Electronic Health Record Usability When Caring for Children With Medical Complexity.

Objectives: To evaluate usability of and clinician satisfaction with the electronic health record (EHR) in the context of caring for children with medical complexity (CMC) at a large academic pediatric hospital and to identify key areas for targeted improvements.

Methods: Cross-sectional study of pediatric faculty and advanced practice providers across several pediatric specialties using an online Research Electronic Data Capture survey. EHR usability was measured with 6 validated questions from the National Usability-Focused Health Information System Scale, and satisfaction with common EHR functionalities was measured with 6 original Likert-scale questions and 3 free-text questions.

Ethnic and racial differences in self-reported symptoms, health status, activity level, and missed work at 3 and 6 months following SARS-CoV-2 infection.

Introduction: Data on ethnic and racial differences in symptoms and health-related impacts following SARS-CoV-2 infection are limited. We aimed to estimate the ethnic and racial differences in symptoms and health-related impacts 3 and 6 months after the first SARS-CoV-2 infection.

Methods: Participants included adults with SARS-CoV-2 infection enrolled in a prospective multicenter US study between 12/11/2020 and 7/4/2022 as the primary cohort of interest, as well as a SARS-CoV-2-negative cohort to account for non-SARS-CoV-2-infection impacts, who completed enrollment and 3-month surveys ( = 3,161; 2,402 SARS-CoV-2-positive, 759 SARS-CoV-2-negative).

Direct Secure Messaging in Practice: Addressing Workflow Challenges.

Direct Secure Messaging (DSM) is a sender-initiated communication technology for exchanging patient-specific information among clinicians and disparate healthcare organizations. As DSM adoption increases it becomes more difficult for clinicians and staff to manage the volume and variety of external data received. This can lead to information hazards that can produce cognitive overload and decrease the ability of clinicians to process patient data when reviewing multiple sources.

Identifying the Optimal Look-back Period for Prior Antimicrobial Resistance Clinical Decision Support.

Background: Lack of consensus on the appropriate look-back period for multi-drug resistance (MDR) complicates antimicrobial clinical decision support. We compared the predictive performance of different MDR look-back periods for five common MDR mechanisms (MRSA, VRE, ESBL, AmpC, CRE).

Methods: We mapped microbiological cultures to MDR mechanisms and labeled them at different look-back periods.

Next-generation study databases require FAIR, EHR-integrated, and scalable Electronic Data Capture for medical documentation and decision support.

Structured patient data play a key role in all types of clinical research. They are often collected in study databases for research purposes. In order to describe characteristics of a next-generation study database and assess the feasibility of its implementation a proof-of-concept study in a German university hospital was performed.

Structure and Funding of Clinical Informatics Fellowships: A National Survey of Program Directors.

Background: In 2011, the American Board of Medical Specialties established clinical informatics (CI) as a subspecialty in medicine, jointly administered by the American Board of Pathology and the American Board of Preventive Medicine. Subsequently, many institutions created CI fellowship training programs to meet the growing need for informaticists. Although many programs share similar features, there is considerable variation in program funding and administrative structures.

Advances in Clinical Decision Support Systems: Contributions from the 2022 Literature.

Objective: To summarize significant research contributions published in 2022 in the field of clinical decision support (CDS) systems and select the best papers for the Decision Support section of the International Medical Informatics Association (IMIA) Yearbook 2023.

Methods: A renewed search query for identifying CDS scholarship was developed using Medical Subject Headings (MeSH) terms and related keywords. The query was executed in PubMed in January 2023.

Creation and Evaluation of a Clinical Informatics Match: Initial Findings.

Background: Clinical Informatics (CI) fellowship programs utilize the Electronic Residency Application Service (ERAS) to gather applications but until recently used an American Medical Informatics Association (AMIA) member-developed, simultaneous offer-acceptance process to match fellowship applicants to programs. In 2021, program directors collaborated with the AMIA to develop a new match to improve the process.

Objective: Describe the results of the first 2 years of the match and address opportunities for improvement.

Limited Clinical Utility of Routine Mycobacterial Cultures for the Management of Diabetic Foot Infections.

Mycobacterial infections of the foot and ankle are uncommon. In a cohort of 2340 patients with diabetic foot infection (DFI) in a region with increased prevalence of mycobacterial disease, we identified no clinically significant positive cultures over a 3-year period. Routine mycobacterial culture of DFIs is of limited clinical utility.

Vanderbilt Electronic Health Record Voice Assistant Supports Clinicians.

Background:  Electronic health records (EHRs) present navigation challenges due to time-consuming searches across segmented data. Voice assistants can improve clinical workflows by allowing natural language queries and contextually aware navigation of the EHR.

Objectives:  To develop a voice-mediated EHR assistant and interview providers to inform its future refinement.

Assessing Racial and Ethnic Bias in Text Generation for Healthcare-Related Tasks by ChatGPT.

Large Language Models (LLM) are AI tools that can respond human-like to voice or free-text commands without training on specific tasks. However, concerns have been raised about their potential racial bias in healthcare tasks. In this study, ChatGPT was used to generate healthcare-related text for patients with HIV, analyzing data from 100 deidentified electronic health record encounters.

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.

Public perception of COVID-19 vaccines through analysis of Twitter content and users.

Background: With the global continuation of the COVID-19 pandemic, the large-scale administration of a SARS-CoV-2 vaccine is crucial to achieve herd immunity and curtail further spread of the virus, but success is contingent on public understanding and vaccine uptake. We aim to understand public perception about vaccines for COVID-19 through the wide-scale, organic discussion on Twitter.

Methods: This cross-sectional observational study included Twitter posts matching the search criteria (('covid*' OR 'coronavirus') AND 'vaccine') posted during vaccine development from February 1st through December 11th, 2020.

The lived experience of people with disabilities during the COVID-19 pandemic on Twitter: Content analysis.

Objective: People with disabilities (PWDs) are at greater risk of COVID-19 infection, complications, and death, and experience more difficulty accessing care. We analyzed Twitter tweets to identify important topics and investigate health policies' effects on PWDs.

Methods: Twitter's application programming interface was used to access its public COVID-19 stream.

Primary Care Framework to Monitor Preterm Infants for Neurodevelopmental Outcomes in Early Childhood.

To support decision-making in the primary care medical home, this clinical report links preterm birth and perinatal complications to early childhood developmental disability risks. It consolidates extensive contemporary outcome research from 2005 onward into an easy-to-use framework and stratifies prematurity and NICU experiences by degree of risk for developmental impairments. This framework informs and prioritizes point-of-care screening and surveillance strategies for pediatricians caring for children born preterm, guides additional assessment and referral for appropriate therapies, and offers opportunities for reassurance (when applicable) in office settings.

ChatGPT and the clinical informatics board examination: the end of unproctored maintenance of certification?

We aimed to assess ChatGPT's performance on the Clinical Informatics Board Examination and to discuss the implications of large language models (LLMs) for board certification and maintenance. We tested ChatGPT using 260 multiple-choice questions from Mankowitz's Clinical Informatics Board Review book, omitting 6 image-dependent questions. ChatGPT answered 190 (74%) of 254 eligible questions correctly.

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.

Correction: The Association of a Geographically Wide Social Media Network on Depression: County-Level Ecological Analysis.

[This corrects the article DOI: 10.2196/43623.].

Analyzing an Emerging Pandemic on Twitter: Monkeypox.

Background: Social media platforms like Twitter provide important insights into the public's perceptions of global outbreaks like monkeypox. By analyzing tweets, we aimed to identify public knowledge and opinions on the monkeypox virus and related public health issues.

Methods: We analyzed English-language tweets using the keyword "monkeypox" from 1 May to 23 July 2022.

The Voice of the Patient and the Electronic Health Record.

The patient's voice, which we define as the words the patient uses found in notes and messages and other sources, and their preferences for care and its outcomes, is too small a part of the electronic health record (EHR). To address this shortcoming will require innovation, research, funding, perhaps architectural changes to commercial EHRs, and that we address barriers that have resulted in this state, including clinician burden and financial drivers for care. Advantages to greater patient voice may accrue to many groups of EHR users and to patients themselves.