Real-Time Electronic Patient Portal Use Among Emergency Department Patients.

Importance: Patients with inequitable access to patient portals frequently present to emergency departments (EDs) for care. Little is known about portal use patterns among ED patients. Objectives: To describe real-time patient portal usage trends among ED patients and compare demographic and clinical characteristics between portal users and nonusers. Design, Setting, and Participants: In this cross-sectional study of 12 teaching and 24 academic-affiliated EDs from 8 health systems in California, Connecticut, Massachusetts, Ohio, Tennessee, Texas, and Washington, patient portal access and usage data were evaluated for all ED patients 18 years or older between April 5, 2021, and April 4, 2022. Exposure: Use of the patient portal during ED visit. Main Outcomes and Measures: The primary outcomes were the weekly proportions of ED patients who logged into the portal, viewed test results, and viewed clinical notes in real time. Pooled random-effects models were used to evaluate temporal trends and demographic and clinical characteristics associated with real-time portal use. Results: The study included 1 280 924 unique patient encounters (53.5% female; 0.6% American Indian or Alaska Native, 3.7% Asian, 18.0% Black, 10.7% Hispanic, 0.4% Native Hawaiian or Pacific Islander, 66.5% White, 10.0% other race, and 4.0% with missing race or ethnicity; 91.2% English-speaking patients; mean [SD] age, 51.9 [19.2] years). During the study, 17.4% of patients logged into the portal while in the ED, whereas 14.1% viewed test results and 2.5% viewed clinical notes. The odds of accessing the portal (odds ratio [OR], 1.36; 95% CI, 1.19-1.56), viewing test results (OR, 1.63; 95% CI, 1.30-2.04), and viewing clinical notes (OR, 1.60; 95% CI, 1.19-2.15) were higher at the end of the study vs the beginning. Patients with active portal accounts at ED arrival had a higher odds of logging into the portal (OR, 17.73; 95% CI, 9.37-33.56), viewing test results (OR, 18.50; 95% CI, 9.62-35.57), and viewing clinical notes (OR, 18.40; 95% CI, 10.31-32.86). Patients who were male, Black, or without commercial insurance had lower odds of logging into the portal, viewing results, and viewing clinical notes. Conclusions and Relevance: These findings suggest that real-time patient portal use during ED encounters has increased over time, but disparities exist in portal access that mirror trends in portal usage more generally. Given emergency medicine's role in caring for medically underserved patients, there are opportunities for EDs to enroll and train patients in using patient portals to promote engagement during and after their visits.

User-Centered Design and Implementation of an Interoperable FHIR Application for Pediatric Pneumonia Prognostication in a Randomized Trial.

OBJECTIVE: To support a pragmatic, electronic health record (EHR)-based randomized controlled trial, we applied user-centered design (UCD) principles, evidence-based risk communication strategies, and interoperable software architecture to design, test, and deploy a prognostic tool for children in emergency departments (EDs) with pneumonia. METHODS: Risk for severe in-hospital outcomes was estimated using a validated ordinal logistic regression model to classify pneumonia severity. To render the results usable for ED clinicians, we created an integrated SMART on FHIR web application built for interoperable use in two pediatric EDs using different EHR vendors: Epic and Cerner. We followed a UCD framework, including problem analysis and user research, conceptual design and early prototyping, user interface development, formative evaluation, and post-deployment summative evaluation. RESULTS: Problem analysis and user research from 39 clinicians and nurses revealed user preferences for risk aversion, accessibility, and timing of risk communication. Early prototyping and iterative design incorporated evidence-based design principles, including numeracy, risk framing, and best-practice visualization techniques. After rigorous unit and end-to-end testing, the application was successfully deployed in both EDs, which facilitatd enrollment, randomization, model visualization, data capture, and reporting for trial purposes. CONCLUSIONS: The successful implementation of a custom application for pneumonia prognosis and clinical trial support in two health systems on different EHRs demonstrates the importance of UCD, adherence to modern clinical data standards, and rigorous testing. Key lessons included the need for understanding users' real-world needs, regular knowledge management, application maintenance, and the recognition that FHIR applications require careful configuration for interoperability.

Is there an association between peri-diagnostic vaccination and clinical outcomes in COVID-19 patients?

Background: Peri-diagnostic vaccination contemporaneous with SARS-CoV-2 infection might boost antiviral immunity and improve patient outcomes. We investigated, among previously unvaccinated patients, whether vaccination (with the Pfizer, Moderna, or J&J vaccines) during the week before or after a positive COVID-19 test was associated with altered 30-day patient outcomes. Methods: Using a deidentified longitudinal EHR repository, we selected all previously unvaccinated adults who initially tested positive for SARS-CoV-2 between December 11, 2020 (the date of vaccine emergency use approval) and December 19, 2021. We assessed whether vaccination between days -7 and +7 of a positive test affected outcomes. The primary measure was progression to a more severe disease outcome within 30 days of diagnosis using the following hierarchy: hospitalization, intensive care, or death. Results: Among 60,031 hospitalized patients, 543 (0.91%) were initially vaccinated at the time of diagnosis and 59,488 (99.09%) remained unvaccinated during the period of interest. Among 316,337 nonhospitalized patients, 2,844 (0.90%) were initially vaccinated and 313,493 (99.1%) remained unvaccinated. In both analyses, individuals receiving vaccines were older, more often located in the northeast, more commonly insured by Medicare, and more burdened by comorbidities. Among previously unvaccinated patients, there was no association between receiving an initial vaccine dose between days -7 and +7 of diagnosis and progression to more severe disease within 30 days compared to patients who did not receive vaccines. Conclusions: Immunization during acute SARS-CoV-2 infection does not appear associated with clinical progression during the acute infectious period.

Risk Factors for SARS-CoV-2 Infection and Severe Outcomes Among People With Human Immunodeficiency Virus: Cohort Study.

Background: Studies on COVID-19 in people with HIV (PWH) have had limitations. Further investigations on risk factors and outcomes of SARS-CoV-2 infection among PWH are needed. Methods: This retrospective cohort study leveraged the national OPTUM COVID-19 data set to investigate factors associated with SARS-CoV-2 positivity among PWH and risk factors for severe outcomes, including hospitalization, intensive care unit stays, and death. A subset analysis was conducted to examine HIV-specific variables. Multiple variable logistic regression was used to adjust for covariates. Results: Of 43 173 PWH included in this study, 6472 had a positive SARS-CoV-2 result based on a polymerase chain reaction test or antigen test. For PWH with SARS-CoV-2 positivity, higher odds were found for those who were younger (18-49 years), Hispanic White, African American, from the US South, uninsured, and a noncurrent smoker and had a higher body mass index and higher Charlson Comorbidity Index. For PWH with severe outcomes, higher odds were identified for those who were SARS-CoV-2 positive, older, from the US South, receiving Medicaid/Medicare or uninsured, a current smoker, and underweight and had a higher Charlson Comorbidity Index. In a subset analysis including PWH with HIV care variables (n = 5098), those with unsuppressed HIV viral load, a low CD4 count, and no antiretroviral therapy had higher odds of severe outcomes. Conclusions: This large US study found significant ethnic, racial, and geographic differences in SARS-CoV-2 infection among PWH. Chronic comorbidities, older age, lower body mass index, and smoking were associated with severe outcomes among PWH during the COVID-19 pandemic. SARS-CoV-2 infection was associated with severe outcomes, but once we adjusted for HIV care variables, SARS-CoV-2 was no longer significant; however, low CD4 count, high viral load, and lack of antiretroviral therapy had higher odds of severe outcomes.

Neurological Examination Frequency and Time-to-Delirium After Traumatic Brain Injury.

BACKGROUND: Frequent neurological examinations in patients with traumatic brain injury (TBI) disrupt sleep-wake cycles and potentially contribute to the development of delirium. OBJECTIVE: To evaluate the risk of delirium among patients with TBI with respect to their neuro-check frequencies. METHODS: A retrospective study of patients presenting with TBI at a single level I trauma center between January 2018 and December 2019. The primary exposure was the frequency of neurological examinations (neuro-checks) assigned at the time of admission. Patients admitted with hourly (Q1) neuro-check frequencies were compared with those who received examinations every 2 (Q2) or 4 (Q4) hours. The primary outcomes were delirium and time-to-delirium. The onset of delirium was defined as the first documented positive Confusion Assessment Method for the Intensive Care Unit score. RESULTS: Of 1552 patients with TBI, 458 (29.5%) patients experienced delirium during their hospital stay. The median time-to-delirium was 1.8 days (IQR: 1.1, 2.9). Kaplan-Meier analysis demonstrated that patients assigned Q1 neuro-checks had the greatest rate of delirium compared with the patients with Q2 and Q4 neuro-checks ( P < .001). Multivariable Cox regression modeling demonstrated that Q2 neuro-checks (hazard ratio: 0.439, 95% CI: 0.33-0.58) and Q4 neuro-checks (hazard ratio: 0.48, 95% CI: 0.34-0.68) were protective against the development of delirium compared with Q1. Other risk factors for developing delirium included pre-existing dementia, tobacco use, lower Glasgow Coma Scale score, higher injury severity score, and certain hemorrhage patterns. CONCLUSION: Patients with more frequent neuro-checks had a higher risk of developing delirium compared with those with less frequent neuro-checks.

Using AI-generated suggestions from ChatGPT to optimize clinical decision support.

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.

Incidence and Risk Factors for Severe Outcomes in Pediatric Patients With COVID-19.

OBJECTIVES: Throughout the pandemic, children with COVID-19 have experienced hospitalization, ICU admission, invasive respiratory support, and death. Using a multisite, national dataset, we investigate risk factors associated with these outcomes in children with COVID-19. METHODS: Our data source (Optum deidentified COVID-19 Electronic Health Record Dataset) included children aged 0 to 18 years testing positive for COVID-19 between January 1, 2020, and January 20, 2022. Using ordinal logistic regression, we identified factors associated with an ordinal outcome scale: nonhospitalization, hospitalization, or a severe composite outcome (ICU, intensive respiratory support, death). To contrast hospitalization for COVID-19 and incidental positivity on hospitalization, we secondarily identified patient factors associated with hospitalizations with a primary diagnosis of COVID-19. RESULTS: In 165 437 children with COVID-19, 3087 (1.8%) were hospitalized without complication, 2954 (1.8%) experienced ICU admission and/or intensive respiratory support, and 31 (0.02%) died. We grouped patients by age: 0 to 4 years old (35 088), and 5 to 11 years old (75 574), 12 to 18 years old (54 775). Factors positively associated with worse outcomes were preexisting comorbidities and residency in the Southern United States. In 0- to 4-year-old children, there was a nonlinear association between age and worse outcomes, with worse outcomes in 0- to 2-year-old children. In 5- to 18-year-old patients, vaccination was protective. Findings were similar in our secondary analysis of hospitalizations with a primary diagnosis of COVID-19, though region effects were no longer observed. CONCLUSIONS: Among children with COVID-19, preexisting comorbidities and residency in the Southern United States were positively associated with worse outcomes, whereas vaccination was negatively associated. Our study population was highly insured; future studies should evaluate underinsured populations to confirm generalizability.

Antibiotic clinical decision support for pneumonia in the ED: A randomized trial.

BACKGROUND: Electronic health record-based clinical decision support (CDS) is a promising antibiotic stewardship strategy. Few studies have evaluated the effectiveness of antibiotic CDS in the pediatric emergency department (ED). OBJECTIVE: To compare the effectiveness of antibiotic CDS vs. usual care for promoting guideline-concordant antibiotic prescribing for pneumonia in the pediatric ED. DESIGN: Pragmatic randomized clinical trial. SETTING AND PARTICIPANTS: Encounters for children (6 months-18 years) with pneumonia presenting to two tertiary care children s hospital EDs in the United States. INTERVENTION: CDS or usual care was randomly assigned during 4-week periods within each site. The CDS intervention provided antibiotic recommendations tailored to each encounter and in accordance with national guidelines. MAIN OUTCOME AND MEASURES: The primary outcome was exclusive guideline-concordant antibiotic prescribing within the first 24 h of care. Safety outcomes included time to first antibiotic order, encounter length of stay, delayed intensive care, and 3- and 7-day revisits. RESULTS: 1027 encounters were included, encompassing 478 randomized to usual care and 549 to CDS. Exclusive guideline-concordant prescribing did not differ at 24 h (CDS, 51.7% vs. usual care, 53.3%; odds ratio [OR] 0.94 [95% confidence interval [CI]: 0.73, 1.20]). In pre-specified stratified analyses, CDS was associated with guideline-concordant prescribing among encounters discharged from the ED (74.9% vs. 66.0%; OR 1.53 [95% CI: 1.01, 2.33]), but not among hospitalized encounters. Mean time to first antibiotic was shorter in the CDS group (3.0 vs 3.4 h; p = .024). There were no differences in safety outcomes. CONCLUSIONS: Effectiveness of ED-based antibiotic CDS was greatest among those discharged from the ED. Longitudinal interventions designed to target both ED and inpatient clinicians and to address common implementation challenges may enhance the effectiveness of CDS as a stewardship tool.

Assessing the Value of ChatGPT for Clinical Decision Support Optimization.

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.

Perspectives of Patients About Immediate Access to Test Results Through an Online Patient Portal.

Importance: The 21st Century Cures Act Final Rule mandates the immediate electronic availability of test results to patients, likely empowering them to better manage their health. Concerns remain about unintended effects of releasing abnormal test results to patients. Objective: To assess patient and caregiver attitudes and preferences related to receiving immediately released test results through an online patient portal. Design, Setting, and Participants: This large, multisite survey study was conducted at 4 geographically distributed academic medical centers in the US using an instrument adapted from validated surveys. The survey was delivered in May 2022 to adult patients and care partners who had accessed test results via an online patient portal account between April 5, 2021, and April 4, 2022. Exposures: Access to test results via a patient portal between April 5, 2021, and April 4, 2022. Main Outcomes and Measures: Responses to questions related to demographics, test type and result, reaction to result, notification experience and future preferences, and effect on health and well-being were aggregated. To evaluate characteristics associated with patient worry, logistic regression and pooled random-effects models were used to assess level of worry as a function of whether test results were perceived by patients as normal or not normal and whether patients were precounseled. Results: Of 43 380 surveys delivered, there were 8139 respondents (18.8%). Most respondents were female (5129 [63.0%]) and spoke English as their primary language (7690 [94.5%]). The median age was 64 years (IQR, 50-72 years). Most respondents (7520 of 7859 [95.7%]), including 2337 of 2453 individuals (95.3%) who received nonnormal results, preferred to immediately receive test results through the portal. Few respondents (411 of 5473 [7.5%]) reported that reviewing results before they were contacted by a health care practitioner increased worry, though increased worry was more common among respondents who received abnormal results (403 of 2442 [16.5%]) than those whose results were normal (294 of 5918 [5.0%]). The result of the pooled model for worry as a function of test result normality was statistically significant (odds ratio [OR], 2.71; 99% CI, 1.96-3.74), suggesting an association between worry and nonnormal results. The result of the pooled model evaluating the association between worry and precounseling was not significant (OR, 0.70; 99% CI, 0.31-1.59). Conclusions and Relevance: In this multisite survey study of patient attitudes and preferences toward receiving immediately released test results via a patient portal, most respondents preferred to receive test results via the patient portal despite viewing results prior to discussion with a health care professional. This preference persisted among patients with nonnormal results.

Improved hospital discharge and cost savings with esophageal cooling during left atrial ablation.

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.

Active esophageal cooling during radiofrequency ablation of the left atrium: data review and update.

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.

Atrial fibrillation is a condition in which the heart beats irregularly, causing symptoms such as palpitations, dizziness, shortness of breath, and chest pain. Atrial fibrillation increases the risk of stroke, heart failure, dementia, and death. One treatment for atrial fibrillation is a procedure called a catheter ablation. This procedure is minimally invasive and is performed by a specialized cardiologist, called an electrophysiologist. The electrophysiologist, or operator, uses an energy source, such as radiofrequency energy (radio waves), to stop erratic electrical signals from traveling through the heart. One complication of the catheter ablation is an inadvertent injury to the esophagus, the organ that passes food from the mouth to the stomach. If the injury is severe, it may develop into an atrioesophageal fistula, which often results in death. In this review, a new technology is described that helps prevent this type of injury and can provide additional benefits for the patient, operator, and hospital.

Reduced Procedure Time and Variability with Active Esophageal Cooling During Radiofrequency Ablation for Atrial Fibrillation.

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.

Real-Time Patient Portal Use Among Emergency Department Patients: An Open Results Study.

OBJECTIVES: We characterized real-time patient portal test result viewing among emergency department (ED) patients and described patient characteristics overall and among those not enrolled in the portal at ED arrival. METHODS: Our observational study at an academic ED used portal log data to trend the proportion of adult patients who viewed results during their visit from May 04, 2021 to April 04, 2022. Correlation was assessed visually and with Kendall's τ. Covariate analysis using binary logistic regression assessed result(s) viewed as a function of time accounting for age, sex, ethnicity, race, language, insurance status, disposition, and social vulnerability index (SVI). A second model only included patients not enrolled in the portal at arrival. We used random forest imputation to account for missingness and Huber-White heteroskedasticity-robust standard errors for patients with multiple encounters (α = 0.05). RESULTS: There were 60,314 ED encounters (31,164 unique patients). In 7,377 (12.2%) encounters, patients viewed results while still in the ED. Patients were not enrolled for portal use at arrival in 21,158 (35.2%) encounters, and 927 (4.4% of not enrolled, 1.5% overall) subsequently enrolled and viewed results in the ED. Visual inspection suggests an increasing proportion of patients who viewed results from roughly 5 to 15% over the study (Kendall's τ = 0.61 [p <0.0001]). Overall and not-enrolled models yielded concordance indices (C) of 0.68 and 0.72, respectively, with significant overall likelihood ratio χ 2 (p <0.0001). Time was independently associated with viewing results in both models after adjustment. Models revealed disparate use between age, race, ethnicity, SVI, sex, insurance status, and disposition groups. CONCLUSION: We observed increased portal-based test result viewing among ED patients over the year since the 21st Century Cures act went into effect, even among those not enrolled at arrival. We observed disparities in those who viewed results.

Decision Support to Improve Critical Care Services Documentation in an Academic Emergency Department.

OBJECTIVES: Critical care services (CCS) documentation affects billing, operations, and research. No studies exist on documentation decision support (DDS) for CCS in the emergency department (ED). We describe the design, implementation, and evaluation of a DDS tool built to improve CCS documentation at an academic ED. METHODS: This quality improvement study reports the prospective design, implementation, and evaluation of a novel DDS tool for CCS documentation at an academic ED. CCS-associated ED diagnoses triggered a message to appear within the physician note attestation workflow for any patient seen in the adult ED. The alert raised awareness of CCS-associated diagnoses without recommending specific documentation practices. The message disappeared from the note automatically once signed. We measured current procedural terminology (CPT) codes 99291 or 99292 (representing CCS rendered) for 8 months before and after deployment to identify CCS documentation rates. We performed state-space Bayesian time-series analysis to evaluate the causal effect of our intervention on CCS documentation capture. We used monthly ED volume and monthly admission rates as covariate time-series for model generation. RESULTS: The study included 92,350 ED patients with an observed mean proportion CCS of 3.9% before the intervention and 5.8% afterward. The counterfactual model predicted an average response of 3.9% [95% CI 3.5-4.3%]. The estimated absolute causal effect of the intervention was 2.0% [95% CI 1.5-2.4%] (p = 0.001). CONCLUSION: A DDS tool measurably increased ED CCS documentation. Attention to user workflows and collaboration with compliance and billing teams avoided alert fatigue and ensures compliance.

Integration of Face-to-Face Screening With Real-time Machine Learning to Predict Risk of Suicide Among Adults.

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.

Improving Emergency Medical Services Information Exchange: Methods for Automating Entity Resolution.

The 21st century has seen an enormous growth in emergency medical services (EMS) information technology systems, with corresponding accumulation of large volumes of data. Despite this growth, integration efforts between EMS-based systems and electronic health records, and public-sector databases have been limited due to inconsistent data structure, data missingness, and policy and regulatory obstacles. Efforts to integrate EMS systems have benefited from the evolving science of entity resolution and record linkage. In this chapter, we present the history and fundamentals of record linkage techniques, an overview of past uses of this technology in EMS, and a look into the future of record linkage techniques for integrating EMS data systems including the use of machine learning-based techniques.

COVID-19 Vaccination Gap in Admitted Trauma Patients: A Critical Opportunity.

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.

Clinician collaboration to improve clinical decision support: the Clickbusters initiative.

OBJECTIVE: We describe the Clickbusters initiative implemented at Vanderbilt University Medical Center (VUMC), which was designed to improve safety and quality and reduce burnout through the optimization of clinical decision support (CDS) alerts. MATERIALS AND METHODS: We developed a 10-step Clickbusting process and implemented a program that included a curriculum, CDS alert inventory, oversight process, and gamification. We carried out two 3-month rounds of the Clickbusters program at VUMC. We completed descriptive analyses of the changes made to alerts during the process, and of alert firing rates before and after the program. RESULTS: Prior to Clickbusters, VUMC had 419 CDS alerts in production, with 488 425 firings (42 982 interruptive) each week. After 2 rounds, the Clickbusters program resulted in detailed, comprehensive reviews of 84 CDS alerts and reduced the number of weekly alert firings by more than 70 000 (15.43%). In addition to the direct improvements in CDS, the initiative also increased user engagement and involvement in CDS. CONCLUSIONS: At VUMC, the Clickbusters program was successful in optimizing CDS alerts by reducing alert firings and resulting clicks. The program also involved more users in the process of evaluating and improving CDS and helped build a culture of continuous evaluation and improvement of clinical content in the electronic health record.