Preoperative Prediction of Unplanned Reoperation in a Broad Surgical Population.

INTRODUCTION: Unplanned reoperation is an undesirable outcome with considerable risks and an increasingly assessed quality of care metric. There are no preoperative prediction models for reoperation after an index surgery in a broad surgical population in the literature. The Surgical Risk Preoperative Assessment System (SURPAS) preoperatively predicts 12 postoperative adverse events using 8 preoperative variables, but its ability to predict unplanned reoperation has not been assessed. This study's objective was to determine whether the SURPAS model could accurately predict unplanned reoperation. METHODS: This was a retrospective analysis of the American College of Surgeons' National Surgical Quality Improvement Program adult database, 2012-2018. An unplanned reoperation was defined as any unintended operation within 30 d of an initial scheduled operation. The 8-variable SURPAS model and a 29-variable "full" model, incorporating all available American College of Surgeons' National Surgical Quality Improvement Program nonlaboratory preoperative variables, were developed using multiple logistic regression and compared using discrimination and calibration metrics: C-indices (C), Hosmer-Lemeshow observed-to-expected plots, and Brier scores (BSs). The internal chronological validation of the SURPAS model was conducted using "training" (2012-2017) and "test" (2018) datasets. RESULTS: Of 5,777,108 patients, 162,387 (2.81%) underwent an unplanned reoperation. The SURPAS model's C-index of 0.748 was 99.20% of that for the full model (C = 0.754). Hosmer-Lemeshow plots showed good calibration for both models and BSs were similar (BS = 0.0264, full; BS = 0.0265, SURPAS). Internal chronological validation results were similar for the training (C = 0.749, BS = 0.0268) and test (C = 0.748, BS = 0.0250) datasets. CONCLUSIONS: The SURPAS model accurately predicted unplanned reoperation and was internally validated. Unplanned reoperation can be integrated into the SURPAS tool to provide preoperative risk assessment of this outcome, which could aid patient risk education.

Does Work Relative Value Unit Measure Surgical Complexity for Risk Adjustment of Surgical Outcomes?

INTRODUCTION: The purpose of this study was to determine whether the work relative value unit (workRVU) of a patient's operation can be useful as a measure of surgical complexity for the risk adjustment of surgical outcomes. METHODS: We retrospectively analyzed the American College of Surgeon's National Surgical Quality Improvement Program database (2005-2018). We examined the associations of workRVU of the patient's primary operation with preoperative patient characteristics and associations with postoperative complications. We performed forward selection multiple logistic regression analysis to determine the predictive importance of workRVU. We then generated prediction models using patient characteristics with and without workRVU and compared c-indexes to assess workRVU's additive predictive value. RESULTS: 7,507,991 operations were included. Patients who were underweight, functionally dependent, transferred from an acute care hospital, had higher American Society of Anesthesiologists class or who had medical comorbidities had operations with higher workRVU (all P < 0.0001). The subspecialties with the highest workRVU were neurosurgery (mean = 22.2), thoracic surgery (mean = 21.1), and vascular surgery (mean = 18.8) (P < 0.0001). For all postoperative complications, mean workRVU was higher for patients with the complication than those without (all P < 0.0001). For eight of 12 postoperative complications, workRVU entered the logistic regression models as a predictor variable in the 1st to 4th steps. Addition of workRVU as a preoperative predictive variable improved the c-index of the prediction models. CONCLUSIONS: WorkRVU was associated with sicker patients and patients experiencing postoperative complications and was an important predictor of postoperative complications. When added to a prediction model including patient characteristics, it only marginally improved prediction. This is possibly because workRVU is associated with patient characteristics.

Inpatient Versus Outpatient Surgery: A Comparison of Postoperative Mortality and Morbidity in Elective Operations.

BACKGROUND: Operations performed outpatient offer several benefits. The prevalence of outpatient operations is growing. Consequently, the proportion of patients with multiple comorbidities undergoing outpatient surgery is increasing. We compared 30-day mortality and overall morbidity between outpatient and inpatient elective operations. METHODS: Using the 2005-2018 ACS-NSQIP database, we evaluated trends in percent of hospital outpatient operations performed over time, and the percent of operations done outpatient versus inpatient by CPT code. Patient characteristics were compared for outpatient versus inpatient operations. We compared unadjusted and risk-adjusted 30-day mortality and morbidity for inpatient and outpatient operations. RESULTS: A total of 6,494,298 patients were included. The proportion of outpatient operations increased over time, from 37.8% in 2005 to 48.2% in 2018. We analyzed the 50 most frequent operations performed outpatient versus inpatient 25-75% of the time (n = 1,743,097). Patients having outpatient operations were younger (51.6 vs 54.6 years), female (70.3% vs 67.3%), had fewer comorbidities, and lower ASA class (I-II, 69.3% vs. 59.9%). On both unadjusted and risk-adjusted analysis, 30-day mortality and overall morbidity were less likely in outpatient versus inpatient operations. CONCLUSION: In this large multi-specialty analysis, we found that patients undergoing outpatient surgery had lower risk of 30-day morbidity and mortality than those undergoing the same inpatient operation. Patients having outpatient surgery were generally healthier, suggesting careful patient selection occurred even with increasing outpatient operation frequency. Patients and providers can feel reassured that outpatient operations are a safe, reasonable option for selected patients.

Using the Surgical Risk Preoperative Assessment System to Define the "High Risk" Surgical Patient.

BACKGROUND: Defining a "high risk" surgical population remains challenging. Using the Surgical Risk Preoperative Assessment System (SURPAS), we sought to define "high risk" groups for adverse postoperative outcomes. MATERIALS AND METHODS: We retrospectively analyzed the 2009-2018 American College of Surgeons National Surgical Quality Improvement Program database. SURPAS calculated probabilities of 12 postoperative adverse events. The Hosmer Lemeshow graphs of deciles of risk and maximum Youden index were compared to define "high risk." RESULTS: Hosmer-Lemeshow plots suggested the "high risk" patient could be defined by the 10th decile of risk. Maximum Youden index found lower cutoff points for defining "high risk" patients and included more patients with events. This resulted in more patients classified as "high risk" and higher number needed to treat to prevent one complication. Some specialties (thoracic, vascular, general) had more "high risk" patients, while others (otolaryngology, plastic) had lower proportions. CONCLUSIONS: SURPAS can define the "high risk" surgical population that may benefit from risk-mitigating interventions.

Associations Between Preoperative Risk, Postoperative Complications, and 30-Day Mortality.

BACKGROUND: Comorbidities and postoperative complications increase mortality, making early recognition and management critical. It is useful to understand how they are associated with one another. This study assesses associations between comorbidities, complications, and mortality. METHODS: We calculated associations between comorbidities, complications, and 30-day mortality using the 2012-2018 ACS-NSQIP database. We examined the association between mortality and number of complications which complications were most associated with mortality. RESULTS: 5,777,108 patients were included. 30-day mortality was 0.95%. For most comorbidities or postoperative complications, patients with these had higher mortality than patients without. Having ≥ 1 complication increased mortality risk by 32.5-fold (6.5% vs. 0.2%). Mortality rate significantly increased with increasing number of complications, particularly after two or more complications. Bleeding and sepsis were associated with the most deaths. CONCLUSION: The 30-day mortality rate was < 1% but was 32-fold higher in patients with complications and increased rapidly for patients with ≥ 2 complications. Bleeding and sepsis were the most prominent complications associated with mortality.

Scaling Beyond Early Adopters: a Content Analysis of Literature and Key Informant Perspectives.

BACKGROUND: Innovations and improvements in care delivery are often not spread across all settings that would benefit from their uptake. Scale-up and spread efforts are deliberate efforts to increase the impact of innovations successfully tested in pilot projects so as to benefit more people. The final stages of scale-up and spread initiatives must contend with reaching hard-to-engage sites. OBJECTIVE: To describe the process of scale-up and spread initiatives, with a focus on hard-to-engage sites and strategies to approach them. DESIGN: Qualitative content analysis of systematically identified literature and key informant interviews. PARTICIPANTS: Leads from large magnitude scale-up and spread projects. APPROACH: We conducted a systematic literature search on large magnitude scale-up and spread and interviews with eight project leads, who shared their perspectives on strategies to scale-up and spread clinical and administrative practices across healthcare systems, focusing on hard-to-engage sites. We synthesized these data using content analysis. KEY RESULTS: Searches identified 1919 titles, of which 52 articles were included. Thirty-four discussed general scale-up and spread strategies, 11 described hard-to-engage sites, and 7 discussed strategies for hard-to-engage sites. These included publications were combined with interview findings to describe a fourth phase of the national scale-up and spread process, common challenges for spreading to hard-to-engage sites, and potential benefits of working with hard-to-engage sites, as well as useful strategies for working with hard-to-engage sites. CONCLUSIONS: We identified scant published evidence that describes strategies for reaching hard-to-engage sites. The sparse data we identified aligned with key informant accounts. Future work could focus on better documentation of the later stages of spread efforts, including specific tailoring of approaches and strategies used with hard-to-engage sites. Spread efforts should include a "flexible, tailored approach" for this highly variable group, especially as implementation science is looking to expand its impact in routine care settings.

A Pilot Study of Patient-Reported Outcome Measures Across a Broad Sample of Surgical Patients.

BACKGROUND: Patient-reported outcomes (PROs) have the potential to aid in surgical decision-making, predict surgical outcomes, assess recovery, and evaluate long-term success. We performed a pilot study testing the ability to use PROs in a broad surgical population in preparation for wide spread use. MATERIAL AND METHODS: Surgical patients completed five Patient-Reported Outcome Measurement Information System (PROMIS) measures during their preoperative encounter in the preanesthesia clinic and again postoperatively via emailed link. Preoperative to postoperative changes in PROMIS scores, factors related to completion of postoperative measures, intercorrelations between PROMIS measures, and numbers of patients with normal function, and mild, moderate, and severe deficits in PROMIS scores were analyzed. RESULTS: A total of 393 patients undergoing surgery in 8 specialties completed preoperative PROMIS measures; 239 (60.8%) completed them postoperatively. Physical function (P < 0.0001), pain (P < 0.0001), and cognitive function (P = 0.03) PROMIS scores significantly worsened after surgery but not mental PROMIS scores (P = 0.48). Hispanic and sicker patients had lower completion rates of postoperative measures. Intercorrelations were very high (>0.80) among the physical function and self-efficacy for activities of daily living PROMIS measures. Physical function and pain PROMIS measures had the largest number of patients in the "severe" range after surgery. CONCLUSIONS: Patients across a broad surgical population completed PROMIS measures successfully, both preoperatively and postoperatively, although the postoperative completion rate was lower than other studies reported in the literature. PROMIS scores were reflective of the effects of surgery. Some of the PROMIS measures were highly correlated suggesting that some measures could be eliminated or replaced with measures assessing other important effects of surgery. Consideration could be made to alert health care providers about patients having PROs in the "severe" range for potential intervention.

Assessment of barriers and facilitators in the implementation of appropriate use criteria for elective percutaneous coronary interventions: a qualitative study.

BACKGROUND: The use of inappropriate elective Percutaneous Coronary Intervention (PCI) has decreased over time, but hospital-level variation in the use of inappropriate PCI persists. Understanding the barriers and facilitators to the implementation of Appropriate Use Criteria (AUC) guidelines may inform efforts to improve elective PCI appropriateness. METHODS: All hospitals performing PCI in Washington State were categorized by their use of inappropriate elective PCI in 2010 to 2013. Semi-structured, qualitative telephone interviews were then conducted with 17 individual interviews at 13 sites in Washington State to identify barriers and facilitators to the implementation of the AUC guidelines. An inductive and deductive, team-based analytical approach, drawing primarily on Matrix analysis was performed to identify factors affecting implementation of the AUC. RESULTS: Specific facilitators were identified that supported successful implementation of the AUC. These included collaborative catheterization laboratory environments that allow all staff to participate with questions and opinions; ongoing AUC education with catheterization laboratory teams and referring providers; internal AUC peer review processes; interventional cardiologist be directly involved with the pre-procedural review process; checklist-based algorithms for pre-procedural documentation; systems redesign to include insurance companies; and AUC educational information with patients. Barriers to implementation of the AUC included external pressures, such as competition for patients, and the lack of shared medical records with sites that referred patients for coronary angiography. CONCLUSIONS: The identified facilitators enabled sites to successfully implement the AUC. Catheterization laboratories struggling to successfully implement the AUC may consider utilizing these strategies to improve their processes to improve patient selection for elective PCI.

Adaptation of Lean Six Sigma Methodologies for the Evaluation of Veterans Choice Program at 3 Urban Veterans Affairs Medical Centers.

OBJECTIVE: The Veterans Health Administration (VHA) is adapting to meet the changing needs of our Veterans. VHA leaders are promoting quality improvement strategies including Lean Six Sigma (LSS). This study used LSS tools to evaluate the Veterans Choice Program (VCP), a program that aims to improve access to health care services for eligible Veterans by expanding health care options to non-VHA providers. RESEARCH DESIGN: LSS was utilized to assess the current process and efficiency patterns of the VCP at 3 VHA Medical Centers. LSS techniques were used to assess data obtained through semistructured interviews with Veterans, staff, and providers to describe and evaluate the VCP process by identifying wastes and defects. RESULTS: The LSS methodology facilitated the process of targeting priorities for improvement and constructing suggestions to close identified gaps and inefficiencies. Identified key process wastes included inefficient exchange of clinical information between stakeholders in and outside of the VHA; poor dissemination of VCP programmatic information; shortages of VCP-participating providers; duplication of appointments; declines in care coordination; and lack of program adaptability to local processes. Recommendations for improvement were formulated using LSS. CONCLUSIONS: This evaluation illustrates how LSS can be utilized to assess a nationally mandated health care program. By focusing on stakeholder, staff, and Veteran perspectives, process defects in the VCP were identified and improvement recommendations were made. However, the current LSS language used is not intuitive in health care and similar applications of LSS may consider using new language and goals adapted specifically for health care.

Evaluation of the Veterans Health Administration's Specialty Care Transformational Initiatives to Promote Patient-Centered Delivery of Specialty Care: A Mixed-Methods Approach.

INTRODUCTION: Veteran's Affairs Office of Specialty Care (OSC) launched four national initiatives (Electronic-Consults [e-Consults], Specialty Care Access Networks-Extension for Community Healthcare Outcomes [SCAN-ECHO], Mini-Residencies, and Specialty Care Neighborhood) to improve specialty care delivery and funded a center to evaluate the initiatives. METHODS: The evaluation, guided by two implementation frameworks, provides formative (administrator/provider interviews and surveys) and summative data (quantitative data on patterns of use) about the initiatives to OSC. RESULTS: Evaluation of initiative implementation is assessed through CFIR (Consolidated Framework for Implementation Research)-grounded qualitative interviews to identify barriers/facilitators. Depending on high or low implementation, factors such as receiving workload credit, protected time, existing workflow/systems compatibility, leadership engagement, and access to information/resources were considered implementation barriers or facilitators. Findings were shared with OSC and used to further refine implementation at additional sites. Evaluation of other initiatives is ongoing. CONCLUSIONS: The mixed-methods approach has provided timely information to OSC about initiative effect and impacted OSC policies on implementation at additional sites.

Temporal Trends in Percutaneous Coronary Intervention Appropriateness: Insights From the Clinical Outcomes Assessment Program.

BACKGROUND: It is unknown whether the appropriate use of percutaneous coronary intervention (PCI) has improved over time and whether trends in PCI appropriateness have been accompanied by changes in the use of PCI. METHODS AND RESULTS: We applied appropriate use criteria to determine the appropriateness of all 51 872 PCI performed in Washington State from 2010 through 2013. We evaluated the number of PCIs performed from 2006 through 2013 to provide a comparator period that preceded statewide appropriateness assessment beginning in 2010. Between 2010 and 2013, the overall number of PCI decreased by 6.8% (13 267 PCIs in 2010 to 12 193 in 2013) with a 43% decline in the number of PCIs for elective indications (3818 PCIs in 2010 to 2193 PCIs in 2013). The decline in the use of elective PCI was significantly larger after the onset of statewide PCI appropriateness assessment in 2010 (P=0.03). The proportion of elective PCIs classified as appropriate increased from 26% in 2010 to 38% in 2013, whereas the proportion of inappropriate PCIs decreased from 16% to 13% (P<0.001 for trends). Significant improvements in the proportion of inappropriate PCI were limited to the tertile of hospitals with the largest decline in PCIs classified as inappropriate (25% in 2010 to 12% in 2013; P=0.03). CONCLUSIONS: In Washington State, the use of PCI for elective indications has decreased over time with concurrent improvements in PCI appropriateness. However, improvements in PCI appropriateness were limited to a minority of hospitals. Understanding processes at these high-performing hospitals may inform efforts to improve PCI appropriateness.

Site-level variation in and practices associated with dabigatran adherence.

IMPORTANCE: Unlike warfarin, which requires routine laboratory testing and dose adjustment, target-specific oral anticoagulants like dabigatran do not. However, optimal follow-up infrastructure and modifiable site-level factors associated with improved adherence to dabigatran are unknown. OBJECTIVES: To assess site-level variation in dabigatran adherence and to identify site-level practices associated with higher dabigatran adherence. DESIGN, SETTING, AND PARTICIPANTS: Mixed-methods study involving retrospective quantitative and cross-sectional qualitative data. A total of 67 Veterans Health Administration sites with 20 or more patients filling dabigatran prescriptions between 2010 and 2012 for nonvalvular atrial fibrillation were sampled (4863 total patients; median, 51 patients per site). Forty-seven pharmacists from 41 eligible sites participated in the qualitative inquiry. EXPOSURE: Site-level practices identified included appropriate patient selection, pharmacist-driven patient education, and pharmacist-led adverse event and adherence monitoring. MAIN OUTCOMES AND MEASURES: Dabigatran adherence (intensity of drug use during therapy) defined by proportion of days covered (ratio of days supplied by prescription to follow-up duration) of 80% or more. RESULTS: The median proportion of patients adherent to dabigatran was 74% (interquartile range [IQR], 66%-80%). After multivariable adjustment, dabigatran adherence across sites varied by a median odds ratio of 1.57. Review of practices across participating sites showed that appropriate patient selection was performed at 31 sites, pharmacist-led education was provided at 30 sites, and pharmacist-led monitoring at 28 sites. The proportion of adherent patients was higher at sites performing appropriate selection (75% vs 69%), education (76% vs 66%), and monitoring (77% vs 65%). Following multivariable adjustment, association between pharmacist-led education and dabigatran adherence was not statistically significant (relative risk [RR], 0.94; 95% CI, 0.83-1.06). Appropriate patient selection (RR, 1.14; 95% CI, 1.05-1.25), and provision of pharmacist-led monitoring (RR, 1.25; 95% CI, 1.11-1.41) were associated with better patient adherence. Additionally, longer duration of monitoring and providing more intensive care to nonadherent patients in collaboration with the clinician improved adherence. CONCLUSIONS AND RELEVANCE: Among nonvalvular atrial fibrillation patients treated with dabigatran, there was variability in patient medication adherence across Veterans Health Administration sites. Specific pharmacist-based activities were associated with greater patient adherence to dabigatran.

The association between obesity and postoperative outcomes in a broad surgical population: A 7-year American College of Surgeons National Surgical Quality Improvement analysis.

BACKGROUND: The number of obese surgical patients continues to grow, and yet obesity's association with surgical outcomes is not totally clear. This study examined the association between obesity and surgical outcomes across a broad surgical population using a very large sample size. METHODS: This was an analysis of the 2012 to 2018 American College of Surgeons National Surgical Quality Improvement database, including all patients from 9 surgical specialties (general, gynecology, neurosurgery, orthopedics, otolaryngology, plastics, thoracic, urology, and vascular). Preoperative characteristics and postoperative outcomes were compared by body mass index class (normal weight 18.5-24.9 kg/m2, overweight 25.0-29.9, obese class I 30.0-34.9, obese II 35.0-39.9, obese III ≥40). Adjusted odds ratios were computed for adverse outcomes by body mass index class. RESULTS: A total of 5,572,019 patients were included; 44.6% were obese. Median operative times were marginally higher for obese patients (89 vs 83 minutes, P < .001). Compared to normal weight patients, overweight and obese patients in classes I, II, and III all had higher adjusted odds of developing infection, venous thromboembolism, and renal complications, but they did not exhibit elevated odds of other postoperative complications (mortality, overall morbidity, pulmonary, urinary tract infection, cardiac, bleeding, stroke, unplanned readmission, or discharge not home (except for class III patients). CONCLUSION: Obesity was associated with increased odds of postoperative infection, venous thromboembolism, and renal but not the other American College of Surgeons National Surgical Quality Improvement complications. Obese patients need to be carefully managed for these complications.

Formative evaluation of the development and implementation of the automated surveillance of postoperative infections tool.

BACKGROUND: The gold standard for detecting postoperative complications uses databases like the American College of Surgeons National Surgical Quality Improvement Program, a multi-centered database based on manual chart review. However, their limitations and costs have led many centers to discontinue participation. Novel techniques to detect postoperative complications must be developed and implemented with surgeon involvement, which is paramount to their adoption. We sought to assess surgeons' opinions of a newly developed postoperative complication detection tool, the Automated Surveillance of Postoperative Infections, within the contextual clinical environment. METHODS: This was a multi-site qualitative formative evaluation of surgeon perceptions of the Automated Surveillance of Postoperative Infections. We conducted semi-structured interviews and focus groups with surgeons and presented the Automated Surveillance of Postoperative Infections concept. Important domains and constructs, as categorized by Consolidated Framework for Implementation Research, were identified to support the successful adoption and implementation of the Automated Surveillance of Postoperative Infections. RESULTS: Twenty-four surgeons with 10 surgical subspecialties were interviewed. The following 4 main themes were found: (1) perception of the Automated Surveillance of Postoperative Infections tool-to provide important data that can improve and support clinical outcomes; (2) environment for implementation-description of factors to support or impede implementation; (3) adaptability of the Automated Surveillance of Postoperative Infections-to work with the complexity of surgical cases; and (4) the Automated Surveillance of Postoperative Infections report format and details. CONCLUSIONS: We successfully captured the perspectives and suggestions of surgeons to improve the Automated Surveillance of Postoperative Infections and potential barriers during the initial development phase. Barriers included fear of punitive action from reports and complex surgical cases. Facilitators identified were the need to improve clinical outcomes and organizational support. The results of this formative evaluation will be used to further develop Automated Surveillance of Postoperative Infections, starting with a prototype, the Automated Surveillance of Postoperative Infections 1.0.

Effect of Present at Time of Surgery on Unadjusted and Risk-Adjusted Postoperative Complication Rate.

BACKGROUND: Present at the time of surgery (PATOS) is an important measure to collect in postoperative complication surveillance systems because it may affect a patient's risk of a subsequent complication and the estimation of postoperative complication rates attributed to the healthcare system. The American College of Surgeons (ACS) NSQIP started collecting PATOS data for 8 postoperative complications in 2011, but no one has used these data to quantify how this may affect unadjusted and risk-adjusted postoperative complication rates. STUDY DESIGN: This study was a retrospective observational study of the ACS NSQIP database from 2012 to 2018. PATOS data were analyzed for the 8 postoperative complications of superficial, deep, and organ space surgical site infection; pneumonia; urinary tract infection; ventilator dependence; sepsis; and septic shock. Unadjusted postoperative complication rates were compared ignoring PATOS vs taking PATOS into account. Observed to expected ratios over time were also compared by calculating expected values using multiple logistic regression analyses with complication as the dependent variable and the 28 nonlaboratory preoperative variables in the ACS NSQIP database as the independent variables. RESULTS: In 5,777,108 patients, observed event rates for each outcome were reduced by between 6.1% (superficial surgical site infection) and 52.5% (sepsis) when PATOS was taken into account. The observed to expected ratios were similar each year for all outcomes, except for sepsis and septic shock in the early years. CONCLUSIONS: Taking PATOS into account is important for reporting unadjusted event rates. The effect varied by type of complication-lowest for superficial surgical site infection and highest for sepsis and septic shock. Taking PATOS into account was less important for risk-adjusted outcomes (observed to expected ratios), except for sepsis and septic shock.

Lessons learned by thoracic surgeons during the COVID-19 pandemic.

Background: The scale of the coronavirus disease 2019 (COVID-19) pandemic has necessitated healthcare systems to adapt and evolve, altering physician roles and expectations. Thoracic surgeons have seen practice changes from new COVID-19 consults to necessary delay and triage of elective care. The goal of this study was to understand the impact of COVID-19 on thoracic surgeon experiences in order to anticipate roles and changes in practice in future such circumstances. Methods: Semi-structured, qualitative individual telephone interviews were conducted with thoracic surgeons. Interviews were structured to understand how surgeons were impacted by the COVID-19 pandemic and to record lessons learned. Interviews were conducted until thematic saturation was achieved. Data were analyzed using matrix analysis. Results: Eleven board-certified general thoracic surgeons from nine institutions were interviewed. Thoracic surgeon roles in COVID-19 care included critical care delivery, performing tracheostomies and establishing related protocols, and interventions for long-term airway complications. Attention was called to the impact of the pandemic on thoracic cancer: patients avoided hospitals because of concern over COVID-19, delaying care. Conclusions: Thoracic surgeons played a critical role in the COVID-19 pandemic response in both technical patient care and administrative capacities. Primary care responsibilities included the development, administration and delivery of tracheostomy protocols, and the care of down-stream airway complications. Thoracic surgeons were critical in triage decisions to minimize the impact of COVID-19 on thoracic cancer care. Lessons learned during the COVID-19 pandemic may provide insight into opportunities to promote collaboration in thoracic surgery and facilitate improved care delivery in future settings of resource limitation.

Development and validation of a multivariable preoperative prediction model for postoperative length of stay in a broad inpatient surgical population.

BACKGROUND: Postoperative length of stay is a meaningful patient-centered outcome and an important determinant of healthcare costs. The Surgical Risk Preoperative Assessment System preoperatively predicts 12 postoperative adverse events using 8 preoperative variables, but its ability to predict postoperative length of stay has not been assessed. We aimed to determine whether the Surgical Risk Preoperative Assessment System variables could accurately predict postoperative length of stay up to 30 days in a broad inpatient surgical population. METHODS: This was a retrospective analysis of the American College of Surgeons' National Surgical Quality Improvement Program adult database from 2012 to 2018. A model using the Surgical Risk Preoperative Assessment System variables and a 28-variable "full" model, incorporating all available American College of Surgeons' National Surgical Quality Improvement Program preoperative nonlaboratory variables, were fit to the analytical cohort (2012-2018) using multiple linear regression and compared using model performance metrics. Internal chronological validation of the Surgical Risk Preoperative Assessment System model was conducted using training (2012-2017) and test (2018) datasets. RESULTS: We analyzed 3,295,028 procedures. The adjusted R2 for the Surgical Risk Preoperative Assessment System model fit to this cohort was 93.3% of that for the full model (0.347 vs 0.372). In the internal chronological validation of the Surgical Risk Preoperative Assessment System model, the adjusted R2 for the test dataset was 97.1% of that for the training dataset (0.3389 vs 0.3489). CONCLUSION: The parsimonious Surgical Risk Preoperative Assessment System model can preoperatively predict postoperative length of stay up to 30 days for inpatient surgical procedures almost as accurately as a model using all 28 American College of Surgeons' National Surgical Quality Improvement Program preoperative nonlaboratory variables and has shown acceptable internal chronological validation.

Barriers and Facilitators in Implementation of an Esophagectomy Care Pathway: a Qualitative Analysis.

INTRODUCTION: A new postoperative esophagectomy care pathway was recently implemented at our institution. Practice pattern change among provider teams can prove challenging; therefore, we sought to study the barriers and facilitators toward pathway implementation at the provider level. METHODS: This qualitative study was guided by the Theoretical Domains Framework (TDF) to study the adoption and implementation of a post-esophagectomy care pathway. Sixteen in-depth interviews were conducted with providers involved with the pathway. Matrix analysis was used to analyze the data. RESULTS: Providers included attending surgeons (n = 6), advanced practice providers (n = 8), registered dietitian (n = 1), and clinic staff (n = 1). TDF domains that were salient across our findings included knowledge, beliefs about consequences, social influences, and environmental context and resources. Identified facilitators included were electronic health record tools, such as note templates including pathway components and a pathway-specific order set, patient satisfaction, and preliminary data indicating clinical benefits such as a reduced anastomotic leak rate. The major barrier reported was a hesitance to abandon previous practice patterns, most prevalent at the attending surgeon level. CONCLUSION: The TDF enabled us to identify and understand the individuals' perceived barriers and facilitators toward adoption and implementation of a postoperative esophagectomy pathway. This analysis can help guide and improve adoption of surgical patient care pathways among providers.

Development and validation of models for detection of postoperative infections using structured electronic health records data and machine learning.

BACKGROUND: Postoperative infections constitute more than half of all postoperative complications. Surveillance of these complications is primarily done through manual chart review, which is time consuming, expensive, and typically only covers 10% to 15% of all operations. Automated surveillance would permit the timely evaluation of and reporting of all operations. METHODS: The goal of this study was to develop and validate parsimonious, interpretable models for conducting surveillance of postoperative infections using structured electronic health records data. This was a retrospective study using 30,639 unique operations from 5 major hospitals between 2013 and 2019. Structured electronic health records data were linked to postoperative outcomes data from the American College of Surgeons National Surgical Quality Improvement Program. Predictors from the electronic health records included diagnoses, procedures, and medications. Infectious complications included surgical site infection, urinary tract infection, sepsis, and pneumonia within 30 days of surgery. The knockoff filter, a penalized regression technique that controls type I error, was applied for variable selection. Models were validated in a chronological held-out dataset. RESULTS: Seven percent of patients experienced at least one type of postoperative infection. Models selected contained between 4 and 8 variables and achieved >0.91 area under the receiver operating characteristic curve, >81% specificity, >87% sensitivity, >99% negative predictive value, and 10% to 15% positive predictive value in a held-out test dataset. CONCLUSION: Surveillance and reporting of postoperative infection rates can be implemented for all operations with high accuracy using electronic health records data and simple linear regression models.