Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programs.

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection.

A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation.

Background: A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC).

Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER program.

Long COVID, or complications arising from COVID-19 weeks after infection, has become a central concern for public health experts. The United States National Institutes of Health founded the RECOVER initiative to better understand long COVID. We used electronic health records available through the National COVID Cohort Collaborative to characterize the association between SARS-CoV-2 vaccination and long COVID diagnosis.

Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs.

Objective: Clinical encounter data are heterogeneous and vary greatly from institution to institution. These problems of variance affect interpretability and usability of clinical encounter data for analysis. These problems are magnified when multisite electronic health record (EHR) data are networked together.

Long COVID Risk and Pre-COVID Vaccination: An EHR-Based Cohort Study from the RECOVER Program.

Importance: Characterizing the effect of vaccination on long COVID allows for better healthcare recommendations.

Objective: To determine if, and to what degree, vaccination prior to COVID-19 is associated with eventual long COVID onset, among those a documented COVID-19 infection.

Design Settings And Participants: Retrospective cohort study of adults with evidence of COVID-19 between August 1, 2021 and January 31, 2022 based on electronic health records from eleven healthcare institutions taking part in the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative, a project of the National Covid Cohort Collaborative (N3C).

Using Electronic Medical Records to Identify Enhanced Recovery After Surgery Cases.

Context: Enhanced recovery after surgery (ERAS) aims to improve surgical outcomes by integrating evidence-based practices across preoperative, intraoperative, and postoperative care. Data in electronic medical records (EMRs) provide insight on how ERAS is implemented and its impact on surgical outcomes. Because ERAS is a multimodal pathway provided by multiple physicians and health care providers over time, identifying ERAS cases in EMRs is not a trivial task.

Method to determine allocation of clinical pharmacist resources.

Purpose: An objective methodology to guide decisions by hospital pharmacy departments on the best use of clinical pharmacist personnel is described.

Summary: To help determine the optimal deployment of state-licensed Clinical Pharmacist Specialist (CPS) staff, a task force led by the pharmacy department at University of North Carolina (UNC) Hospitals developed an objective approach to evaluating the relative need for and potential impact of CPS expertise within the medical center's many service units. After analyzing several years of patient census and medication-use data and using information from proprietary databases (Thomson Reuters) to calculate a "service-specific pharmacy intensity score" for each hospital service, the task force identified five staff-allocation metrics best suited to the medical center's service-based pharmacy coverage model.

Cost-effectiveness of electrocardiography vs. electrocardiography plus limited echocardiography to diagnose LVH in young, newly identified, hypertensives.

Background: In the United States, screening for left ventricular hypertrophy (LVH) in a newly diagnosed hypertensive patient is typically performed using electrocardiography (ECG). Echocardiography (echo) is a more accurate but also more expensive procedure. However, the introduction of limited echo within the past decade has made sonographic imaging of the heart less expensive and more available for routine screening.

A longitudinal study on the relationship between weight loss, medical expenditures, and absenteeism among overweight employees in the WAY to Health study.

Objective: To quantify the extent to which successful weight loss among overweight/obese employees translates into subsequent savings in medical expenditures and absenteeism.

Methods: This analysis relied on medical claims and absenteeism data collected from overweight/obese employees at 17 community colleges in North Carolina.

Results: We find no evidence that participants achieving at least a 5% weight loss experienced reduced medical expenditures or lower absenteeism during the 12-month weight loss intervention or in the subsequent 2 years.