Combined telemedicine-first and direct primary care as a promising model of healthcare delivery.

Telemedicine is comparable in quality to in-person care, adequate for many primary care concerns, acceptable to patients, and can overcome barriers to care. However, patients are reluctant to pay the same for telemedicine as in-person care and uncertainty about future payor reimbursement makes it risky to base a clinical practice primarily on telemedicine. Physical exam-supported information collection and relationship-building are limited in telemedicine, but can be mitigated through remote patient monitoring and ample access to a provider and clinical team.

Diagnoses per Encounter by Telephone, Televideo, and In-Office Visits.

Introduction: We sought to determine if there are differences between number of International Classification of Disease-10 (ICD-10) codes per visit before and after COVID-19 when comparing in-office visits and between telemedicine vs in-office visits, toward the goal of determining value of telemedicine visits relative to in-office visits.

Methods: We did a chart review study assessing the number of ICD-10 codes noted by providers at a large academic medical institution in 2019 and 2020. Only in-office visits were reviewed in 2019.

X-ray absorption spectroscopy and actinide electrochemistry: a setup dedicated to radioactive samples applied to neptunium chemistry.

A spectroelectrochemical setup has been developed to investigate radioactive elements in small volumes (0.7 to 2 ml) under oxidation-reduction (redox) controlled conditions by X-ray absorption spectroscopy (XAS). The cell design is presented together with in situ XAS measurements performed during neptunium redox reactions.

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record's Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study.

Background: Nonvalvular atrial fibrillation (NVAF) affects almost 6 million Americans and is a major contributor to stroke but is significantly undiagnosed and undertreated despite explicit guidelines for oral anticoagulation.

Objective: The aim of this study is to investigate whether the use of semisupervised natural language processing (NLP) of electronic health record's (EHR) free-text information combined with structured EHR data improves NVAF discovery and treatment and perhaps offers a method to prevent thousands of deaths and save billions of dollars.

Methods: We abstracted 96,681 participants from the University of Buffalo faculty practice's EHR.

What's Happening in Your Head: Overcoming Our Assumptions to Work Better Together.

Introduction: It is crucial that residents learn in environments that are psychologically safe and free of morale-harming rumors. This workshop introduced the Ladder of Inference as a means for programs to foster psychological safety, mitigate against rumors, and increase trust.

Methods: Residents and faculty of two residency programs (cohorts A and B) were introduced to the Ladder of Inference.

Electrochemical and Spectroscopic Study of Eu and Eu Coordination in the 1-Ethyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide Ionic Liquid.

Separation processes based on room temperature ionic liquids (RTIL) and electrochemical refining are promising strategies for the recovery of lanthanides from primary ores and electronic waste. However, they require the speciation of dissolved elements to be known with accuracy. In the present study, Eu coordination and Eu /Eu electrochemical behavior as a function of water content in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIm][NTf ]) was investigated using UV-visible spectrophotometry, time-resolved laser fluorescence spectroscopy, electrochemistry, and X-ray absorption spectroscopy.

Clinical Tractor: A Framework for Automatic Natural Language Understanding of Clinical Practice Guidelines.

Computational representations of the semantic knowledge embedded within clinical practice guidelines (CPGs) may be a significant aid in creating computer interpretable guidelines (CIGs). Formalizing plain text CPGs into CIGs manually is a laborious and burdensome task, even using CIG tools and languages designed to improve the process. Natural language understanding (NLU) systems perform automated reading comprehension, parsing text and using reasoning to convert syntactic information from unstructured text into semantic information.

Comparison of Changes in the Number of Included Patients Between Interventional Trials and Observational Studies Published from 1995 to 2014 in Three Leading Journals.

Introduction: Since the late 1990s, research and administrative institutions have been developing health data warehouses and increasingly reusing claims data. The impact of these changes is not yet completely quantified. Our objective was to compare the change in the number of patients included per study between observational and interventional studies over a 20-year period starting in 1995.

Surveying Applicants to Improve the Family Medicine Residency Interview Day.

Introduction: The diversity of family medicine residency programs across the country makes a generalized assessment of applicant preferences and experiences regarding the interview experience difficult. As such, there have been few publications in recent years relating to interview trail trends and modification of the interview day process to meet the needs of applicants. The purpose of this project was to identify applicant preferences and trends among applicants interviewing at Penn State Health's Milton S.

Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with self-diagnosis of knee problems and to thereby facilitate referral to the right orthopedic subspecialist. They had two independent sports medicine physicians review 469 cases.

HTP-NLP: A New NLP System for High Throughput Phenotyping.

Secondary use of clinical data for research requires a method to quickly process the data so that researchers can quickly extract cohorts. We present two advances in the High Throughput Phenotyping NLP system which support the aim of truly high throughput processing of clinical data, inspired by a characterization of the linguistic properties of such data. Semantic indexing to store and generalize partially-processed results and the use of compositional expressions for ungrammatical text are discussed, along with a set of initial timing results for the system.

Automatically Expanding the Synonym Set of SNOMED CT using Wikipedia.

Clinical terminologies and ontologies are often used in natural language processing/understanding tasks as a method for semantically tagging text. One ontology commonly used for this task is SNOMED CT. Natural language is rich and varied: many different combinations of words may be used to express the same idea.

Prediction of hospital disposition after thrombolysis for acute ischemic stroke using the National Institutes of Health Stroke Scale.

Background: Early determination of discharge destination after acute stroke may promote earlier rehabilitation and reduce costs by shortening the duration of hospitalization.

Objective: To determine whether the National Institutes of Health Stroke Scale (NIHSS) score predicts disposition in stroke patients treated with thrombolysis.

Design: Cohort study.

Utility of the NIH Stroke Scale as a predictor of hospital disposition.

Background And Purpose: Early identification of stroke patients in need of rehabilitation or long-term nursing facility (NF) care may promote more efficient use of health care resources and lead to better outcomes. The NIH Stroke Scale (NIHSS) is an attractive candidate predictor of disposition because it is widely used, is easily learned, and can be performed rapidly on admission.

Methods: We present a retrospective study of stroke patients admitted within 24 hours of symptom onset to a university hospital from March through June 2000.