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The Impact of Anesthesia-Influenced Process Measure Compliance on Length of Stay: Results From an Enhanced Recovery After Surgery for Colorectal Surgery Cohort

Grant, Michael C. MD*; Pio Roda, Claro M. DrPH*; Canner, Joseph K. MHS*; Sommer, Philip MD*; Galante, Daniel DO*; Hobson, Deborah BSN*; Gearhart, Susan MD*; Wu, Christopher L. MD*; Wick, Elizabeth MD

doi: 10.1213/ANE.0000000000003458
Perioperative Medicine: Original Clinical Research Report
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BACKGROUND: Process measure compliance has been associated with improved outcomes in enhanced recovery after surgery (ERAS) programs. Herein, we sought to assess the impact of compliance with measures directly influenced by anesthesiology in an ERAS for colorectal surgery cohort.

METHODS: From January 2013 to April 2015, data from 1140 consecutive patients were collected for all patients before (pre-ERAS) and after (ERAS) implementation of an ERAS program. Compliance with 9 specific process measures directly influenced by the anesthesiologist or acute pain service was analyzed to determine the impact on hospital length of stay (LOS).

RESULTS: Process measure compliance was associated with a stepwise reduction in LOS. Patients who received >4 process measures (high compliance) had a significantly shorter LOS (incident rate ratio [IRR], 0.77; 95% CI, 0.70–0.85); P < .001) compared to low compliance (0–2 process measures) counterparts. Multivariable regression suggests that utilization of multimodal nausea and vomiting prophylaxis (IRR, 0.78; 95% CI, 0.68–0.89; P < .001), scheduled postoperative nonsteroidal pain medication use (IRR, 0.76; 95% CI, 0.67–0.85; P < .001), and strict adherence to a postoperative opioid administration (IRR, 0.58; 95% CI, 0.51–0.67; P < .001) protocol for breakthrough pain were independently associated with reduced LOS.

CONCLUSIONS: Our findings suggest that increased compliance with process measures directly influenced by the anesthesiologists and in concert with a formal anesthesia protocol is associated with reduced LOS. Engaging anesthesiology colleagues throughout the surgical encounter increases the overall value of perioperative care.

From the *Johns Hopkins Medical Institutions, Baltimore, Maryland

University of California, San Francisco, San Francisco, California.

Published ahead of print 12 April 2018.

Accepted for publication April 12, 2018.

Funding: None.

The authors declare no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website.

Reprints will not be available from the authors.

Address correspondence to Michael C. Grant, MD, Department of Anesthesiology, The Johns Hopkins Medical Institutions, Zayed 6208-P, 1800 Orleans St, Baltimore, MD 21287. Address e-mail to mgrant17@jhmi.edu.

Enhanced recovery after surgery (ERAS) programs are designed to optimize perioperative care through engagement of the patient, mitigation of the physiological stressors associated with surgery, reduction in preventable postoperative harm, and improvement in the rates of postoperative recovery.1 The overwhelming success of these protocols has led to national and international enhanced recovery societies along with associated guidelines for perioperative management.2 These efforts have been largely forged by surgeons, who recognize the stepwise incremental benefits of various interventions throughout the preoperative, intraoperative, and postoperative phases of care. Institutional enhanced recovery teams have evolved to include leadership from surgery, anesthesia, nursing, nutrition, and other ancillary staff.3,4 As a result, service lines are increasingly utilizing a transdisciplinary approach to perioperative patient care that implements best practices in a bundled fashion to leverage local expertise and maximize value in the patient care experience.

Recently, providers have directed their attention to the relationship between process measure compliance and its impact on the success of ERAS programs. This can be challenging to do given that many pathways include upwards of 30 different process measures that may be coordinated by a number of different disciplines. Several recent publications have been devoted to the topic, with the conclusion that increased compliance with not only individual choice elements but bundled process measures as a whole is associated with reduced length of stay (LOS) and reduced postoperative morbidity.5–8 These trials have pointed to the benefits of several measures traditionally influenced directly by anesthesiologists, including titration of intraoperative fluids, perioperative analgesia, and even maintenance anesthetics. In response, programs are beginning to incorporate a concerted anesthesia protocol and acute pain service (APS) management into ERAS frameworks.9,10 Given the growing interest in exploring the impact of individual process measures on various patient care outcomes, our group reviewed our experience involving an established ERAS for colorectal surgery program. In doing so, we sought to evaluate the use of a concerted anesthesia protocol to identify the key measures that are influenced primarily by the anesthesiologists and acute pain providers on overall index hospitalization LOS.

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METHODS

Study Overview

This study was approved by the appropriate institutional review board and the requirement for written informed consent was waived by the institutional review board. From the period of January 2013 to April 2015, data were prospectively collected and analyzed for patients undergoing colorectal surgery at Johns Hopkins Hospital, a 1059-bed tertiary care academic medical center. Patients enrolled after February 2014 were uniformly placed on the ERAS for colorectal surgery pathway (ERAS), whereas patients enrolled before that date received traditional perioperative care (pre-ERAS) as dictated by individual surgical teams. Patients included were adults (≥18 years of age) scheduled for colorectal surgery under general anesthesia in 1 of 2 operating room suites. Surgeries were performed by 1 of 5 primary board-certified colorectal surgeons and included the following: protectomy, rectopexy, ileocecectomy, laparotomy, sigmoidectomy, low anterior resection, Hartmann’s procedure, abdominal perineal resection, colostomy, colectomy, ileostomy, and bowel resection. Patients were excluded from this study if their procedures were deemed urgent or emergent (nonscheduled), outpatient in nature, occurred >1 day after hospital admission, or there was a direct contraindication for any process measure intervention.

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Colorectal ERAS Pathway

Specific process measures included within the Johns Hopkins Hospital ERAS pathway for colorectal surgery have been developed from both international guidelines and institutional experience. Published previously, the pathway consists of approximately 30 patient care process measures used throughout the perioperative period.4 In addition, the pathway included a concerted perioperative anesthesia practice protocol, outlined in Supplemental Digital Content 1, Document, http://links.lww.com/AA/C401. The program was designed to: (1) attenuate the stress response associated with surgery, (2) hasten postoperative recovery, (3) mitigate preventable perioperative harms, and (4) engage patients and family members in their own care. As part of the protocol implementation, it was decided that a dedicated team of anesthesia providers would be assigned to the ERAS colorectal cases in the operating room and all patients would be followed by the institutional APS after surgery. This represented a paradigm shift in both the intraoperative and postoperative role of anesthesiology in the care of colorectal surgery patients. Before the pathway implementation, anesthesia providers were assigned on a daily basis in an ad hoc fashion based on the overall scope of activity in the operating rooms and APS was typically involved postoperatively only in patients who exhibited high tolerance to opioids or received catheter-based regional analgesia techniques.

Patients enrolled as part of the colorectal ERAS initiative were initially intended to receive all pathway measures. Individual process measure compliance rates, along with relevant patient-specific variables such as age, sex, race, American Society of Anesthesiology (ASA) physical status, surgeon, procedure, and surgical exposure (laproscopic versus open) were collected and analyzed.

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Outcome Variables

The primary outcome of interest was postoperative index hospitalization LOS (number of nights in the hospital from the date of surgery until date of discharge). To investigate the potential association between compliance with process measures directly influenced by anesthesiologists and outcomes of interest, data were collected and analyzed on the following process measures divided here into their perioperative time course categories.

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Preoperative

  • 1. Consumption of a carbohydrate drink at least 2 hours before surgery and liberalization of the institutional nil per os policy regarding preoperative clear liquid ingestion.
  • 2. Administration of all medications in the preoperative multimodal pain medication bundle (includes gabapentin, acetaminophen, and celecoxib).
  • 3. Placement of a preincisional thoracic epidural or perioperative transversus abdominus plane block.
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Intraoperative

  • 4. Administration of an intravenous fluid warmer, forced air body warmer, and maintenance of normothermia throughout the surgical procedure (>36°C).
  • 5. Use of total intravenous anesthesia (no intraoperative inhaled agent) with propofol as the primary maintenance anesthetic.
  • 6. Adherence to multimodal postoperative nausea and vomiting (PONV) prevention (utilization of both a preoperative scopolamine patch and administration of intraoperative ondansetron).
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Postoperative

  • 7. Adherence to conservative fluid administration strategy (defined as <4 L of fluid in the initial 24-hour period including the intraoperative phase of the procedure).
  • 8. Administration of either a scheduled intravenous or oral nonsteroidal anti-inflammatory drug (NSAID) in the postoperative period for at least 48 hours.
  • 9. Adherence to a postoperative opioid administration protocol (provision of opioids only for breakthrough pain when nonopioid alternatives are insufficient).

Our group defined conservative fluid administration as 4 L in 24 hours as this represented the median value (~4100 mL) for the entire cohort. These 9 process measures were chosen due to 4 primary reasons: (1) their compliance designation (“yes” or “no”) is binary in nature, promoting higher fidelity in data capture; (2) administration could be readily traced using the available electronic data systems at our disposal; (3) they were primarily influenced by the anesthesiologist or acute pain specialist; and (4) all of these process measures were uniformly instituted as part of the anesthesia protocol at the time of ERAS for colorectal surgery pathway implementation. For example, our group specifically did not study preexisting anesthesia process measures such as subcutaneous heparin administration or antibiotic prophylaxis as these efforts had been formally initiated through alternative initiatives before the ERAS pathway. Process measures such as patient and family education, compliance with mechanical bowel preparation with oral antibiotics, chlorhexidine bathing before surgery, early mobility, and resumption of oral intake after surgery were excluded from this analysis because these were not under the direct influence of the anesthesia provider or APS. Supplemental Digital Content 2, Document, http://links.lww.com/AA/C402, provides a list of these relevant surgical process measures.

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Compliance Stratification

Compliance with anesthesia process measures was first analyzed among the entirety of the cohort irrespective of pre-ERAS or ERAS designation. In addition, patients were further categorized into low (0–2 anesthesia process measures administered), moderate (3–4 measures), and high (>4 measures) compliance groups to determine if increased compliance was associated with primary end points of interest. Ultimately, data were stratified based on period of enrollment (pre-ERAS versus ERAS) to determine the overall effects of ERAS implementation on rates of compliance, which included unrecorded or unidentified elements of the ERAS program (surgical process measures, institutional or systems-level factors, patient engagement, and education and others) on primary end points of interest.

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Data Collection

Data were derived by querying existing institutional information systems including Metavision (electronic intraoperative anesthesia data record), Sunrise Eclipsys Provider Order Entry (electronic medical record and electronic medication administration record), and Keane (hospital billing and registration) systems. A surgical complexity score was derived from this lattermost system based on the estimated complexity of the surgical procedure with respect to coded procedure type and baseline diagnosis. Scores ranged from 1 to 4 with higher numbers associated with increased surgical complexity. The hospital is also an active participant in the National Surgical Quality Improvement Program (NSQIP),11 and individual data were extracted from this database where appropriate.

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Statistical Analysis

All relevant data from the included systems for each patient were combined into a single patient database. Data were processed and analyzed with the software programs Excel v. 14.0 (Microsoft Inc, Redmond, WA) and Stata v. 14.2 (StataCorp, College Station, TX) statistical packages. Comparisons were made between means using the unpaired Students t test. Categorical variables were assessed by the χ2 or Fisher exact test where appropriate. Univariable and multivariable regression was conducted for each of the outcome variables of interest while adjusting for age, sex, race, ASA physical status, surgical exposure (laparoscopic versus open), and surgical procedure complexity. Regression models were assessed for collinearity by calculating a variance inflation factor for each covariable to determine if individual variables significantly impacted one another (ie, the use of epidurals may be highly associated with increased fluid administration). Truncated negative binomial regression was selected to analyze index hospitalization LOS with the model truncated at zero, which assumes all LOS values are at least 1 day. P < .05 was considered statistically significant. Statistical analysis was performed with the assistance of an in-house departmental statistician.

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RESULTS

Study Population and Overall LOS

Table 1.

Table 1.

In total, 1163 patients were evaluated and following the exclusion of 23 patients (2.0%), 1140 patients were included in our study. These patients were divided between the pre-ERAS (n = 512) and ERAS (n = 628) cohorts. Baseline demographic data were similar between groups (Table 1). This included similarity with respect to ASA status, coded surgical complexity score, and laparoscopic approach. Implementation of the ERAS program for colorectal surgery led to a significant reduction in average index hospitalization LOS compared to pre-ERAS (6.6 ± 7.8 vs 7.3 ± 6.6 days; P = .05). ERAS was also associated with a significant reduction in LOS based on univariable (incidence rate ratio [IRR], 0.89; 95% CI, 0.80–0.98; P = .03) and multivariable (IRR, 0.88; 95% CI, 0.80–0.97; P = .01) truncated negative binomial regression compared to pre-ERAS patients. Based on these analyses, enrollment in ERAS was associated with an approximate reduction of 11%–12% in LOS.

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Compliance Rates and Index Hospitalization LOS

Overall anesthesia process measure compliance rates are provided in Table 2. Of note, pre-ERAS patients almost never received a preoperative carbohydrate drink (0.0%) or formal multimodal PONV prophylaxis (0.6%). The majority of the included anesthesia process measures had a statistically significant increase in compliance rates between pre-ERAS and ERAS patients with the exception of provision of a fluid warmer and body warmer, which remained stable. Patients in the ERAS group received an average of 4.6 ± 1.3 anesthesia process measures compared to 1.9 ± 0.9 for the pre-ERAS group (P < .001), which corresponds to an overall average of 3.0 ± 1.8 for the entire cohort. Compliance rates with designated surgical process measures, where available, are provided in Supplemental Digital Content 3, Document, http://links.lww.com/AA/C403.

Table 2.

Table 2.

Individual patients were assessed for their composite compliance with anesthesia-influenced measures, represented by the sum total process measures they received during their perioperative encounter. The association between the number of process measures successfully administered—irrespective of ERAS status—and subsequent index hospitalization LOS is shown in Figure 1. Of note, there is a stepwise negative correlation between an increased rate of composite process measure compliance and overall average LOS across all patients regardless of ERAS enrollment status. All patients—irrespective of ERAS status—were stratified into 3 separate compliance groups (low = 0–2 anesthesia process measures; moderate = 3–4; high = >4). Graphic depiction of average LOS as a function of compliance group shows that patients in the high compliance group experienced a statistically significant shorter LOS compared to low (4.9 vs 8.3 days; P < .01) or moderate (4.9 vs 6.9 days; P < .04) groups, respectively (Figure 2).

Figure 1.

Figure 1.

Figure 2.

Figure 2.

Figure 3.

Figure 3.

A significantly higher percentage of pre-ERAS patients were noted to be in the low compliance group and a significantly higher percentage of ERAS patients were noted to be in the high compliance group (P < .01). When analyzing compliance groups based on enrollment in the ERAS program (pre-ERAS versus ERAS), there is a statistically significant decrease in LOS for ERAS patients compared to pre-ERAS within each compliance group (low: 7.6 vs 10.6; P < .001; medium: 6.9 vs 8.3; P < .008; high: 3.5 vs 5.0; P < .01), respectively (Figure 3).

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Regression Analysis and Index Hospitalization LOS

Univariable analysis was performed to determine the association between individual process measures influenced by the anesthesiologist and index hospitalization LOS. Results of this analysis are summarized in Table 3. Of note, compliance with each individual process measure was associated with a shortened LOS, except for utilization of a forced air and fluid-warming device. Further investigation using multivariable analysis suggested that the individual process measures most strongly associated with shorter LOS were multimodal PONV prophylaxis (IRR, 0.78; 95% CI, 0.68–0.89; P < .001), postoperative scheduled NSAID use (IRR, 0.76; 95% CI, 0.67–0.85; P < .001), and adherence to the postoperative opioid administration (IRR, 0.68; 95% CI, 0.56–0.79; P < .001) protocol. Evaluation of collinearity did not demonstrate a significant relationship between individual covariables included in the regression analysis (variance inflation factor <2 for all instances).

Table 3.

Table 3.

A multivariable regression model was further developed to assess the effect of process measure compliance in the context of other major patient-related covariates by first determining the association between baseline demographics and overall index hospitalization LOS. Based on univariable analysis, male (IRR, 1.13; 95% CI, 1.03–1.25; P = .01), non-Caucasian (IRR, 1.13; 95% CI, 1.01–1.26; P = .03), and higher ASA physical status (IRR, 1.45; 95% CI, 1.30–1.61; P < .001) covariates were associated with a longer LOS. ERAS status (IRR, 0.88; 95% CI, 0.80–0.97; P = .01), laparoscopic approach (IRR, 0.76; 95% CI, 0.68–0.84; P < .001), moderate compliance (IRR, 0.84; 95% CI, 0.75–0.95; P = .004), and high compliance (IRR, 0.60; 95% CI, 0.54–0.68; P < .001) were associated with a shorter LOS. Of note, the length of surgery (minutes of documented procedure time) was not shown to impact LOS. Multivariable regression analysis that included covariates of age, sex, race, ASA physical status, surgical procedure complexity score, and compliance category revealed that the only variable with a statistically significant association with shorter LOS was high compliance with process measures directly influenced by the anesthesiologist (IRR, 0.77; 95% CI, 0.70–0.85; P < .001).

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DISCUSSION

While ERAS programs are designed to optimize surgical recovery and shorten LOS, their ultimate goal is to improve the overall value of perioperative care. In an era where institutions are evaluating the importance of a transdisciplinary approach, individual provider groups are charged with showing their added value to the perioperative landscape. Prior study has suggested a strong association between certain ERAS process measures and improved postoperative outcomes.5–8 While consideration was provided to certain traditional anesthesia-related process measures, only limited discussion has centered on the potential benefits of a concerted anesthesia protocol—developed collaboratively with surgery and nursing—in ERAS for colorectal surgery. The data presented in this study suggest that increased compliance with a formal anesthesia protocol is associated with a stepwise reduction in index hospitalization LOS. Furthermore, the results of a multivariable model that incorporated patient comorbidities and surgical complexity suggest that high compliance with process measures influenced by the anesthesiologist and acute pain provider was shown to be strongly associated with a shorter hospital LOS.

The results of this study highlight a controversy regarding how to formally evaluate ERAS programs. To date, auditing of ERAS has been largely performed in a manner similar to intention-to-treat analysis, such that only the treatment assignment (pre-ERAS versus ERAS) is relevant. Based on these before-and-after analyses, ERAS programs have been deemed successful. Herein, we have also evaluated the additive or incremental benefit associated with increased compliance with individual process measures that are directly influenced by the anesthesiologist in concert with a formal anesthesia protocol. According to our results, there is a stepwise relationship between overall compliance rates and subsequent LOS.

While we have introduced and analyzed the 9 chosen measures as independent events, it is worth noting that several of these process measures overlap in indication and may serve to impact one another. For example, application of a preoperative oral multimodal pain regimen and preincisional epidural or transversus abdominus plane block may influence the ability to limit patients’ opioid requirements in the postoperative period.12,13 The utilization of total intravenous anesthesia for anesthetic maintenance has been previously shown to impact incidence of PONV.14 The 3 process measures independently associated with a reduction in LOS were multimodal PONV prophylaxis, postoperative NSAID use, and protocolized administration of postoperative opioids. Though well recognized for its importance in ambulatory procedures, aggressive PONV prophylaxis is still not overly emphasized in the same day or extended stay surgery.14 In this cohort, prevention of PONV could have influenced the ability to provide earlier enteral feeding, reduce maintenance fluid, and hasten advancement in the surgical pathway. Similarly, multimodal postoperative pain control that ultimately limits the reliance on opioids has been shown to improve disposition after major surgery.11,15 Optimal pain control, which may promote early ambulation, and reduced opioid administration, which may limit harmful opioid side effects such as ileus, nausea, or respiratory depression, may unpin the noted association with reduced LOS. In this manner, successful compliance with process measures influenced by the anesthesiologist may also improve compliance with other measures more traditionally associated with surgical management.

Importantly, our study examined the impact of compliance across both the pre-ERAS and ERAS phases. However, we also assess how ERAS implementation itself influenced process measure compliance. As shown, compliance with ERAS measures improved with program implementation. In addition, this analysis provided an opportunity to examine the impact of unmeasured variables (ie, surgeon, nursing or administrator-derived process measures, cultural shifts, systems-level changes) at the time of ERAS implementation. Our results show a significant decrease in LOS in ERAS within each compliance group compared to pre-ERAS figures. This effect likely represents the benefits of surgical, nursing, and ancillary service interventions, as well as institutional systems-level changes, patient engagement and education, and other unrecorded factors. This reasserts the importance of coupling a concerted anesthesia protocol and engaging anesthesiology colleagues with other system interventions—not en lieu of other group-specific input—to extract the greatest benefit to the patient. Our results underline the importance of adherence to a formal evidence-based best practice protocol for provision of anesthesia in ERAS for colorectal surgery as we were unable to systematically capture interventions attributed to all other provider groups. Therefore, our analysis prevents us from being able to adequately evaluate anesthesia-influenced process measures in the context of those influenced by surgeons, nurses, or other ancillary providers.

The implication of the results of this study is that specific process measures lead directly in causal fashion to improved outcomes. While this may be the case, it may also be that increased compliance serves as a marker for anticipated success. Patients who are successful recipients of the majority of care elements might represent those who “remain on pathway” and do not have specific contraindications to certain process measures and ought to be optimistically graduated along their intended postoperative course. Or perhaps the corollary is just as vital: noncompliance can provide a kind of early warning sign that a patient is at risk for a protracted hospital course or future complication. This may inform further investigation into patient- or disease-specific etiology for noncompliance. Either consideration provides potentially vital insight into the care of individual patients.

Interpretation of our study is limited by several important considerations. These results are based on our experience at a single large academic hospital. As such, the available resources, varied anesthesia provider experience, and infrastructure in place may drive success with certain process measures. However, it is likely that the overarching principles are transferrable (use of a concerted protocol, PONV prevention, postoperative NSAID use, and directed opioid administration). In addition, although increased compliance with these 9 chosen process measures is associated with a reduction in LOS, we cannot exclude the impact of other associated changes at the time of program implementation. These include other process measures under the primary influence of surgical counterparts, administrative and nursing culture shifts, resource allocation, and disposition planning not adequately captured in our analysis. The decision to examine anesthesia-influenced interventions in isolation is designed to evaluate the potential incremental benefit of the anesthesiologist and acute pain specialist within the complicated perioperative environment. However, the decision to do so potentially undermines the perceived impact of other providers’ roles and interventions in ERAS for colorectal surgery. Therefore, our results should be interpreted with caution.

Our results suggest that increased compliance with process measures under the direct influence of anesthesiologists is strongly associated with a stepwise reduction in index hospitalization LOS for colorectal surgery. Development of a concerted anesthesia protocol for ERAS is an important aspect of improving compliance with evidence-based best practice bundles. Although further prospective study is required to determine causal links between individual process measures and subsequent surgical outcome, our data suggest that in a time of increasing institutional and national scrutiny that adherence to a formal anesthesia ERAS protocol adds value to the patient care experience.

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DISCLOSURES

Name: Michael C. Grant, MD.

Contribution: This author helped design the study, conduct the study, and write the manuscript.

Name: Claro M. Pio Roda, DrPH.

Contribution: This author helped conduct the study and write the manuscript.

Name: Joseph K. Canner, MHS.

Contribution: This author helped analyze the data and write the manuscript.

Name: Philip Sommer, MD.

Contribution: This author helped conduct the study and write the manuscript.

Name: Daniel Galante, DO.

Contribution: This author helped conduct the study and draft the manuscript.

Name: Deborah Hobson, BSN.

Contribution: This author helped design the study and conduct the study.

Name: Susan Gearhart, MD.

Contribution: This author helped conduct the study and write the manuscript.

Name: Christopher L. Wu, MD.

Contribution: This author helped conduct the study and write the manuscript.

Name: Elizabeth Wick, MD.

Contribution: This author helped design the study, conduct the study, and write the manuscript.

This manuscript was handled by: Tong J. Gan, MD.

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REFERENCES

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