ArticleAIDS care2014
Development of an electronic medical record-based algorithm to identify patients with unknown HIV status.
Article in AIDS care, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 40 citations in OpenAlex.
- The impact of nurse-driven targeted HIV screening in 8 emergency departments: study protocol for the DICI-VIH cluster-randomized two-period crossover trial.BMC infectious diseases · 2016Trial
- Development and Evaluation of a Novel Algorithm to Identify Doxycycline Postexposure Prophylaxis Users at a Large Healthcare System in the Bronx, New York.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Article
- Heart Failure Risk in Patients With Systemic Autoimmune Inflammatory Diseases.Journal of the American Heart Association · 2026Article
- Automated HIV Case Identification from the MIMIC-IV Database.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Association of HIV and viral suppression status with hospital acute kidney injury in the era of antiretroviral therapy.Kidney international · 2023Observational
- Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV.JAMIA open · 2023Article
- Comparison of algorithms for identifying people with HIV from electronic medical records in a large, multi-site database.JAMIA open · 2022Article
- Phenotypic Presentations of Heart Failure Among Patients With Chronic Inflammatory Diseases.Frontiers in cardiovascular medicine · 2022Article
- A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study.JMIR formative research · 2021Article
- Optimizing Identification of People Living with HIV from Electronic Medical Records: Computable Phenotype Development and Validation.Methods of information in medicine · 2021Article
- Brief Report: Acute Kidney Injury in People Living With HIV Hospitalized With Coronavirus Disease 2019: Clinical Characteristics and Outcomes.Journal of acquired immune deficiency syndromes (1999) · 2021Article
- Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review.JMIR medical informatics · 2021Article
- Comparative Risk of Incident Coronary Heart Disease Across Chronic Inflammatory Diseases.Frontiers in cardiovascular medicine · 2021Article
- Differential Associations of Chronic Inflammatory Diseases With Incident Heart Failure.JACC. Heart failure · 2020Article
- Differences in statin utilization and lipid lowering by race, ethnicity, and HIV status in a real-world cohort of persons with human immunodeficiency virus and uninfected persons.American heart journal · 2019Article
- Adjudicated Heart Failure in HIV-Infected and Uninfected Men and Women.Journal of the American Heart Association · 2018Article
- Development and Validation of an Electronic Medical Record-Based Algorithm to Identify Patient Milestones in the Hepatitis C Virus Care Cascade.Open forum infectious diseases · 2018Article
- Development and validation of an electronic medical record (EMR)-based computed phenotype of HIV-1 infection.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Atrial arrhythmia prevalence and characteristics for human immunodeficiency virus-infected persons and matched uninfected controls.PloS one · 2018Article
- Clinical characteristics of HIV-infected patients with adjudicated heart failure.European journal of preventive cardiology · 2017Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Individuals with unknown HIV status are at risk for undiagnosed HIV, but practical and reliable methods for identifying these individuals have not been described. We developed an algorithm to identify patients with unknown HIV status using data from the electronic medical record (EMR) of a large health care system. We developed EMR-based criteria to classify patients as having known status (HIV-positive or HIV-negative) or unknown status and applied these criteria to all patients seen in the affiliated health care system from 2008 to 2012. Performance characteristics of the algorithm for identifying patients with unknown HIV status were calculated by comparing a random sample of the algorithm's results to a reference standard medical record review. The algorithm classifies all patients as having either known or unknown HIV status. Its sensitivity and specificity for identifying patients with unknown status are 99.4% (95% CI: 96.5-100%) and 95.2% (95% CI: 83.8-99.4%), respectively, with positive and negative predictive values of 98.7% (95% CI: 95.5-99.8%) and 97.6% (95% CI: 87.1-99.1%), respectively. Using commonly available data from an EMR, our algorithm has high sensitivity and specificity for identifying patients with unknown HIV status. This algorithm may inform expanded HIV testing strategies aiming to test the untested.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.