Underuse and Variability in Substance Use Screening Among Adult Trauma Patients in the U.S.: A Nationwide Retrospective Cohort Study.

OBJECTIVE: To characterize the rates and variability in substance screening among adult trauma patients in the U.S. SUMMARY BACKGROUND DATA: Emergency Department trauma visits provide a unique opportunity to identify patients with substance use disorders. Despite the existence of screening guidelines, underscreening and variability in screening practices remain. METHODS: Retrospective cohort study including adult trauma patients (18- 64-year-old) from the ACS-TQIP 2017-18 database. Multivariable logistic regressions were performed to adjust for demographics, clinical, and facility factors, and marginal probabilities were calculated using these multivariable models. The primary outcomes were substance screening and positivity, which were defined relative to the observation-weighted grand mean (mean). RESULTS: 2,048,176 patients were contained in the TQIP dataset, 809,878 (39.5%) were screened for alcohol (20.8% positive), and 617,129 (30.1%) were screened for drugs (37.3% positive). After all exclusion criteria were applied, 765,897 patients were included in the analysis, 394,391 (52.9%) were screened for alcohol (22.1% tested positive), and 279,531 (36.5%) were screened for drugs (44.3% tested positive). Among the patients included in our study, significant variability in screening rates existed with respect to demo-graphic, trauma mechanism, injury severity, and facility factors. Furthermore, in several cases, patient subpopulations who were less likely to be screened were in fact more likely to screen positive or vice versa. CONCLUSIONS: Effective substance-screening guidelines should be predicated on achieving universal screening. Current lapses in screening, along with the observed variability, likely affect different patient populations in disparate manners and lead to both under-detection as well as waste of valuable resources.

Validation of the Al-based Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) Calculator in Patients 65 Years and Older.

OBJECTIVE: We sought to assess the performance of the Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) tool in elderly emergency surgery (ES) patients. SUMMARY BACKGROUND DATA: The POTTER tool was derived using a novel Artificial Intelligence (AI)-methodology called optimal classification trees and validated for prediction of ES outcomes. POTTER outperforms all existent risk-prediction models and is available as an interactive smartphone application. Predicting outcomes in elderly patients has been historically challenging and POTTER has not yet been tested in this population. METHODS: All patients ≥65 years who underwent ES in the ACS-NSQIP 2017 database were included. POTTER's performance for 30-day mortality and 18 postoperative complications (eg, respiratory or renal failure) was assessed using c-statistic methodology, with planned sub-analyses for patients 65 to 74, 75 to 84, and 85+ years. RESULTS: A total of 29,366 patients were included, with mean age 77, 55.8% females, and 62% who underwent emergency general surgery. POTTER predicted mortality accurately in all patients over 65 (c-statistic 0.80). Its best performance was in patients 65 to 74 years (c-statistic 0.84), and its worst in patients ≥85 years (c-statistic 0.71). POTTER had the best discrimination for predicting septic shock (c-statistic 0.90), respiratory failure requiring mechanical ventilation for ≥48 hours (c-statistic 0.86), and acute renal failure (c-statistic 0.85). CONCLUSIONS: POTTER is a novel, interpretable, and highly accurate predictor of in-hospital mortality in elderly ES patients up to age 85 years. POTTER could prove useful for bedside counseling and for benchmarking of ES care.

Enhanced Recovery After Surgery Patients Are Prescribed Fewer Opioids at Discharge: A Propensity-score Matched Analysis.

OBJECTIVE: We aimed to compare discharge opioid prescriptions pre- and post-ERAS implementation. SUMMARY OF BACKGROUND DATA: ERAS programs decrease inpatient opioid use, but their relationship with postdischarge opioids remains unclear. METHODS: All patients undergoing hysterectomy between October 2016 and November 2020 and pancreatectomy or hepatectomy between April 2017 and November 2020 at 1 tertiary care center were included. For each procedure, ERAS was implemented during the study period. PSM was performed to compare pre - versus post-ERAS patients on discharge opioids (number of pills and oral morphine equivalents). Patients were matched on age, sex, race, payor, American Society of Anesthesiologists score, prior opioid use, and procedure. Sensitivity analyses in open versus minimally invasive surgery cohorts were performed. RESULTS: A total of 3983 patients were included (1929 pre-ERAS; 2054 post-ERAS). Post-ERAS patients were younger (56.0 vs 58.4 years; P < 0.001), more often female (95.8% vs 78.1%; P < 0.001), less often white (77.2% vs 82.0%; P < 0.001), less often had prior opioid use (20.1% vs 28.1%; P < 0.001), and more often underwent hysterectomy (91.1% vs 55.7%; P < 0.001). After PSM, there were no significant differences between cohorts in baseline characteristics. Matched post-ERAS patients were prescribed fewer opioid pills (17.4 pills vs 22.0 pills; P < 0.001) and lower oral morphine equivalents (129.4 mg vs 167.6 mg; P < 0.001) than pre-ERAS patients. Sensitivity analyses confirmed these findings [open (18.8 pills vs 25.4 pills; P < 0.001 \ 138.9 mg vs 198.7 mg; P < 0.001); minimally invasive surgery (17.2 pills vs 21.1 pills; P < 0.001 \ 127.1 mg vs 160.1 mg; P < 0.001). CONCLUSIONS: Post-ERAS patients were prescribed significantly fewer opioids at discharge compared to matched pre-ERAS patients.

Increasing Frequency of Interpreting Services is Associated With Shorter Peri-operative Length of Stay.

BACKGROUND: Patients with limited English proficiency have barriers to accessing care. Rather than a binary use or no use, this study uses granular data on frequency of interpreting services to determine if this frequency is associated with differences in peri-operative length of stay for patients with limited English proficiency. MATERIALS AND METHODS: This is a cross sectional study on length of stay for peri-operative admissions of at least one night during 2018, for patients who used medical interpreting services in an academic medical center in Boston, Massachusetts. The participants are split into quartiles of ascending number of interpreting events per day. The exposure for the primary outcome is the frequency of interpreting events per day during peri-operative admission. The primary study outcome measurement is peri-operative length of stay in days. RESULTS: There was a statistically significant decrease in length of stay for patients in the highest two quartiles of interpreting service frequency, compared to the lowest quartile: quartile 2 trended shorter by 1.4 d (95% CI -4.5 to 1.7, P = 0.37), quartile 3 was 4.2 d shorter (95% CI -7.6 to -0.7, P = 0.02), and quartile 4 was 4.6 d shorter (95% CI -8.1 to -1.1, P = 0.01). CONCLUSIONS: More frequent interpreting services per day during peri-operative admission are associated with shorter length of stay in adjusted analysis. The findings merit further study in an intervention to increase use of interpreting services for surgical patients with limited English proficiency to study the impact of increased frequency of culturally competent care.

Lower Mortality with Cryoprecipitate During Massive Transfusion in Penetrating but Not Blunt Trauma.

BACKGROUND: Balanced blood product transfusion improves the outcomes of trauma patients with exsanguinating hemorrhage, but it remains unclear whether administering cryoprecipitate improves mortality. We aimed to examine the impact of early cryoprecipitate transfusion on the outcomes of the trauma patients needing massive transfusion (MT). METHODS: All MT patients 18 years or older in the 2017 Trauma Quality Improvement Program (TQIP) were retrospectively reviewed. MT was defined as the transfusion of ≥10 units of blood within 24 hours. Propensity score analysis (PSA) was used to 1:1 match then compare patients who received and those who did not receive cryoprecipitate in the first 4 hours after injury. Outcomes included in-hospital mortality, 1-day mortality, in-hospital complications and transfusion needs at 24 hours. RESULTS: Of 1,004,440 trauma patients, 1,454 MT patients received cryoprecipitate and 2,920 did not. After PSA, 877 patients receiving cryoprecipitate were matched to 877 patients who did not. In-hospital mortality was lower among patients who received cryoprecipitate (49.4% v. 54.9%, P = 0.022), as was 1-day mortality. Sub-analyses showed that mortality was lower with cryoprecipitate in patients with penetrating (37.5% versus. 48%, adjusted P = 0.008), but not blunt trauma (58.5% versus. 59.8%, adjusted P = 1.000). In penetrating trauma, the cryoprecipitate group also had lower 1-day mortality (21.8% versus. 38.6%, P <0.001) and a higher rate of hemorrhage control surgeries performed within 24 hours (71.4% versus. 63.3%, P = 0.018). CONCLUSIONS: Cryoprecipitate in MT is associated with improved survival in penetrating, but not blunt, trauma. Randomized trials are needed to better define the role of cryoprecipitate in MT.

Preperitoneal Pelvic Packing is Associated With Increased Risk of Venous Thromboembolism.

INTRODUCTION: Preperitoneal pelvic packing (PPP) is an important intervention for control of severe pelvic hemorrhage in blunt trauma patients. We hypothesized that PPP is associated with an increased incidence of deep vein thrombosis (DVT) and pulmonary embolism (PE). METHODS: A retrospective cohort analysis of blunt trauma patients with severe pelvic fractures (AIS ≥4) using the 2015-2017 American College of Surgeons-Trauma Quality Improvement Program database was performed. Patients who underwent PPP within four hours of admission were matched to patients who did not using propensity score matching. Matching was performed based on demographics, comorbidities, injury- and resuscitation-related parameters, vital signs at presentation, and initiation and type of prophylactic anticoagulation. The rates of DVT and PE were compared between the matched groups. RESULTS: Out of 5129 patients with severe pelvic fractures, 157 (3.1%) underwent PPP within four h of presentation and were matched with 157 who did not. No significant differences were detected between the two matched groups in any of the examined baseline variables. Similarly, mortality and end-organ failure rates were not different. However, PPP patients were significantly more likely to develop DVT (12.7% versus 5.1%, P = 0.028) and PE (5.7% versus 0.0%, P = 0.003). CONCLUSIONS: PPP in severe pelvic fractures secondary to blunt trauma is associated with an increased risk of DVT and PE. A high index of suspicion and a low threshold for screening for these conditions should be maintained in patients who undergo PPP.

Hospital Academic Status and the Volume-Outcome Association in Postoperative Patients Requiring Intensive Care: Results of a Nationwide Analysis of Intensive Care Units in the United States.

Objective: To determine whether the outcomes of postoperative patients admitted directly to an intensive care unit (ICU) differ based on the academic status of the institution and the total operative volume of the unit. Methods: This was a retrospective analysis using the eICU Collaborative Research Database v2.0, a national database from participating ICUs in the United States. All patients admitted directly to the ICU from the operating room were included. Transfer patients and patients readmitted to the ICU were excluded. Patients were stratified based on admission to an ICU in an academic medical center (AMC) versus non-AMC, and to ICUs with different operative volume experience, after stratification in quartiles (high, medium-high, medium-low, and low volume). Primary outcomes were ICU and hospital mortality. Secondary outcomes included the need for continuous renal replacement therapy (CRRT) during ICU stay, ICU length of stay (LOS), and 30-day ventilator free days. Results: Our analysis included 22,180 unique patients; the majority of which (15,085[68%]) were admitted to ICUs in non-AMCs. Cardiac and vascular procedures were the most common types of procedures performed. Patients admitted to AMCs were more likely to be younger and less likely to be Hispanic or Asian. Multivariable logistic regression indicated no meaningful association between academic status and ICU mortality, hospital mortality, initiation of CRRT, duration of ICU LOS, or 30-day ventilator-free-days. Contrarily, medium-high operative volume units had higher ICU mortality (OR = 1.45, 95%CI = 1.10-1.91, p-value = 0.040), higher hospital mortality (OR = 1.33, 95%CI = 1.07-1.66, p-value = 0.033), longer ICU LOS (Coefficient = 0.23, 95%CI = 0.07-0.39, p-value = 0.038), and fewer 30-day ventilator-free-days (Coefficient = -0.30, 95%CI = -0.48 - -0.13, p-value = 0.015) compared to their high operative volume counterparts. Conclusions: This study found that a volume-outcome association in the management of postoperative patients requiring ICU level of care immediately after a surgical procedure may exist. The academic status of the institution did not affect the outcomes of these patients.

Artificial Intelligence, Machine Learning, and Surgical Science: Reality Versus Hype.

Artificial intelligence (AI) has made increasing inroads in clinical medicine. In surgery, machine learning-based algorithms are being studied for use as decision aids in risk prediction and even for intraoperative applications, including image recognition and video analysis. While AI has great promise in surgery, these algorithms come with a series of potential pitfalls that cannot be ignored as hospital systems and surgeons consider implementing these technologies. The aim of this review is to discuss the progress, promise, and pitfalls of AI in surgery.

Non-English Primary Language is Associated with Emergency Surgery for Diverticulitis.

BACKGROUND: Language barriers can limit access to care for patients with a non-English primary language (NEPL). The objective of this study was to define the association between primary language and emergency versus elective surgery among diverticulitis patients. MATERIALS AND METHODS: Retrospective cohort study of adult patients from the 2009-2014 New Jersey State Inpatient Database. Patients were included if they had primary language data and underwent a partial colon resection for diverticulitis. Primary language was dichotomized into NEPL versus English primary language (EPL). The primary outcome was surgical admission type - urgent/emergent (referred to as "emergency") versus elective. Descriptive and multivariable analyses were performed. RESULTS: A total of 9,453 patients underwent surgery for diverticulitis, of which 592 (6.3%) had NEPL. Among NEPL patients, 300 (51%) had Spanish as primary language and 292 (49%) had another non-Spanish primary language. Patients with NEPL and EPL were similar in age (median age 58 versus 59 years; P = 0.54) and sex (52% versus 53% female; P = 0.45). Patients with NEPL were less likely to have commercial insurance (45% versus 59%; P <0.001). On multivariable analysis, compared to patients with EPL, NEPL was associated with increased odds of emergency surgery for diverticulitis (OR 1.35; 95% Confidence Interval 1.13-1.62; P = 0.001) CONCLUSION: Patients with NEPL have higher odds of emergency versus elective surgery for diverticulitis compared to patients with EPL. Further research is needed to examine differences in referral pathways, patient-provider communication, and health literacy that may hinder access to elective surgery in patients with diverticulitis.

Rhabdomyolysis in Severe COVID-19: Male Sex, High Body Mass Index, and Prone Positioning Confer High Risk.

BACKGROUND: Bedside experience and studies of critically ill patients with coronavirus disease 2019 (COVID-19) indicate COVID-19 to be a devastating multisystem disease. We aim to describe the incidence, associated variables, and outcomes of rhabdomyolysis in critically ill COVID-19 patients. MATERIALS AND METHODS: Data for all critically ill adult patients (≥18 years old) admitted to the ICU at a large academic medical center with confirmed COVID-19 between March 13, 2020 and April 18, 2020 were prospectively collected. Patients with serum creatine kinase (CK) concentrations greater than 1000 U/L were diagnosed with rhabdomyolysis. Patients were further stratified as having moderate (serum CK concentration 1000-4999 U/L) or severe (serum CK concentration ≥5000 U/L) rhabdomyolysis. Univariate and multivariate analyses were performed to identify outcomes and variables associated with the development of rhabdomyolysis. RESULTS: Of 235 critically ill COVID-19 patients, 114 (48.5%) met diagnostic criteria for rhabdomyolysis. Patients with rhabdomyolysis more often required mechanical ventilation (P < 0.001), prone positioning (P < 0.001), pharmacological paralysis (P < 0.001), renal replacement therapy (P = 0.010), and extracorporeal membrane oxygenation (ECMO) (P = 0.025). They also had longer median ICU length of stay (LOS) (P < 0.001) and hospital LOS (P < 0.001). No difference in mortality was observed. Male sex, patients with morbid obesity, SOFA score, and prone positioning were independently associated with rhabdomyolysis. CONCLUSIONS: Nearly half of critically ill COVID-19 patients in our cohort met diagnostic criteria for rhabdomyolysis. Male sex, morbid obesity, SOFA score, and prone position were independently associated with rhabdomyolysis.

American Black Authorship Has Decreased Across All Clinical Specialties Despite an Increasing Number of Black Physicians Between 1990 and 2020 in the USA.

PURPOSE: Many diversity, equity, and inclusion initiatives assume that attainment of a racially diverse healthcare workforce will translate to increased diversity elsewhere in the healthcare system (e.g., leadership roles or academic authorship). We sought to investigate these trends over time by examining the evolution of physician demographics in the USA, in concert with demographic changes in US authorship in US medical journals from 1990 to 2020 across 25 specialties. METHODS: We reviewed all articles indexed in PubMed, with a primary author affiliation located in the USA and limited to journals based in the USA, relative to the proportion of medical professionals in the CMS National Provider Registry. We employed a previously peer-reviewed/validated algorithm called "averaging-of-proportions" that probabilistically predicts racial identity from surname using the US Census to assess the relationship between diversity among medical professionals and diversity in medical journal authorship. RESULTS: Data reveals a sharp disconnect between the demographic breakdown of physicians and authors. Despite an increase in the number of Black physicians (from 8.5% in 2005 to 9.1% in 2020), there has been a decrease in Black early-career authorship from 7.2% in 1990 to 5.8% in 2020. The percentage of Black early-career authors across all specialties in 2020 is lower than the average per specialty in 1990. Similar trends were noted for Black senior authorship, decreasing from 7.6% in 1990 to 6.2% in 2020, as well as a plateau in Hispanic authorship over the same time interval despite an increasing number of Hispanic physicians. CONCLUSION: Modest advances in physician diversity have not translated to increased diversity in academic authorship. Increasing diversity requires initiatives focused beyond recruitment of underrepresented minorities to medical schools or residencies.

Contemporary Surgical Management of Pancreatic Necrosis.

Importance: For decades, infected or symptomatic pancreatic necrosis was managed by open surgical necrosectomy, an approach that has now been largely supplanted by an array of techniques referred to as the step-up approach. Observations: This review describes the evidence base behind the step-up approach, when to use the different techniques, and their technical basics. The most common treatment strategies are included: percutaneous drainage, video-assisted retroperitoneal debridement, sinus tract endoscopy, endoscopic transgastric necrosectomy, and surgical transgastric necrosectomy. Also included is the evidence base around management of common complications that can occur during step-up management, such as hemorrhage, intestinal fistula, and thrombosis, in addition to associated issues that can arise during step-up management, such as the need for cholecystectomy and disconnected pancreatic duct syndrome. Conclusions and Relevance: The treatment strategies highlighted in this review are those most commonly used during step-up management, and this review is designed as a guide to the evidence base underlying these strategies, as surgeons tailor their therapeutic approach to individual patients.

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

Importance: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to postinjury rehabilitation services. Objective: To leverage a novel, interpretable AI-based technology to uncover racial disparities in access to postinjury rehabilitation care and create an AI-based prescriptive tool to address these disparities. Design, Setting, and Participants: This cohort study used data from the 2010-2016 American College of Surgeons Trauma Quality Improvement Program database for Black and White patients with a penetrating mechanism of injury. An interpretable AI methodology called optimal classification trees (OCTs) was applied in an 80:20 derivation/validation split to predict discharge disposition (home vs postacute care [PAC]). The interpretable nature of OCTs allowed for examination of the AI logic to identify racial disparities. A prescriptive mixed-integer optimization model using age, injury, and gender data was allowed to "fairness-flip" the recommended discharge destination for a subset of patients while minimizing the ratio of imbalance between Black and White patients. Three OCTs were developed to predict discharge disposition: the first 2 trees used unadjusted data (one without and one with the race variable), and the third tree used fairness-adjusted data. Main Outcomes and Measures: Disparities and the discriminative performance (C statistic) were compared among fairness-adjusted and unadjusted OCTs. Results: A total of 52 468 patients were included; the median (IQR) age was 29 (22-40) years, 46 189 patients (88.0%) were male, 31 470 (60.0%) were Black, and 20 998 (40.0%) were White. A total of 3800 Black patients (12.1%) were discharged to PAC, compared with 4504 White patients (21.5%; P < .001). Examining the AI logic uncovered significant disparities in PAC discharge destination access, with race playing the second most important role. The prescriptive fairness adjustment recommended flipping the discharge destination of 4.5% of the patients, with the performance of the adjusted model increasing from a C statistic of 0.79 to 0.87. After fairness adjustment, disparities disappeared, and a similar percentage of Black and White patients (15.8% vs 15.8%; P = .87) had a recommended discharge to PAC. Conclusions and Relevance: In this study, we developed an accurate, machine learning-based, fairness-adjusted model that can identify barriers to discharge to postacute care. Instead of accidentally encoding bias, interpretable AI methodologies are powerful tools to diagnose and remedy system-related bias in care, such as disparities in access to postinjury rehabilitation care.

Artificial intelligence versus surgeon gestalt in predicting risk of emergency general surgery.

BACKGROUND: Artificial intelligence (AI) risk prediction algorithms such as the smartphone-available Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) for emergency general surgery (EGS) are superior to traditional risk calculators because they account for complex nonlinear interactions between variables, but how they compare to surgeons' gestalt remains unknown. Herein, we sought to: (1) compare POTTER to surgeons' surgical risk estimation and (2) assess how POTTER influences surgeons' risk estimation. STUDY DESIGN: A total of 150 patients who underwent EGS at a large quaternary care center between May 2018 and May 2019 were prospectively followed up for 30-day postoperative outcomes (mortality, septic shock, ventilator dependence, bleeding requiring transfusion, pneumonia), and clinical cases were systematically created representing their initial presentation. POTTER's outcome predictions for each case were also recorded. Thirty acute care surgeons with diverse practice settings and levels of experience were then randomized into two groups: 15 surgeons (SURG) were asked to predict the outcomes without access to POTTER's predictions while the remaining 15 (SURG-POTTER) were asked to predict the same outcomes after interacting with POTTER. Comparing to actual patient outcomes, the area under the curve (AUC) methodology was used to assess the predictive performance of (1) POTTER versus SURG, and (2) SURG versus SURG-POTTER. RESULTS: POTTER outperformed SURG in predicting all outcomes (mortality-AUC: 0.880 vs. 0.841; ventilator dependence-AUC: 0.928 vs. 0.833; bleeding-AUC: 0.832 vs. 0.735; pneumonia-AUC: 0.837 vs. 0.753) except septic shock (AUC: 0.816 vs. 0.820). SURG-POTTER outperformed SURG in predicting mortality (AUC: 0.870 vs. 0.841), bleeding (AUC: 0.811 vs. 0.735), pneumonia (AUC: 0.803 vs. 0.753) but not septic shock (AUC: 0.712 vs. 0.820) or ventilator dependence (AUC: 0.834 vs. 0.833). CONCLUSION: The AI risk calculator POTTER outperformed surgeons' gestalt in predicting the postoperative mortality and outcomes of EGS patients, and when used, improved the individual surgeons' risk prediction. Artificial intelligence algorithms, such as POTTER, could prove useful as a bedside adjunct to surgeons when preoperatively counseling patients. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level II.

Use of artificial intelligence for nonlinear benchmarking of surgical care.

BACKGROUND: Existent methodologies for benchmarking the quality of surgical care are linear and fail to capture the complex interactions of preoperative variables. We sought to leverage novel nonlinear artificial intelligence methodologies to benchmark emergency surgical care. METHODS: Using a nonlinear but interpretable artificial intelligence methodology called optimal classification trees, first, the overall observed mortality rate at the index hospital's emergency surgery population (index cohort) was compared to the risk-adjusted expected mortality rate calculated by the optimal classification trees from the American College of Surgeons National Surgical Quality Improvement Program database (benchmark cohort). Second, the artificial intelligence optimal classification trees created different "nodes" of care representing specific patient phenotypes defined by the artificial intelligence optimal classification trees without human interference to optimize prediction. These nodes capture multiple iterative risk-adjusted comparisons, permitting the identification of specific areas of excellence and areas for improvement. RESULTS: The index and benchmark cohorts included 1,600 and 637,086 patients, respectively. The observed and risk-adjusted expected mortality rates of the index cohort calculated by optimal classification trees were similar (8.06% [95% confidence interval: 6.8-9.5] vs 7.53%, respectively, P = .42). Two areas of excellence and 4 for improvement were identified. For example, the index cohort had lower-than-expected mortality when patients were older than 75 and in respiratory failure and septic shock preoperatively but higher-than-expected mortality when patients had respiratory failure preoperatively and were thrombocytopenic, with an international normalized ratio ≤1.7. CONCLUSION: We used artificial intelligence methodology to benchmark the quality of emergency surgical care. Such nonlinear and interpretable methods promise a more comprehensive evaluation and a deeper dive into areas of excellence versus suboptimal care.

Trauma patients with limited English proficiency: Outcomes from two level one trauma centers.

BACKGROUND: Outcomes for surgical patients with limited English proficiency (LEP) may be worse compared to patients with English proficiency. We sought to evaluate the association of LEP with outcomes for trauma patients. METHODS: Admitted adult patients on trauma service at two Level One trauma centers from 2015 to 2019 were identified. RESULTS: 12,562 patients were included in total; 7.3% had LEP. On multivariable analyses, patients with LEP had lower odds of discharge to post-acute care versus home compared to patients with English proficiency (OR 0.69; 95% CI 0.58-0.83; p < 0.001) but had similar length of stay (Beta coefficient 1.16; 95% CI 0.00-2.32; p = 0.05), and 30-day readmission (OR 1.08; 95% CI 0.87-1.35; p = 0.46). CONCLUSIONS: Trauma patients with LEP had comparable short-term outcomes to English proficient patients but were less likely to be discharged to post-acute care facilities. The role of structural barriers, family preferences, and other factors merit future investigation.

Does An ERAS Protocol Reduce Postoperative Opiate Prescribing in Plastic Surgery?

BACKGROUND: Enhanced recovery after surgery (ERAS) protocols are effective at reducing inpatient opiate use. There is a paucity of studies on the effects of an ERAS protocol on outpatient opiate prescriptions. The aim of this study was to determine whether an ERAS protocol for plastic and reconstructive surgery would reduce opiate use in the outpatient postoperative setting. METHODS: A statewide (Massachusetts, USA) controlled substance prescription monitoring database was retrospectively reviewed to assess the prescribing patterns of a single academic plastic surgeon performing common plastic surgical outpatient operations. The time period prior to implementation of the ERAS protocol was then compared with the time period following protocol implementation. An additional three months of post-implementation data were then compared with those of each of the previous time periods to investigate whether the results were sustained. RESULTS: A comparison of opiate prescriptions in pre-ERAS, immediate post-ERAS procedures, and follow-up ERAS implementation procedures revealed a statistically significant decrease in opiate prescriptions after ERAS protocol implementation. This decrease in the quantity of opiates prescribed was sustained over time . CONCLUSIONS: ERAS protocols are effective at reducing outpatient opiate prescriptions after a variety of plastic surgery operations. Appropriate patient and physician education is paramount for success.