Artificial Intelligence-enabled Decision Support in Surgery: State-of-the-art and Future Directions.

OBJECTIVE: To summarize state-of-the-art artificial intelligence-enabled decision support in surgery and to quantify deficiencies in scientific rigor and reporting. BACKGROUND: To positively affect surgical care, decision-support models must exceed current reporting guideline requirements by performing external and real-time validation, enrolling adequate sample sizes, reporting model precision, assessing performance across vulnerable populations, and achieving clinical implementation; the degree to which published models meet these criteria is unknown. METHODS: Embase, PubMed, and MEDLINE databases were searched from their inception to September 21, 2022 for articles describing artificial intelligence-enabled decision support in surgery that uses preoperative or intraoperative data elements to predict complications within 90 days of surgery. Scientific rigor and reporting criteria were assessed and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. RESULTS: Sample size ranged from 163-2,882,526, with 8/36 articles (22.2%) featuring sample sizes of less than 2000; 7 of these 8 articles (87.5%) had below-average (<0.83) area under the receiver operating characteristic or accuracy. Overall, 29 articles (80.6%) performed internal validation only, 5 (13.8%) performed external validation, and 2 (5.6%) performed real-time validation. Twenty-three articles (63.9%) reported precision. No articles reported performance across sociodemographic categories. Thirteen articles (36.1%) presented a framework that could be used for clinical implementation; none assessed clinical implementation efficacy. CONCLUSIONS: Artificial intelligence-enabled decision support in surgery is limited by reliance on internal validation, small sample sizes that risk overfitting and sacrifice predictive performance, and failure to report confidence intervals, precision, equity analyses, and clinical implementation. Researchers should strive to improve scientific quality.

Parent Activation in the Neonatal Intensive Care Unit.

OBJECTIVE: Patient activation is the knowledge, skills, and confidence to manage one's health; parent activation is a comparable concept related to a parent's ability to manage a child's health. Activation in adults is a modifiable risk factor and associated with clinical outcomes and health care utilization. We examined activation in parents of hospitalized newborns observing temporal trends and associations with sociodemographic characteristics, neonate characteristics, and outcomes. STUDY DESIGN: Participants included adult parents of neonates admitted to a level-IV neonatal intensive care unit in an academic medical center. Activation was measured with the 10-item Parent version of the Patient Activation Measure (P-PAM) at admission, discharge, and 30 days after discharge. Associations with sociodemographic variables, health literacy, clinical variables, and health care utilization were evaluated. RESULTS: A total of 96 adults of 64 neonates were enrolled. The overall mean P-PAM score on admission was 81.8 (standard deviation [SD] = 18), 88.8 (SD = 13) at discharge, and 86.8 (SD = 16) at 30-day follow-up. Using linear mixed regression model, P-PAM score was significantly associated with timing of measurement. Higher P-PAM scores were associated with higher health literacy (p = 0.002) and higher in mothers compared to fathers (p = 0.040). There were no significant associations of admission P-PAM scores with sociodemographic characteristics. Parents of neonates who had a surgical diagnosis had a statistically significant (p = 0.003) lower score than those who did not. There were no associations between discharge P-PAM scores and neonates' lengths of stay or other indicators of illness severity. CONCLUSION: Parental activation in the NICU setting was higher than reported in the adult and limited pediatric literature; scores increased from admission to discharge and 30-day postdischarge. Activation was higher in mothers and parents with higher health literacy. Additional larger scale studies are needed to determine whether parental activation is associated with long-term health care outcomes as seen in adults. KEY POINTS: · Little is known about activation in parents of neonates.. · Activation plays a role in health outcomes in adults.. · Larger studies are needed to explore parent activation..

The Perceived Impact and Usability of a Care Management and Coordination System in Delivering Services to Vulnerable Populations: Mixed Methods Study.

BACKGROUND: People with complex needs, such as those experiencing homelessness, require concurrent, seamless support from multiple social service agencies. Sonoma County, California has one of the nation's largest homeless populations among largely suburban communities. To support client-centered care, the county deployed a Care Management and Coordination System (CMCS). This system comprised the Watson Care Manager (WCM), a front-end system, and Connect 360, which is an integrated data hub that aggregates information from various systems into a single client record. OBJECTIVE: The aim of this study is to evaluate the perceived impact and usability of WCM in delivering services to the homeless population in Sonoma County. METHODS: A mixed methods study was conducted to identify ways in which WCM helps to coordinate care. Interviews, observations, and surveys were conducted, and transcripts and field notes were thematically analyzed and directed by a grounded theory approach. Responses to the Technology Acceptance Model survey were analyzed. RESULTS: A total of 16 participants were interviewed, including WCM users (n=8) and department leadership members (n=8). In total, 3 interdisciplinary team meetings were observed, and 8 WCM users were surveyed. WCM provided a central shared platform where client-related, up-to-date, comprehensive, and reliable information from participating agencies was consolidated. Factors that facilitated WCM use were users' enthusiasm regarding the tool functionalities, scalability, and agency collaboration. Constraining factors included the suboptimal awareness of care delivery goals and functionality of the system among the community, sensitivities about data sharing and legal requirements, and constrained funding from government and nongovernment organizations. Overall, users found WCM to be a useful tool that was easy to use and helped to enhance performance. CONCLUSIONS: WCM supports the delivery of care to individuals with complex needs. Integration of data and information in a CMCS can facilitate coordinated care. Future research should examine WCM and similar CMCSs in diverse populations and settings.

Automating the Classification of Complexity of Medical Decision-Making in Patient-Provider Messaging in a Patient Portal.

BACKGROUND: Patient portals are consumer health applications that allow patients to view their health information. Portals facilitate the interactions between patients and their caregivers by offering secure messaging. Patients communicate different needs through portal messages. Medical needs contain requests for delivery of care (e.g. reporting new symptoms). Automating the classification of medical decision complexity in portal messages has not been investigated. MATERIALS AND METHODS: We trained two multiclass classifiers, multinomial Naïve Bayes and random forest on 500 message threads, to quantify and label the complexity of decision-making into four classes: no decision, straightforward, low, and moderate. We compared the performance of the models to using only the number of medical terms without training a machine learning model. RESULTS: Our analysis demonstrated that machine learning models have better performance than the model that did not use machine learning. Moreover, machine learning models could quantify the complexity of decision-making that the messages contained with 0.59, 0.45, and 0.58 for macro, micro, and weighted precision and 0.63,0.41, and 0.63 for macro, micro, and weighted recall. CONCLUSIONS: This study is one of the first to attempt to classify patient portal messages by whether they involve medical decision-making and the complexity of that decision-making. Machine learning classifiers trained on message content resulted in better message thread classification than classifiers that employed medical terms in the messages alone.

Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization.

BACKGROUND: The extent to which obesity and genetics determine postoperative complications is incompletely understood. METHODS: We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components. RESULTS: Individuals with overweight or obese BMI (≥25 kg/m2) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10-20), and people with obesity (BMI ≥ 30 kg/m2) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10-5). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10-6) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10-6). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures. CONCLUSIONS: Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.

Care Delivered by Pediatric Surgical Specialties Through Patient Portal Messaging.

BACKGROUND: Patient portals are online applications that typically allow users to interact with providers using secure messaging. Portal messaging use and content have not been studied in pediatric surgical specialties. MATERIALS AND METHODS: We obtained all message threads initiated by pediatric patients/caregivers and sent to pediatric surgical providers through the Vanderbilt University Medical Center patient portal from June 1, 2014 to December 31, 2014. We collected patient demographics and providers' surgical specialties. We determined the number of message threads and individual messages sent by patients/caregivers and providers by specialty. Message content was analyzed by semantic types using a validated consumer health taxonomy. RESULTS: Most threads were about male (176, 60.3%), white (239, 81.8%), non-Hispanic (278, 95.2%) patients with a median age of 6 y (range: 0-21 y). A total of 292 message threads containing 1679 individual messages were sent with mean 5.8 (standard deviation [SD] 5.0) messages per thread. Messages were sent more frequently regarding younger patients (P = 0.001). Physicians directly contributed to 161 (55%) message threads. Otolaryngology received the most threads (123, 42.1%) and messages (790, 47.1%). Specialties exchanging the most messages per thread were cardiac surgery (mean 7.0, SD 11.7), and dermatology (7.0, SD 6.9). Most message threads (273, 93.5%) involved delivery of medical care with 123 (42.1%) involving appointments/scheduling; 99 (33.9%) medical problems; 81 (27.7%) treatments; 68 (23.3%) testing; and 29 (9.9%) referrals. CONCLUSIONS: Pediatric surgeons deliver substantial care within portal messages exchanged with pediatric patients and caregivers. Institutions adopting portals should consider effects on provider workload and potential disparities in access to care.

Complexity of medical decision-making in care provided by surgeons through patient portals.

BACKGROUND: Patient portals are online applications that allow patients to interact with healthcare organizations and view information. Portal messages exchanged between patients and providers contain diverse types of communications, including delivery of medical care. The types of communications and complexity of medical decision-making in portal messages sent to surgeons have not been studied. MATERIALS AND METHODS: We obtained all message threads initiated by patients and exchanged with surgical providers through the Vanderbilt University Medical Center patient portal from June 1 to December 31, 2014. Five hundred randomly selected messages were manually analyzed by two research team members to determine the types of communication (i.e., informational, medical, logistical, or social), whether medical care was delivered, and complexity of medical decision-making as defined for outpatient billing in each message thread. RESULTS: A total of 9408 message threads were sent to 401 surgical providers during the study period. In the 500 threads selected for detailed analysis, 1293 distinct issues were communicated, with an average of 2.6 issues per thread. Medical needs were communicated in 453 message threads (90.6%). Further, 339 message threads (67.8%) contained medical decision-making. Overall complexity of medical decision-making was straightforward in 210 messages (62%), low in 102 messages (30%), and moderate in 27 messages (8%). No highly complex decisions were made over portal messaging. CONCLUSIONS: Through patient portal messages, surgeons deliver substantial medical care with varied levels of medical complexity. Models for compensation of online care must be developed as consumer and surgeon adoption of these technologies increases.

Review of information technology for surgical patient care.

BACKGROUND: Electronic health records (EHRs), computerized provider order entry (CPOE), and patient portals have experienced increased adoption by health care systems. The objective of this study was to review evidence regarding the impact of such health information technologies (HIT) on surgical practice. MATERIALS AND METHODS: A search of Medline, EMBASE, CINAHL, and the Cochrane Library was performed to identify data-driven, nonsurvey studies about the effects of HIT on surgical care. Domain experts were queried for relevant articles. Two authors independently reviewed abstracts for inclusion criteria and analyzed full text of eligible articles. RESULTS: A total of 2890 citations were identified. Of them, 32 observational studies and two randomized controlled trials met eligibility criteria. EHR or CPOE improved appropriate antibiotic administration for surgical procedures in 13 comparative observational studies. Five comparative observational studies indicated that electronically generated operative notes had increased accuracy, completeness, and availability in the medical record. The Internet as an information resource about surgical procedures was generally inadequate. Surgical patients and providers demonstrated rapid adoption of patient portals, with increasing proportions of online versus inperson outpatient surgical encounters. CONCLUSIONS: The overall quality of evidence about the effects of HIT in surgical practice was low. Current data suggest an improvement in appropriate perioperative antibiotic administration and accuracy of operative reports from CPOE and EHR applications. Online consumer health educational resources and patient portals are popular among patients and families, but their impact has not been studied well in surgical populations. With increasing adoption of HIT, further research is needed to optimize the efficacy of such tools in surgical care.

Fundamental Use of Surgical Energy (FUSE) certification: validation and predictors of success.

INTRODUCTION: The Fundamental Use of Surgical Energy (FUSE) program includes a Web-based didactic curriculum and a high-stakes multiple-choice question examination with the goal to provide certification of knowledge on the safe use of surgical energy-based devices. The purpose of this study was (1) to set a passing score through a psychometrically sound process and (2) to determine what pretest factors predicted passing the FUSE examination. METHODS: Beta-testing of multiple-choice questions on 62 topics of importance to the safe use of surgical energy-based devices was performed. Eligible test takers were physicians with a minimum of 1 year of surgical training who were recruited by FUSE task force members. A pretest survey collected baseline information. RESULTS: A total of 227 individuals completed the FUSE beta-test, and 208 completed the pretest survey. The passing/cut score for the first test form of the FUSE multiple-choice examination was determined using the modified Angoff methodology and for the second test form was determined using a linear equating methodology. The overall passing rate across the two examination forms was 81.5%. Self-reported time studying the FUSE Web-based curriculum for a minimum of >2 h was associated with a passing examination score (p < 0.001). Performance was not different based on increased years of surgical practice (p = 0.363), self-reported expertise on one or more types of energy-based devices (p = 0.683), participation in the FUSE postgraduate course (p = 0.426), or having reviewed the FUSE manual (p = 0.428). Logistic regression found that studying the FUSE didactics for >2 h predicted a passing score (OR 3.61; 95% CI 1.44-9.05; p = 0.006) independent of the other baseline characteristics recorded. CONCLUSION(S): The development of the FUSE examination, including the passing score, followed a psychometrically sound process. Self-reported time studying the FUSE curriculum predicted a passing score independent of other pretest characteristics such as years in practice and self-reported expertise.

National learning curves among robotic thoracic surgeons in the United States: Quantifying the impact of procedural experience on efficiency and productivity gains.

OBJECTIVE: This study aims to characterize the aggregate learning curves of US surgeons for robotic thoracic procedures and to quantify the impact on productivity. METHODS: National average console times relative to cumulative case number were extracted from the My Intuitive application (Version 1.7.0). Intuitive da Vinci robotic system data for 56,668 lung resections performed by 870 individual surgeons between 2021 and 2022 were reviewed. Console time and hourly productivity (work relative value units/hour) were analyzed using linear regression models. RESULTS: Average console times improved for all robotic procedures with cumulative case experience (P = .003). Segmentectomy and thymectomy had the steepest initial learning curves with a 33% and 34% reduction of the average console time for proficient (51-100 cases) relative to novice surgeons (1-10 cases), respectively. The hourly productivity increase for proficient surgeons ranged from 11.4 work relative value units/hour (+26%) for lobectomy to 17.0 work relative value units/hour (+50%) for segmentectomy. At the expert level (101+ cases), average console times continued to decrease significantly for esophagectomy (-18%) and lobectomy (-23%), but only minimally for wedge resections (-1%) (P = .003). The work relative value units/hour increase at the expert level reached 50% for lobectomy and 40% for esophagectomy. Surgeon experience level, dual console use, system model, and robotic stapler use were factors independently associated with console time for robotic lobectomy. CONCLUSIONS: The aggregate learning curve for robotic thoracic surgeons in the United States varies significantly by procedure type and demonstrate continued improvements in efficiency beyond 100 cases for lobectomy and esophagectomy. Improvements in efficiency with growing experiences translate to substantial productivity gains.

Competencies for the Use of Artificial Intelligence-Based Tools by Health Care Professionals.

PURPOSE: The expanded use of clinical tools that incorporate artificial intelligence (AI) methods has generated calls for specific competencies for effective and ethical use. This qualitative study used expert interviews to define AI-related clinical competencies for health care professionals. METHOD: In 2021, a multidisciplinary team interviewed 15 experts in the use of AI-based tools in health care settings about the clinical competencies health care professionals need to work effectively with such tools. Transcripts of the semistructured interviews were coded and thematically analyzed. Draft competency statements were developed and provided to the experts for feedback. The competencies were finalized using a consensus process across the research team. RESULTS: Six competency domain statements and 25 subcompetencies were formulated from the thematic analysis. The competency domain statements are: (1) basic knowledge of AI: explain what AI is and describe its health care applications; (2) social and ethical implications of AI: explain how social, economic, and political systems influence AI-based tools and how these relationships impact justice, equity, and ethics; (3) AI-enhanced clinical encounters: carry out AI-enhanced clinical encounters that integrate diverse sources of information in creating patient-centered care plans; (4) evidence-based evaluation of AI-based tools: evaluate the quality, accuracy, safety, contextual appropriateness, and biases of AI-based tools and their underlying data sets in providing care to patients and populations; (5) workflow analysis for AI-based tools: analyze and adapt to changes in teams, roles, responsibilities, and workflows resulting from implementation of AI-based tools; and (6) practice-based learning and improvement regarding AI-based tools: participate in continuing professional development and practice-based improvement activities related to use of AI tools in health care. CONCLUSIONS: The 6 clinical competencies identified can be used to guide future teaching and learning programs to maximize the potential benefits of AI-based tools and diminish potential harms.

Mutational profiles of head and neck squamous cell carcinomas based upon human papillomavirus status in the Veterans Affairs National Precision Oncology Program.

BACKGROUND: Patients with advanced head and neck squamous cell carcinoma (HNSCC) associated with human papillomavirus (HPV) demonstrate favorable clinical outcomes compared to patients bearing HPV-negative HNSCC. We sought to characterize the association between HPV status and mutational profiles among patients served by the Veterans Health Administration (VHA). METHODS: We performed a retrospective analysis of all Veterans with primary HNSCC tumors who underwent next-generation sequencing (NGS) through the VHA's National Precision Oncology Program between July 2016 and February 2019. HPV status was determined by clinical pathology reports of p16 immunohistochemical staining; gene variant pathogenicity was classified using OncoKB, an online precision oncology knowledge database, and mutation frequencies were compared using Fisher's exact test. RESULTS: A total of 79 patients met inclusion criteria, of which 48 (60.8%) had p16-positive tumors. Patients with p16-negative HNSCC were more likely to have mutations in TP53 (p < 0.0001), and a trend towards increased mutation frequency was observed within NOTCH1 (p = 0.032) and within the composite CDK/Rb pathway (p = 0.065). Mutations in KRAS, NRAS, HRAS, and FBXW7 were exclusively identified within p16-positive tumors, and a trend towards increased frequency was observed within the PI3K pathway (p = 0.051). No difference in overall mutational burden was observed between the two groups. CONCLUSIONS: In accordance with the previous studies, no clear molecular basis for improved prognosis among patients harboring HPV-positive disease has been elucidated. Though no targeted therapies are approved based upon HPV-status, current efforts to trial PI3K inhibitors and mTOR inhibitors across patients with HPV-positive disease bear genomic rationale based upon the current findings.

A tribute to Karen Greenwood and her contributions to the American Medical Informatics Association.

After 25 years of service to the American Medical Informatics Association (AMIA), Ms Karen Greenwood, the Executive Vice President and Chief Operating Officer, is leaving the organization. In this perspective, we reflect on her accomplishments and her effect on the organization and the field of informatics nationally and globally. We also express our appreciation and gratitude for Ms Greenwood's role at AMIA.

Electronic Patient Portal Access, Retention in Care, and Viral Suppression Among People Living With HIV in Southeastern United States: Observational Study.

BACKGROUND: Approximately 1.1 million people living with HIV live in the United States, and the incidence is highest in Southeastern United States. Electronic patient portal prevalence is increasing and can improve engagement in primary medical care. Retention in care and viral suppression-measures of engagement in HIV care-are associated with decreased HIV transmission, morbidity, and mortality. OBJECTIVE: We aimed to determine if patient portal access among people living with HIV was associated with retention and viral suppression. METHODS: We conducted an observational cohort study among people living with HIV in care at the Vanderbilt Comprehensive Care Clinic (Nashville, Tennessee) from 2011-2016. Individual access was defined as patient portal account registration at any point in the year prior. Retention was defined as ≥2 kept appointments or HIV lab measurements ≥3 months apart within a 12-month period. Viral suppression was defined as the last viral load in the calendar year <200 copies/mL. We calculated adjusted prevalence ratios (aPRs) and 95% CIs using modified Poisson regression with generalized estimating equations to estimate the association of portal access with retention and viral suppression. RESULTS: We included 4237 people living with HIV contributing 16,951 person-years of follow-up (median 5, IQR 3-5 person-years). The median age was 43 (IQR 33-50) years. Of the 4237 people living with HIV, 78.1% (n=4237) were male, 40.8% (n=1727) were Black non-Hispanic, and 56.5% (n=2395) had access. Access was independently associated with retention (aPR 1.13, 95% CI 1.10-1.17) and viral suppression (aPR 1.18, 95% CI 1.14-1.22). CONCLUSIONS: In this population, patient portal access was associated with retention and viral suppression. Future prospective studies should assess the impact of increasing portal access among people living with HIV on these HIV outcomes.

Understanding a Care Management System's Role in Influencing a Transitional-Aged Youth Program's Practice: Mixed Methods Study.

BACKGROUND: Extended foster care programs help prepare transitional-aged youth (TAY) to step into adulthood and live independent lives. Aspiranet, one of California's largest social service organizations, used a social care management solution (SCMS) to meet TAY's needs. OBJECTIVE: We aimed to investigate the impact of an SCMS, IBM Watson Care Manager (WCM), in transforming foster program service delivery and improving TAY outcomes. METHODS: We used a mixed methods study design by collecting primary data from stakeholders through semistructured interviews in 2021 and by pulling secondary data from annual reports, system use logs, and data repositories from 2014 to 2021. Thematic analysis based on grounded theory was used to analyze qualitative data using NVivo software. Descriptive analysis of aggregated outcome metrics in the quantitative data was performed and compared across 2 periods: pre-SCMS implementation (before October 31, 2016) and post-SCMS implementation (November 1, 2016, and March 31, 2021). RESULTS: In total, 6 Aspiranet employees (4 leaders and 2 life coaches) were interviewed, with a median time of 56 (IQR 53-67) minutes. The majority (5/6, 83%) were female, over 30 years of age (median 37, IQR 32-39) with a median of 6 (IQR 5-10) years of experience at Aspiranet and overall field experience of 10 (IQR 7-14) years. Most (4/6, 67%) participants rated their technological skills as expert. Thematic analysis of participants' interview transcripts yielded 24 subthemes that were grouped into 6 superordinate themes: study context, the impact of the new tool, key strengths, commonly used features, expectations with WCM, and limitations and recommendations. The tool met users' initial expectations of streamlining tasks and adopting essential functionalities. Median satisfaction scores around pre- and post-WCM workflow processes remained constant between 2 life coaches (3.25, IQR 2.5-4); however, among leaders, post-WCM scores (median 4, IQR 4-5) were higher than pre-WCM scores (median 3, IQR 3-3). Across the 2 study phases, Aspiranet served 1641 TAY having consistent population demographics (median age of 18, IQR 18-19 years; female: 903/1641, 55.03%; race and ethnicity: Hispanic or Latino: 621/1641, 37.84%; Black: 470/1641, 28.64%; White: 397/1641, 24.19%; Other: 153/1641, 9.32%). Between the pre- and post-WCM period, there was an increase in full-time school enrollment (359/531, 67.6% to 833/1110, 75.04%) and a reduction in part-time school enrollment (61/531, 11.5% to 91/1110, 8.2%). The median number of days spent in the foster care program remained the same (247, IQR 125-468 years); however, the number of incidents reported monthly per hundred youth showed a steady decline, even with an exponentially increasing number of enrolled youth and incidents. CONCLUSIONS: The SCMS for coordinating care and delivering tailored services to TAY streamlined Aspiranet's workflows and processes and positively impacted youth outcomes. Further enhancements are needed to better align with user and youth needs.

SARS-CoV-2 Testing of Aerosols Emitted During Pediatric Minimally Invasive Surgery: A Prospective, Case-Controlled Study.

BACKGROUND: The COVID-19 pandemic has presented significant safety concerns for healthcare providers, especially those performing aerosol-generating procedures. Several surgical societies issued early warnings that aerosols generated during minimally invasive surgery (MIS) could harbor infectious quantities of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This study tested the hypothesis that MIS-aerosols contain SARS-CoV-2. METHODS: To evaluate SARS-CoV-2 presence in aerosols emitted during intracavitary MIS, children <18 years who required emergent MIS and were discovered to be SARS-CoV-2-positive were enrolled. Swabs were obtained from the port in-line with a filtered smoke evacuation system, the tubing adjacent to this port, the fluid collection chamber and filter, and the distal endotracheal tube (ETT). All swabs were analyzed for SARS-CoV-2 using quantitative reverse-transcription polymerase chain reaction. To evaluate viral distribution in tissues, fluorescence in situ hybridization for SARS-CoV-2 was performed on resected specimens. Outcomes were recorded, and participating healthcare workers were tracked for SARS-CoV-2 conversion. RESULTS: From July 1, 2020, to June 30, 2021, 11 children requiring emergent MIS were discovered preoperatively to be SARS-CoV-2 positive (median age: 14 years [5-17]). SARS-CoV-2 was detected only in ETT swabs and not in surgical aerosols or specimens. Median operative time was 56.5 minutes (IQR: 46-66), and postoperative stay was 21.2 hours (IQR: 1.97-57.57). No complications or viral eruption were recorded, and none of 63 healthcare workers tested positive for SARS-CoV-2 within 6 weeks. DISCUSSION: SARS-CoV-2 was detected only in ETT secretions and not in surgical aerosols or specimens among a pediatric cohort of asymptomatic patients having emergent MIS.

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics.

OBJECTIVE: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach. METHODS: This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank. RESULTS: Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux. CONCLUSIONS: This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

The burden of the digital environment: a systematic review on organization-directed workplace interventions to mitigate physician burnout.

OBJECTIVE: To conduct a systematic review identifying workplace interventions that mitigate physician burnout related to the digital environment including health information technologies (eg, electronic health records) and decision support systems) with or without the application of advanced analytics for clinical care. MATERIALS AND METHODS: Literature published from January 1, 2007 to June 3, 2020 was systematically reviewed from multiple databases and hand searches. Subgroup analysis identified relevant physician burnout studies with interventions examining digital tool burden, related workflow inefficiencies, and measures of burnout, stress, or job satisfaction in all practice settings. RESULTS: The search strategy identified 4806 citations of which 81 met inclusion criteria. Thirty-eight studies reported interventions to decrease digital tool burden. Sixty-eight percent of these studies reported improvement in burnout and/or its proxy measures. Burnout was decreased by interventions that optimized technologies (primarily electronic health records), provided training, reduced documentation and task time, expanded the care team, and leveraged quality improvement processes in workflows. DISCUSSION: The contribution of digital tools to physician burnout can be mitigated by careful examination of usability, introducing technologies to save or optimize time, and applying quality improvement to workflows. CONCLUSION: Physician burnout is not reduced by technology implementation but can be mitigated by technology and workflow optimization, training, team expansion, and careful consideration of factors affecting burnout, including specialty, practice setting, regulatory pressures, and how physicians spend their time.

Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research.

PURPOSE: We developed a system to automate analysis of the clinical oncology scientific literature from bibliographic databases and match articles to specific patient cohorts to answer specific questions regarding the efficacy of a treatment. The approach attempts to replicate a clinician's mental processes when reviewing published literature in the context of a patient case. We describe the system and evaluate its performance. METHODS: We developed separate ground truth data sets for each of the tasks described in the paper. The first ground truth was used to measure the natural language processing (NLP) accuracy from approximately 1,300 papers covering approximately 3,100 statements and approximately 25 concepts; performance was evaluated using a standard F1 score. The ground truth for the expert classifier model was generated by dividing papers cited in clinical guidelines into a training set and a test set in an 80:20 ratio, and performance was evaluated for accuracy, sensitivity, and specificity. RESULTS: The NLP models were able to identify individual attributes with a 0.7-0.9 F1 score, depending on the attribute of interest. The expert classifier machine learning model was able to classify the individual records with a 0.93 accuracy (95% CI, 0.9 to 0.96, P < .0001), and sensitivity and specificity of 0.95 and 0.91, respectively. Using a decision boundary of 0.5 for the positive (expert) label, the classifier demonstrated an F1 score of 0.92. CONCLUSION: The system identified and extracted evidence from the oncology literature with a high degree of accuracy, sensitivity, and specificity. This tool enables timely access to the most relevant biomedical literature, providing critical support to evidence-based practice in areas of rapidly evolving science.

Effectiveness of non-pharmaceutical interventions related to social distancing on respiratory viral infectious disease outcomes: A rapid evidence-based review and meta-analysis.

OBJECTIVES: Non-pharmaceutical interventions (e.g. quarantine and isolation) are used to mitigate and control viral infectious disease, but their effectiveness has not been well studied. For COVID-19, disease control efforts will rely on non-pharmaceutical interventions until pharmaceutical interventions become widely available, while non-pharmaceutical interventions will be of continued importance thereafter. METHODS: This rapid evidence-based review provides both qualitative and quantitative analyses of the effectiveness of social distancing non-pharmaceutical interventions on disease outcomes. Literature was retrieved from MEDLINE, Google Scholar, and pre-print databases (BioRxiv.org, MedRxiv.org, and Wellcome Open Research). RESULTS: Twenty-eight studies met inclusion criteria (n = 28). Early, sustained, and combined application of various non-pharmaceutical interventions could mitigate and control primary outbreaks and prevent more severe secondary or tertiary outbreaks. The strategic use of non-pharmaceutical interventions decreased incidence, transmission, and/or mortality across all interventions examined. The pooled attack rates for no non-pharmaceutical intervention, single non-pharmaceutical interventions, and multiple non-pharmaceutical interventions were 42% (95% confidence interval = 30% - 55%), 29% (95% confidence interval = 23% - 36%), and 22% (95% confidence interval = 16% - 29%), respectively. CONCLUSION: Implementation of multiple non-pharmaceutical interventions at key decision points for public health could effectively facilitate disease mitigation and suppression until pharmaceutical interventions become available. Dynamics around R 0 values, the susceptibility of certain high-risk patient groups to infection, and the probability of asymptomatic cases spreading disease should be considered.