Abstract

BACKGROUND: Overlapping surgery is a common practice to improve surgical efficiency, but there are limited data on its safety.

OBJECTIVE: To analyze the patient outcomes of overlapping vs nonoverlapping surgeries performed by multiple neurosurgeons.

METHODS: Retrospective review of 7358 neurosurgical procedures, 2012 to 2015, at an urban academic hospital. Collected variables: patient age, gender, insurance, American Society of Anesthesiologists score, severity of illness, mortality risk, admission type, transfer source, procedure type, surgery date, number of cosurgeons, presence of neurosurgery resident/fellow/another attending, and overlapping vs nonoverlapping surgery. Outcomes: procedure time, length of stay, estimated blood loss, discharge location, 30-day mortality, 30-day readmission, return to operating room, acute respiratory failure, and severe sepsis. Statistics: univariate, then multivariate mixed-effect models.

RESULTS: Overlapping surgery patients (n = 3725) were younger and had lower American Society of Anesthesiologists scores, severity of illness, and mortality risk (P < .0001) than nonoverlapping surgery patients (n = 3633). Overlapping surgeries had longer procedure times (214 vs 172 min; P < .0001), but shorter length of stay (7.3 vs 7.9 d; P = .010) and lower estimated blood loss (312 vs 363 mL’s; P = .003). Overlapping surgery patients were more likely to be discharged home (73.6% vs 66.2%; P < .0001), and had lower mortality rates (1.3% vs 2.5%; P = .0005) and acute respiratory failure (1.8% vs 2.6%; P = .021). In multivariate models, there was no significant difference between overlapping and nonoverlapping surgeries for any patient outcomes, except for procedure duration, which was longer in overlapping surgery (estimate = 23.03; P < .001).

CONCLUSIONS: When planned appropriately, overlapping surgery can be performed safely within the infrastructure at our academic institution.

Overlapping surgeries are also known as concurrent or simultaneous procedures. They occur when a single attending surgeon “runs 2 rooms” at the same time, so that cases in 2 separate operating rooms (ORs) have overlapping procedure times (Figure 1).1 The American College of Surgeons and the major neurosurgical societies further distinguish between overlapping procedures (in which the primary surgeon performs the critical portion of the procedure, but others assist with opening and closure) vs concurrent procedures (in which the critical portion of the procedure occurs simultaneously in 2 different operating rooms).2,3 In our neurosurgical department, many surgeons routinely perform overlapping surgeries assisted by cosurgeons, residents, and fellows, who are present throughout the duration of the case and perform noncritical portions of the procedures. Overlapping surgery is thought to improve efficiency, encourage surgical education for residents and fellows by promoting autonomy, allow for cases to be done with daytime staff (instead of late into the night with a less experienced team), and allow faster access to high-demand specialty surgeons.1

FIGURE 1.

Schematic representation of overlapping surgery, also known as “running 2 rooms.”

FIGURE 1.

Schematic representation of overlapping surgery, also known as “running 2 rooms.”

This practice has recently come under close scrutiny, after a case with a poor outcome at Massachusetts General Hospital (MGH).1,4 The patient had not been informed that his surgeon would be running 2 rooms, a practice that is now well disclosed to every patient before undergoing surgery at MGH.5 This case also prompted a senate inquiry into the safety of overlapping surgery,6 which despite being common in hospitals across the country, has not been rigorously studied.

Several opinion pieces argue that overlapping surgery is safe,7 but there are limited data on this topic. On its website, MGH reports on a small number of overlapping surgeries (n = 418),8 and an abstract from the annual meeting of the American Association of Thoracic Surgeons describes no difference in operative time or outcomes across 1378 thoracic surgery procedures at a single institution.9 In a recent study, our group performed the first analysis of overlapping vs nonoverlapping surgeries done by a single vascular neurosurgeon.10 Building on this prior work, the goal of the present study was to analyze the patient outcomes of overlapping vs nonoverlapping surgeries performed by multiple neurosurgeons at our institution.

METHODS

Study Design

We performed a retrospective review of all neurosurgical cases 2012 to 2015 at an urban academic hospital. Patient informed consent was not needed, as this retrospective review was performed for internal quality improvement purposes. Publication of these data was approved by our hospital's institutional review board (IRB) (#16-19200).

The study cohort was identified from the University of California, San Francisco (UCSF) clinical database by determining all procedures in the operating room performed by the neurosurgery service from June 2, 2012

to December 31, 2015. We excluded procedures done by an attending neurosurgeon who had performed <20 overlapping surgeries, leaving us with 7358 total consecutive cases performed by 9 different attendings. All patient/surgical data elements were derived by the primary data analyst (JL) from UCSF’s internal clinical application (Epic, which was introduced at UCSF in June 2012 [Epic, Verona, Wisconsin]); current procedural terminology (CPT)/diagnosis codes were derived from UCSF’s administrative billing application, and were linked to clinical elements by the patient medical record number. Output records from these queries were saved and analyzed using SAS (version 9.4, SAS Institute, Inc., Cary, North Carolina). To ensure data accuracy and integrity, we randomly selected a set of patients, and an independent clinician (distinct from the data analyst) performed manual chart review in Epic. Follow-up for each patient was that reported to UCSF at the time of database review in May 2016.

Variables

For each case, our data analyst obtained the following patient demographics/clinical indicators, procedure characteristics, and patient outcome variables from the electronic medical record:

Patient Demographics/Clinical Indicators

Age, gender, insurance (Medicare, Medicaid, commercial/private, and others including worker's compensation, prisoners, uninsured), American Society of Anesthesiology (ASA) score, severity of illness (SOI), risk of mortality (ROM), admission type (routine/elective, urgent, emergent), and source of transfer (Emergency Department, physician referral, transfer—acute hospital, transfer—outside emergency department, other). SOI and ROM are from the All Patient Refined Diagnosis Related Group licensed software (3M, St. Paul, Minnesota) and incorporate the principal diagnosis, principal procedure, secondary diagnoses, secondary procedures, age, sex, birth weight, discharge date, status of discharge, and days on mechanical ventilator for each patient. Note that 10% of cases (717 out of 7358) did not have ASA scores; 4% (n = 268) did not have SOI scores, as these are only calculated for inpatients.

Procedure Characteristics

Procedure type (defined by our institution's specific booking code, eg, “transsphenoidal for pituitary tumor,” “craniotomy for aneurysm clipping”), year, day of week, number of cosurgeons, presence of neurosurgery resident (yes vs no), presence of neurosurgery fellow (yes vs no), presence of another attending surgeon (yes vs no), and overlapping vs nonoverlapping surgery. Overlapping surgeries were defined as those with ≥1 minute of overlapping procedure times.

Patient Outcomes

Procedure time (in minutes, from incision to wound closure), in-room time (total in-room time for patient, in minutes), length of hospital stay (in days), estimated blood loss (EBL; in mL’s), discharge to home vs other location, 30-day mortality (as reported to UCSF), 30-day unplanned readmission, unplanned return to OR, acute respiratory failure (identified by discharge codes of ICD9-CM 518.81 or ICD10-CM J96.00 not present on admission), and severe sepsis (identified by discharge codes of ICD9-CM 998.92 or ICD10-CM R65.2 not present on admission). Note that all planned variables were collected for each patient in an automated fashion from the electronic medical record. Independent manual chart review was performed by a research assistant for each patient with a 30-day readmission in order to determine if the admission was planned vs unplanned. Similarly, manual chart review was performed for each patient who returned to the OR with the neurosurgery service within 30 days to determine if the OR return was planned or unplanned.

Statistical Methods

We aggregated the data and performed statistical analyses in SAS. Averages are expressed ±standard deviation. To compare individual variables between overlapping and nonoverlapping cases, we performed chi-squared or student t-tests. We then built multivariate models to adjust for the effect of patient demographics/clinical indicators and procedure characteristics on patient outcomes. More specifically, we created mixed-effect models with surgeon and procedure type as random effects in order to account for differences between procedure types and clustering by surgeon. The following variables were all selected as fixed effects: patient age, gender, insurance, admission source, SOI, presence of neurosurgery resident, presence of neurosurgery fellow, and presence of another attending surgeon. The main effect of interest was overlapping vs nonoverlapping surgery. We built separate mixed-effect models for each outcome: procedure time, length of stay (LOS), EBL, discharge location, 30-day mortality, 30-day readmission, return to OR, acute respiratory failure, and severe sepsis. For patients with any missing data, a dummy variable was included in the regression models to capture the potential effect on our study outcomes. For binary outcome variables (eg, 30-day mortality, 30-day readmission), we calculated odds ratios (OdR) with 95% confidence intervals; for continuous outcome variables, such as procedure time and LOS, we determined estimates with P-values.

RESULTS

Descriptive Data

A total of 7358 procedures were done by 9 attendings (6 cranial, 3 spinal neurosurgeons), who each performed ≥20 overlapping surgeries over this time period. There were 3725 cases (50.6%) performed in an overlapping fashion, while 3633 (49.4%) were nonoverlapping. The average age of patients who had overlapping surgery was less than those who had nonoverlapping surgery (53.7 ± 16.5 vs 55.6 ± 16.3; P < .0001; Table 1). Patients who underwent overlapping surgery were more likely to be female than those who underwent nonoverlapping surgery (55.4% vs 50.7%; P < .0001) and were more likely to have commercial/private insurance (43.4% vs 39.4%; P < .0001; Table 1). These patients were also less sick, with lower ASA scores, SOI, and ROM, as shown in Table 1 (all P < .0001). Overlapping surgery patients were more likely than nonoverlapping surgery patients to be routine/elective admissions (72.9% vs 62.3%; P < .0001) and physician referrals (74.8% vs 59.8%; P < .0001; Table 1).

TABLE 1.

Patient Demographics and Clinical indicators of Overlapping (n = 3725) vs Nonoverlapping (n = 3633) Neurosurgical Procedures, 2012 to 2015

 Overlapping cases (n = # cases, %) Nonoverlapping cases (n = # cases, %) P-value 
Patient demographics    
Age (mean ± SD) 53.7 (±16.5) 55.6 (±16.3) <.0001 
Gender   <.0001 
Female 2062 (55.4%) 1843 (50.7%)  
Male 1663 (44.6%) 1790 (49.3%)  
Insurance   <.0001 
Medicare 1219 (32.7%) 1381 (38.0%)  
Medicaid 720 (19.3%) 657 (18.1%)  
Commercial 1617 (43.4%) 1432 (39.4%)  
Others (worker's compensation, uninsured, prison, etc.) 169 (4.5%) 163 (4.5%)  
Clinical indicators    
ASA status   <.0001 
125 (3.4%) 131 (3.6%)  
1790 (48.1%) 1599 (42.9%)  
1294 (34.7%) 1387 (38.2%)  
125 (3.4%) 201 (5.5%)  
8 (0.2%) 21 (0.6%)  
Missing 383 (10.3%) 334 (9.2%)  
Severity of illness   <.0001 
Minor 1193 (33.1%) 1018 (28.0%)  
Moderate 1451 (39.0%) 1302 (35.8%)  
Major 687 (18.4%) 785 (21.6%)  
Extreme 272 (7.3%) 382 (10.5%)  
Risk of mortality   <.0001 
Minor 2388 (64.1%) 2070 (57.0%)  
Moderate 647 (17.4%) 741 (20.4%)  
Major 337 (9.1%) 363 (10.0%)  
Extreme 231 (6.2%) 313 (8.6%)  
Admission type   <.0001 
Routine/elective 2713 (72.9%) 2263 (62.3%)  
Emergent 331 (8.9%) 471 (13.0%)  
Urgent 680 (18.3%) 896 (24.7%)  
Source of transfer   <.0001 
Physician referral 2785 (74.8%) 2173 (59.8%)  
ED 229 (6.2%) 365 (10.1%)  
Transfer—acute hospital 284 (7.6%) 374 (10.3%)  
Transfer—other ED 313 (8.4%) 435 (12.0%)  
Other 114 (3.1%) 286 (7.9%)  
 Overlapping cases (n = # cases, %) Nonoverlapping cases (n = # cases, %) P-value 
Patient demographics    
Age (mean ± SD) 53.7 (±16.5) 55.6 (±16.3) <.0001 
Gender   <.0001 
Female 2062 (55.4%) 1843 (50.7%)  
Male 1663 (44.6%) 1790 (49.3%)  
Insurance   <.0001 
Medicare 1219 (32.7%) 1381 (38.0%)  
Medicaid 720 (19.3%) 657 (18.1%)  
Commercial 1617 (43.4%) 1432 (39.4%)  
Others (worker's compensation, uninsured, prison, etc.) 169 (4.5%) 163 (4.5%)  
Clinical indicators    
ASA status   <.0001 
125 (3.4%) 131 (3.6%)  
1790 (48.1%) 1599 (42.9%)  
1294 (34.7%) 1387 (38.2%)  
125 (3.4%) 201 (5.5%)  
8 (0.2%) 21 (0.6%)  
Missing 383 (10.3%) 334 (9.2%)  
Severity of illness   <.0001 
Minor 1193 (33.1%) 1018 (28.0%)  
Moderate 1451 (39.0%) 1302 (35.8%)  
Major 687 (18.4%) 785 (21.6%)  
Extreme 272 (7.3%) 382 (10.5%)  
Risk of mortality   <.0001 
Minor 2388 (64.1%) 2070 (57.0%)  
Moderate 647 (17.4%) 741 (20.4%)  
Major 337 (9.1%) 363 (10.0%)  
Extreme 231 (6.2%) 313 (8.6%)  
Admission type   <.0001 
Routine/elective 2713 (72.9%) 2263 (62.3%)  
Emergent 331 (8.9%) 471 (13.0%)  
Urgent 680 (18.3%) 896 (24.7%)  
Source of transfer   <.0001 
Physician referral 2785 (74.8%) 2173 (59.8%)  
ED 229 (6.2%) 365 (10.1%)  
Transfer—acute hospital 284 (7.6%) 374 (10.3%)  
Transfer—other ED 313 (8.4%) 435 (12.0%)  
Other 114 (3.1%) 286 (7.9%)  

SD: Standard Deviation, ED: Emergency Department. P-value Calculated from Chi-squared Test or t-test were Appropriate for All Categories Under the Particular Variable.

Table 2 shows that certain procedure types were more likely than others to be overlapping (eg, transsphenoidal for pituitary tumor; craniotomy for aneurysm clipping; suboccipital craniotomy for microvascular decompression), due to the preferences, case volume, and scheduled block time of the surgeons who perform these specific procedures at our institution. Overlapping surgeries were also more likely to be performed on Mondays and Fridays, once again due to neurosurgeons’ scheduled block time. While there was an increase in the number of overlapping surgeries from 2012 to 2013, the number of overlapping operations decreased slightly from 2014 to 2015 (1065 to 949; see Table 2). The number of cosurgeons (including residents, fellows, and other surgical attendings) was higher in overlapping, as compared to nonoverlapping, procedures (1.46 ± 0.86 vs 1.42 ± 0.90; P = .027). Overlapping cases were more likely to have a neurosurgery resident present (86.0% vs 79.9%; P < .0001) and less likely to have another attending surgeon present in the operating room (21.5% vs 25.4%; P < .0001; Table 2). Note that these other attending surgeons included cosurgeons from other departments, such as a vascular surgeon who exposes an anterior spine case, or an otolaryngologist who assists with the exposure in an endoscopic tumor case.

TABLE 2.

Procedure Characteristics of Overlapping (n = 3725) vs Nonoverlapping (n = 3633) Neurosurgical Procedures, 2012 to 2015

 Overlapping cases (n = # cases, %) Nonoverlapping cases (n = # cases, %) P-value 
Procedure type   <.0001 
Transsphenoidal for pituitary tumor 392 (25.6%) 296 (22.0%)  
Crani for aneurysm clipping 340 (22.2%) 170 (12.6%)  
Crani for resection of glioma 137 (9.0%) 115 (8.5%)  
Crani for tumor resection asleep 118 (7.7%) 132 (9.8%)  
Lumbar/lumbosacral posterior spine fusion, 1 to 3 segments 101 (6.6%) 143 (10.6%)  
Lumbar laminetomy 83 (5.4%) 159 (11.8%)  
Lumbar/lumbosacral posterior spine fusion, 4 to 6 segments 75 (4.9%) 113 (8.4%)  
Suboccipital craniotomy for microvascular decompression 163 (10.7%) 24 (1.8%)  
VP shunt insertion w/ GS assist 74 (4.9%) 84 (6.2%)  
Thoracic spine posterior fusion, 7 to 12 segments 45 (2.9%) 112 (8.3%)  
Year of procedure   <.0001 
2012 549 (14.7%) 502 (13.9%)  
2013 1162 (31.2%) 962 (26.5%)  
2014 1065 (28.6%) 1088 (30.0%)  
2015 949 (25.5%) 1080 (29.7%)  
Day of week of procedure   <.0001 
Monday 1071 (28.8%) 795 (21.9%)  
Tuesday 760 (20.4%) 960 (26.4%)  
Wednesday 839 (22.5%) 814 (22.4%)  
Thursday 23 (0.6%) 312 (8.6%)  
Friday 1029 (27.6%) 536 (14.8%)  
Saturday 3 (0.1%) 138 (3.8%)  
Sunday 0 (0.0%) 78 (2.2%)  
Number of cosurgeons (mean ± SD) 1.46 (±0.86) 1.42 (±0.90) .027 
Presence of neurosurgery fellow: yes/no 528 (14.2%) 3197 (85.8%) 504 (13.9%) 3129 (86.1%) .710 
Presence of neurosurgery resident: yes/no 3202 (86.0%) 523 (14.0%) 2904 (79.9) 729 (20.1%) <.0001 
Presence of another attending: yes/no 802 (21.5%) 2923 (78.5%) 921 (25.4%) 1712 (74.6%) <.0001 
 Overlapping cases (n = # cases, %) Nonoverlapping cases (n = # cases, %) P-value 
Procedure type   <.0001 
Transsphenoidal for pituitary tumor 392 (25.6%) 296 (22.0%)  
Crani for aneurysm clipping 340 (22.2%) 170 (12.6%)  
Crani for resection of glioma 137 (9.0%) 115 (8.5%)  
Crani for tumor resection asleep 118 (7.7%) 132 (9.8%)  
Lumbar/lumbosacral posterior spine fusion, 1 to 3 segments 101 (6.6%) 143 (10.6%)  
Lumbar laminetomy 83 (5.4%) 159 (11.8%)  
Lumbar/lumbosacral posterior spine fusion, 4 to 6 segments 75 (4.9%) 113 (8.4%)  
Suboccipital craniotomy for microvascular decompression 163 (10.7%) 24 (1.8%)  
VP shunt insertion w/ GS assist 74 (4.9%) 84 (6.2%)  
Thoracic spine posterior fusion, 7 to 12 segments 45 (2.9%) 112 (8.3%)  
Year of procedure   <.0001 
2012 549 (14.7%) 502 (13.9%)  
2013 1162 (31.2%) 962 (26.5%)  
2014 1065 (28.6%) 1088 (30.0%)  
2015 949 (25.5%) 1080 (29.7%)  
Day of week of procedure   <.0001 
Monday 1071 (28.8%) 795 (21.9%)  
Tuesday 760 (20.4%) 960 (26.4%)  
Wednesday 839 (22.5%) 814 (22.4%)  
Thursday 23 (0.6%) 312 (8.6%)  
Friday 1029 (27.6%) 536 (14.8%)  
Saturday 3 (0.1%) 138 (3.8%)  
Sunday 0 (0.0%) 78 (2.2%)  
Number of cosurgeons (mean ± SD) 1.46 (±0.86) 1.42 (±0.90) .027 
Presence of neurosurgery fellow: yes/no 528 (14.2%) 3197 (85.8%) 504 (13.9%) 3129 (86.1%) .710 
Presence of neurosurgery resident: yes/no 3202 (86.0%) 523 (14.0%) 2904 (79.9) 729 (20.1%) <.0001 
Presence of another attending: yes/no 802 (21.5%) 2923 (78.5%) 921 (25.4%) 1712 (74.6%) <.0001 

For Procedure Type, Only Top 10 Most Common Procedure Types (as Determined by the Booking Code) Across All Neurosurgical Cases are Shown. Crani: Craniotomy; VP: Ventriculoperitoneal; GS: General Surgery; SD: Standard Deviation. P-value Calculated from Chi-squared Test or t-test were Appropriate for All Categories Under the Particular Variable.

Outcome Data

In univariate analyses, overlapping surgeries had significantly longer procedure times (214 ± 127 vs 172 ± 119 min; P < .0001) and in-room times (296 ± 139 vs 249 ± 135; P < .001; Table 3 and Figure 2). However, the LOS was shorter (7.3 ± 10.7 vs 7.9 ± 10.3 days; P = .010) and EBL was lower (312 ± 636 vs 363 ± 744 mL’s; P = .003) in overlapping, as compared to nonoverlapping surgeries (Table 3 and Figure 2). Patients who underwent overlapping surgery were more likely to be discharged to home (73.6% vs 66.2%; P < .0001), and had lower rates of 30-day mortality (1.3% vs 2.5%; P = .0005) and acute respiratory failure (1.8% vs 2.6%; P = .021; Table 3 and Figure 2). Rates of unplanned 30-day readmission, unplanned return to OR, and severe sepsis were not statistically different between the 2 groups (Table 3 and Figure 2).

FIGURE 2.

Unadjusted patient outcomes of overlapping (blue) vs nonoverlapping (red) neurosurgical procedures at an urban academic hospital, 2012 to 2015: A, procedure time (minutes), B, in-room time (minutes), C, EBL (mL), D, LOS (days), E, rates of discharge to location other than home, 30-day mortality, 30-day unplanned readmission, unplanned return to OR, acute respiratory failure, and severe sepsis. P-value calculated from chi-squared test or t-test where appropriate: (*) P < .05; (**) P < .01; (***) P < .001.

FIGURE 2.

Unadjusted patient outcomes of overlapping (blue) vs nonoverlapping (red) neurosurgical procedures at an urban academic hospital, 2012 to 2015: A, procedure time (minutes), B, in-room time (minutes), C, EBL (mL), D, LOS (days), E, rates of discharge to location other than home, 30-day mortality, 30-day unplanned readmission, unplanned return to OR, acute respiratory failure, and severe sepsis. P-value calculated from chi-squared test or t-test where appropriate: (*) P < .05; (**) P < .01; (***) P < .001.

TABLE 3.

Unadjusted Outcomes of Overlapping (n = 3725) vs Nonoverlapping (n = 3633) Neurosurgical Procedures, 2012 to 2015

 Overlapping cases (n = # cases, %) Nonoverlapping cases (n = # cases, %) P-value 
Procedure time (minutes, mean ± SD) 214.2 (±126.5) 171.5 (±119.1) <.0001 
In-room time (minutes, mean ± SD) 295.6 (±138.9) 248.9 (±135.1) <.0001 
Length of stay (days, mean ± SD) 7.3 (±10.7) 7.9 (±10.3) .010 
Estimated blood loss (mL, mean ± SD) 311.8 (±636.2) 362.6 (±743.9) .003 
Discharge disposition   <.0001 
Home, self or home care 2741 (73.6%) 2405 (66.2%)  
Not home 984 (26.4%) 1228 (33.8%)  
30-day mortality   .0005 
Deceased 50 (1.3%) 89 (2.5%)  
Survived 3675 (98.7%) 3544 (97.6%)  
30-day unplanned readmission   .498 
Yes 263 (7.1%) 242 (6.7%)  
No 3462 (92.9%) 3391 (93.3%)  
Unplanned return to OR   .125 
Yes 80 (2.2%) 98 (2.7%)  
No 3645 (97.8%) 3312 (97.3%)  
Complication: acute respiratory failure   .021 
Yes 48 (1.8%) 95 (2.6%)  
No 3657 (98.2%) 3538 (97.4%)  
Complication: severe sepsis   .064 
Yes 21 (0.6%) 34 (0.9%)  
No 3704 (99.4%) 3599 (99.1%)  
 Overlapping cases (n = # cases, %) Nonoverlapping cases (n = # cases, %) P-value 
Procedure time (minutes, mean ± SD) 214.2 (±126.5) 171.5 (±119.1) <.0001 
In-room time (minutes, mean ± SD) 295.6 (±138.9) 248.9 (±135.1) <.0001 
Length of stay (days, mean ± SD) 7.3 (±10.7) 7.9 (±10.3) .010 
Estimated blood loss (mL, mean ± SD) 311.8 (±636.2) 362.6 (±743.9) .003 
Discharge disposition   <.0001 
Home, self or home care 2741 (73.6%) 2405 (66.2%)  
Not home 984 (26.4%) 1228 (33.8%)  
30-day mortality   .0005 
Deceased 50 (1.3%) 89 (2.5%)  
Survived 3675 (98.7%) 3544 (97.6%)  
30-day unplanned readmission   .498 
Yes 263 (7.1%) 242 (6.7%)  
No 3462 (92.9%) 3391 (93.3%)  
Unplanned return to OR   .125 
Yes 80 (2.2%) 98 (2.7%)  
No 3645 (97.8%) 3312 (97.3%)  
Complication: acute respiratory failure   .021 
Yes 48 (1.8%) 95 (2.6%)  
No 3657 (98.2%) 3538 (97.4%)  
Complication: severe sepsis   .064 
Yes 21 (0.6%) 34 (0.9%)  
No 3704 (99.4%) 3599 (99.1%)  

SD: Standard Deviation, LTAC: Long-term Acute Care Facility. P-value Calculated from Chi-squared Test or t-test were Appropriate for all Categories Under the Particular Variable.

After adjusting for surgeon, procedure type, patient demographics, clinical indicators, and procedure characteristics in multivariate models, there was no significant difference between overlapping and nonoverlapping surgeries for the following patient outcomes: unplanned return to OR, 30-day unplanned readmission, 30-day mortality, acute respiratory failure, severe sepsis, discharge location, EBL, or LOS (all P-values not significant; Tables 4 and 5; Figure 3). The only significant difference between the 2 groups was that overlapping surgeries had significantly longer procedure durations (estimate = 23.03; P < .001) even after adjusting for all these factors (Table 5).

FIGURE 3.

Adjusted patient outcomes of overlapping vs nonoverlapping neurosurgical procedures at an urban academic hospital, 2012 to 2015. OdRs (with 95% confidence interval) are results of multivariate model that adjusts for surgeon, procedure type, patient demographics, and clinical indicators.

FIGURE 3.

Adjusted patient outcomes of overlapping vs nonoverlapping neurosurgical procedures at an urban academic hospital, 2012 to 2015. OdRs (with 95% confidence interval) are results of multivariate model that adjusts for surgeon, procedure type, patient demographics, and clinical indicators.

TABLE 4.

Multivariate Model to Test the Effect of Overlapping vs Nonoverlapping cases (total n = 7358) on the Following Outcomes (after Adjusting for Patient/Clinical Factors, Surgeon, and Procedure Type): Unplanned Return to OR, 30-day Unplanned Readmission, 30-day Mortality, Acute Respiratory Failure, and Severe Sepsis

 Outcomes odds ratio (95% CI), P-value 
Fixed effects Unplanned return to OR 30-day unplanned readmission 30-day mortality Acute respiratory failure Severe sepsis 
Patient and clinical factors      
Age 0.99 (0.98-1.00), P = .128 1.00, P < .001 1.00 (0.99-1.01), P = .942 1.00 (0.99-1.02), P = .563 1.00 (0.98-1.02), P = .794 
Female (vs male) 0.76 (0.56-1.04), P = .087 1.00 (0.60-1.65), P = .992 0.51 (0.34-0.75), P < .001 0.85 (0.61-1.18), P = .327 0.78 (0.44-1.36), P = .376 
Medicare (vs commercial) 1.00 (0.65-1.53), P = .992 1.18 (0.73-1.89), P = .505 0.81 (0.49-1.35), P = .417 1.11 (0.71-1.75), P = .636 2.03 (0.92-4.50), P = .080 
Medicaid (vs commercial) 0.97 (0.64-1.46), P = .876 1.41 (1.05-1.89), P = .021 0.77 (0.46-1.27), P = .305 0.82 (0.51-1.33), P = .426 1.20 (0.53-2.74), P = .663 
Other insurance (vs commercial)  1.09 (0.53-2.27), P = .809  0.76 (0.40-1.43), P = .389  0.84 (0.33-2.16), P = .722  1.39 (0.65-2.94), P = .395  1.77 (0.48-6.57), P = .392 
Routine/elective (vs emergent/urgent) 0.49 (0.34-0.71), P < .001 0.88, P < .001 0.60 (0.37-0.96), P = .034 0.52 (0.35-0.77), P < .001 0.29 (0.15-0.60), P < .001 
ASA Score: ASA 2 vs 1 ASA 3 vs 1 ASA 4/5 vs 1 1.13 (0.32-4.03), P = .849 2.40 (0.67-8.58), P = .178 3.26 (0.84-12.6), P = .087  1.25 (0.97-1.62), P = .088 1.74, P < .001 1.64 (0.85-3.17), P = .141  0.35 (0.03-3.90), P = .390 3.91 (0.41-36.9), P = .230 26.3 (2.7-254.6), P < .001  4.04 (0.11-143.6), P = .443 13.7 (0.39-482.3), P = .149 52.5 (1.47-999), P = .030  1.43 (0.03-60.3), P = .852 3.76 (0.09-154.9), P = .485 14.1 (0.33-596.8), P = .167 
Presence of fellow (yes vs no) 1.15 (0.72-1.84), P = .553 1.13 (0.76-1.67), P = .557 1.16 (0.66-2.05), P = .610 1.92 (1.19-3.10), P = .008 1.82 (0.88-3.73), P = .104 
Presence of resident (yes vs no) 0.82 (0.53-1.27), P < .372 1.16, P < .001 2.34 (1.15-4.76), P = .020 1.57 (1.01-2.77), P = .046 1.60 (0.68-3.75), P = .282 
Presence of another attending (yes vs no) 1.19 (0.77-1.84), P = .436 1.33, P < .001 1.04 (0.57-1.90), P = .900 1.80 (1.15-2.81), P = .010 1.16 (0.55-2.44), P = .700 
Overlapping cases (vs nonoverlapping) 0.86 (0.62-1.19), P = .366 1.09 (0.82-1.46), P = .538 0.71 (0.48-1.06), P = .095 0.81 (0.57-1.15), P = .242 0.78 (0.44-1.38), P = .393 
 Outcomes odds ratio (95% CI), P-value 
Fixed effects Unplanned return to OR 30-day unplanned readmission 30-day mortality Acute respiratory failure Severe sepsis 
Patient and clinical factors      
Age 0.99 (0.98-1.00), P = .128 1.00, P < .001 1.00 (0.99-1.01), P = .942 1.00 (0.99-1.02), P = .563 1.00 (0.98-1.02), P = .794 
Female (vs male) 0.76 (0.56-1.04), P = .087 1.00 (0.60-1.65), P = .992 0.51 (0.34-0.75), P < .001 0.85 (0.61-1.18), P = .327 0.78 (0.44-1.36), P = .376 
Medicare (vs commercial) 1.00 (0.65-1.53), P = .992 1.18 (0.73-1.89), P = .505 0.81 (0.49-1.35), P = .417 1.11 (0.71-1.75), P = .636 2.03 (0.92-4.50), P = .080 
Medicaid (vs commercial) 0.97 (0.64-1.46), P = .876 1.41 (1.05-1.89), P = .021 0.77 (0.46-1.27), P = .305 0.82 (0.51-1.33), P = .426 1.20 (0.53-2.74), P = .663 
Other insurance (vs commercial)  1.09 (0.53-2.27), P = .809  0.76 (0.40-1.43), P = .389  0.84 (0.33-2.16), P = .722  1.39 (0.65-2.94), P = .395  1.77 (0.48-6.57), P = .392 
Routine/elective (vs emergent/urgent) 0.49 (0.34-0.71), P < .001 0.88, P < .001 0.60 (0.37-0.96), P = .034 0.52 (0.35-0.77), P < .001 0.29 (0.15-0.60), P < .001 
ASA Score: ASA 2 vs 1 ASA 3 vs 1 ASA 4/5 vs 1 1.13 (0.32-4.03), P = .849 2.40 (0.67-8.58), P = .178 3.26 (0.84-12.6), P = .087  1.25 (0.97-1.62), P = .088 1.74, P < .001 1.64 (0.85-3.17), P = .141  0.35 (0.03-3.90), P = .390 3.91 (0.41-36.9), P = .230 26.3 (2.7-254.6), P < .001  4.04 (0.11-143.6), P = .443 13.7 (0.39-482.3), P = .149 52.5 (1.47-999), P = .030  1.43 (0.03-60.3), P = .852 3.76 (0.09-154.9), P = .485 14.1 (0.33-596.8), P = .167 
Presence of fellow (yes vs no) 1.15 (0.72-1.84), P = .553 1.13 (0.76-1.67), P = .557 1.16 (0.66-2.05), P = .610 1.92 (1.19-3.10), P = .008 1.82 (0.88-3.73), P = .104 
Presence of resident (yes vs no) 0.82 (0.53-1.27), P < .372 1.16, P < .001 2.34 (1.15-4.76), P = .020 1.57 (1.01-2.77), P = .046 1.60 (0.68-3.75), P = .282 
Presence of another attending (yes vs no) 1.19 (0.77-1.84), P = .436 1.33, P < .001 1.04 (0.57-1.90), P = .900 1.80 (1.15-2.81), P = .010 1.16 (0.55-2.44), P = .700 
Overlapping cases (vs nonoverlapping) 0.86 (0.62-1.19), P = .366 1.09 (0.82-1.46), P = .538 0.71 (0.48-1.06), P = .095 0.81 (0.57-1.15), P = .242 0.78 (0.44-1.38), P = .393 

Surgeon and Procedure Type are not Included in the Table Because They are Random Effects in the Mixed-effects Model; Only Fixed Effects are Shown in the Table. Abbreviations: OR: Operating Room; CI: Confidence Interval; P = P-value.

TABLE 5.

Multivariate Model to Test the Effect of Overlapping vs Nonoverlapping Cases (Total n = 7358) on the following Outcomes (After Adjusting for Patient/Clinical Factors, Surgeon, and Procedure Type): Discharge (Home vs Not Home), Procedure Duration (in minutes), Estimated Blood Loss (in mL), and Length of Stay (in Days)

 Outcomes odds ratio (95% confidence interval) or estimate (SE), P-value 
Effect Discharge (home vs not) Estimated blood loss Length of stay Procedure duration 
Patient and clinical factors     
Age 0.97 (0.97-0.98), P < .001 0.22 (0.00), P < .001 −0.01 (0.01), P = .111 −0.24 (0.00), P < .001 
Female (vs male) 1.01 (0.89-1.14), P = .904 −49.17 (14.33), P < .001 −0.29 (0.22), P = .174 −7.52 (1.96), P < .001 
Medicare (vs commercial) Medicaid (vs commercial) Others (vs commercial) 0.63 (0.53-0.75), P < .001 0.60 (0.50-0.72), P < .001 0.64 (0.47-0.86), P = .004 34.08 (19.69), P = .0835 5.80 (20.29), P = .775 50.53 (35.14), P = .150 −0.11 (0.30), P = .714 2.58 (0.30), P < .001 0.17 (0.53), P = .744 −0.69 (2.68), P = .798 1.73 (2.75), P = .528 9.96 (4.81), P = .038 
Routine/elective (vs emergent/urgent) 4.38 (3.76-5.09) P < .001 −10.83 (18.36), P = .555 −6.29 (0.27), P < .001 11.75 2.53), P < .001 
ASA Score: 2 vs 1 3 vs 1 4/5 vs 1  0.55 (0.30-0.99), P = .047 0.27 (0.15-0.50), P < .001 0.05 (0.03-0.10), P < .001 1.96 (39.32), P = .960 29.58 (41.17), P = .472 160 (53.32), P = .0027  1.02 (0.60), P = .089 3.06 (0.63), P < .001 10.0 (0.81), P < .001  6.42 (5.41), P = .235 8.41 (5.67), P = .138 4.60 (7.33), P = .530 
Presence of fellow (yes vs no) 0.87 (0.70-1.07), P = .185 74.10 (24.60), P = .003 −0.69 (0.37), P = .065 15.76 (3.39), P < .001 
Presence of resident (yes vs no) 0.87 (0.72-1.04), P = .118 −8.22 (21.17), P = .698 −0.23 (0.32) P = .476 9.16 (2.89), P = .002 
Presence of another attending (yes vs no) 0.57 (0.47-0.68), P < .001 214.9 (22.58), P < .001 1.80 (0.33), P < .001 60.33 (3.20), P < .001 
Overlapping cases (vs nonoverlapping) 0.94 (0.82-1.08), P = .372 11.65 (15.08), P = .440 0.11 (0.23), P = .645 23.03 (2.07), P < .001 
 Outcomes odds ratio (95% confidence interval) or estimate (SE), P-value 
Effect Discharge (home vs not) Estimated blood loss Length of stay Procedure duration 
Patient and clinical factors     
Age 0.97 (0.97-0.98), P < .001 0.22 (0.00), P < .001 −0.01 (0.01), P = .111 −0.24 (0.00), P < .001 
Female (vs male) 1.01 (0.89-1.14), P = .904 −49.17 (14.33), P < .001 −0.29 (0.22), P = .174 −7.52 (1.96), P < .001 
Medicare (vs commercial) Medicaid (vs commercial) Others (vs commercial) 0.63 (0.53-0.75), P < .001 0.60 (0.50-0.72), P < .001 0.64 (0.47-0.86), P = .004 34.08 (19.69), P = .0835 5.80 (20.29), P = .775 50.53 (35.14), P = .150 −0.11 (0.30), P = .714 2.58 (0.30), P < .001 0.17 (0.53), P = .744 −0.69 (2.68), P = .798 1.73 (2.75), P = .528 9.96 (4.81), P = .038 
Routine/elective (vs emergent/urgent) 4.38 (3.76-5.09) P < .001 −10.83 (18.36), P = .555 −6.29 (0.27), P < .001 11.75 2.53), P < .001 
ASA Score: 2 vs 1 3 vs 1 4/5 vs 1  0.55 (0.30-0.99), P = .047 0.27 (0.15-0.50), P < .001 0.05 (0.03-0.10), P < .001 1.96 (39.32), P = .960 29.58 (41.17), P = .472 160 (53.32), P = .0027  1.02 (0.60), P = .089 3.06 (0.63), P < .001 10.0 (0.81), P < .001  6.42 (5.41), P = .235 8.41 (5.67), P = .138 4.60 (7.33), P = .530 
Presence of fellow (yes vs no) 0.87 (0.70-1.07), P = .185 74.10 (24.60), P = .003 −0.69 (0.37), P = .065 15.76 (3.39), P < .001 
Presence of resident (yes vs no) 0.87 (0.72-1.04), P = .118 −8.22 (21.17), P = .698 −0.23 (0.32) P = .476 9.16 (2.89), P = .002 
Presence of another attending (yes vs no) 0.57 (0.47-0.68), P < .001 214.9 (22.58), P < .001 1.80 (0.33), P < .001 60.33 (3.20), P < .001 
Overlapping cases (vs nonoverlapping) 0.94 (0.82-1.08), P = .372 11.65 (15.08), P = .440 0.11 (0.23), P = .645 23.03 (2.07), P < .001 

Surgeon and Procedure Type are not Included in the Table Because They are Random Effects in the Mixed-effects Model; Only Fixed Effects are Shown in the Table. Abbreviations: OR: Operating Room; CI: Confidence Interval; SE: Standard Error; P = P-value.

Of note, in the multivariate models, females had lower mortality (OdR = 0.51; P < .001). Routine/elective cases had lower rates of return to OR, 30-day readmission, 30-day mortality, acute respiratory failure, and severe sepsis as compared to urgent/emergent cases (all OdRs < 1; P < .05; Table 4), as well as shorter LOS, higher rates of discharge to home, and longer procedure durations (all P < .001; Table 5). Medicaid patients were more likely than those with commercial insurance to be readmitted within 30 days of discharge (OdR = 1.41, P = .021). Medicaid patients also had longer LOS and were less likely to discharge to home, as compared to those with commercial insurance (both P < .001; Table 5). In fact, patients with Medicaid, Medicare, or “other” insurance were all less likely to be discharged to home, as compared to those with commercial insurance (all OdR < 0.64; P < .01; Table 5). Higher ASA scores (ie, sicker patients) were associated with higher rates of 30-day mortality and acute respiratory failure (ASA 4/5 vs 1: OdR = 26.3 for 30-day mortality, P < .001; OdR = 52.5 for acute respiratory failure, P = .030; Table 4), as well as longer LOS, lower rates of discharge to home, and higher EBL (Table 5).

The presence of a resident in the OR was associated with a higher mortality rate, 30-day readmission, and acute respiratory failure (OdRs = 1.16, 2.34, and 1.57, respectively; all P < .05), as well as a longer procedure duration (estimate = 9.16; P = .002; Tables 4 and 5). Similarly, the presence of a fellow or another attending in the OR was both associated with longer procedure duration, higher EBL, and lower rates of discharge to home (Table 5). Older patients had higher EBL (estimate = 0.22; P < .001), shorter procedure duration (estimate = –0.24; P < .001), and were less likely to be discharged to home (OdR = 0.97; P < .001).

DISCUSSION

Key Results

Our analysis of 7358 cases showed significant differences in the types of overlapping vs nonoverlapping surgeries, across multiple procedure types and multiple neurosurgeons at our institution. More specifically, routine/elective cases for younger, less sick patients were more likely to be done in an overlapping fashion. This may be the result of case scheduling and purposeful selection of less difficult cases for overlapping surgery by the attending surgeon. This bias in case scheduling was also present in a prior analysis looking at only vascular neurosurgical procedures at our institution.10 Given this bias, we attempted to control for these cofounders in multivariate models. We did not detect a difference in basic patient outcomes (30-day mortality, 30-day unplanned readmission, unplanned return to OR, discharge status, LOS, or EBL) in overlapping vs nonoverlapping surgeries, after adjusting for surgeon, procedure type, patient demographics, and clinical indicators.

Interpretation

We therefore suggest that overlapping neurosurgery can be performed safely and efficiently by these 9 surgeons at our institution, consistent with smaller unpublished studies of concurrent thoracic surgeries at the University of Virginia9 and procedures at MGH.8 Overlapping surgery enables surgeons at our institution to provide more care to patients during daylight hours, and to avoid operating late at night with inexperienced surgical teams. It allows surgeons to deal efficiently with urgent or emergent cases (such as subdural hematomas or cauda equina cases that require immediate surgical treatment in order to prevent significant patient morbidity or mortality), although the number of such cases is relatively low at our level II trauma center. Another potential advantage of overlapping surgery is that it enables surgeons (attendings and residents) to gain more operative experience earlier in their careers, potentially making them better and safer surgeons, as patient outcomes have been shown to improve over the course of a surgeon's career.11 It also promotes resident and fellow autonomy and operative education, which is essential for training the next generation of competent surgeons.

While procedure time was significantly longer in overlapping neurosurgical cases at our institution, we did not detect an increase in acute respiratory failure from prolonged anesthetic time in our adjusted multivariate analyses. We also did not observe an increased rate of postoperative sepsis with longer procedure duration in the overlapping surgeries. However, we acknowledge that longer procedure and anesthetic times could lead to other complications not captured in this study. There are many variables that affect the length of a procedure, all of which might be impossible to accurately include in this analysis. Importantly, the presence of another attending in the OR was associated with longer procedure times. Since the other attendings were usually cosurgeons from other departments (eg, vascular surgeon for an anterior lumbar interbody fusion, otolaryngoloist for an acoustic neuroma), this finding likely reflects the fact that procedures that require attending cosurgeons from other specialties are usually more complex cases that take longer amounts of time. Similarly, the presence of a resident or fellow in the OR was also associated with longer procedure duration, which may indicate the increased difficulty and complexity of these cases.

Limitations

An important limitation is the single-site nature of our study. Although we examined data from multiple neurosurgeons in various subspecialties, our results may not apply to other surgeons or to institutions without residents/fellows or similar overlapping surgery policies. The 9 attending neurosurgeons who run 2 rooms at our institution are all mid- or senior-level attendings with many years of experience postresidency, high case volumes, and a large percentage of complex cases. The most common overlapping procedures at our institution were transsphenoidals for pituitary tumors, craniotomies for aneurysm clippings, and craniotomies for gliomas—a case mix that may not reflect the case mix of surgeons at community hospitals or even other academic centers. In addition, our analysis relies on the UCSF clinical database. As a result, if a patient was readmitted or required reoperation

at another hospital, or if the patient passed away, but this was not reported to UCSF, then these data were not captured in our study.

Guidelines

The surgeons who perform overlapping surgeries adhere to the following policies at our institution. When performing overlapping surgeries, attendings will often, but not always, operate in adjoining operating rooms so they can easily move back and forth between cases. Our perioperative infrastructure allows for staggered case starts, which are occasionally used. When running 2 rooms, attending surgeons will nearly always have a chief resident or fellow/clinical instructor attending assistant. There is no hospital-wide definition of the “critical period,” as there is tremendous variability between our cases, but each attending surgeon defines the critical period for each procedure (eg, clipping of aneurysm, tumor resection), and is present in the OR for this portion of the case. It is made clear to resident trainees (with signed acknowledgment forms) that when they reach the start of the critical portion of the procedure, they must call the attending surgeon to let them know. When performing overlapping surgeries, attending surgeons must also identify a back-up attending surgeon when running 2 rooms with resident assistants; the back-up surgeon should be available on campus throughout the operation to assist if needed. Attending surgeons are limited to running 2 rooms at once, and cannot have a third or fourth operating room during this time. They must stay at the main hospital, and are not allowed to operate at distant sites.

In addition, while not mandated by our hospital, surgeons tend to select lower risk patients for overlapping surgeries, as highlighted above. Finally, our hospital's recently updated overlapping surgery policy specifically delineates that overlapping surgery may occur so that there is explicit patient disclosure in the surgical consent form, as advocated in a recent JAMA Surgery opinion piece.12

CONCLUSION

To the best of our knowledge, our study represents the largest analysis of the safety of overlapping operations in the surgical literature. Across 7358 procedures performed by 9 attending surgeons in various neurosurgical subspecialties, there was a statistically significant difference in the types of cases performed in an overlapping fashion, with more routine/elective cases for younger, less sick patients done as overlapping procedures. After controlling for these cofounders in multivariate models, procedure duration was significantly longer in the overlapping cases, but we did not detect a significant difference in the following patient outcomes: 30-day mortality, 30-day readmission, return to OR, discharge status, LOS, or EBL. This suggests that overlapping neurosurgery may be performed safely by these 9 specific surgeons at our institution, adhering to the policies outlined above. It is an important practice for increasing efficiency and promoting surgical education of residents and fellows, but we caution that our findings may not be generalizable to other institutions without trainees or an appropriate infrastructure to support overlapping surgeries.

Disclosures

Dr Zygourakis has received travel grants from Nuvasive and Globus to attend resident education courses. She is supported by a research fellowship from the UCSF Center for Healthcare Value. Ms. Keefe is a consultant for DePuy Synthes Spine. Dr Mummaneni has received a grant and honoraria from AO Spine; is a consultant for DePuy Spine; receives royalties from Springer Publishing, Thieme Publishing, and Francis Publishers; and owns stock in Spinicity/ISD. Dr Lawton has received speaker consultant fees from Zeiss and DePuy and a consulting fee from Stryker. The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article.

1
Harbaugh RE. Neurosurgery's founding principles. J Neurosurg. 2015;123:1351-1357.

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COMMENTS

This study represents the single-center outcomes for concurrent vs nonconcurrent surgeries. The authors retrospectively reviewed surgical records for 9 surgeons totaling over 7000 neurosurgical procedures, representing the largest series on concurrent neurosurgical procedures. Undoubtedly prompting this study is concern by the public and healthcare payers after reports of a bad outcome occurred during a concurrent surgery in Boston. While this practice is commonplace, it has never been analyzed in the neurosurgery literature and will now serve as a quality and value metric. The authors demonstrate with a robust data set and appropriate statistical analysis that concurrent surgery is safe and effective in appropriately selected patients. The authors should be commended for their work on this important socioeconomic issue.

The cohorts were evenly split between concurrent and nonconcurrent procedures by a surgeon who “routinely” performs concurrent surgery at the authors’ institution. The surgeons in this cohort appear to be able to self-regulate with regards to appropriate patient selection for concurrent surgery—as patients undergoing concurrent surgery were significantly younger and less ill. Several quality measures were studied including operative time, LOS, EBL, 30-day mortality, 30-day readmission, return to OR, respiratory failure, and sepsis. While concurrent surgeries had longer procedure times (likely due to involvement of a trainee in significant portions of the procedure), they also demonstrated lower mortality rates, return to OR, and acute respiratory failure (likely surrogate markers for patient acuity and complexity of procedure). A crucial component of surgeons able to perform concurrent surgery is resident and fellow support to perform more routine (parts of) procedures in appropriately indicated cases. Although not examined, we would presume that resident involvement fell into 1 of 2 categories—performing routine/less complex procedures nearly in their entirely, or performing routine exposures for more complex procedures (ie, craniotomy for aneurysm, microvascular decompression (MVD), spinal decompression, and fusion).

“Running 2 rooms” will now be scrutinized and we agree with the authors’ conclusions that this study should be repeated on a larger scale involving multiple centers. While this report proves that “it can be done,” it does not reach any level of external validity. Understanding the key factors leading to the success or failure of concurrent surgery (such as required infrastructure, staggered starts, case mix, patient demographics) will be important for patients, neurosurgeons, hospitals, and healthcare payers.

Stephen Reintjes

Tampa, Florida

Zachary Naren Litvack

Seattle, Washington

The authors present a retrospective review of 7358 neurosurgical procedures performed at an academic hospital comparing surgical outcomes in patients who had overlapping surgery to those who did not. Overlapping surgeries had longer procedure times, a shorter length of hospital stay, were more likely to be discharged home and had lower mortality rates and fewer episodes of acute respiratory failure. In multivariate models that took into account differences in the patient populations, there were no significant differences between overlapping and nonoverlapping surgeries for any patient outcome, except procedure duration, which was longer in the overlapping surgery group. The authors conclude that, when planned appropriately, overlapping surgery can be performed safely at their academic institution. They have done an excellent analysis at a single institution, and it will be important to document if this pattern exists for other academic neurosurgery programs. I suspect that it does.

This is certainly a timely study. We have heard a good deal of negative press recently about concurrent surgery. Concurrent surgery is quite different from overlapping surgery. The position statement of organized neurosurgery on this issue states that overlapping operations—in which key or critical elements of one operation are complete, and a second operation is started while a qualified practitioner performs noncritical components of the first operation such as wound closure—are acceptable. Concurrent operations—during which the same primary surgeon is responsible for critical or key components of 2 or more procedures at the same time—are not. We must really strive to make this distinction clear to our patients and to the public at large.

As I noted in my American Association of Neurological Surgeons (AANS) Presidential address,1 being a neurosurgeon is a very odd way to make a living. We sit down with people we have never met and 30 min later they have agreed to let us perform operations that may leave them disabled or dead. This is a remarkable expression of trust and it only works if our patients are certain that we are doing what we believe is best for them. This trust is the fundamental basis of the patient–physician relationship, and if we lose it we will not be able to get it back. We also have obligations to future patients, to our specialty and to our society that include training those who will follow us and managing resources as efficiently as possible. To meet these obligations neurosurgeons may schedule 2 operations that overlap and delegate portions of an operation to a resident or fellow. We must do this in a way that is safe for our patients and does not violate their trust. Safety requires that we only allow our residents or fellows to perform the parts of our procedures commensurate with their skills, and trust requires an honest informed consent process that lets patients know of the roles that trainees will play in their care.

Robert E. Harbaugh

Hershey, Pennsylvania

The authors describe a retrospective cohort study of 7358 neurosurgical procedures comparing outcomes following overlapping and nonoverlapping surgeries at their institution. In this series, overlapping surgery was more likely to be performed for routine, elective cases on younger, healthier patients. After adjusting for other variables, overlapping surgery was associated with longer anesthesia times but otherwise no difference in outcomes. The authors conclude that overlapping surgeries can be performed safely in appropriately selected patients at their institution.

This is a timely contribution to a pressing national discussion about the role of overlapping surgeries. Overlapping surgeries, in which the attending surgeon is present for the critical portion of the procedure but may leave the initial setup and noncritical portions of the wound opening or closure to a qualified assistant, have historically been an important part of surgeon training and operating room efficiency. Recent media reports have highlighted several cases of negative outcomes following overlapping surgery. These reports raised important questions about whether overlapping surgery puts patients at higher risk of negative outcomes, what portion of a procedure should be considered the critical portion, and how much patients know about the involvement of assistants and trainees in their surgery when giving consent.

The authors have demonstrated that overlapping surgeries can be performed safely by a group of surgeons at their institution for certain types of surgeries in select patients. Further studies will be needed to see if their findings are generalizable to other institutions, surgeries, and patient populations. There will no doubt be more efforts to better define the critical portion of procedures. Our institution has modified its informed surgical consent forms to document that patients have given their permission if overlapping surgery is to occur. However, it should be recognized that there will always be some variability in each planned surgery, level of training of assistants, and expectations of patients. Individual surgeons will need to be responsible for determining what portions of a procedure can be safely performed by an assistant. Finally, open conversations are essential to ensure a transparent consent process that reinforces the trust that patients place in their surgeons.

Brett E. Youngerman

Jeffrey N. Bruce

New York

The authors present a timely study on staggered/overlapping surgeries given the recent lay press focus that emanated from a Boston Academic Medical Center. Even when only supervising a single operating room, it is not uncommon for the attending surgeon to not be present for certain tasks during some operations based on a host of factors. These tasks may include patient positioning, surgical site preparation, draping, skin incision, routine surgical approach dissection, routine wound closure, dressing application, and drain insertion. The complexity of the case, age, health, and risk factors of the patient should also go into the determination of acceptable cases for staggered surgery. During these nonroutine tasks and during the room cleaning and turnover time, the surgeon may be nearby attending to consults, inpatients, medical record charting, dictating, emails, or other tasks provided adequately trained surrogates are present (residents, fellows, and/or surgical assistants). This study supports the experience of many surgeons that running a staggered second room, with the right type of patients and surgical cases, can allow the surgeon to be helping other patients surgically during those routine tasks and operating room turnover time in the first room. When planned correctly, scheduling staggered cases should not change which portions of the surgery the surgeon is present for, but rather make their down time between cases more productive.

Scott Boden

Atlanta, Georgia