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Article ; Online: An Open Letter Arguing for Closure of the Practice Pathway for Clinical Informatics Medical Subspecialty Certification.

Turer, Robert W / Levy, Bruce P / Hron, Jonathan D / Pageler, Natalie M / Mize, Dara E / Kim, Ellen / Lehmann, Christoph U

Applied clinical informatics

2022 Volume 13, Issue 1, Page(s) 301–303

MeSH term(s)	Certification ; Medical Informatics ; United States
Language	English
Publishing date	2022-02-26
Publishing country	Germany
Document type	Letter
ISSN	1869-0327
ISSN (online)	1869-0327
DOI	10.1055/s-0042-1744386
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Article ; Online: Patient Perceptions of Receiving COVID-19 Test Results via an Online Patient Portal: An Open Results Survey.

Turer, Robert W / DesRoches, Catherine M / Salmi, Liz / Helmer, Tara / Rosenbloom, S Trent

Applied clinical informatics

2021 Volume 12, Issue 4, Page(s) 954–959

Abstract: Background: In the United States, attention has been focused on "open notes" and "open results" since the Office of the National Coordinator for Health Information Technology implemented the 21st Century Cures Act Final Rule on information blocking. ... ...

Abstract	Background: In the United States, attention has been focused on "open notes" and "open results" since the Office of the National Coordinator for Health Information Technology implemented the 21st Century Cures Act Final Rule on information blocking. Open notes is an established best practice, but open results remains controversial, especially for diseases associated with stigma, morbidity, and mortality. Coronavirus disease 2019 (COVID-19) is associated with all three of these effects and represents an ideal disease for the study of open results for sensitive test results. Objectives: This study evaluates patient perspectives related to receiving COVID-19 test results via an online patient portal prior to discussion with a clinician. Methods: We surveyed adults who underwent COVID-19 testing between March 1, 2020 and October 21, 2020 who agreed to be directly contacted about COVID-19-related research about their perspectives on receiving test results via a patient portal. We evaluated user roles (i.e., patient vs. care partner), demographic information, ease of use, impact of immediate release, notification of results, impact of viewing results on health management, and importance of sharing results with others. Results: Users were mostly patients themselves. Users found the portal easy to use but expressed mixed preferences about the means of notification of result availability (e.g., email, text, or phone call). Users found immediate access to results useful for managing their health, employment, and family/childcare. Many users shared their results and encouraged others to get tested. Our cohort consisted mostly of non-Hispanic white, highly educated, English-speaking patients. Conclusion: Overall, patients found open results useful for COVID-19 testing and few expressed increased worries from receiving their results via the patient portal. The demographics of our cohort highlight the need for further research in patient portal equity in the age of open results.
MeSH term(s)	Adult ; COVID-19 ; COVID-19 Testing ; Humans ; Patient Portals ; Perception ; SARS-CoV-2 ; United States
Language	English
Publishing date	2021-10-13
Publishing country	Germany
Document type	Journal Article
ISSN	1869-0327
ISSN (online)	1869-0327
DOI	10.1055/s-0041-1736221
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Article ; Online: Reply to Barthell et al.

Turer, Robert W / Jones, Ian / Rosenbloom, S Trent / Slovis, Corey / Ward, Michael J

Journal of the American Medical Informatics Association : JAMIA

2020 Volume 27, Issue 9, Page(s) 1498

MeSH term(s)	COVID-19 ; Electronics ; Emergency Service, Hospital ; Humans ; Personal Protective Equipment ; SARS-CoV-2
Language	English
Publishing date	2020-06-01
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocaa111
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Article ; Online: Reduced Procedure Time and Variability with Active Esophageal Cooling During Radiofrequency Ablation for Atrial Fibrillation.

Joseph, Christopher / Cooper, Julie / Turer, Robert W / McDonald, Samuel A / Kulstad, Erik Benjamin / Daniels, James

Journal of visualized experiments : JoVE

2022 , Issue 186

Abstract: Various methods are utilized during radiofrequency (RF) pulmonary vein isolation (PVI) for the treatment of atrial fibrillation (AF) to protect the esophagus from inadvertent thermal injury. Active esophageal cooling is increasingly being used over ... ...

Abstract	Various methods are utilized during radiofrequency (RF) pulmonary vein isolation (PVI) for the treatment of atrial fibrillation (AF) to protect the esophagus from inadvertent thermal injury. Active esophageal cooling is increasingly being used over traditional luminal esophageal temperature (LET) monitoring, and each approach may influence procedure times and the variability around those times. The objective of this study is to measure the effects on procedure time and variability in procedure time of two different esophageal protection strategies utilizing advanced informatics techniques to facilitate data extraction. Trained clinical informaticists first performed a contextual inquiry in the catheterization laboratory to determine laboratory workflows and observe the documentation of procedural data within the electronic health record (EHR). These EHR data structures were then identified in the electronic health record reporting database, facilitating data extraction from the EHR. A manual chart review using a REDCap database created for the study was then performed to identify additional data elements, including the type of esophageal protection used. Procedure duration was then compared using summary statistics and standard measures of dispersion. A total of 164 patients underwent radiofrequency PVI over the study timeframe; 63 patients (38%) were treated with LET monitoring, and 101 patients (62%) were treated with active esophageal cooling. The mean procedure time was 176 min (SD of 52 min) in the LET monitoring group compared to 156 min (SD of 40 min) in the esophageal cooling group (P = 0.012). Thus, active esophageal cooling during PVI is associated with reduced procedure time and reduced variation in procedure time when compared to traditional LET monitoring.
MeSH term(s)	Atrial Fibrillation/surgery ; Body Temperature ; Catheter Ablation/adverse effects ; Esophagus/injuries ; Humans ; Pulmonary Veins/surgery
Language	English
Publishing date	2022-08-25
Publishing country	United States
Document type	Journal Article ; Video-Audio Media
ZDB-ID	2259946-0
ISSN	1940-087X ; 1940-087X
ISSN (online)	1940-087X
ISSN	1940-087X
DOI	10.3791/64417
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Article ; Online: Active esophageal cooling during radiofrequency ablation of the left atrium: data review and update.

Cooper, Julie / Joseph, Christopher / Zagrodzky, Jason / Woods, Christopher / Metzl, Mark / Turer, Robert W / McDonald, Samuel A / Kulstad, Erik / Daniels, James

Expert review of medical devices

2022 Volume 19, Issue 12, Page(s) 949–957

Abstract: Introduction: Radiofrequency (RF) ablation of the left atrium of the heart is increasingly used to treat atrial fibrillation (AF). Unfortunately, inadvertent thermal injury to the esophagus can occur during this procedure, potentially creating an ... ...

Abstract	Introduction: Radiofrequency (RF) ablation of the left atrium of the heart is increasingly used to treat atrial fibrillation (AF). Unfortunately, inadvertent thermal injury to the esophagus can occur during this procedure, potentially creating an atrioesophageal fistula (AEF) which is 80% fatal. The ensoETM (Attune Medical, Chicago, IL), is an esophageal cooling device that has been shown to reduce thermal injury to the esophagus during RF ablation. Areas covered: This review summarizes growing evidence related to active esophageal cooling during RF ablation for the treatment of AF. The review presents data demonstrating improved outcomes related to patient safety and procedural efficiency and suggests directions for future research. Expert opinion: The use of active esophageal cooling during RF ablation reduces esophageal injury, reduces or eliminates fluoroscopy requirements, reduces procedure duration and post-operative pain, and increases long-term freedom from arrhythmia. These effects in turn increase patient same-day discharge rates, decrease operator cognitive load, and reduce cost. These findings are likely to further accelerate the adoption of active esophageal cooling.
MeSH term(s)	Humans ; Catheter Ablation ; Heart Atria/surgery ; Esophagus/surgery ; Atrial Fibrillation/surgery ; Radiofrequency Ablation/adverse effects
Language	English
Publishing date	2022-11-27
Publishing country	England
Document type	Review ; Journal Article
ZDB-ID	2250857-0
ISSN	1745-2422 ; 1743-4440
ISSN (online)	1745-2422
ISSN	1743-4440
DOI	10.1080/17434440.2022.2150930
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Article ; Online: Improved hospital discharge and cost savings with esophageal cooling during left atrial ablation.

Joseph, Christopher / Cooper, Julie / Sikka, Rishi / Zagrodzky, Jason / Turer, Robert W / McDonald, Samuel A / Kulstad, Erik / Daniels, James

Journal of medical economics

2022 Volume 26, Issue 1, Page(s) 158–167

Abstract: Background: Left atrial ablation to obtain pulmonary vein isolation (PVI) for the treatment of atrial fibrillation (AF) is a technologically intensive procedure utilizing innovative and continually improving technology. Changes in the technology ... ...

Abstract	Background: Left atrial ablation to obtain pulmonary vein isolation (PVI) for the treatment of atrial fibrillation (AF) is a technologically intensive procedure utilizing innovative and continually improving technology. Changes in the technology utilized for PVI can in turn lead to changes in procedure costs. Because of the proximity of the esophagus to the posterior wall of the left atrium, various technologies have been utilized to protect against thermal injury during ablation. The impact on hospital costs during PVI ablation from utilization of different technologies for esophageal protection during ablation has not previously been evaluated. Objective: To compare the costs of active esophageal cooling to luminal esophageal temperature (LET) monitoring during left atrial ablation. Methods: We performed a time-driven activity-based costing (TDABC) analysis to determine costs for PVI procedures. Published data and literature review were utilized to determine differences in procedure time and same-day discharge rates using different esophageal protection technologies and to determine the cost impacts of same-day discharge versus overnight hospitalization after PVI procedures. The total costs were then compared between cases using active esophageal cooling to those using LET monitoring. Results: The effect of implementing active esophageal cooling was associated with up to a 24.7% reduction in mean total procedure time, and an 18% increase in same-day discharge rate. TDABC analysis identified a $681 reduction in procedure costs associated with the use of active esophageal cooling after including the cost of the esophageal cooling device. Factoring in the 18% increase in same-day discharge resulted in an increased cost savings of $2,135 per procedure. Conclusions: The use of active esophageal cooling is associated with significant cost-savings when compared to traditional LET monitoring, even after accounting for the additional cost of the cooling device. These savings originate from a per-patient procedural time savings and a per-population improvement in same-day discharge rate.
MeSH term(s)	Humans ; Atrial Fibrillation/surgery ; Patient Discharge ; Cost Savings ; Esophagus/surgery ; Esophagus/injuries ; Heart Atria/surgery ; Catheter Ablation/methods ; Treatment Outcome
Language	English
Publishing date	2022-12-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2270945-9
ISSN	1941-837X ; 1369-6998
ISSN (online)	1941-837X
ISSN	1369-6998
DOI	10.1080/13696998.2022.2160596
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Article ; Online: COVID-19 Vaccination Gap in Admitted Trauma Patients: A Critical Opportunity.

Turer, Robert W / Chen, Qingxia / Jones, Ian D / Gondek, Stephen P / Guillamondegui, Oscar D / Dennis, Bradley M

Journal of the American College of Surgeons

2022 Volume 234, Issue 5, Page(s) 727–735

Abstract: Background: Coronavirus disease 2019 (COVID-19) vaccination is the core strategy for pandemic management. We hypothesized that a vaccination gap might exist between emergency department (ED) patients admitted for trauma and other ED patients.: Study ... ...

Abstract	Background: Coronavirus disease 2019 (COVID-19) vaccination is the core strategy for pandemic management. We hypothesized that a vaccination gap might exist between emergency department (ED) patients admitted for trauma and other ED patients. Study design: This was an observational quality improvement study using electronic health record data at an academic level-1 trauma center. Participants were all patients presenting to the adult ED with a Tennessee home address between January 1 and June 1, 2021. We measured the proportional difference in vaccination between admitted trauma patients and other ED patients over time (by week) and association via Spearman's rank correlation coefficient. Binary logistic regression facilitated covariate analysis to account for age, sex, race, home county, and ethnicity without and then with interaction between trauma admission and time. Geographic visual analysis compared county-level vaccination rates with odds of trauma admission by home county using a bivariate chloropleth map. Results: The proportional difference in vaccination between trauma-admitted and other ED patients increased over time (Spearman's = 0.699). Adjusting for age, sex, race, home county, and ethnicity, there was a statistically significant vaccination difference between trauma-admitted and other ED patients (odds ratio = 0.53, 95% CI 0.43-0.65, p < 0.0001). Geographic analysis revealed increased trauma admission odds and lower vaccination rates in surrounding counties compared with Davidson County. Conclusions: We observed a widening COVID-19 vaccination gap between trauma-admitted and other ED patients. Vaccine outreach during trauma admission may provide a valuable point of contact for unvaccinated patients.
MeSH term(s)	Adult ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Vaccines ; Emergency Service, Hospital ; Hospitalization ; Humans ; Vaccination
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2022-05-18
Publishing country	United States
Document type	Journal Article ; Observational Study
ZDB-ID	1181115-8
ISSN	1879-1190 ; 1072-7515
ISSN (online)	1879-1190
ISSN	1072-7515
DOI	10.1097/XCS.0000000000000133
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Article ; Online: Integration of Face-to-Face Screening With Real-time Machine Learning to Predict Risk of Suicide Among Adults.

Wilimitis, Drew / Turer, Robert W / Ripperger, Michael / McCoy, Allison B / Sperry, Sarah H / Fielstein, Elliot M / Kurz, Troy / Walsh, Colin G

JAMA network open

2022 Volume 5, Issue 5, Page(s) e2212095

Abstract: Importance: Understanding the differences and potential synergies between traditional clinician assessment and automated machine learning might enable more accurate and useful suicide risk detection.: Objective: To evaluate the respective and ... ...

Abstract	Importance: Understanding the differences and potential synergies between traditional clinician assessment and automated machine learning might enable more accurate and useful suicide risk detection. Objective: To evaluate the respective and combined abilities of a real-time machine learning model and the Columbia Suicide Severity Rating Scale (C-SSRS) to predict suicide attempt (SA) and suicidal ideation (SI). Design, setting, and participants: This cohort study included encounters with adult patients (aged ≥18 years) at a major academic medical center. The C-SSRS was administered during routine care, and a Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) prediction was generated in the electronic health record. Encounters took place in the inpatient, ambulatory surgical, and emergency department settings. Data were collected from June 2019 to September 2020. Main outcomes and measures: Primary outcomes were the incidence of SA and SI, encoded as International Classification of Diseases codes, occurring within various time periods after an index visit. We evaluated the retrospective validity of the C-SSRS, VSAIL, and ensemble models combining both. Discrimination metrics included area under the receiver operating curve (AUROC), area under the precision-recall curve (AUPR), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: The cohort included 120 398 unique index visits for 83 394 patients (mean [SD] age, 51.2 [20.6] years; 38 107 [46%] men; 45 273 [54%] women; 13 644 [16%] Black; 63 869 [77%] White). Within 30 days of an index visit, the combined models had higher AUROC (SA: 0.874-0.887; SI: 0.869-0.879) than both the VSAIL (SA: 0.729; SI: 0.773) and C-SSRS (SA: 0.823; SI: 0.777) models. In the highest risk-decile, ensemble methods had PPV of 1.3% to 1.4% for SA and 8.3% to 8.7% for SI and sensitivity of 77.6% to 79.5% for SA and 67.4% to 70.1% for SI, outperforming VSAIL (PPV for SA: 0.4%; PPV for SI: 3.9%; sensitivity for SA: 28.8%; sensitivity for SI: 35.1%) and C-SSRS (PPV for SA: 0.5%; PPV for SI: 3.5%; sensitivity for SA: 76.6%; sensitivity for SI: 68.8%). Conclusions and relevance: In this study, suicide risk prediction was optimal when leveraging both in-person screening (for acute measures of risk in patient-reported suicidality) and historical EHR data (for underlying clinical factors that can quantify a patient's passive risk level). To improve suicide risk classification, prediction systems could combine pretrained machine learning with structured clinician assessment without needing to retrain the original model.
MeSH term(s)	Adolescent ; Adult ; Cohort Studies ; Female ; Humans ; Machine Learning ; Male ; Middle Aged ; Retrospective Studies ; Suicidal Ideation ; Suicide, Attempted
Language	English
Publishing date	2022-05-02
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ISSN	2574-3805
ISSN (online)	2574-3805
DOI	10.1001/jamanetworkopen.2022.12095
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Article ; Online: Using AI-generated suggestions from ChatGPT to optimize clinical decision support.

Liu, Siru / Wright, Aileen P / Patterson, Barron L / Wanderer, Jonathan P / Turer, Robert W / Nelson, Scott D / McCoy, Allison B / Sittig, Dean F / Wright, Adam

Journal of the American Medical Informatics Association : JAMIA

2023 Volume 30, Issue 7, Page(s) 1237–1245

Abstract: Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions.: Methods: We supplied summaries of CDS logic to ChatGPT, an ... ...

Abstract	Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods: We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy. Results: Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy. Conclusion: AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.
MeSH term(s)	Humans ; Artificial Intelligence ; Decision Support Systems, Clinical ; Language ; Learning Health System ; Workflow
Language	English
Publishing date	2023-03-21
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocad072
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Article: Assessing the Value of ChatGPT for Clinical Decision Support Optimization.

Liu, Siru / Wright, Aileen P / Patterson, Barron L / Wanderer, Jonathan P / Turer, Robert W / Nelson, Scott D / McCoy, Allison B / Sittig, Dean F / Wright, Adam

medRxiv : the preprint server for health sciences

2023

Abstract	Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods: We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy. Results: Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy. Conclusion: AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.
Language	English
Publishing date	2023-02-23
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.02.21.23286254
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