2011 ACGME Duty Hour Limits had No Association With Breast Reconstruction Complications

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2011 ACGME Duty Hour Limits had No Association With Breast Reconstruction Complications Andrew M. Simpson, MD,a Alvin C. Kwok, MD, MPH,a Willem H. Collier, BS,b Jaewhan Kim, PhD,c Jacob Veith, MD,a and Jayant P. Agarwal, MDa,* a

Division of Plastic and Reconstructive Surgery, University of Utah, School of Medicine, Salt Lake City, Utah Department of Population Health Sciences, University of Utah, Salt Lake City, Utah c Department of Health, Kinesiology and Recreation, University of Utah, Salt Lake City, Utah b

article info

abstract

Article history:

Background: In 2011, the Accreditation Council for Graduate Medical Education (ACGME)

Received 26 March 2019

instituted further duty hour restrictions in response to concerns over long work hours and

Received in revised form

sleep deprivation in trainees and their effects on patient outcomes. The effect of duty hour

29 June 2019

restrictions on complications after breast reconstruction procedures has not been clarified.

Accepted 25 September 2019

Materials and methods: A retrospective cross-sectional analysis was designed. The National

Available online xxx

Inpatient Sample database was queried in the 2 y before and 2 y after the 2011 duty hour changes. Patients undergoing breast reconstruction, the most common elective admission

Keywords:

diagnosis for plastic surgery patients, were selected for analysis. Patient groups were

Surgical education

separated by teaching hospitals (THs) and nonteaching hospitals and by pre- and post-

ACGME

ACGME change periods. Surgical complication rates, length of stay, and procedures were

Duty hour restriction

analyzed using complex survey-weighted univariate and multivariate logistic regression

Breast reconstruction

analysis, with additional sensitivity analysis applied.

Complications

Results: The number of procedures did not vary significantly in the period after duty hour restrictions in THs (n ¼ 46,188, pre-ACGME versus n ¼ 48,980, post-ACGME). Overall complication rates in teaching (9.54%, pre-ACGME versus 9.04%, post-ACGME; P ¼ 0.561) and nonteaching hospitals (8.54%, pre-ACGME versus 7.70%, post-ACGME; P ¼ 0.319) did not significantly change after the implementation of duty hour changes. On multivariate analysis, surgery performed in resident THs after duty hour changes was not associated with a significant change in overall (odds ratio [OR], 1.03; 95% confidence interval [95% CI], 0.77-1.37; P ¼ 0.857) breast-specific complications (OR, 1.06; 95% CI, 0.77-1.46; P ¼ 0.731) or general complications (OR, 1.11; 95% CI, 0.80-1.54; P ¼ 0.541). Conclusions: Duty hour restrictions enacted in 2011 were not associated with postoperative complications after breast reconstruction. ª 2019 Elsevier Inc. All rights reserved.

* Corresponding author. Division of Plastic and Reconstructive Surgery, University of Utah, School of Medicine, 30 N 1900 E, 3B400, Salt Lake City, UT 84132. Tel.: þ1 801 213 4335; fax: þ1 801 585 3749. E-mail address: [email protected] (J.P. Agarwal). 0022-4804/$ e see front matter ª 2019 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jss.2019.09.058

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Introduction Graduate medical education has undergone significant changes in the last 15 y. In response to concerns regarding long working hours and physician burnout and their effects on patient care, national changes to resident physician working hours were enacted in 2003, affecting all residency programs.1,2 Despite these changes, concern regarding long working hours in trainees and patient care quality persisted, and in 2011, the Accreditation Council for Graduate Medical Education (ACGME) implemented a second national reform, further restricting resident duty hours.3 Changes from both 2003 and 2011 are described in Table 1. Both reforms have been met with mixed opinions. It is accepted that resident fatigue and sleep deprivation can lead to decreased clinical performance, quality of life, and cognition, whereas increasing the risk of needle stick injuries and motor vehicle collisions.5e10 Proponents of duty hour reform point to improvements in resident well-being safety and possible reduction of avoidable medical adverse events.11e13 Others believe that increased resident handover combined with a reduction in clinical experience caused by truncated work hours may lead to increased medical error and worsened patient outcomes.14e18 Examinations of the effect of duty hour restrictions have been performed in numerous surgical specialties.19e22 The impact of changes on plastic surgery inpatient outcomes has not been ascertained. Breast reconstruction is performed often by plastic surgeons and is a good procedure to study to understand outcomes in procedures performed by plastic surgeons. Fatigued residents may be prone to mistakes during breast reconstruction operations. Possible errors after the reform include errors in handoff or errors made by rounding residents who did not operate on a patient because of the operating resident requiring a day off. The purpose of this study was to examine a national database for the effects of the 2011 duty hour implementation on inpatient postoperative outcomes after breast reconstruction.

Materials and methods Database The National Inpatient Sample (NIS) is a component of the Healthcare Cost and Utilization Project (HCUP) and is the largest all-payer inpatient care database currently available to the public in the United States. The NIS gathers information from the care of patients covered by Medicare, Medicare Advantage, Medicaid, private insurance, and from the uninsured. The database does not identify individual hospitals; however, it does classify them on their teaching status. Since 2012, the NIS contains information from a 20% stratified sample of US hospitals, including academic and community centers, totaling approximately 8 million hospital stays from 1000 hospitals.23 Before 2012, the NIS sampled 100% of hospital discharges from a sample of 20% of US hospitals. For either sampling strategy, the weighted

NIS can be used to estimate national surgical complication rates.

Study design This study was deemed institutional review board exempt on the basis of deidentified information. A retrospective crosssectional analysis was conducted using NIS data from January 1, 2009 to December 31, 2010 (pre-ACGME changes) and from January 1, 2012 to December 31, 2013 (post-ACGME changes). The 2011 ACGME duty hour restrictions went into enforceable effect on July 1, 2011.1,3 Data from January 1, 2011 to December 31, 2011 were excluded. Individual discharges were separated by teaching hospital (TH) designation. To identify THs versus nonteaching hospitals (NTHs), two variables in NIS were used: location/teaching status of hospital and teaching status of hospital. When hospitals were indicated in the teaching or urban teaching variables, they were classified as the TH. Hospitals not receiving a TH designation were classified as NTH. Patient cases were identified using International Classification of Diseases, Ninth Revision procedural codes for breast reconstruction.24 The codes used are listed in Table 2. These included tissue expanderebased reconstruction, latissimus dorsi flaps, pedicled transverse rectus abdominis myocutaneous (TRAM) flaps, deep inferior epigastric artery perforator (DIEP) flaps, gluteal artery perforator flaps, superficial inferior epigastric artery perforator flaps, and other total reconstruction of breast. Demographic information, including age and race, and patient comorbidities, including obesity, hypertension, diabetes, and smoking status, were collected. The type of insurance used and teaching status of the hospital for each case were identified.

Outcome measures The primary outcomes of interest were general and breastspecific complications, identified via International Classification of Diseases, Ninth Revision codes (Table 2). Length of inpatient stay is a core variable in NIS and was collected for each case. General complications included bleeding complications, infection, wound dehiscence, urinary tract infection, and incidence of blood transfusion. Breast-specific complications included hematoma, revision of anastomosis, flap failure, and anastomotic failure. The incidence of complications was grouped in teaching versus nonteaching cohorts and pre- and post-ACGME changes. Individual complications were combined for grouped analysis for breast-specific, general, and overall complications (general plus breast specific).

Statistical analysis A complex survey design was used for analysis, as is guided by HCUP NIS recommendations.25 The survey (svy) suite of commands of STATA (StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP) were used, where a complex survey design was established using patient discharge weights, clustering at the hospital level, and postdischarge stratification. The NIS is prepackaged with all such

simpson et al  duty hour restrictions and complications

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Table 1 e Summary of standards enacted during the 2003 and 2011 ACGME duty hour reforms. Category

2003 ACGME reform

2011 ACGME reform

Adequate supervision required for all trainees

PGY-1 residents must have direct supervision from a senior resident or attending at all times

Maximum number of hours per week

Total work hours limited to 80 h per week averaged during 4 wk

Total work hours limited to 80 h per week averaged during 4 wk

Mandatory time free of duty

Residents must have 1 d free from educational and clinical responsibilities in 7 d, averaged during 4 wk

Residents must have 1 d free from educational and clinical responsibilities in 7 d, averaged during 4 wk, and at-home call cannot be assigned during those days

Mandatory length of duty period

No new patients may be accepted after 24 h on duty. Residents may remain for 6 h after 24 h to participate in educational or transfer of care duties, to attend outpatient clinics and maintain continuity

Duty periods of PGY-1 residents must not exceed 16 h in duration. Duty periods of PGY-2 residents and above may be scheduled to a maximum of 24 h with an additional 4 h to complete work; no clinic duties or admissions after 24 h of duty

There should be a 10-h period between all daily duty periods and after in-house call

Residents must have 8 h between duty periods and should have 10 h between duty periods. Residents must have at least 14 h free of duty after 24 h of in-house duty

Maximum in-house on-call frequency

In-house call can occur no more frequently than every third night, averaged during 4 wk

PGY-2 residents and above must be scheduled for in-house call no more frequently than every third night

At-home call

Hours spent in hospital while on at-home call must count toward the 80-h per week limit

Hours spent in hospital while on at-home call must count toward the 80-h per week limit

N/A

Residents must not be scheduled for more than six consecutive nights of night float call

Supervision

Duty hours

Minimum time off between scheduled duty periods

Call

Maximum frequency of inhouse night float PGY ¼ postgraduate year; N/A ¼ not applicable. Amended from Ref.4

information associated with each discharge. We applied the same survey design setup according to weights, clustering, and strata for each discharge, despite the sampling design change implemented in the NIS at the beginning of 2012. After the complex survey weighting is applied, the NIS is considered to be reflective of all inpatient discharges from academic and community hospitals in the United States, excluding rehabilitation hospitals and long-term acute care hospitals. Weighting is routinely performed in analysis of NIS data.23,25,26 Initially, descriptive statistics and univariate tests were performed to compare demographic characteristics, procedure type, and postoperative complications to pre- and postACGME periods in both THs and NTHs. Survey-weighted univariate logistic regression was performed for continuous independent variables. For binary variables, we used the Pearson chi-square statistic, which is corrected for the weighted population with second-order correction by Rao and Scott27 and converted to an F-test statistic. We used surveyweighted multivariate logistic regression to model overall postoperative complications, breast reconstructionespecific complications, and general surgical complications on age, race, pre- or post-ACGME changes, and TH status. For comparison variables, white race and private insurance were used as reference terms, as previously described.28e31 To account

for surgical complexity in the analysis, autologous reconstruction (including latissimus dorsi flaps, DIEP flaps, gluteal artery perforator flaps, and superficial inferior epigastric artery perforator flaps) was included in the model. An interaction term was created between the post-ACGME binary variable and TH status. The term was included to measure the effect of the ACGME policy change specifically in hospitals whose care it was designed to affect, that is, THs.

Sensitivity analyses For each of the three survey-weighted multivariate logistic regressions, we performed two sensitivity analyses. We noticed preliminarily that for all variables in our data set except for race, the proportion of missing data was less than 1%. Race data were missing in 9% of cases. As such, we first performed the logistic regressions omitting all rows with missing values. We then performed logistic regressions treating the missing race values as a sixth race category to assess whether the missing data in race influence either model fit or the statistical significance of other variables. We also performed all multivariate logistic regressions with and without the interaction term. All P values were two sided, and we considered any effect to be significant given the corresponding P < 0.05. Data

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Table 2 e International Classification of Diseases, Ninth Revision codes used to describe patient cohort and complications in NIS. Code(s)

Description

Breast reconstruction 85.71

Latissimus dorsi myocutaneous flap

85.72

Pedicled TRAM flap

85.73

DIEP flap

85.75

SIEAP flap

85.76

GAP flap

85.79

Other total reconstruction of breast

85.95

Insertion of tissue expander

Breast-specific complications 998.32

Dehiscence

996.52

Flap ischemia/failure

996.79

Anastomotic failure of flap

996.49

Failure of internal implant or graft

85.96

Removal of breast expander

998.12

Hematoma

39.49

Revision of anastomosis

996.69

Breast implant infection

General complications 998.59, 998.5, 998.51

Postoperative infection

995.91

Sepsis, unspecified

995.92

Sepsis, with organ dysfunction

998.1, 998.11, 998.13 599 998.8, 998.81, 998.89, 998.9

Hemorrhage UTI Unspecified procedural complications

998.83

Nonhealing surgical wound

998.2

Accidental perforation of vessel/ nerve/organ

998.6

Postoperative fistula

998

Shock

998.4

Retained foreign body

99.04

Blood transfusion

SIEAP ¼ superficial inferior epigastric artery perforator; GAP ¼ gluteal artery perforator; UTI ¼ urinary tract infection.

management and analysis was performed using STATA 15 (StataCorp LP, 2017).

Patient demographic and hospital information The mean age of patients undergoing breast reconstruction did not significantly vary after ACGME changes in the TH cohort (50.86  10.39, pre-ACGME versus 51.24  10.59, postACGME; P ¼ 0.191), patients were older after 2011 in the NTH cohort (51.77  10.54 y, pre-ACGME versus 52.39  10.62 y, postACGME; P ¼ 0.023). The distribution of white, black, Hispanic, Asian/Pacific Islander, and Native American patients undergoing breast reconstruction did not differ in either the TH cohort or the NTH cohort. The number of patients identifying as other increased significantly in the TH group (1100, preACGME versus 2040, post-ACGME; P ¼ 0.044). The distribution of payers for breast reconstruction did not change between the pre- and post-ACGME groups in the TH cohort. In the NTH cohort, Medicare (13.4%, pre-ACGME versus 16.3%, postACGME; P ¼ 0.003) and Medicaid (5.7%, pre-ACGME versus 7.8%, post-ACGME; P ¼ 0.013) payers increased significantly in the post-ACGME period, whereas private insurance (77.0%, pre-ACGME versus 71.7%, post-ACGME; P ¼ 0.001) payers significantly decreased. Obesity (body mass index >30 kg/m2) significantly increased (5.3%, pre-ACGME versus 8.03%, post-ACGME; P < 0.001) between the periods in the TH cohort. It was not significantly changed in the NTH group (7.0%, pre-ACGME versus 7.5%, post-ACGME; P ¼ 0.117). The rate of hypertension, diabetes, and smoking status did not significantly change in the pre- and post-ACGME groups in either the TH cohort or the NTH cohort. The length of stay decreased statistically in the NTH groups (2.45  2.16 d, pre-ACGME versus 2.23  1.73 d, post-ACGME; P ¼ 0.010) but was unaffected in the TH groups (2.64  2.21 d, pre-ACGME versus 2.54  2.54 d, postACGME; P ¼ 0.350) (Table 3).

Distribution of breast reconstruction cases We separated the particular breast reconstruction techniques performed by period (pre- and post-ACGME) and hospital status (TH versus NTH). The number of DIEP flaps performed (as a percent of total reconstructions) decreased significantly in the NTH group (6.5%, pre-ACGME versus 4.55%, postACGME; P ¼ 0.019) but was unchanged in the TH group (10.69%, pre-ACGME versus 10.93%, post-ACGME; P ¼ 0.881). The number of pedicled TRAM flaps performed decreased significantly in both the TH (10.98%, pre-ACGME versus 6.76%, post-ACGME; P < 0.001) and the NTH (8.41%, pre-ACGME versus 6.14%, post-ACGME; P ¼ 0.005) groups (Table 4).

Inpatient complications after breast reconstruction

Results Database There were 38,051,324 unweighted individual discharges in the HCUP NIS database from 2009 to 2013. Of these, 36,479 were inpatient stays after breast reconstruction. Cases from 2011, corresponding to 8076 cases, were excluded. After weighting the data according to standard NIS protocols, there were 139,758 individual cases for analysis; 69,223 in the preACGME cohort and 70,535 in the post-ACGME cohort (Figure).

Descriptive statistics and univariate comparison between periods in TH and NTH are shown in Table 5. The total breastspecific complication incidence was 5.1% (pre-ACGME) and 5.0% (post-ACGME) (P ¼ 0.855) in the TH cohort and 4.2% (pre2011) and 3.8% (post-2011) (P ¼ 0.439) in the NTH cohort. The most frequent breast-specific complication after reconstruction in both groups was hematoma. The incidence of total and any individual breast-specific complication did not vary significantly in either of the groups. Total general complications did not change significantly in either the TH cohort

simpson et al  duty hour restrictions and complications

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HCUP NIS Total Discharges 2009-2013 N = 189,116,625 (Weighted) N = 38,051,324 (Unweighted)

Total Breast Reconstructions 2009-2013 N = 176,691 (Weighted) N = 36,479 (Unweighted)

Excluding Cases from 2011 N = 36,933 (Weighted) N = 8,076 (Unweighted)

Total Cases from 20092010 and 2012-2013 N = 139,758 (Weighted) N = 28,403 (Unweighted)

Total Cases 2009-2010 (Pre-ACGME) N = 69,223 (Weighted) N = 14,296 (Unweighted)

Teaching Hospital Cases N = 44,104 (Weighted) N = 9,066 (Unweighted)

Non-Teaching Hospital Cases N = 23,872 (Weighted) N = 4,963 (Unweighted)

Total Cases 2012-2013 (Post-ACGME) N = 70,535 (Weighted) N = 14,107 (Unweighted)

Teaching Hospital Cases N = 48,790 (Weighted) N = 19,070 (Unweighted)

Non-Teaching Hospital Cases N = 21,745 (Weighted) N = 4,349 (Unweighted)

Figure e Flowsheet for patient identification in the NIS based on ICD-9 codes.

(7.1%, pre-ACGME versus 6.8%, post-ACGME; P ¼ 0.689) or the NTH cohort (6.8%, pre-ACGME versus 5.9%, post-ACGME; P ¼ 0.200). Hemorrhage increased in the TH cohort (2.5%, pre-ACGME versus 3.1%, post-ACGME; P ¼ 0.044) and was statistically unchanged in the NTH cohort (2.8%, pre-ACGME versus 2.5%, post-ACGME; P ¼ 0.431). No other individual complications changed significantly. The results from our multivariate analysis are shown in Table 6. All variables represented within rows in the table were included in the models. As such, all associations represented are independent of all else included in the models. Age was not found to be associated with either overall complications (odds ratio [OR], 1.00; 95% confidence interval [95% CI], 0.99-1.00; P ¼ 0.838), breast-specific complications (OR, 1.00; 95% CI, 0.99-1.01; P ¼ 0.763), or general complications (OR, 1.00; 95% CI, 0.99-1.01; P ¼ 0.808). In contrast, autologous reconstruction was significantly associated with overall (OR, 3.97; 95% CI, 3.57-4.42; P < 0.001), breast-specific (OR, 2.70; 95% CI, 2.38-3.06; P < 0.001), and general (OR, 3.64; 95% CI, 3.23-4.10; P < 0.001) complications. Obesity was associated with overall (OR, 1.41; 95% CI, 1.20-1.66; P < 0.001) and general (OR, 1.58;

95% CI, 1.33-1.87; P < 0.001) complications but not breastspecific (OR, 1.20; 95% CI, 0.95-1.51; P ¼ 0.124) complications. Hypertension was associated with increased overall (OR, 1.17; 95% CI, 1.05-1.31; P ¼ 0.004) and general (OR, 1.22; 95% CI, 1.071.38; P ¼ 0.002) complications but not breast-specific (OR, 1.08; 95% CI, 0.93-1.25; P ¼ 0.299) complications. Similar to obesity and hypertension, diabetes was also associated with increased overall (OR, 1.24; 95% CI, 1.05-1.47; P ¼ 0.010) and general (OR, 1.27; 95% CI, 1.06-1.44; P ¼ 0.010) complications but not with breast-specific (OR, 1.09; 95% CI, 0.87-1.38; P ¼ 0.454) complications. Black race was significantly associated with overall (OR, 1.21; 95% CI, 1.05-1.40; P ¼ 0.010) and general (OR, 1.37; 95% CI, 1.16-1.60; P < 0.001) complications but not breast-specific (OR, 0.96; 95% CI, 0.79-1.17; P ¼ 0.682) complications. Other race variables were not significantly associated with complications. The designations of TH, NTH, any hospitals’ post-ACGME changes, and THs’ post-ACGME changes were not associated with increased overall, specific, or general complications. Similarly, the type of insurance payer was not independently associated with either overall, specific, or general

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Table 3 e Demographic information of patients undergoing breast reconstruction in THs and NTHs before and after ACGME changes. Demographics

TH

P

Pre-ACGME changes, n (%)

Post-ACGME changes, n (%)

50.86  10.39

51.24  10.59

29,511 (75.8)

Black Hispanic

NTH

P

Pre-ACGME changes, n (%)

Post-ACGME changes, n (%)

0.191

51.77  10.54

52.39  10.62

0.023

33,485 (73.0)

0.609

17,872 (79.6)

15,945 (76.5)

0.582

3900 (10.0)

5200 (11.3)

0.168

1683 (7.8)

1765 (8.5)

0.207

3207 (8.2)

3565 (7.8)

0.976

1388 (6.4)

1620 (7.8)

0.091

Asian/Pacific Islander

987 (2.5)

1410 (3.1)

0.158

672 (3.1)

725 (3.5)

0.365

Native American

234 (0.6)

150 (0.3)

0.498

34 (0.1)

25 (0.1)

0.712

1100 (2.8)

2040 (4.4)

0.044

611 (2.8)

755 (3.6)

0.212

Medicare

5078 (11.5)

6155 (12.6)

0.162

3200 (13.4)

3545 (16.3)

0.003

Medicaid

3746 (8.5)

4965 (10.2)

0.124

1355 (5.7)

1685 (7.8)

0.013

18,357 (77.0)

15,585 (71.7)

0.001

Age (y), mean  SD Race White

Other Type of insurance

Private insurance

33,616 (76.3)

35,680 (73.2)

0.101

Other insurance

1622 (3.7)

1935 (4.0)

0.642

929 (3.9)

910 (4.2)

0.774

<0.001

0.117

Comorbidities Obesity (BMI >30 mg/kg2) Hypertension Diabetes Smoking status LOS (d), mean  SD

2326 (5.3)

3920 (8.03)

1659 (7.0)

1630 (7.5)

10,594 (24.0)

12,220 (25.05)

0.371

6047 (25.3)

5740 (26.4)

0.351

2705 (6.1)

2935 (6.0)

0.816

1496 (6.3)

1585 (7.3)

0.090

2386 (5.4)

2750 (5.64)

0.616

1617 (6.8)

2.64  2.21

2.54  2.54

0.350

2.45  2.16

1425 (6.55) 2.23  1.73

0.725 0.010

SD ¼ standard deviation; BMI ¼ body mass index; LOS ¼ length of stay.

complications (Table 6). We also noted that in no modeling context run for sensitivity analyses did any previously statistically significant relationship become nonstatistically significant. Similarly, no nonstatistically significant relationship became statistically significant. For the relationships that remained statistically significant in sensitivity analyses, the effect size associated with such variables changed in no clinically meaningful way. Finally, in all other attempted models, TH status overall and in the post-ACGME period remained a nonindependent predictor of any complication.

Discussion The 2003 ACGME duty hour reform limited residents to 80 h of work per week, with 1 d free of patient care per week averaged during 4 wk. Other changes included were a 24-h limit on continuous duty, with 6 h allowed for transfer of care and educational activities, and a maximum of 1 d in 3 call frequency.1,2 These changes were in place for 7 y, when the ACGME again decided to enact duty hour reform because of ongoing concerns. The second standard required residents working 24-h shifts to have a maximum of 4 h for transfer of care duties, minimum of 14 h off between work periods, and required first-year residents to have a maximum of 16 h of continuous duty with direct senior supervision at all times while in house (Table 2).3 Implementation of duty hour restrictions has been met with a mixed reaction from trainees and educators. The

primary intentions of these reforms were to reduce sleep deprivation among trainees and therefore improve performance and patient care, with a secondary benefit of improvement in resident quality of life. A purported drawback of these changes has been increases in patient handover and less time spent on patient care, with accompanying increases in medical error and decreases in care quality and technical competence. There are continued concerns regarding the effect on patient outcomes. In the present study, the 2011 duty hour reform was not found to be associated with an increase in inpatient complications after breast reconstruction. There have been multiple studies examining the implications of both the 2003 and 2011 duty hour reforms on patient outcomes, resident well-being, and educator and trainee opinion. Two early studies examining the effect of the 2003 reforms on Medicare and Veterans Affairs populations determined no association with increased mortality after surgery.32,33 This patient population had undergone general, orthopedic, and vascular surgery procedures in the 2 y after the 2003 duty hour restrictions. In obstetrics and gynecology, one study evaluating the 2003 reforms also showed no changes in surgical outcomes.34 In the neurosurgery literature, one study examining effects of the first reform found increased morbidity, but not mortality, among patients undergoing intracranial and spinal surgeries.18 Similarly, an orthopedic study of patients undergoing hip fractures repair found higher rates of postoperative morbidity, but not mortality, after the 2003 reforms.35 A large review of more than 14 million admissions demonstrated no change in the rate of

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Table 4 e Distribution of breast reconstruction cases performed in THs and NTHs before and after implementation of duty hour changes. Procedure

Insertion of tissue expander

TH

P

Pre-ACGME changes, n (%)

Post-ACGME changes, n (%)

30,134 (68.32)

NTH

P

Pre-ACGME changes, n (%)

Post-ACGME changes, n (%)

34,725 (71.17)

0.311

18,423 (77.17)

17,345 (79.77)

0.087

Latissimus dorsi

6570 (14.8)

8430 (17.28)

0.114

3479 (14.57)

3335 (15.34)

0.578

Pedicled TRAM flap

4844 (10.98)

3300 (6.76)

2008 (8.41)

1335 (6.14)

0.005

DIEP flap

4715 (10.69)

5335 (10.93)

0.881

1552 (6.5)

990 (4.55)

0.019

GAP flap

146 (0.33)

175 (0.36)

0.864

65 (0.30)

0.401

510 (1.17)

525 (1.08)

0.827

53 (0.22)

45 (0.21)

0.900

1109 (2.52)

1725 (3.54)

0.143

457 (1.91)

730 (3.36)

0.006

SIEAP flap Other total reconstruction of breast

<0.001

41 (0.17)

GAP ¼ gluteal artery perforator; SIEAP ¼ superficial inferior epigastric artery perforator.

surgical and procedural patient safety indicators in the 2 y after the 2003 changes were implemented.36 The 2011 duty hour reform has fewer studies describing patient outcomes. Rajaram et al.20 found that the latest restrictions were not associated with increased morbidity or mortality after general surgery procedures. The same group extended their analysis to neurosurgery, obstetrics and gynecology, orthopedics, urology, and vascular surgery patients, again finding no association between reform and changes in outcomes.19 Bilimoria et al.37 found in a national randomized trial of surgical training institutions that there was no change in outcomes with institutions implementing the new changes in duty hour restrictions. Similar analyses specifically in plastic surgery patient populations have not been performed. The differences in training models between specialties warrant individual attention in our field. Plastic surgery programs tend to be smaller, with fewer trainees, and often rely on athome call coverage regimens. These differences compared with typically larger programs, such as general and orthopedic surgery, may yield variation in patient outcomes after duty hour reform. Trainee opinion on duty hour reform has been mixed. A national survey of residents administered in 2010 demonstrated concerns that new reforms would increase the length of residency and fellowship training, and that they would not improve [.] education, experience, and fund of knowledge.4 One study found that there was no reduction in resident operative experience after the 2003 reforms,38 whereas several studies have found no improvement in resident safety and quality of life indicators, including sleep, depression, and motor vehicle crashes in the same period.39,40 Bilimoria et al.37 found no differences in resident satisfaction, resident wellbeing, or education quality. The present study examined breast reconstruction outcomes in the 2 y before and the 2 y after the 2011 duty hour reform and compared these cohorts in TH and NTH settings, with the NTH group considered a control. This patient group was selected as it represents the largest population of patients cared for exclusively by plastic surgeons in an inpatient setting. The NIS, containing the largest stratified sample of inpatient admissions in the United States, was chosen for its ability to identify specific complications postoperatively and because of the finding that other large databases are not

reliable in analysis of flap failure.23,41 NIS separates hospitals by teaching status. Although not all THs will have plastic surgery programs, the large number of cases analyzed should eliminate this unknown as a potential confounder. We found that the number of pedicled TRAM flaps performed declined significantly, which is consistent with previous findings during this period42 and probably explained by the advancement of surgical techniques and surgeon comfort with less morbid muscle-sparing flaps. DIEP flaps decreased at NTHs, likely because of the realization that these lengthy and difficult procedures are less feasible without resident or fellow support. On univariate analysis, hemorrhage complications increased in the TH cohort. This small increase (0.6%) is unlikely to be clinically significant and did not affect total general complications. A multivariate model was created with interaction variables including TH status and complications after ACGME duty hour changes. To account for the effect of patient-related and surgery-related factors on outcomes, variables, including autologous reconstruction, obesity, hypertension, smoking, and diabetes, were included in the analysis. We have determined that breast and general complications did not increase in the inpatient postoperative period among breast reconstruction patients after implementation of the 2011 ACGME duty hour reform. This work adds to the body of literature examining the impact of duty hour reform on patient outcomes.18e22,43,44 Although this work is limited to breast reconstruction patients, it is the only study analyzing outcomes in the plastic surgery population. Further studies are required to fully examine the impact of duty hour reform on other patient outcomes, educators, and trainees.

Limitations This study has limitations. Because of the nature of the data set and when it was purchased by our institution, we were only able to evaluate the 2 y before and the 2 y after the 2011 ACGME reform. It is possible that long-term analysis could yield significant differences. Multiple similar studies have used the NIS database in this context.20,21,35,43,45 Although NIS uses stringent quality control regimens, there is a degree of data entry error and miscoding. This bias should affect all entries equally, and its impact should therefore be mitigated

8

j o u r n a l o f s u r g i c a l r e s e a r c h  - 2 0 1 9 ( - ) 1 e1 0

Table 5 e Distribution of complications among all breast reconstructive patients in THs and NTHs before and after ACGME duty hour restrictions. Complications

TH

P

Pre-ACGME changes, n (%)

Post-ACGME changes, n (%)

4209 (9.54)

4410 (9.04)

2240 (5.1)

2435 (5.0)

Hematoma

827 (1.9)

Revision of anastomosis

203 (0.5)

Dehiscence Flap ischemia/failure

Overall complications

NTH

P

Pre-ACGME changes, n (%)

Post-ACGME changes, n (%)

0.561

2040 (8.54)

1675 (7.70)

0.319

0.855

1010 (4.2)

835 (3.8)

0.439

1065 (2.2)

0.169

458 (1.9)

350 (1.6)

0.286

190 (0.4)

0.504

18 (0.1)

20 (0.1)

0.824

174 (0.4)

160 (0.3)

0.534

75 (0.3)

95 (0.4)

0.324

293 (0.7)

250 (0.5)

0.239

77 (0.3)

90 (0.4)

0.448

Breast-specific complications Total

Anastomotic failure of flap

808 (1.8)

670 (1.4)

0.054

358 (1.5)

275 (1.3)

0.436

Implant infection

215 (0.5)

360 (0.7)

0.066

104 (0.4)

90 (0.4)

0.887

3119 (7.1)

3315 (6.8)

0.689

1631 (6.8)

1275 (5.9)

0.200

312 (0.7)

335 (0.7)

0.886

110 (0.5)

125 (0.6)

0.434

Sepsis

28 (0.1)

50 (0.1)

0.368

15 (0.1)

10 (0.0)

0.717

Sepsis, with organ dysfunction

24 (0.1)

10 (0.0)

0.233

15 (0.1)

0 (0.0)

0.082

1121 (2.5)

1505 (3.1)

0.044

672 (2.8)

550 (2.5)

0.431

178 (0.4)

200 (0.4)

0.940

76 (0.3)

85 (0.4)

0.926

72 (0.2)

110 (0.2)

0.361

34 (0.1)

40 (0.2)

0.584

General complications Total Postoperative infection

Hemorrhage UTI Unspecified procedural complications Accidental perforation of vessel/nerve/organ Blood transfusion

88 (0.2)

60 (0.1)

0.215

19 (0.1)

35 (0.2)

0.615

1730 (3.9)

1530 (3.1)

0.163

943 (3.9)

585 (2.7)

0.268

UTI ¼ urinary tract infection.

in the analysis.23,26 In addition, HCUP altered its sampling strategy for the NIS beginning in the year 2012, which corresponds to our post-ACGME period. The sampling redesign was intended to improve precision of statistical estimates and provide a more accurately nationally representative sample according to hospital characteristics, such as teaching status, size, and urban versus rural status, as well as patient characteristics such as diagnosis-related group. We used complex survey methods according to the post 2012 change but cannot rule out that some differences in surgeries and outcomes observed in our study are attributable to the sampling redesign. However, we feel that because of our adjustment methods, the lack of influence of teaching status in the postACGME period on complication rates is realistic and not influenced by the redesign. The status of TH does not guarantee that breast reconstruction cases were performed with resident involvement, or that these patients were subsequently cared for by residents while admitted to the hospital. Conversely, it is also possible that cases performed in NTHs were assisted by visiting or moonlighting trainees. Although this does introduce a potential confounder, the large number of cases analyzed should mitigate the overall significance of these outliers. Prospective trials would be required to control for this variability. We accounted for surgical case complexity (autologous reconstruction) and patient-related risk factors (diabetes, obesity, and hypertension) in our multivariable model to limit confounders. Although we found no increase in complications in THs or NTHs, it is possible that unforeseen patient-related factors that were not accounted for

skewed our findings toward no difference. Resident noncompliance or falsification of duty hour reporting has been found to be somewhat common and may bias the study.46,47 There are several inherent limitations of the database that prohibit generalizability. NIS captures complications arising in the inpatient period only. Complications that arise after discharge are not included. It is possible that in examining these factors significant differences could be found, and therefore, our analyses should only be interpreted as inpatient outcomes after breast reconstruction. NIS has no metric to quantify outcomes, such as surgeon- or patient-reported satisfaction, readmissions, or complications encountered at clinic visits or outside hospitals. It is possible that both factors could be significantly different in the presence of trainees; future studies examining this aspect may prove interesting. We selected breast reconstruction patients in this analysis for several reasons: they are almost always performed by plastic surgeons, they are performed in both THs and NTHs, and finally that they are high-volume procedures and almost always incur a routine inpatient stay postoperatively. Other broad procedural domains of plastic surgeons are unlikely to encompass all these features and may be unsuitable for examination using this database and study design. Although this approach afforded us a homogeneous and ideal study population, it does limit generalizability. Further studies examining the impact of duty reform in other plastic surgery subspecialties are indicated to broaden the scope of these findings.

9

simpson et al  duty hour restrictions and complications

Table 6 e Multivariate analysis of patient and procedural factors contributing to complications. Clinical characteristics

Overall

Breast-specific complications P

OR

95% CI

P

General complications

OR

95% CI

OR

95% CI

P

Age

1.00

0.99-1.00

0.838

1.00

0.99-1.01

0.763

1.00

0.99-1.01

0.808

Autologous reconstruction

3.97

3.57-4.42

<0.001

2.70

2.38-3.06

<0.001

3.64

3.23-4.10

<0.001

Obesity

1.41

1.20-1.66

<0.001

1.20

0.95-1.51

0.124

1.58

1.33-1.87

<0.001

Hypertension

1.17

1.05-1.31

0.004

1.08

0.93-1.25

0.299

1.22

1.07-1.38

0.002

Diabetes

1.24

1.05-1.47

0.010

1.09

0.87-1.38

0.454

1.27

1.06-1.44

0.010

White

*

*

*

*

*

Race *

*

*

*

Black

1.21

1.05-1.40

0.010

0.96

0.79-1.17

0.682

1.37

1.16-1.60

<0.001

Hispanic

0.94

0.79-1.11

0.472

0.86

0.67-1.12

0.264

1.00

0.83-1.20

0.995

Asian/Pacific Islander

1.02

0.80-1.30

0.861

0.82

0.57-1.17

0.280

1.10

0.83-1.45

0.528

Other

1.19

0.93-1.51

0.162

1.19

0.87-1.64

0.279

1.16

0.90-1.50

0.258

TH

1.00

0.78-1.28

0.996

1.10

0.85-1.42

0.475

0.93

0.70-1.23

0.587

All hospitals post-ACGME

0.91

0.72-1.15

0.438

0.95

0.73-1.24

0.705

0.85

0.65-1.11

0.226

THs’ post-ACGME

1.03

0.77-1.37

0.857

1.06

0.77-1.46

0.731

1.11

0.80-1.54

0.541

*

*

*

*

Medicare

1.04

0.90-1.21

0.601

0.94

0.76-1.17

0.599

1.01

0.85-1.20

0.904

Medicaid

1.16

0.99-1.37

0.075

1.03

0.82-1.28

0.821

1.07

0.89-1.29

0.474

Other insurance

0.95

0.76-1.20

0.685

0.94

0.69-1.27

0.669

1.05

0.83-1.33

0.709

Hospital-level factors

Type of insurance Private insurance

*

*

*

*

*

*

Reference value.

Conclusions Graduate medical education must balance resident wellbeing, training competency, and patient safety. Ongoing attempts by the ACGME to regulate trainee working hours have been met with mixed reviews and conflicting findings on patient outcomes. This study demonstrates that complication rates after breast reconstruction did not significantly change after implementation of the 2011 duty hour reform.

Acknowledgment Authors’ contributions: AMS: Conception of study, creation of mock tables, data interpretation, drafting of manuscript, editing of manuscript, and submission of manuscript; ACK: Drafting of manuscript and provision of database editing of manuscript; WHC: Database coding, interpretation, statistics, and editing of manuscript; JK: Database coding, interpretation, statistics, and editing of manuscript; and JPV: Editing of manuscript and submission of manuscript. JPA: Conception of study, interpretation of data, supervision, editing of manuscript, and submission of manuscript.

Disclosure This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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