (34.8–46.9) −7.0 0.4213 1
 Male 37.8 (35.2–40.6)
Independent
 Female 24.5 (16–37.7) 37.0 0.0626 0.2504
 Male 39 (30.9–49.1)
Military
 Female 34 (25.7–45) −51.3 0.0305 0.1523
 Male 22.5 (17.5–28.8)
NA
 Female 19.5 (6.9–54.7) 34.3 0.4419 1
 Male 29.7 (22.1–39.9)
Private
 Female 38.2 (31.5–46.3) 4.0 0.7225 1
 Male 39.8 (35.5–44.6)
NA, not able to assess.

Table 7. - Major Case Differences by Sex and Practice Setting
Category Mean Major Cases (95% CI) Difference (%) p Adjusted p
Academic
 Female 75.11 (68.78–82.02) 15.1 0.0012 0.0048
 Male 89.53 (84.37–95.01)
Independent
 Female 68.73 (56.2–84.05) 24.3 0.0309 0.0901
 Male 90.8 (77.91–105.82)
Military
 Female 81 (54.22–121.02) −7.7 0.7664 0.7664
 Male 76.18 (56.99–101.83)
NA
 Female 44.5 (34.14–58) 56.9 <0.0001 <0.0001
 Male 103.2 (78.77–135.2)
Private
 Female 79.73 (71.47–88.95) 11.7 0.03 0.901
 Male 92.87 (85.41–100.99)
NA, not able to assess.

F2
Fig. 2.:
Number of major cases related to practice setting and sex. NA, not able to assess.

DISCUSSION

Although a large volume of research has discussed the existence of a wage gap between men and women in medicine and surgery, there has been little agreement regarding the primary causes. This study supports the hypothesis that differences in earnings between male and female plastic surgeons are related to the number of major operative cases performed and how they are coded. Significant differences were found between male and female surgeons in the total number of cases performed over a 9-month case collection period, the total number of major cases performed, the total work relative value units billed, the average number of work relative value units billed per case, and the average number of CPT codes billed per case. Our primary hypothesis, that differences would be greater than 10 percent between the sexes, was supported for all but the average number of cases performed (9.9 percent) and the average number of CPT codes per case (4.3 percent). All differences in the aforementioned variables were statistically significant. The largest discrepancy was for total work relative value units billed, where male surgeons billed 19.3 percent more compared to female surgeons over the 9-month case collection period. Surgeon sex related to practice type showed differences in the number of CPT codes billed per case in the private practice setting and for the number of major cases performed in the academic practice type.

If we were to assign the theoretical average dollar value of $65.45 per work relative value unit to the mean total work relative value units found in this data set, female plastic surgeons would have earned an average of $171,747 and male plastic surgeons $212,922 over a 9-month period, or an estimated $228,996 and $283,896 annually, respectively, a difference of $54,900 (19.3 percent). The annual earnings estimated in this population are less than those noted in the Doximity survey of plastic surgeons for several reasons: the majority of the oral board candidates are early in their careers, whereas surgeons in the Doximity survey can have been in practice for any number of years; cosmetic cases are not coded using the standard CPT methodology, and cosmetic surgery is not a fungible product, leading to a potentially large variation in procedural charges; multiple financial facets of a practice—including clinic visits, charges for noninvasive procedures, service, leadership, and research—are not included in this data set.

Our findings reflect those of Jagsi et al. in the cardiology literature: there is a relationship between income and the type of work performed.8 They found that women were less likely to perform highly reimbursed procedures and more likely to perform noninterventional ones. Female surgeons were less likely to have hospital-intense practices and less likely to fully participate in call. The work of female surgeons generated 7400 work relative value units annually compared to 9500 for male surgeons. Interestingly, even accounting for these differences in productivity, female surgeons’ incomes were $31,800 lower than expected. Likewise, a study of the sex-based wage gap in general practitioners in southern France found that men were more likely to provide increased intensity of services (e.g., electrocardiograms, minor surgery, and trauma care), explaining 61 percent of the 26 percent wage gap.25 In a study of ophthalmologists by Reddy et al., when clinical activity was standardized, collections were still significantly less for women at each level of activity.5 Similar to our findings, female ophthalmologists submitted fewer charges and used fewer CPT codes than their male counterparts, ultimately collecting 44 percent less in wages.5 Holliday et al. observed that when Medicare reimbursement of specific codes related to total knee and hip arthroplasty was evaluated, male and female surgeons earned the same.13 However, male orthopedic surgeons had higher total claims ($127,876 ± $151,325 versus $61,215 ± $90,151; p < 0.001) and higher claims per procedure ($41,144 ± $67,135 versus $12,532 ± $25,122; p < 0.001) than female orthopedic surgeons.13

The lack of a significant income difference in military settings in this study reflects findings of Veterans Health Administration surgeons.26 Although there was an overall gender pay gap in the Veterans Health Administration, the gap did not apply within surgical specialties. Predictors of a lower salary for health providers at the Veterans Health Administration remain dependent on gender, specialty, H-index, location, and years in practice.26

It was beyond the scope of this study to review every code billed by every surgeon to identify granular points of difference, but our study shows that differences in billing add up over time. Other shortcomings include the fact that the dollar value of each code does not reflect actual reimbursement. Surgeons may bill for codes performed but not be reimbursed for them. It is common, for example, when repairing multiple tendons, to be paid 100 percent for the first repair and a declining percentage for the repair of subsequent tendons. However, in some institutions, surgeons are reimbursed for CPT codes billed rather than by the amount paid the institution by the insurer. Reimbursement varies across the country and across institutions, so specific monetary values cannot be readily generalized.

This work provides new insight into and compelling evidence explaining some of the gender wage gap in plastic surgical practice. It is not simply the volume of surgery that affects annual income but the types of cases performed. Given that significant differences between male and female surgeons were also found in the average number of work relative value units billed per case and the average number of CPT codes billed per case, additional studies should be performed in the area of sex-based differences in coding practices. The practical implication of these findings is obvious: it is important to code accurately, not only for oneself, but for appropriate reimbursement and documentation of patient illness severity for the medical system to ensure that reimbursement is dispersed equitably. A wide body of literature across multiple specialties has demonstrated that erroneous coding is common. In a study of 600 family physicians, 33 percent of established patient notes were undercoded and 82 percent of new patient notes were overcoded when reviewed by a professional coder.27 No relationships were found between coding efficacy and physician age, years in practice, or participation in formal training. Young et al. found that both family medicine faculty and residents commonly undercoded clinic notes and that overcoding was rare.28 Interestingly, a study in a plastic surgery clinic of hypothetical cases detected a 28 percent error rate in coding among faculty, and a 43 percent error rate among residents.29 Although residents classified themselves as beginner level coders, 58 percent of staff physicians rated themselves as advanced and 16 percent as expert. Opportunities for improvement include adding a coding curriculum to residency training programs, creating internal networks for systemic collaboration, taking coding courses offered by professional societies, and using a coding specialist.30,31

This study should encourage acknowledgement of gender disparities in surgical practice types, and in billing and coding practices. The wage gap may be improved by asking different questions of colleagues and employers alike. Are the differences in major cases attributable to a more aggressive practice strategy by male plastic surgeons? Are major cases more infrequently referred to female plastic surgeons?14,32 Are female surgeons less likely to take on major cases because of other conflicting responsibilities? Should more effort be made to teach trainees and young surgeons optimal coding techniques? What is the role of mentoring in the professional development of female surgeons?33 Future work will be devoted to parsing out the differences in billing and coding by male and female plastic surgeons across the career spectrum.

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