Does Procedural Timing Impact Perioperative Morbidity in Elective Surgery?
Conditions: Perioperative Complication
Sponsor: TriHealth Inc.

16-0491 
 
Smith 
 
Date: 
  5-9-19 
Title 
Does procedural timing impact perioperative morbidity in elective surgery?   
Principal 
Investigator: 
 Rachel Pauls MD 
Sub-
Investigators: 
--- 
Research 
Specialist 
Vivian Ghodsi , Eunsun Yook 
TriHealth 
Department 
Affiliation: 
Urogynecology Division of Ob/Gyn 
Hatton #: 
16-049 
 
IRB Review Type: 
 
☐ Exempt 
 
☒Expedited  
☐ Full Board 
 
Purpose of Study: Please describe: 
   
To evaluate if there are differences in perioperative morbidity for elective surgery based on the 
time of the year surgery is performed.  
  
Hypothesis or Research Question  
 
We hypothesize that surgical complication rates are higher at certain times during the year than 
others.  Specifically; 
Primary hypothesis:  Perioperative morbidity will be highest toward the end of the calendar 
year (December) corresponding with insurance deductible year-end. 
   
Secondary hypothesis:  Perioperative morbidity will be high as well with the start of academic 
trainees (July).   
 
Background 
 
Surgical complications are a significant cause of morbidity and mortality. Surgical complications 
account for up to 40% of hospital complications [1]. Complications and adverse events are also 
becoming increasingly important for measuring health care quality. Investigation into possible 
risk factors for complications is a popular topic for research. Studies are often designed to 
evaluate either patient related factors or surgeon related factors that may lead to an increase 
in adverse events. Common outcomes reported include surgical time, length of hospital stay, 
infections, injury to surrounding organs, surgeon volume, readmission, and mortality. However, 

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risk factors and outcome measures will vary depending on the patient population and 
procedures being studied.  
 
Commonly studied patient related factors that may impact perioperative morbidity include age, 
body mass index (BMI), American Society of Anesthesiologists classification (ASA), and medical 
comorbidities such as diabetes, heart disease, and pulmonary disease. Visser and colleagues 
performed a systematic review that analyzed 30 articles [2]. They found 9 significant patient 
related factors that contribute to surgical outcomes. Age, BMI, and ASA classification were the 
most commonly reported and most significant factors. Increased rates of surgical site infection 
have been described in patients with recent hospitalization prior to surgery [3, 4]. Borenstein 
and colleagues found that prior admission within 30 days was associated with an increased risk 
of adverse outcomes such as hospital acquired infections, adverse drug reactions and length of 
stay [5].  However, few studies have assessed prior admissions beyond 30 days. 
 
Patients who meet their insurance deductibles are likely more eager to proceed with an 
elective procedure, as they will little or no out of pocket cost. Many physician practices notice a 
surge of patients seeking care at the end of the year compared to other times of the year. 
Patients who have met their deductible likely utilize more healthcare resources because they 
have more health problems, or have had more procedures performed during that year. Thus 
there may be potential for sicker and more complicated patients to undergo surgery at the end 
of the year as compared to other times of the year. These patients may suffer more surgical 
complications that could then lead to an overall greater cost for healthcare. If so, this difference 
could impact future health care policy and rationing of resources. 
 
Surgeon related factors that contribute to perioperative morbidity have also become 
increasingly important and some authors have evaluated these possible factors. Surgeon 
related factors that have been studied include surgeon volume, surgeon workload per day, 
procedure timing, and trainee participation. One study found that low-volume surgeons have a 
higher risk of complications than high-volume surgeons [6]. Hsu and colleagues found that 
patients receiving an implantable cardioverter-defibrillator implant in the afternoon/evening 
and on weekends or holidays had higher rates of adverse events [7]. The total number of hours 
a surgeon operates per day was found to be independently associated with an increased risk of 
complications when performing pulmonary lobectomies [8]. Trainee participation has been 
associated with major complications in vaginal hysterectomy and with minor complications in 
all routes of hysterectomy [9].  
 
Prior studies have often evaluated the “July effect” which is the beginning of a new academic 
year at teaching hospitals. This time of the year is important, as it is when trainees are moving 
up in their roles involving patient care and taking on more responsibility. Not only are new 
interns involved in patient care but trainees at all levels are in participating in a new role. 
Recently graduated senior residents are now in attending surgeon positions. Findings have 

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been conflicting on whether there are differences in outcomes and complications at this time of 
the year. Englesbe and colleagues found an 18% higher postoperative morbidity rate and 41% 
high mortality rate in July-August compared to April-June [10]. Likewise, another study found 
higher morbidity and mortality in July for patients after surgery for spinal metastases [11]. 
However, Highstead, et al. found no difference in complications in July-August compared to 
April-May for over 3,000 patients admitted to a level 1 trauma service [12].  
 
Identifying which patients are at a higher risk for perioperative morbidity is important to help 
prevent surgical complications and lower healthcare costs. Proper patient selection and 
appropriate timing for elective procedures will positively impact these adverse outcomes.  
 
 
Research Plan 
● Study Design  
o Retrospective cohort study using Electronic Privacy Identification Center (EPIC) database 
 
● Setting for the study 
o Good Samaritan and Bethesda North Hospitals 
 
● Participants  
o Describe  
▪ 
All patients 18 years and older who underwent a surgical procedure in the main 
operating rooms  at Good Samaritan Hospital and Bethesda North Hospital between 
January 1, 2015 and December 31, 2016. 
▪ 
Approximately 9,000 cases are performed annually at the Good Samaritan Hospital 
main OR and 15,000 cases are performed annually at the Bethesda North main OR. 
 
o Inclusion criteria 
▪ 
All persons aged 18 and older undergoing surgical procedures in the main operating 
room during the study period 
 
o Exclusion criteria 
▪ 
Patients under the age of 18 
▪ 
Procedures done outside of the main operating suites (Endoscopy suite, Labor and 
Delivery) 
 
o Sample Size  
▪ 
About 48,000 chart review is expected. 
 
● Data Collection 
o Basic demographics and surgical procedure data will be collected. 

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o Date of surgery, surgery location, and surgeon name will be collected.  
o Trainee participation will be recorded – resident or fellow participation in case. 
o Patient comorbidities will be collected including but not limited to obesity, tobacco use, 
ASA classification, DM, HTN, heart disease, pulmonary disease, chronic kidney disease, 
prior surgical history in past 6 months, preoperative lab data. 
o Intraoperative surgical complications and hospital length of stay will be collected. 
o Insurance information will be collected 
o Postoperative complications including but not limited to reoperation, readmission 
within 90 days of surgery for any reason, death within 90 days will be collected. 
Complications inherent to most surgical procedures including excessive blood loss, need 
for blood transfusion, infection, thromboembolic events, and injury to surrounding 
organs will be collected.  
 
● Intervention or experimental aspect of the study 
o Not applicable as it is a retrospective chart review 
 
● Statistical Analysis 
o Descriptive statistics will be calculated for demographics, preoperative, and 
intraoperative information. Chi-squared tests will be employed for categorical variables 
and t test or Mann-Whitney U test for continuous variables. Mean (SD) values will be 
used for data meeting the assumptions for normality; median (IQR) values will be used 
for data not meeting the assumptions for parametric procedures. Multivariate logistic 
regression model will be implemented for a prediction model. 
 
 
Ethical Considerations 
● Informed consent  
o Since this is a retrospective study, waivers of Informed Consent and Authorization will  
be requested. 
● Privacy information 
o Patient surgery date and procedure will be collected during this study. 
 
 
Estimated Period of time to complete study:  
● When will study begin? Following IRB approval  
● What is the estimated duration of the study? 
o Pre data collection: July-August 2016 
o Data collection: through the end of August 2017 
o Data analysis: through December 2017 
● When and how will results be disseminated?   

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● The results from this study will be presented at one of the scientific meetings for the Society 
of Gynecologic Surgeons or the American Urogynecology Society or another national 
American Medical Society.  
 
● References 
 
1. Vries, E., et al. (2008). “The incidence and nature of in-hospital adverse events: A 
systematic review.” Quality and Safety in Healthcare 17; 216-223 
2. Visser, A., et al. (2015). “Predictors of surgical complications: A systematic review.” 
Surgery 158; 58-65 
3. Iniu T., et al. (2015). “Vasular surgical site infection: risk factors and preventive 
measures.” Seminars in Vascular Surgery 28: 201-207 
4. Sanford D., et al. (2015). “The impact of recent hospitalization on surgical site infection 
after pacreatectomy.” International Hepato-Pancreato-Biliary Association 17; 819-823 
5. Borenstein J., et al. (2013). Early recognition of risk factors for adverse outcomes during 
hospitalization among Medicare patients: a prospective cohort study.” Biomed Central 
Geriatrics. 13:72 
6. Worley M., et al. (2012). “Impact of surgeon volume on patient safety in laparoscopic 
gynecologic surgery.” Gynecologic Oncology. 125; 241-244 
7. Hsu, J., et al. (2015). “Procedure timing as a predictor of inhospital adverse outcomes 
from implantable cardioverter-defibrillator implantation: Insights from the National 
Cardiovascular Data Registry.” American Heart Journal 169; 45-53 
8. Thomas, M., et al. (2012). “Does surgeon workload per day affect outcomes after 
pulmonary lobectomies?” Annals of Thoracic Surgery 94; 966-973 
9. Barber E., et al. (2016). “Trainee participation and perioperative complications in benign 
hysterectomy: the effect of route of surgery.” American Journal of Obstetrics and 
Gynecology Epub 
10. Englesbe, M., et al. (2007). “Seasonal variation in surgical outcomes as measured by the 
American College of Surgeons-National Surgical Quality Improvement Program (ACS-
NSQIP).” Annals of Surgery 246; 456-465 
11. Desenbrock, H., et al. (2012). “The Impact of July hospital admission on outcome after 
surgery for spinal metasteses at academic medical centers in the United States, 2005 to 
2008.” Cancer 1429-1438. 
12. Highstead, M., et al. (2009). “July – As good as time as any to be injured.” Journal of 
Trauma 67: 1087-1090.