Electronic phenotypes to distinguish clinician attention to high body mass index, hypertension, lipid disorders, fatty liver and diabetes in pediatric primary care: Diagnostic accuracy of electronic phenotypes compared to masked comprehensive chart review.

Background/objectives: Electronic phenotyping is a method of using electronic-health-record (EHR) data to automate identifying a patient/population with a characteristic of interest. This study determines validity of using EHR data of children with overweight/obesity to electronically phenotype evidence of clinician 'attention' to high body mass index (BMI) and each of four distinct comorbidities.

Methods: We built five electronic phenotypes classifying 2-18-year-old children with overweight/obesity (n = 17,397) by electronic/health-record evidence of distinct attention to high body mass index, hypertension, lipid disorders, fatty liver, and prediabetes/diabetes.

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.

District-Level Universal Masking Policies and COVID-19 Incidence During the First 8 Weeks of School in Texas.

Texas discontinued state-sponsored business restrictions and mask mandates on March 10, 2021, and mandated that no government officials, including public school officials, may implement mask requirements even in areas where COVID-19 hospitalizations comprised more than 15% of hospitalizations. Nonetheless, some public school districts began the 2021-2022 school year with mask mandates in place. We used quasi-experimental methods to analyze the impact of school mask mandates, which appear to have resulted in approximately 40 fewer student cases per week in the first eight weeks of school.

Rolling Up the Sleeve: Equitable, Efficient, and Safe COVID-19 Mass Immunization for Academic Medical Center Employees.

Background: Novel coronavirus disease 2019 (COVID-19) vaccine administration has faced distribution barriers across the United States. We sought to delineate our vaccine delivery experience in the first week of vaccine availability, and our effort to prioritize employees based on risk with a goal of providing an efficient infrastructure to optimize speed and efficiency of vaccine delivery while minimizing risk of infection during the immunization process.

Objective: This article aims to evaluate an employee prioritization/invitation/scheduling system, leveraging an integrated electronic health record patient portal framework for employee COVID-19 immunizations at an academic medical center.

COVID-19 Mass Vaccination Resource Calculator.

Background: Despite the recent emergency use authorization of two vaccines for the prevention of the 2019 novel coronavirus (COVID-19) disease, vaccination rates are lower than expected. Vaccination efforts may be hampered by supply, delivery, storage, patient prioritization, administration infrastructure or logistics problems. To address the last issue, our institution is sharing publically a calculator to optimize the management of staffing and facility resources in an outpatient mass vaccination effort.

Managing Pandemics with Health Informatics: Successes and Challenges.

Introduction: The novel COVID-19 pandemic struck the world unprepared. This keynote outlines challenges and successes using data to inform providers, government officials, hospitals, and patients in a pandemic.

Methods: The authors outline the data required to manage a novel pandemic including their potential uses by governments, public health organizations, and individuals.

Derivation With Internal Validation of a Multivariable Predictive Model to Predict COVID-19 Test Results in Emergency Department Patients.

Objectives: The COVID-19 pandemic has placed acute care providers in demanding situations in predicting disease given the clinical variability, desire to cohort patients, and high variance in testing availability. An approach to stratifying patients by likelihood of disease based on rapidly available emergency department (ED) clinical data would offer significant operational and clinical value. The purpose of this study was to develop and internally validate a predictive model to aid in the discrimination of patients undergoing investigation for COVID-19.

Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter.

Objective: Social distancing policies are key in curtailing severe acute respiratory coronavirus virus 2 (SARS-CoV-2) spread, but their effectiveness is heavily contingent on public understanding and collective adherence. We studied public perception of social distancing through organic, large-scale discussion on Twitter.

Design: Retrospective cross-sectional study.

User stories as lightweight requirements for agile clinical decision support development.

Objective: We sought to demonstrate applicability of user stories, progressively elaborated by testable acceptance criteria, as lightweight requirements for agile development of clinical decision support (CDS).

Materials And Methods: User stories employed the template: As a [type of user], I want [some goal] so that [some reason]. From the "so that" section, CDS benefit measures were derived.

Correction: SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets.

[This corrects the article DOI: 10.2196/11487.].

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets.

Background: Defining clinical phenotypes from electronic health record (EHR)-derived data proves crucial for clinical decision support, population health endeavors, and translational research. EHR diagnoses now commonly draw from a finely grained clinical terminology-either native SNOMED CT or a vendor-supplied terminology mapped to SNOMED CT concepts as the standard for EHR interoperability. Accordingly, electronic clinical quality measures (eCQMs) increasingly define clinical phenotypes with SNOMED CT value sets.

Agile Co-Development for Clinical Adoption and Adaptation of Innovative Technologies.

Even the most innovative healthcare technologies provide patient benefits only when adopted by clinicians and/or patients in actual practice. Yet realizing optimal positive impact from a new technology for the widest range of individuals who would benefit remains elusive. In software and new product development, iterative rapid-cycle "agile" methods more rapidly provide value, mitigate failure risks, and adapt to customer feedback.

SNOMED CT Concept Hierarchies for Sharing Definitions of Clinical Conditions Using Electronic Health Record Data.

Background: Defining clinical conditions from electronic health record (EHR) data underpins population health activities, clinical decision support, and analytics. In an EHR, defining a condition commonly employs a diagnosis value set or "grouper." For constructing value sets, Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) offers high clinical fidelity, a hierarchical ontology, and wide implementation in EHRs as the standard interoperability vocabulary for problems.

Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

Background: Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common.