Inferring Population HIV Viral Load From a Single HIV Clinic's Electronic Health Record: Simulation Study With a Real-World Example.

BACKGROUND: Population viral load (VL), the most comprehensive measure of the HIV transmission potential, cannot be directly measured due to lack of complete sampling of all people with HIV. OBJECTIVE: A given HIV clinic's electronic health record (EHR), a biased sample of this population, may be used to attempt to impute this measure. METHODS: We simulated a population of 10,000 individuals with VL calibrated to surveillance data with a geometric mean of 4449 copies/mL. We sampled 3 hypothetical EHRs from (A) the source population, (B) those diagnosed, and (C) those retained in care. Our analysis imputed population VL from each EHR using sampling weights followed by Bayesian adjustment. These methods were then tested using EHR data from an HIV clinic in Delaware. RESULTS: Following weighting, the estimates moved in the direction of the population value with correspondingly wider 95% intervals as follows: clinic A: 4364 (95% interval 1963-11,132) copies/mL; clinic B: 4420 (95% interval 1913-10,199) copies/mL; and clinic C: 242 (95% interval 113-563) copies/mL. Bayesian-adjusted weighting further improved the estimate. CONCLUSIONS: These findings suggest that methodological adjustments are ineffective for estimating population VL from a single clinic's EHR without the resource-intensive elucidation of an informative prior.

Data Quality in Electronic Health Record Research: An Approach for Validation and Quantitative Bias Analysis for Imperfectly Ascertained Health Outcomes Via Diagnostic Codes.

It is incumbent upon all researchers who use the electronic health record (EHR), including data scientists, to understand the quality of such data. EHR data may be subject to measurement error or misclassification that have the potential to bias results, unless one applies the available computational techniques specifically created for this problem. In this article, we begin with a discussion of data-quality issues in the EHR focusing on health outcomes. We review the concepts of sensitivity, specificity, positive and negative predictive values, and demonstrate how the imperfect classification of a dichotomous outcome variable can bias an analysis, both in terms of prevalence of the outcome, and relative risk of the outcome under one treatment regime (aka exposure) compared to another. This is then followed by a description of a generalizable approach to probabilistic (quantitative) bias analysis using a combination of regression estimation of the parameters that relate the true and observed data and application of these estimates to adjust the prevalence and relative risk that may have existed if there was no misclassification. We describe bias analysis that accounts for both random and systematic errors and highlight its limitations. We then motivate a case study with the goal of validating the accuracy of a health outcome, chronic infection with hepatitis C virus, derived from a diagnostic code in the EHR. Finally, we demonstrate our approaches on the case study and conclude by summarizing the literature on outcome misclassification and quantitative bias analysis.

Inverse probability weighting for selection bias in a Delaware community health center electronic medical record study of community deprivation and hepatitis C prevalence.

PURPOSE: To demonstrate how selection into a healthcare facility can induce bias in an electronic medical record-based study of community deprivation and chronic hepatitis C virus infection, in order to more accurately identify local risk factors and prevalence. METHODS: We created a catchment model that attempted to define the probability of selection into a retrospective cohort. Then using the inverse of this probability, we compared naïve unweighted and weighted models to demonstrate the impact of selection bias. RESULTS: ZIP code-level ecological plots of the cohort demonstrated that there was a pattern of the community deprivation, hepatitis C outcome, and distance to the health center (an intuitive proxy for being within catchments). The naïve multilevel analysis found that living in an area with greater deprivation resulted in 1.25 times greater odds of HCV (95% CI: 1.06, 1.48), whereas the weighted analysis found less certainty of this effect due to a selection bias. CONCLUSIONS: We observed that selection into the catchment area of the studied healthcare facility may bias the association of community deprivation and hepatitis C. This may be mitigated through inverse probability weighting.

A Qualitative Study of Implementing Universal Hepatitis C Screening Among Adults at an Urban Community-Based Health Provider in Delaware.

OBJECTIVES: We conducted a qualitative study of primary care providers to assess the challenges and opportunities in implementing a universal screening program for Hepatitis C Virus (HCV) at an urban community-based health center serving a largely disadvantaged population. METHODS: Qualitative semi-structured interviews of prescribing providers took place pre- and post-educational intervention, at a single federally qualified health center in Wilmington, Delaware, between September 2018 and July 2019. The intervention included a two-day didactic session and shadowing specialist providers. Data captured provider perspectives on universal screening and treatment. The interviews were transcribed verbatim, then grouped into codes, then finally, themes. RESULTS: Emergent themes included hesitancy in managing universal screening programs in the primary care environment, positive attitudes surrounding treatment, fewer HCV cases than expected, and concern with both patient-level barriers and practice-level barriers. Pre-intervention and post-intervention themes were similar. CONCLUSIONS: Implementation programs exploring universal HCV screening in the primary care environment should include educational opportunities that are available to all individuals in the practice, sustained organizational support, and available patient literature targeted to patients with varying health literacy and in languages other than English. In short, universal HCV screening and treatment is feasible in the primary medical environment but requires ongoing support and education for providers to ensure success.

Characteristics and Outcomes of SARS-CoV-2 Infection Among Adults Living With HIV In Delaware:: The Story of a Syndemic During the First 12 Months of the SARS-CoV-2 Pandemic.

Objective: To better characterize the intersection of the HIV and SARS-CoV-2 pandemics, including our robust statewide panel of people living with HIV, in the State of Delaware. Methods: We conducted a retrospective descriptive case-series that identified people living with HIV ≥ 18 years old co-infected with SARS-CoV-2 from 1 March 2020 through 9 March 2021 who attended our ambulatory HIV program, through review of testing results, electronic medical records and external clinical records. Results: There were 105 confirmed cases of SARS-CoV-2 infection and 4 attributable deaths from COVID-19 among adult people living with HIV from 1 March 2020 through 9 March 2021. Co-infected patients had very high rates of ART prescription and virologic suppression, with robust CD4 counts. 24/105 (22.9%) SARS-CoV-2 cases were hospitalized due to COVID-19 and had a significant burden of co-morbidities; a vast majority were AIDS-defined. Age, BMI >30 kg/m2, cardiovascular disease, chronic kidney disease and cirrhosis were independently associated with hospitalization by logistic regression. Black patients appeared to have lower rates of testing and higher rates of hospitalization. Additionally, those with history of natural immunity to hepatitis B virus exhibited a low rate of hospitalization. Conclusions: Our cohort data is the first to capture the experience of patients co-infected with HIV/SARS-CoV-2 in Delaware, demonstrating the risk of long-term immunosuppression and burden of comorbid disease, even in the setting of virologic suppression. Although not reaching statistical significance, we identified high rates of resolved hepatitis B virus infection amongst non-hospitalized co-infected patients and postulate there may be an underlying immunologic mechanism to this hypothesis-generating observation. Our results also highlight the role that healthcare disparities have played during these overlapping pandemics. Policy Implications: Pronounced healthcare disparities are known to worsen outcomes in a variety of disease states. From our descriptive data, we suggest continued efforts to address the social determinants of health, especially as they pertain to common chronic comorbid conditions and certain Black communities.

Epidemiology of Hepatitis C in Delaware.

Infection with hepatitis C virus (HCV) is pervasive throughout the United States of America as we fight the ongoing urban and rural opioid epidemics and rising rates of fatal and non-fatal overdoses. While risk factors for incident HCV abound, our country and the State of Delaware have increasing access to highly effective, short-course, curative HCV treatments. Despite unprecedented medical advances for HCV, as well as expanded HCV screening guidelines calling for universal adult HCV screening and screening during every pregnancy, the epidemiology of HCV at the national and statewide levels continues to be lacking. In attempting to gather, interpret, and present the highest quality available data, we conclude that HCV remains a pressing public and individual health concern for Delawareans, and our nation at large. We urge stakeholders in Delaware to make concerted efforts to fill in the many remaining gaps of HCV epidemiology in order to better inform public health resource allocation, educate the public and healthcare professionals regarding viral hepatitis, and ultimately improve the HCV care continuum, spanning from increasing rates of universal HCV screening and diagnosis to linkage to care to treatment initiation all the way to cure and beyond.

Expanding care for patients infected with Hepatitis C through community partnership in Delaware.

BACKGROUND: Hepatitis C virus (HCV) is the most common blood-borne pathogen in the U.S., and Delaware has one of the highest sero-prevalence rates in the country. As a cause of significant morbidity and mortality, it is a public health priority to identify and link individuals with HCV to care. The demand of patients with HCV far exceeds the current availability of providers in Delaware that offer HCV management. . OBJECTIVE: To propose a framework for enabling non-specialist providers within Westside Family Healthcare to manage patients with HCV. METHODS: As a recipient of a Harrington Value Institute Community Partnership grant, the HIV Community Program of Christiana Care Health System (CCHS) started working together with the NE Wilmington pilot site of Westside in July 2018 to: 1) provide HCV education to Westside, 2) implement an HCV care model at Westside, and 3) conduct programmatic evaluation of this framework's effectiveness. Our goal is to improve Westside rates of HCV knowledge amongst patients and staff, as well as to improve the HCV care continuum, starting with universal HCV screening. RESULTS AND CONCLUSIONS: Results from the first year of collaboration will be available in August 2019.  Implementation of this partnership will enable future expansion and continuation of HCV management amongst Westside sites.