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Background: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging., Objectives: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients., Materials and Methods: In May 2023, the Division of Clinical Informatics at Beth Israel Deaconess Medical Center and the American Medical Informatics Association co-sponsored a working group on AI in healthcare. In August 2023, there were 4 webinars on AI topics and a 2-day workshop in September 2023 for consensus-building. The event included over 200 industry stakeholders, including clinicians, software developers, academics, ethicists, attorneys, government policy experts, scientists, and patients. The goal was to identify challenges associated with the trusted use of AI-enabled CDS in medical practice. Key issues were identified, and solutions were proposed through qualitative analysis and a 4-month iterative consensus process., Results: Our work culminated in several key recommendations: (1) building safe and trustworthy systems; (2) developing validation, verification, and certification processes for AI-CDS systems; (3) providing a means of safety monitoring and reporting at the national level; and (4) ensuring that appropriate documentation and end-user training are provided., Discussion: AI-enabled Clinical Decision Support (AI-CDS) systems promise to revolutionize healthcare decision-making, necessitating a comprehensive framework for their development, implementation, and regulation that emphasizes trustworthiness, transparency, and safety. This framework encompasses various aspects including model training, explainability, validation, certification, monitoring, and continuous evaluation, while also addressing challenges such as data privacy, fairness, and the need for regulatory oversight to ensure responsible integration of AI into clinical workflow., Conclusions: Achieving responsible AI-CDS systems requires a collective effort from many healthcare stakeholders. This involves implementing robust safety, monitoring, and transparency measures while fostering innovation. Future steps include testing and piloting proposed trust mechanisms, such as safety reporting protocols, and establishing best practice guidelines., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Introduction: Robotic surgery continues to drive evolution in minimally invasive surgery. Due to the confined operative fields encountered, pediatric surgeons may uniquely benefit from the precise control offered by robotic technologies compared to open and laparoscopic techniques. We describe a unique collaborative implementation of robotic surgery into an academic pediatric surgery practice through adult robotic surgeon partnership. We compare robotic cholecystectomy (RC) and laparoscopic cholecystectomy (LC) outcomes, hypothesizing that RC will be equivalent to LC in key quality outcomes., Methods: We evaluate 14 mo of systems development and training, and 24 mo of collaborative operative experience evoking a purposeful tiered case progression, establishing core robotic competencies, prior to advancing operative complexity. Univariate analyses compared LC versus RC., Results: 36 robotic operations were performed in children aged 8-18 y, in a tiered progression from 24 cholecystectomies to 2 ileocecectomies, 2 paraesophageal hernia repairs, 1 anterior rectopexy, 1 spleen-preserving distal pancreatectomy, 1 Heller myotomy, 1 choledochal cyst resection with roux-en-y hepaticojejunostomy, 1 median arcuate ligament release, and 1 thoracic esophageal duplication cyst resection. For LC and RC, there were no significant differences in procedure duration, discharge opioids, hospital readmission, or rates of surgical site infection or bile duct injury., Conclusions: Robotic surgery has potential to significantly enhance pediatric surgery. RC appears equivalent to LC but presents multiple additional theoretical benefits in pediatric patients. Our pilot program experience supports the feasibility and safety of pediatric robotic surgery. We emphasize the importance of a stepwise progression in operative difficulty and collaboration with adult robotic surgery experts., (Copyright © 2024. Published by Elsevier Inc.)

Rationale: Charge transfer dissociation (CTD) is a novel fragmentation technique that demonstrates enhanced structural characterization for a wide variety of molecules compared to standard fragmentation techniques like collision-induced dissociation (CID). Alternative fragmentation techniques, such as electron transfer dissociation, electron capture dissociation, and ultraviolet photodissociation, also overcome many of the shortfalls of CID, but none of them are a silver bullet that can adequately characterize a wide variety of structures and charge states of target compounds. Given the diversity of structural classes and their occasional obstinance towards certain activation techniques, alternative fragmentation techniques are required that rely on novel or alternative modes of activation., Methods: Herein, we present a step-by-step protocol for the installation of CTD on a quadrupole ion trap mass spectrometer and best practices for optimizing the signal-to-noise ratio and acquisition times for CTD mass spectra., Results: In addition to two CTD installations in the Jackson laboratory, CTD has also been installed, and is currently in operation, on two 3D ion trap mass spectrometers in France: one in the laboratory of Dr. David Ropartz and Dr. Hélène Rogneaux at INRAE in Nantes, and the other in the laboratory of Dr. Jean-Yves Salpin at Université d'Évry Val-d'Essonne, part of the Paris-Saclay University system., Conclusions: Here, we provide a visual protocol to help others accomplish the instrument modification., (© 2024 Triad National Security and The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Objective: The COVID-19 pandemic presented a challenge to inpatient safety. It is unknown whether there were spillover effects due to COVID-19 into non-COVID-19 care and safety. We sought to evaluate the changes in inpatient Agency for Healthcare Research and Quality patient safety indicators (PSIs) in the United States before and during the first surge of the pandemic among patients admitted without COVID-19., Methods: We analyzed trends in PSIs from January 2019 to June 2020 in patients without COVID-19 using data from IBM MarketScan Commercial Database. We included members of employer-sponsored or Medicare supplemental health plans with inpatient, non-COVID-19 admissions. The primary outcomes were risk-adjusted composite and individual PSIs., Results: We analyzed 1,869,430 patients admitted without COVID-19. Among patients without COVID-19, the composite PSI score was not significantly different when comparing the first surge (Q2 2020) to the prepandemic period (e.g., Q2 2020 score of 2.46 [95% confidence interval {CI}, 2.34-2.58] versus Q1 2020 score of 2.37 [95% CI, 2.27-2.46]; P = 0.22). Individual PSIs for these patients during Q2 2020 were also not significantly different, except in-hospital fall with hip fracture (e.g., Q2 2020 was 3.42 [95% CI, 3.34-3.49] versus Q4 2019 was 2.45 [95% CI, 2.40-2.50]; P = 0.01)., Conclusions: The first surge of COVID-19 was not associated with worse inpatient safety for patients without COVID-19, highlighting the ability of the healthcare system to respond to the initial surge of the pandemic., Competing Interests: D.W.B. consults for EarlySense, which makes patient safety monitoring systems. He receives cash compensation from CDI (Negev), Ltd, which is a not-for-profit incubator for health IT startups. He receives equity from ValeraHealth, which makes software to help patients with chronic diseases. He receives equity from Clew, which makes software to support clinical decision making in intensive care. He receives equity from MDClone, which takes clinical data and produces deidentified versions of it. He receives equity from AESOP, which makes software to reduce medication error rates. He has received research funding from IBM Watson Health. D.W.B.’s financial interests have been reviewed by Brigham and Women’s Hospital and Partners HealthCare in accordance with their institutional policies. L.S. receives research funding from the National Institute of Diabetes and Digestive and Kidney Diseases (grant no. R01DK116898). The views expressed in this article are those of the authors and do not necessarily reflect the views and policy of the National Institutes of Health. K.N., H.H., Y.P., A.R., and G.P.J. are employees of IBM Corporation. The other authors disclose no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: Advances in informatics research come from academic, nonprofit, and for-profit industry organizations, and from academic-industry partnerships. While scientific studies of commercial products may offer critical lessons for the field, manuscripts authored by industry scientists are sometimes categorically rejected. We review historical context, community perceptions, and guidelines on informatics authorship., Process: We convened an expert panel at the American Medical Informatics Association 2022 Annual Symposium to explore the role of industry in informatics research and authorship with community input. The panel summarized session themes and prepared recommendations., Conclusions: Authorship for informatics research, regardless of affiliation, should be determined by International Committee of Medical Journal Editors uniform requirements for authorship. All authors meeting criteria should be included, and categorical rejection based on author affiliation is unethical. Informatics research should be evaluated based on its scientific rigor; all sources of bias and conflicts of interest should be addressed through disclosure and, when possible, methodological mitigation., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Delirium is a complex condition, stressful for all involved. Although highly prevalent in palliative care settings, it remains underdiagnosed and associated with poor outcomes. Guideline-adherent delirium care may improve its detection, assessment and management., Aim: To inform a future definitive study that tests whether an implementation strategy designed to improve guideline-adherent delirium care in palliative care settings improves patient outcomes (reduced proportion of in-patient days with delirium)., Design: With Patient Involvement members, we conducted a feasibility study to assess the acceptability of and engagement with the implementation strategy by hospice staff (intervention), and whether clinical record data collection of process (e.g. guideline-adherent delirium care) and clinical outcomes (evidence of delirium using a validated chart-based instrument;) pre- and 12-weeks post-implementation of the intervention would be possible., Setting/participants: In-patient admissions in three English hospices., Results: Between June 2021 and December 2022, clinical record data were extracted from 300 consecutive admissions. Despite data collection during COVID-19, target clinical record data collection ( n  = 300) was achieved. Approximately two-thirds of patients had a delirium episode during in-patient stay at both timepoints. A 6% absolute reduction in proportion of delirium days in those with a delirium episode was observed. Post-implementation improvements in guideline-adherent metrics include: clinical delirium diagnosis 15%-28%; delirium risk assessment 0%-16%; screening on admission 7%-35%., Conclusions: Collection of data on delirium outcomes and guideline-adherence from clinical records is feasible. The signal of patient benefit supports formal evaluation in a large-scale study., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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., (Copyright © 2023 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)

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.., Competing Interests: G.P.J. is employed through IBM Watson Health., (Thieme. All rights reserved.)

This is the second of two manuscripts describing how general linear modeling (GLM) of a selection of the most abundant normalized fragment ion abundances of replicate mass spectra from one laboratory can be used in conjunction with binary classifiers to enable specific and selective identifications with reportable error rates of spectra from other laboratories. Here, the proof-of-concept uses a training set of 128 replicate cocaine spectra from one crime laboratory as the basis of GLM modeling. GLM models for the 20 most abundant fragments of cocaine were then applied to 175 additional test/validation cocaine spectra collected in more than a dozen crime laboratories and 716 known negative spectra, which included 10 spectra of three diastereomers of cocaine. Spectral similarity and dissimilarity between the measured and predicted abundances were assessed using a variety of conventional measures, including the mean absolute residual and NIST's spectral similarity score. For each spectral measure, GLM predictions were compared to the traditional exemplar approach, which used the average of the cocaine training set as the consensus spectrum for comparisons. In unsupervised models, EASI provided better than a 95% true positive rate for cocaine with a 0% false positive rate. A supervised binary logistic regression model provided 100% accuracy and no errors using EASI-predicted abundances of only four peaks at m / z 152, 198, 272, and 303. Regardless of the measure of spectral similarity, error rates for identifications using EASI were superior to the traditional exemplar/consensus approach. As a supervised binary classifier, EASI was more reliable than using Mahalanobis distances.

This study aims to resolve one of the longest-standing problems in mass spectrometry, which is how to accurately identify an organic substance from its mass spectrum when a spectrum of the suspected substance has not been analyzed contemporaneously on the same instrument. Part one of this two-part report describes how Rice-Ramsperger-Kassel-Marcus (RRKM) theory predicts that many branching ratios in replicate electron-ionization mass spectra will provide approximately linear correlations when analysis conditions change within or between instruments. Here, proof-of-concept general linear modeling is based on the 20 most abundant fragments in a database of 128 training spectra of cocaine collected over 6 months in an operational crime laboratory. The statistical validity of the approach is confirmed through both analysis of variance (ANOVA) of the regression models and assessment of the distributions of the residuals of the models. General linear modeling models typically explain more than 90% of the variance in normalized abundances. When the linear models from the training set are applied to 175 additional known positive cocaine spectra from more than 20 different laboratories, the linear models enabled ion abundances to be predicted with an accuracy of <2% relative to the base peak, even though the measured abundances vary by more than 30%. The same models were also applied to 716 known negative spectra, including the diastereomers of cocaine: allococaine, pseudococaine, and pseudoallococaine, and the residual errors were larger for the known negatives than for known positives. The second part of the manuscript describes how general linear regression modeling can serve as the basis for binary classification and reliable identification of cocaine from its diastereomers and all other known negatives.

Mass spectrometry has made profound contributions to the criminal justice system by providing an instrumental method of analysis that delivers exquisite analytical figures of merit for a wide variety of samples and analytes. Applications include the characterization of trace metal impurities in hair and glass to the identification of drugs, explosives, polymers, and ignitable liquids. This review describes major historical developments and, where possible, relates the developed capabilities to casework and legal precedents. This review also provides insight into how historical applications have evolved into, and out of, modern consensus standards. Unlike many pattern-based techniques and physical-matching methods, mass spectrometry has strong scientific foundations and a long history of successful applications that have made it one of the most reliable and respected sources of scientific evidence in criminal and civil cases. That said, in several appellate decisions in which mass spectrometric evidence was challenged but admitted, decisions sometimes still went against the mass spectrometric data anyway, which goes to show that mass spectrometric evidence is always just one piece of the larger legal puzzle.

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., Competing Interests: T.J.L. was supported by the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health under Award Number K23GM140268 and by the Thomas H. Maren Junior Investigator Fund. Y.R. is the founder of RightBMI, LLC, a company that has developed a fully automated responsive web software application that generates individualized and structured nutritional and exercise plans and adjusts antihypertensive and antidiabetic medications. He has received research grants from Lexington Medical, Heron Therapeutics, and Allurion Technologies. He is also in the Speaker Bureau of Heron Therapeutics. G.P.J. is an employee of Intuitive Surgical and a shareholder of Intuitive Surgical, IBM, and Kyndryl. The remaining authors declare no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Evidence-based point-of-care information (POCI) tools can facilitate patient safety and care by helping clinicians to answer disease state and drug information questions in less time and with less effort. However, these tools may also be visually challenging to navigate or lack the comprehensiveness needed to sufficiently address a medical issue., Objective: This study aimed to collect clinicians' feedback and directly observe their use of the combined POCI tool DynaMed and Micromedex with Watson, now known as DynaMedex. EBSCO partnered with IBM Watson Health, now known as Merative, to develop the combined tool as a resource for clinicians. We aimed to identify areas for refinement based on participant feedback and examine participant perceptions to inform further development., Methods: Participants (N=43) within varying clinical roles and specialties were recruited from Brigham and Women's Hospital and Massachusetts General Hospital in Boston, Massachusetts, United States, between August 10, 2021, and December 16, 2021, to take part in usability sessions aimed at evaluating the efficiency and effectiveness of, as well as satisfaction with, the DynaMed and Micromedex with Watson tool. Usability testing methods, including think aloud and observations of user behavior, were used to identify challenges regarding the combined tool. Data collection included measurements of time on task; task ease; satisfaction with the answer; posttest feedback on likes, dislikes, and perceived reliability of the tool; and interest in recommending the tool to a colleague., Results: On a 7-point Likert scale, pharmacists rated ease (mean 5.98, SD 1.38) and satisfaction (mean 6.31, SD 1.34) with the combined POCI tool higher than the physicians, nurse practitioner, and physician's assistants (ease: mean 5.57, SD 1.64, and satisfaction: mean 5.82, SD 1.60). Pharmacists spent longer (mean 2 minutes, 26 seconds, SD 1 minute, 41 seconds) on average finding an answer to their question than the physicians, nurse practitioner, and physician's assistants (mean 1 minute, 40 seconds, SD 1 minute, 23 seconds)., Conclusions: Overall, the tool performed well, but this usability evaluation identified multiple opportunities for improvement that would help inexperienced users., (©Angela Rui, Pamela M Garabedian, Marlika Marceau, Ania Syrowatka, Lynn A Volk, Heba H Edrees, Diane L Seger, Mary G Amato, Jacob Cambre, Sevan Dulgarian, Lisa P Newmark, Karen C Nanji, Petra Schultz, Gretchen Purcell Jackson, Ronen Rozenblum, David W Bates. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 17.04.2023.)

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., (Copyright © 2022 by the Association of American Medical Colleges.)

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., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

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., (©Rubina F Rizvi, Courtney B VanHouten, Van C Willis, Bedda L Rosario, Brett R South, Megan Sands-Lincoln, David Brotman, Jeffery Lenert, Jane L Snowdon, Gretchen P Jackson. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 16.12.2022.)

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., (© 2022 The Obesity Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Background: The first surge of the COVID-19 pandemic entirely altered healthcare delivery. Whether this also altered the receipt of high- and low-value care is unknown., Objective: To test the association between the April through June 2020 surge of COVID-19 and various high- and low-value care measures to determine how the delivery of care changed., Design: Difference in differences analysis, examining the difference in quality measures between the April through June 2020 surge quarter and the January through March 2020 quarter with the same 2 quarters' difference the year prior., Participants: Adults in the MarketScan® Commercial Database and Medicare Supplemental Database., Main Measures: Fifteen low-value and 16 high-value quality measures aggregated into 8 clinical quality composites (4 of these low-value)., Key Results: We analyzed 9,352,569 adults. Mean age was 44 years (SD, 15.03), 52% were female, and 75% were employed. Receipt of nearly every type of low-value care decreased during the surge. For example, low-value cancer screening decreased 0.86% (95% CI, -1.03 to -0.69). Use of opioid medications for back and neck pain (DiD +0.94 [95% CI, +0.82 to +1.07]) and use of opioid medications for headache (DiD +0.38 [95% CI, 0.07 to 0.69]) were the only two measures to increase. Nearly all high-value care measures also decreased. For example, high-value diabetes care decreased 9.75% (95% CI, -10.79 to -8.71)., Conclusions: The first COVID-19 surge was associated with receipt of less low-value care and substantially less high-value care for most measures, with the notable exception of increases in low-value opioid use., (© 2022. The Author(s), under exclusive licence to Society of General Internal Medicine.)

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.

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., (©Cassandra Oliver Schember, Sarah E Scott, Cathy A Jenkins, Peter F Rebeiro, Megan Turner, Sally S Furukawa, Carmen Bofill, Zhou Yan, Gretchen P Jackson, April C Pettit. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 25.07.2022.)

The combination of helium charge transfer dissociation mass spectrometry (He-CTD-MS) with ultrahigh performance liquid chromatography (UHPLC) is presented for the analysis of a complex mixture of acidic and neutral human milk oligosaccharides (HMOs). The research focuses on the identification of the monosaccharide sequence, the branching patterns, the sialylation/fucosylation arrangements, and the differentiation of isomeric oligosaccharides in the mixture. Initial studies first optimized the conditions for the UHPLC separation and the He-CTD-MS conditions. Results demonstrate that He-CTD is compatible with UHPLC timescales and provides unambiguous glycosidic and cross-ring cleavages from both the reducing and the nonreducing ends, which is not typically possible using collision-induced dissociation. He-CTD produces informative fragments, including 0,3An and 0,4An ions, which have been observed with electron transfer dissociation, electron detachment dissociation, and ultraviolet photodissociation (UVPD) and are crucial for differentiating the α-2,3- versus α-2,6-linked sialic acid (Neu5Ac) residues present among sialyllacto-N-tetraose HMOs. In addition to the linkage positions, He-CTD is able to differentiate structural isomers for both sialyllacto-N-tetraoses and lacto-N-fucopentaoses structures by providing unique, unambiguous cross-ring cleavages of types 0,2An, 0,2Xn, and 1,5An while preserving most of the labile Neu5Ac and fucose groups., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., (Published by Oxford University Press on behalf of the American Medical Informatics Association 2022. This work is written by a US Government employee and is in the public domain in the US.)

As technology continues to improve, health care systems have the opportunity to use a variety of innovative tools for decision-making, including artificial intelligence (AI) applications. However, there has been little research on the feasibility and efficacy of integrating AI systems into real-world clinical practice, especially from the perspectives of clinicians who use such tools. In this paper, we review physicians' perceptions of and satisfaction with an AI tool, Watson for Oncology, which is used for the treatment of cancer. Watson for Oncology has been implemented in several different settings, including Brazil, China, India, South Korea, and Mexico. By focusing on the implementation of an AI-based clinical decision support system for oncology, we aim to demonstrate how AI can be both beneficial and challenging for cancer management globally and particularly for low-middle-income countries. By doing so, we hope to highlight the need for additional research on user experience and the unique social, cultural, and political barriers to the successful implementation of AI in low-middle-income countries for cancer care., (©Srinivas Emani, Angela Rui, Hermano Alexandre Lima Rocha, Rubina F Rizvi, Sergio Ferreira Juaçaba, Gretchen Purcell Jackson, David W Bates. Originally published in JMIR Cancer (https://cancer.jmir.org), 07.04.2022.)

Research in natural products (NPs) has gained interest as drug developers turn to nature to combat problems with drug resistance, drug delivery, and emerging diseases. Whereas NPs offer a tantalizing source of new pharmacologically active compounds, their structural complexity presents a challenge for analytical characterization and organic synthesis. Of particular concern is the characterization of cyclic-, polycyclic-, or macrocyclic compounds. One example of endogenous compounds as inspiration for NP development are cobalamins, like vitamin B 12 . An example of exogenous NPs is the class of macrolides that includes erythromycin. Both classes of macrocycles feature analogues with a range of modifications on their macrocyclic cores, but because of their cyclic nature, they are generally resistant to fragmentation by collision-induced dissociation (CID). In the present work, charge-transfer dissociation (CTD) was employed, with or without supplemental collisional activation, to produce radical-driven, high-energy fragmentation products of different macrocyclic precursors. With the assistance of collisional activation of CTnoD products, CTD frequently cleaved two covalent bonds within the macrocycle cores to reveal rich, informative spectra that helped identify sites of modification and resolve structural analogues. In a third example of macrocycle fragmentation, CTD enabled an impurity in a biological sample to be characterized as a cyclic polymer of nylon-6,6. In each example, CTD spectra are starkly different from CID and are highly reminiscent of other high-energy fragmentation techniques like extreme ultraviolet dissociative photoionization (XUV-DPI) and electron ionization-induced dissociation (EID). The results indicate that CTD-MS is a useful tool for the characterization of natural and synthetic macrocycles.

Rationale: The function of a protein or the binding affinity of an antibody can be substantially altered by the replacement of leucine (Leu) with isoleucine (Ile), and vice versa, so the ability to identify the correct isomer using mass spectrometry can help resolve important biological questions. Tandem mass spectrometry approaches for Leu/Ile (Xle) discrimination have been developed, but they all have certain limitations., Methods: Four model peptides and two wild-type peptide sequences containing either Leu or Ile residues were subjected to charge transfer dissociation (CTD) mass spectrometry on a modified three-dimensional ion trap. The peptides were analyzed in both the 1+ and 2+ charge states, and the results were compared to conventional collision-induced dissociation spectra of the same peptides obtained using the same instrument., Results: CTD resulted in 100% sequence coverage for each of the studied peptides and provided a variety of side-chain cleavages, including d, w and v ions. Using CTD, reliable d and w ions of Xle residues were observed more than 80% of the time. When present, d ions are typically greater than 10% of the abundance of the corresponding a ions from which they derive, and w ions are typically more abundant than the z ions from which they derive., Conclusions: CTD has the benefit of being applicable to both 1+ and 2+ precursor ions, and the overall performance is comparable to that of other high-energy activation techniques like hot electron capture dissociation and UV photodissociation. CTD does not require chemical modifications of the precursor peptides, nor does it require additional levels of isolation and fragmentation., (© 2021 John Wiley & Sons Ltd.)

The ability to understand the function of a protein often relies on knowledge about its detailed structure. Sometimes, seemingly insignificant changes in the primary structure of a protein, like an amino acid substitution, can completely disrupt a protein's function. Long-lived proteins (LLPs), which can be found in critical areas of the human body, like the brain and eye, are especially susceptible to primary sequence alterations in the form of isomerization and epimerization. Because long-lived proteins do not have the corrective regeneration capabilities of most other proteins, points of isomerism and epimerization that accumulate within the proteins can severely hamper their functions and can lead to serious diseases like Alzheimer's disease, cancer and cataracts. Whereas tandem mass spectrometry (MS/MS) in the form of collision-induced dissociation (CID) generally excels at peptide characterization, MS/MS often struggles to pinpoint modifications within LLPs, especially when the differences are only isomeric or epimeric in nature. One of the most prevalent and difficult-to-identify modifications is that of aspartic acid between its four isomeric forms: L-Asp, L-isoAsp, D-Asp, and D-isoAsp. In this study, peptides containing isomers of Asp were analyzed by charge transfer dissociation (CTD) mass spectrometry to identify spectral features that could discriminate between the different isomers. For the four isomers of Asp in three model peptides, CTD produced diagnostic ions of the form c n +57 on the N-terminal side of iso-Asp residues, but not on the N-terminal side of Asp residues. Using CTD, the L- and D forms of Asp and isoAsp could also be differentiated based on the relative abundance of y - and z ions on the C-terminal side of Asp residues. Differentiation was accomplished through a chiral discrimination factor, R , which compares an ion ratio in a spectrum of one epimer or isomer to the same ion ratio in the spectrum of a different epimer or isomer. The R values obtained using CTD are as robust and statistically significant as other fragmentation techniques, like radical directed dissociation (RDD). In summary, the extent of backbone and side-chain fragments produced by CTD enabled the differentiation of isomers and epimers of Asp in a variety of peptides.

Competing Interests: Competing interests: DB reports grants and personal fees from EarlySense, personal fees from CDI Negev, equity from ValeraHealth, equity from Clew, equity from MDClone, personal fees and equity from AESOP, personal fees and equity from FeelBetter, and grants from IBM Watson Health, outside the submitted work. KR was employed by IBM Watson Health and now is employed by CVS Health. GPJ is employed by IBM Watson Health.

Ultra-high-performance liquid chromatography (UHPLC) with charge transfer dissociation mass spectrometry (CTD-MS) is presented for the analysis of a mixture of complex sulfated oligosaccharides. The mixture contained kappa (κ), iota (ι), and lambda (λ) carrageenans that contain anhydro bridges, different degrees of sulfation ranging from one to three per dimer, different positioning of the sulfate groups along the backbone, and varying degrees of polymerization (DP) between 4 and 12. Optimization studies using standard mixtures of carrageenans helped establish the optimal conditions for online UHPLC-CTD-MS/MS analysis. Optimization included (1) UHPLC conditions; (2) ion source conditions, such as the capillary voltage, drying gas and nebulizing gas temperature, and flow rate; and (3) CTD-MS conditions, including data-dependent CTD-MS. The UHPLC-CTD results were contrasted with UHPLC-CID results of the same mixture on the same instrument. Whereas CID tends to produce B/Y and C/Z ions with many neutral losses, CTD produced more abundant A/X ions and less abundant neutral losses, which enabled more confident structural detail. The results demonstrate that He-CTD is compatible with the timescale of UHPLC and provides more structural information about carrageenans compared to state-of-the-art methods like UHPLC-CID analysis., (© 2021. Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Contact tracing in association with quarantine and isolation is an important public health tool to control outbreaks of infectious diseases. This strategy has been widely implemented during the current COVID-19 pandemic. The effectiveness of this nonpharmaceutical intervention is largely dependent on social interactions within the population and its combination with other interventions. Given the high transmissibility of SARS-CoV-2, short serial intervals, and asymptomatic transmission patterns, the effectiveness of contact tracing for this novel viral agent is largely unknown., Objective: This study aims to identify and synthesize evidence regarding the effectiveness of contact tracing on infectious viral disease outcomes based on prior scientific literature., Methods: An evidence-based review was conducted to identify studies from the PubMed database, including preprint medRxiv server content, related to the effectiveness of contact tracing in viral outbreaks. The search dates were from database inception to July 24, 2020. Outcomes of interest included measures of incidence, transmission, hospitalization, and mortality., Results: Out of 159 unique records retrieved, 45 (28.3%) records were reviewed at the full-text level, and 24 (15.1%) records met all inclusion criteria. The studies included utilized mathematical modeling (n=14), observational (n=8), and systematic review (n=2) approaches. Only 2 studies considered digital contact tracing. Contact tracing was mostly evaluated in combination with other nonpharmaceutical interventions and/or pharmaceutical interventions. Although some degree of effectiveness in decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality was observed, these results were highly dependent on epidemic severity (R0 value), number of contacts traced (including presymptomatic and asymptomatic cases), timeliness, duration, and compliance with combined interventions (eg, isolation, quarantine, and treatment). Contact tracing effectiveness was particularly limited by logistical challenges associated with increased outbreak size and speed of infection spread., Conclusions: Timely deployment of contact tracing strategically layered with other nonpharmaceutical interventions could be an effective public health tool for mitigating and suppressing infectious outbreaks by decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality., (©Kelly Jean Thomas Craig, Rubina Rizvi, Van C Willis, William J Kassler, Gretchen Purcell Jackson. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 06.10.2021.)

Introduction: Clinicians rely on pharmacologic knowledge bases to answer medication questions and avoid potential adverse drug events. In late 2018, an artificial intelligence-based conversational agent, Watson Assistant (WA), was made available to online subscribers to the pharmacologic knowledge base, Micromedex®. WA allows users to ask medication-related questions in natural language. This study evaluated search method-dependent differences in the frequency of information accessed by traditional methods (keyword search and heading navigation) vs conversational agent search., Materials and Methods: We compared the proportion of information types accessed through the conversational agent to the proportion of analogous information types accessed by traditional methods during the first 6 months of 2020., Results: Addition of the conversational agent allowed early adopters to access 22 different information types contained in the 'quick answers' portion of the knowledge base. These information types were accessed 117,550 times with WA during the study period, compared to 33,649,651 times using traditional search methods. The distribution across information types differed by method employed (c 2 test, P < .0001). Single drug/dosing, FDA/non-FDA uses, adverse effects, and drug administration emerged as 4 of the top 5 information types accessed by either method. Intravenous compatibility was accessed more frequently using the conversational agent (7.7% vs. 0.6% for traditional methods), whereas dose adjustments were accessed more frequently via traditional methods (4.8% vs. 1.4% for WA)., Conclusion: In a widely used pharmacologic knowledge base, information accessed through conversational agents versus traditional methods differed. User-centered studies are needed to understand these differences., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Various samples of the Eastern oyster, Crassostrea virginica, were collected from five harvest bay areas in the Gulf of Mexico coastal waters of Florida (FL), Louisiana (LA) and Texas (TX). Cadmium and lead concentrations from the extracted whole-body soft tissues were analyzed by inductively coupled plasma-mass spectrometry (ICP-MS), and bulk δ13C and δ15N isotope ratios and amino-acid-specific δ13C values were analyzed via isotope ratio mass-spectrometry (IRMS). The combined data was subjected to multivariate statistical analysis to assess whether oysters could be linked to their harvest area. Results indicate that discriminant analysis using the δ13C values of five amino acids-serine, glycine, valine, lysine and phenylalanine-could discriminate oysters from two adjacent harvesting in Florida with 90% success rate, using leave-one-out cross validation. The combination of trace elements and isotope ratios could also predict geographic provenance of oysters with a success rate superior to the isolated use of each technique. The combinatory approach proposed in this study is a proof-of-concept that compound specific stable isotope analysis is a potential tool for oyster fisheries managers, wildlife, and food safety enforcement officers, as well as to forensics and ecology research areas, although significantly more work would need to be completed to fully validate the approach and achieve more reliable statistical results.

Alkali and alkaline earth metal adducts of a branched glycan, XXXG, were analyzed with helium charge transfer dissociation (He-CTD) and low-energy collision-induced dissociation (LE-CID) to investigate if metalation would impact the type of fragments generated and the structural characterization of the analyte. The studied adducts included 1+ and 2+ precursors involving one or more of the cations: H + , Na + , K + , Ca 2+ , and Mg 2+ . Regardless of the metal adduct, He-CTD generated abundant and numerous glycosidic and cross-ring cleavages that were structurally informative and able to identify the 1,4-linkage and 1,6-branching patterns. In contrast, the LE-CID spectra mainly contained glycosidic cleavages, consecutive fragments, and numerous neutral losses, which complicated spectral interpretation. LE-CID of [M + K + H] 2+ and [M + Na] + precursors generated a few cross-ring cleavages, but they were not sufficient to identify the 1,4-linkage and 1,6-branching pattern of the XXXG xyloglucan. He-CTD predominantly generated 1+ fragments from 1+ precursors and 2+ product ions from 2+ precursors, although both LE-CID and He-CTD were able to generate 1+ product ions from 2+ adducts of magnesium and calcium. The singly charged fragments derive from the loss of H + from the metalated product ions and the formation of a protonated complementary product ion; such observations are similar to previous reports for magnesium and calcium salts undergoing electron capture dissociation (ECD) activation. However, during He-CTD, the [M + Mg] 2+ precursor generated more singly charged product ions than [M + Ca] 2+ , either because Mg has a higher second ionization potential than Ca or because of conformational differences and the locations of the charging adducts during fragmentation. He-CTD of the [M + 2Na] 2+ and the [M + 2 K] 2+ precursors generated singly charged product ions from the loss of a sodium ion and potassium ion, respectively. In summary, although the metal ions influence the mass and charge state of the observed product ions, the metal ions had a negligible effect on the types of cross-ring cleavages observed., (© 2021 John Wiley & Sons, Ltd.)

Purpose: Next-generation sequencing (NGS) gene panels are frequently completed for patients with advanced non-small-cell lung cancer (NSCLC). Patients with highly actionable gene variants have improved outcomes and reduced toxicities with the use of corresponding targeted agents. We sought to identify barriers to targeted agent use within the Veterans Health Affairs' National Precision Oncology Program (NPOP)., Methods: A retrospective evaluation of patients with NSCLC who underwent NGS multigene panels through NPOP between July 2015 and February 2019 was conducted. Patients who were assigned level 1 or 2A evidence for oncogenic gene variants by an artificial intelligence offering (IBM Watson for Genomics [WfG]) and NPOP staff were selected. Antineoplastic drug prescriptions and provider notes were reviewed. Reasons for withholding targeted treatments were categorized., Results: Of 1,749 patients with NSCLC who successfully underwent NGS gene panel testing, 112 (6.4%) patients were assigned level 1 and/or 2A evidence for available targeted treatments by WfG and NPOP staff. All highly actionable gene variants were within ALK , BRAF , EGFR , ERBB2 , MET , RET , and ROS1 . Of these, 36 (32.1%) patients were not prescribed targeted agents. The three most common reasons were (1) patient did not carry a diagnosis of metastatic disease (33.3%), (2) treating provider did not comment on the NGS results (25.0%), and (3) provider felt that patient could not tolerate therapy (19.4%). No patients were denied access to level 1 or 2A targeted drugs because of rejection of a nonformulary drug request., Conclusion: A substantial minority of patients with NSCLC bearing highly actionable gene variants are not prescribed targeted agents. Further provider- and pathologist-directed educational efforts and implementation of health informatics systems to provide real-time decision support for test ordering and interpretation are needed., Competing Interests: Vishal VashisthaEmployment: UnitedHealthcare (I)Research Funding: IBM Watson HealthOther Relationship: IBMUncompensated Relationships: IBM Watson Health Pradeep J. PoonnenHonoraria: M3, Sermo Jane L. SnowdonEmployment: IBMStock and Other Ownership Interests: IBM Dilhan WeeraratneEmployment: IBM David BrotmanEmployment: IBM Gretchen P. JacksonEmployment: IBM, Vanderbilt University Medical CenterLeadership: IBM, American Medical Informatics AssociationStock and Other Ownership Interests: IBMSpeakers' Bureau: IBMResearch Funding: IBMTravel, Accommodations, Expenses: IBM Michael J. KelleyConsulting or Advisory Role: IBMResearch Funding: Novartis, AstraZeneca, Bristol-Myers Squibb, Regeneron, GenentechOther Relationship: IBMOpen Payments Link: https://openpaymentsdata.cms.gov/physician/827136No other potential conflicts of interest were reported.

Artificial intelligence (AI) represents a valuable tool that could be widely used to inform clinical and public health decision-making to effectively manage the impacts of a pandemic. The objective of this scoping review was to identify the key use cases for involving AI for pandemic preparedness and response from the peer-reviewed, preprint, and grey literature. The data synthesis had two parts: an in-depth review of studies that leveraged machine learning (ML) techniques and a limited review of studies that applied traditional modeling approaches. ML applications from the in-depth review were categorized into use cases related to public health and clinical practice, and narratively synthesized. One hundred eighty-three articles met the inclusion criteria for the in-depth review. Six key use cases were identified: forecasting infectious disease dynamics and effects of interventions; surveillance and outbreak detection; real-time monitoring of adherence to public health recommendations; real-time detection of influenza-like illness; triage and timely diagnosis of infections; and prognosis of illness and response to treatment. Data sources and types of ML that were useful varied by use case. The search identified 1167 articles that reported on traditional modeling approaches, which highlighted additional areas where ML could be leveraged for improving the accuracy of estimations or projections. Important ML-based solutions have been developed in response to pandemics, and particularly for COVID-19 but few were optimized for practical application early in the pandemic. These findings can support policymakers, clinicians, and other stakeholders in prioritizing research and development to support operationalization of AI for future pandemics.

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., Competing Interests: Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2021.)

In recent years, the field of artificial intelligence (AI) in oncology has grown exponentially. AI solutions have been developed to tackle a variety of cancer-related challenges. Medical institutions, hospital systems, and technology companies are developing AI tools aimed at supporting clinical decision making, increasing access to cancer care, and improving clinical efficiency while delivering safe, high-value oncology care. AI in oncology has demonstrated accurate technical performance in image analysis, predictive analytics, and precision oncology delivery. Yet, adoption of AI tools is not widespread, and the impact of AI on patient outcomes remains uncertain. Major barriers for AI implementation in oncology include biased and heterogeneous data, data management and collection burdens, a lack of standardized research reporting, insufficient clinical validation, workflow and user-design challenges, outdated regulatory and legal frameworks, and dynamic knowledge and data. Concrete actions that major stakeholders can take to overcome barriers to AI implementation in oncology include training and educating the oncology workforce in AI; standardizing data, model validation methods, and legal and safety regulations; funding and conducting future research; and developing, studying, and deploying AI tools through multidisciplinary collaboration., (© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Charge transfer dissociation mass spectrometry (CTD-MS) has been shown to induce high energy fragmentation of biological ions in the gas phase and provide fragmentation spectra similar to extreme ultraviolet photodissociation (XUVPD). To date, CTD has typically employed helium cations with kinetic energies between 4-10 keV to initiate radical-directed fragmentation of analytes. However, as a reagent, helium has recently been listed as a critical mineral that is becoming scarcer and more expensive, so this study explored the potential for using cheaper and more readily available reagent gases. A model peptide, bradykinin, and a model oligosaccharide, κ-carrageenan with a degree of polymerization of 4, were fragmented using a variety of CTD reagent gases, which included helium, hydrogen, oxygen, nitrogen, argon and lab air. The CTD results were also contrasted with low-energy collision-induced dissociation (LE-CID), which were collected on the same 3D ion trap. Using constant reagent ion fluxes and kinetic energies, all five alterative reagent gases generated remarkably consistent sequence coverage and fragmentation efficiencies relative to He-CTD, which suggests that the ionization energy of the reagent gas has a negligible effect on the activation of the biological ions. The CTD efficiencies of all the gases ranged from 11-13% for bradykinin and 7-8% for κ-carrageenan. Within these tight ranges, the abundance of the CTnoD peak of bradykinin and the efficiency of CTD fragmentation of bradykinin both correlated with the ionization energy of the CTD reagent gas, which suggests that resonant charge transfer plays a small role in the activation of this peptide. The majority of the excitation energy for bradykinin and for κ-carrageenan comes from an electron stopping mechanism, which is described by long-range interactions between the reagent cations and electrons in the highest occupied molecular orbitals (HOMOs) of the biological ions. The CTD spectra do not provide any evidence for covalently bound products between the biological ions and the more-reactive gases like hydrogen, oxygen and nitrogen, which implies that the high kinetic energies of the reagent ions make them unavailable for covalent reactions. This work demonstrates that any of the substitute reagent gases tested are viable options for future CTD-MS experiments., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Background: Screening patients for eligibility for clinical trials is labor intensive. It requires abstraction of data elements from multiple components of the longitudinal health record and matching them to inclusion and exclusion criteria for each trial. Artificial intelligence (AI) systems have been developed to improve the efficiency and accuracy of this process., Objective: This study aims to evaluate the ability of an AI clinical decision support system (CDSS) to identify eligible patients for a set of clinical trials., Methods: This study included the deidentified data from a cohort of patients with breast cancer seen at the medical oncology clinic of an academic medical center between May and July 2017 and assessed patient eligibility for 4 breast cancer clinical trials. CDSS eligibility screening performance was validated against manual screening. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for eligibility determinations were calculated. Disagreements between manual screeners and the CDSS were examined to identify sources of discrepancies. Interrater reliability between manual reviewers was analyzed using Cohen (pairwise) and Fleiss (three-way) κ, and the significance of differences was determined by Wilcoxon signed-rank test., Results: In total, 318 patients with breast cancer were included. Interrater reliability for manual screening ranged from 0.60-0.77, indicating substantial agreement. The overall accuracy of breast cancer trial eligibility determinations by the CDSS was 87.6%. CDSS sensitivity was 81.1% and specificity was 89%., Conclusions: The AI CDSS in this study demonstrated accuracy, sensitivity, and specificity of greater than 80% in determining the eligibility of patients for breast cancer clinical trials. CDSSs can accurately exclude ineligible patients for clinical trials and offer the potential to increase screening efficiency and accuracy. Additional research is needed to explore whether increased efficiency in screening and trial matching translates to improvements in trial enrollment, accruals, feasibility assessments, and cost., (©Tufia Haddad, Jane M Helgeson, Katharine E Pomerleau, Anita M Preininger, M Christopher Roebuck, Irene Dankwa-Mullan, Gretchen Purcell Jackson, Matthew P Goetz. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.03.2021.)

Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety of care. Major adverse events in healthcare include: healthcare-associated infections, adverse drug events, venous thromboembolism, surgical complications, pressure ulcers, falls, decompensation, and diagnostic errors. The objective of this scoping review was to summarize the relevant literature and evaluate the potential of AI to improve patient safety in these eight harm domains. A structured search was used to query MEDLINE for relevant articles. The scoping review identified studies that described the application of AI for prediction, prevention, or early detection of adverse events in each of the harm domains. The AI literature was narratively synthesized for each domain, and findings were considered in the context of incidence, cost, and preventability to make projections about the likelihood of AI improving safety. Three-hundred and ninety-two studies were included in the scoping review. The literature provided numerous examples of how AI has been applied within each of the eight harm domains using various techniques. The most common novel data were collected using different types of sensing technologies: vital sign monitoring, wearables, pressure sensors, and computer vision. There are significant opportunities to leverage AI and novel data sources to reduce the frequency of harm across all domains. We expect AI to have the greatest impact in areas where current strategies are not effective, and integration and complex analysis of novel, unstructured data are necessary to make accurate predictions; this applies specifically to adverse drug events, decompensation, and diagnostic errors.

The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. Although Adaptive CDS represents an expected progression from earlier work, the activities needed to appropriately manage and support the establishment and evolution of Adaptive CDS require new, coordinated initiatives and oversight that do not currently exist. In this AMIA position paper, the authors describe current and emerging challenges to the safe use of Adaptive CDS and lay out recommendations for the effective management and monitoring of Adaptive CDS., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: IBM(R) Watson for Oncology (WfO) is a clinical decision-support system (CDSS) that provides evidence-informed therapeutic options to cancer-treating clinicians. A panel of experienced oncologists compared CDSS treatment options to treatment decisions made by clinicians to characterize the quality of CDSS therapeutic options and decisions made in practice., Methods: This study included patients treated between 1/2017 and 7/2018 for breast, colon, lung, and rectal cancers at Bumrungrad International Hospital (BIH), Thailand. Treatments selected by clinicians were paired with therapeutic options presented by the CDSS and coded to mask the origin of options presented. The panel rated the acceptability of each treatment in the pair by consensus, with acceptability defined as compliant with BIH's institutional practices. Descriptive statistics characterized the study population and treatment-decision evaluations by cancer type and stage., Results: Nearly 60% (187) of 313 treatment pairs for breast, lung, colon, and rectal cancers were identical or equally acceptable, with 70% (219) of WfO therapeutic options identical to, or acceptable alternatives to, BIH therapy. In 30% of cases (94), 1 or both treatment options were rated as unacceptable. Of 32 cases where both WfO and BIH options were acceptable, WfO was preferred in 18 cases and BIH in 14 cases. Colorectal cancers exhibited the highest proportion of identical or equally acceptable treatments; stage IV cancers demonstrated the lowest., Conclusion: This study demonstrates that a system designed in the US to support, rather than replace, cancer-treating clinicians provides therapeutic options which are generally consistent with recommendations from oncologists outside the US., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

The rapidly evolving science about the Coronavirus Disease 2019 (COVID-19) pandemic created unprecedented health information needs and dramatic changes in policies globally. We describe a platform, Watson Assistant (WA), which has been used to develop conversational agents to deliver COVID-19 related information. We characterized the diverse use cases and implementations during the early pandemic and measured adoption through a number of users, messages sent, and conversational turns (ie, pairs of interactions between users and agents). Thirty-seven institutions in 9 countries deployed COVID-19 conversational agents with WA between March 30 and August 10, 2020, including 24 governmental agencies, 7 employers, 5 provider organizations, and 1 health plan. Over 6.8 million messages were delivered through the platform. The mean number of conversational turns per session ranged between 1.9 and 3.5. Our experience demonstrates that conversational technologies can be rapidly deployed for pandemic response and are adopted globally by a wide range of users., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

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., (©Rubina Rizvi, Courtney VanHouten, Tiffani J Bright, Mollie M McKillop, Shira Alevy, David Brotman, Megan Sands-Lincoln, Jane Snowdon, Barbie J Robinson, Carolyn Staats, Gretchen P Jackson, William J Kassler. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.03.2021.)

Pectins are natural polysaccharides made from galacturonic acid residues, and they are widely used as an excipient in food and pharmaceutical industries. The degree of methyl-esterification, the monomeric composition, and the linkage pattern are all important factors that influence the physical and chemical properties of pectins, such as the solubility. This work focuses on the successful online coupling of charge transfer dissociation-mass spectrometry (CTD-MS) with ultrahigh-performance liquid chromatography (UHPLC) to differentiate isomers of oligogalacturonans derived from citrus pectins. This work employed CTD fragmentation of the pectin mixtures in data-dependent acquisition mode. Compared to the UHPLC with collision-induced dissociation mass spectrometry (UHPLC-CID-MS), UHPLC-CTD-MS yielded fewer ambiguous ions and more structurally informative results. The developed UHPLC-CTD-MS method resulted in abundant cross-ring cleavages-and especially 1,4 X n , 1,5 X n , and 2,4 X n ions-which helped to identify most of the isomers. The Gal A isomers differed only in the methyl group position along the galacturonic acid backbone. The combination of CTD in real time with UHPLC provides a new tool for the structural characterization of complex mixtures of oligogalacturonans and potentially other classes of oligosaccharides.

In-source collision-induced dissociation (CID) is commonly used with single-stage high-resolution mass spectrometers to gather both a molecular formula and structural information through the collisional activation of analytes with residual background gas in the source region of the mass spectrometer. However, unlike tandem mass spectrometry, in-source CID does not involve an isolation step prior to collisional activation leading to a product ion spectrum composed of fragment ions from any analyte present during the activation event. This work provides the first comparison of in-source CID and beam-type CID spectra of emerging synthetic drugs on the same instrument to understand the fragmentation differences between the two techniques and to contribute to the scientific foundations of in-source CID. Electrospray ionization-quadrupole time-of-flight (ESI-Q-TOF) mass spectrometry was used to generate product ion spectra from in-source CID and beam-type CID for a series of well-characterized fentanyl analogs and synthetic cathinones. A comparison between the fragmentation patterns and relative ion abundances for each technique was performed over a range of fragmentor offset voltages for in-source CID and a range of collision energies for beam-type CID. The results indicate that large fragmentor potentials for in-source CID tend to favor higher energy fragmentation pathways that result in both kinetically favored pathways and consecutive neutral losses, both of which produce more abundant lower mass product ions relative to beam-type CID. Although conditions can be found in which in-source CID and beam-type CID provide similar overall spectra, the in-source CID spectra tend to contain elevated noise and additional chemical background peaks relative to beam-type CID., (© 2020 John Wiley & Sons, Ltd.)