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. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease.

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. Among patients with a COVID-19 infection between August 1, 2021 and January 31, 2022, we defined two cohorts using distinct definitions of long COVID-a clinical diagnosis (n = 47,404) or a previously described computational phenotype (n = 198,514)-to compare unvaccinated individuals to those with a complete vaccine series prior to infection. Evidence of long COVID was monitored through June or July of 2022, depending on patients' data availability. We found that vaccination was consistently associated with lower odds and rates of long COVID clinical diagnosis and high-confidence computationally derived diagnosis after adjusting for sex, demographics, and medical history.

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. This article presents a novel, generalizable method for resolving encounter heterogeneity for analysis by combining related atomic encounters into composite "macrovisits." MATERIALS AND METHODS: Encounters were composed of data from 75 partner sites harmonized to a common data model as part of the NIH Researching COVID to Enhance Recovery Initiative, a project of the National Covid Cohort Collaborative. Summary statistics were computed for overall and site-level data to assess issues and identify modifications. Two algorithms were developed to refine atomic encounters into cleaner, analyzable longitudinal clinical visits. RESULTS: Atomic inpatient encounters data were found to be widely disparate between sites in terms of length-of-stay (LOS) and numbers of OMOP CDM measurements per encounter. After aggregating encounters to macrovisits, LOS and measurement variance decreased. A subsequent algorithm to identify hospitalized macrovisits further reduced data variability. DISCUSSION: Encounters are a complex and heterogeneous component of EHR data and native data issues are not addressed by existing methods. These types of complex and poorly studied issues contribute to the difficulty of deriving value from EHR data, and these types of foundational, large-scale explorations, and developments are necessary to realize the full potential of modern real-world data. CONCLUSION: This article presents method developments to manipulate and resolve EHR encounter data issues in a generalizable way as a foundation for future research and analysis.

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). Exposures: Pre-COVID-19 receipt of a complete vaccine series versus no pre-COVID-19 vaccination. Main Outcomes and Measures: Two approaches to the identification of long COVID were used. In the clinical diagnosis cohort (n=47,752), ICD-10 diagnosis codes or evidence of a healthcare encounter at a long COVID clinic were used. In the model-based cohort (n=199,498), a computable phenotype was used. The association between pre-COVID vaccination and long COVID was estimated using IPTW-adjusted logistic regression and Cox proportional hazards. Results: In both cohorts, when adjusting for demographics and medical history, pre-COVID vaccination was associated with a reduced risk of long COVID (clinic-based cohort: HR, 0.66; 95% CI, 0.55-0.80; OR, 0.69; 95% CI, 0.59-0.82; model-based cohort: HR, 0.62; 95% CI, 0.56-0.69; OR, 0.70; 95% CI, 0.65-0.75). Conclusions and Relevance: Long COVID has become a central concern for public health experts. Prior studies have considered the effect of vaccination on the prevalence of future long COVID symptoms, but ours is the first to thoroughly characterize the association between vaccination and clinically diagnosed or computationally derived long COVID. Our results bolster the growing consensus that vaccines retain protective effects against long COVID even in breakthrough infections. Key Points: Question: Does vaccination prior to COVID-19 onset change the risk of long COVID diagnosis?Findings: Four observational analyses of EHRs showed a statistically significant reduction in long COVID risk associated with pre-COVID vaccination (first cohort: HR, 0.66; 95% CI, 0.55-0.80; OR, 0.69; 95% CI, 0.59-0.82; second cohort: HR, 0.62; 95% CI, 0.56-0.69; OR, 0.70; 95% CI, 0.65-0.75).Meaning: Vaccination prior to COVID onset has a protective association with long COVID even in the case of breakthrough infections.

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. To better understand how EMRs can be used to study ERAS, we describe our experience with using current methodologies and the development and rationale of a new method for retrospectively identifying ERAS cases in EMRs. CASE DESCRIPTION: Using EMR data from surgical departments at the University of North Carolina at Chapel Hill, we first identified ERAS cases using a protocol-based method, using basic information including the date of ERAS implementation, surgical procedure and date, and primary surgeon. We further examined two operational flags in the EMRs, a nursing order and a case request for OR order. Wide variation between the methods compelled us to consult with ERAS surgical staff and explore the EMRs to develop a more refined method for identifying ERAS cases. METHOD: We developed a two-step method, with the first step based on the protocol definition and the second step based on an ERAS-specific medication definition. To test our method, we randomly sampled 150 general, gynecological, and urologic surgeries performed between January 1, 2016 and March 30, 2017. Surgical cases were classified as ERAS or not using the protocol definition, nursing order, case request for OR order, and our two-step method. To assess the accuracy of each method, two independent reviewers assessed the charts to determine whether cases were ERAS. FINDINGS: Of the 150 charts reviewed, 74 were ERAS cases. The protocol only method and nursing order flag performed similarly, correctly identifying 74 percent and 73 percent of true ERAS cases, respectively. The case request for OR order flag performed less well, correctly identifying only 44 percent of the true ERAS cases. Our two-step method performed well, correctly identifying 98 percent of true ERAS cases. CONCLUSION: ERAS pathways are complex, making study of them from EMRs difficult. Current strategies for doing so are relatively easy to implement, but unreliable. We have developed a reproducible and observable ERAS computational phenotype that identifies ERAS cases reliably. This is a step forward in using the richness of EMR data to study ERAS implementation, efficacy, and how they can contribute to surgical care improvement.

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. By applying the methodology, it was determined that CPS expertise was most needed in the UNC Hospitals adult medicine oncology service, the bone marrow transplant service, and the medical and neonatal intensive care units. The tool was initially used to validate the pharmacy department's existing human resource allocation and has since been used to guide budgeting for and deployment of newly added CPS positions. CONCLUSION: A novel tool to guide the application of pharmacy human resources incorporates the objective criteria of patient census, patient acuity, teaching involvement, drug expenditures, and use of high-risk medications. The tool can be used to determine the appropriate allocation and placement of clinical pharmacist resources in a service-based 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. METHODS: The cost per additional correct diagnosis of LVH for ECG vs. ECG plus limited echo (with limited echo utilized in patients without ECG evidence of LVH) was analyzed using decision analytic modeling. A structured literature search was used to parameterize model probabilities, and costs are based on the 2008 Medicare Physician Fee Schedule. The study population consisted of black and white cohorts ~50 years of age with new diagnosis of hypertension. Outcomes included short-term results of LVH screening and diagnosis, and the study perspective was health system. RESULTS: Base-case results indicate each additional correct LVH diagnosis by ECG plus limited echocardiography instead of ECG cost $655 in the black cohort and $829 in the white cohort. Results in both cohorts were most sensitive to the cost of echocardiography. Simulation-generated cost-effectiveness acceptability curves demonstrated costs per additional correct diagnosis have a 90% likelihood of being below $993 and $1,420 in the black and white cohorts, respectively. CONCLUSIONS: LVH detection by ECG plus limited echocardiography may be an economically feasible alternative to ECG due to increased accuracy. However, final recommendations require analysis of long-term effects on morbidity, mortality, quality of life, and subsequent treatment costs between the diagnostic approaches.

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. CONCLUSIONS: These results suggest that a quick return on investment from weight loss programs, even effective ones, is unlikely. Nevertheless, as with other employee benefit decisions, the decision about whether to offer weight loss programs should take into account many factors, such as employee health, in addition to the potential for a quick return on investment.