scholarly journals Development and validation of an electronic medical record (EMR)-based computed phenotype of HIV-1 infection

2017 ◽  
Vol 25 (2) ◽  
pp. 150-157 ◽  
Author(s):  
Devon W Paul ◽  
Nigel B Neely ◽  
Meredith Clement ◽  
Isaretta Riley ◽  
Mashael Al-Hegelan ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Sensitivity And Specificity ◽  
International Classification Of Diseases ◽  
Veterans Health ◽  
Health Administration ◽  
Classification Of Diseases ◽  
Novel Algorithms ◽  
Sensitivity Specificity

Abstract Background Electronic medical record (EMR) computed algorithms allow investigators to screen thousands of patient records to identify specific disease cases. No computed algorithms have been developed to detect all cases of human immunodeficiency virus (HIV) infection using administrative, laboratory, and clinical documentation data outside of the Veterans Health Administration. We developed novel EMR-based algorithms for HIV detection and validated them in a cohort of subjects in the Duke University Health System (DUHS). Methods We created 2 novel algorithms to identify HIV-infected subjects. Algorithm 1 used laboratory studies and medications to identify HIV-infected subjects, whereas Algorithm 2 used International Classification of Diseases, Ninth Revision (ICD-9) codes, medications, and laboratory testing. We applied the algorithms to a well-characterized cohort of patients and validated both against the gold standard of physician chart review. We determined sensitivity, specificity, and prevalence of HIV between 2007 and 2011 in patients seen at DUHS. Results A total of 172 271 patients were detected with complete data; 1063 patients met algorithm criteria for HIV infection. In all, 970 individuals were identified by both algorithms, 78 by Algorithm 1 alone, and 15 by Algorithm 2 alone. The sensitivity and specificity of each algorithm were 78% and 99%, respectively, for Algorithm 1 and 77% and 100% for Algorithm 2. The estimated prevalence of HIV infection at DUHS between 2007 and 2011 was 0.6%. Conclusions EMR-based phenotypes of HIV infection are capable of detecting cases of HIV-infected adults with good sensitivity and specificity. These algorithms have the potential to be adapted to other EMR systems, allowing for the creation of cohorts of patients across EMR systems.

scholarly journals Modern Look at Transverse Myelitis and Inflammatory Myelopathy

2021 ◽  
Vol 8 (6) ◽  
pp. e1071
Author(s):  
Justin R. Abbatemarco ◽  
Jonathan R. Galli ◽  
Michael L. Sweeney ◽  
Noel G. Carlson ◽  
Verena C. Samara ◽  
...  
Keyword(s):  
Transverse Myelitis ◽  
Population Level ◽  
International Classification Of Diseases ◽  
Mortality Data ◽  
Veterans Health ◽  
Health Administration ◽  
Level Data ◽  
High Prevalence ◽  
Classification Of Diseases

Background and ObjectivesTo characterize population-level data associated with transverse myelitis (TM) within the US Veterans Health Administration (VHA).MethodsThis retrospective review used VHA electronic medical record from 1999 to 2015. We analyzed prevalence, disease characteristics, modified Rankin Scale (mRS) scores, and mortality data in patients with TM based on the 2002 Diagnostic Criteria.ResultsWe identified 4,084 patients with an International Classification of Diseases (ICD) code consistent with TM and confirmed the diagnosis in 1,001 individuals (90.7% males, median age 64.2, 67.7% Caucasian, and 31.4% smokers). The point prevalence was 7.86 cases per 100,000 people. Less than half of the cohort underwent a lumbar puncture, whereas only 31.8% had a final, disease-associated TM diagnosis. The median mRS score at symptom onset was 3 (interquartile range 2–4), which remained unchanged at follow-up, although less than half (43.2%) of the patients received corticosteroids, IVIg, or plasma exchange. Approximately one-quarter of patients (24.3%) had longitudinal extensive TM, which was associated with poorer outcomes (p = 0.002). A total of 108 patients (10.8%) died during our review (94.4% males, median age 66.5%, and 70.4% Caucasian). Mortality was associated with a higher mRS score at follow-up (OR 1.94, 95% CI, 1.57–2.40) and tobacco use (OR 1.87, 95% CI, 1.17–2.99).DiscussionThis national TM review highlights the relatively high prevalence of TM in a modern cohort. It also underscores the importance of a precise and thorough workup in this disabling disorder to ensure diagnostic precision and ensure optimal management for patients with TM in the future.

scholarly journals Population genealogy resource shows evidence of familial clustering for Alzheimer disease

2018 ◽  
Vol 4 (4) ◽  
pp. e249
Author(s):  
Lisa Anne Cannon-Albright ◽  
Sue Dintelman ◽  
Tim Maness ◽  
Johni Cerny ◽  
Alun Thomas ◽  
...  
Keyword(s):  
Alzheimer Disease ◽  
International Classification Of Diseases ◽  
Veterans Health ◽  
Health Administration ◽  
Significant Excess ◽  
Relative Risks ◽  
Multiple Phenotypes ◽  
The Us ◽  
Familial Clustering ◽  
Classification Of Diseases

ObjectiveTo show the potential of a resource consisting of a genealogy of the US record linked to National Veterans Health Administration (VHA) patient data for investigation of the genetic contribution to health-related phenotypes, we present an analysis of familial clustering of VHA patients diagnosed with Alzheimer disease (AD).MethodsPatients with AD were identified by the International Classification of Diseases code. The Genealogical Index of Familiality method was used to compare the average relatedness of VHA patients with AD with expected relatedness. Relative risks for AD were estimated in first- to fifth- degree relatives of patients with AD using population rates for AD.ResultsEvidence for significant excess relatedness and significantly elevated risks for AD in relatives was observed; multiple pedigrees with a significant excess of VHA patients with AD were identified.ConclusionsThis analysis of AD shows the nascent power of the US Veterans Genealogy Resource, in early stages, to provide evidence for familial clustering of multiple phenotypes, and shows the utility of this VHA genealogic resource for future genetic studies.

scholarly journals Measuring Performance Directly Using the Veterans Health Administration Electronic Medical Record

Medical Care ◽  
2007 ◽  
Vol 45 (1) ◽  
pp. 73-79 ◽  
Author(s):  
Joseph L. Goulet ◽  
Joseph Erdos ◽  
Sue Kancir ◽  
Forrest L. Levin ◽  
Steven M. Wright ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Veterans Health Administration ◽  
Veterans Health ◽  
Health Administration

scholarly journals Association between hemoglobin A1c variability and hypoglycemia-related hospitalizations in veterans with diabetes mellitus

2021 ◽  
Vol 9 (1) ◽  
pp. e001797
Author(s):  
Molly J Y Zhao ◽  
Julia C Prentice ◽  
David C Mohr ◽  
Paul R Conlin
Keyword(s):  
Diabetes Mellitus ◽  
Hemoglobin A1c ◽  
Severe Hypoglycemia ◽  
International Classification Of Diseases ◽  
Baseline Period ◽  
Veterans Health ◽  
Health Administration ◽  
Classification Of Diseases ◽  
The Impact

IntroductionTo study the impact of hemoglobin A1c (A1c) variability on the risk of hypoglycemia-related hospitalization (HRH) in veterans with diabetes mellitus.Research design and methods342 059 veterans with diabetes aged 65 years or older were identified for a retrospective cohort study. All participants had a 3-year baseline period from January 1, 2005 to December 31, 2016, during which they had at least four A1c tests. A1c variability measures included coefficient of variation (A1c CV), A1c SD, and adjusted A1c SD. HRH was identified during a 2-year follow-up period from Medicare and the Veterans Health Administration through validated algorithms of International Classification of Diseases (ICD)-9 and ICD-10 codes. Logistic regression modeling was used to evaluate the relationship between A1c variability and HRH risk while controlling for relevant clinical covariates.Results2871 patients had one or more HRH in the 2-year follow-up period. HRH risk increased with greater A1c variability, and this was consistent across A1c CV, A1c SD, and adjusted A1c SD. Average A1c levels were also independently associated with HRH, with levels <7.0% (53 mmol/mol) having lower risk and >9% (75 mmol/mol) with greater risk. The relationships between A1c variability remained significant after controlling for average A1c levels and prior HRH during the baseline period.ConclusionIncreasing A1c variability and elevated A1c levels are associated with a greater risk of HRH in older adults with diabetes. Clinicians should consider A1c variability when assessing patients for risk of severe hypoglycemia.

scholarly journals Validation of ICD-10-CM codes for injuries complicating pregnancy, childbirth and the puerperium: a medical record review

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i9-i12
Author(s):  
Anna Hansen ◽  
Dana Quesinberry ◽  
Peter Akpunonu ◽  
Julia Martin ◽  
Svetla Slavova
Keyword(s):  
Emergency Department ◽  
Medical Record ◽  
International Classification Of Diseases ◽  
Medical Record Review ◽  
Full Sample ◽  
Emergency Department Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Record Review

IntroductionThe purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.MethodsA medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an abstraction form to collect information on documented presence of injury and PCP complications. The study estimated the PPVs and the 95% CIs of O9A.2-O9A.4 codes for (1) capturing injuries and (2) capturing injuries complicating PCP.ResultsThe estimated PPV for the codes O9A.2-O9A.4 to identify injury in the full sample was 79.6% (95% CI 73.3% to 85.9%) and the PPV for capturing injuries complicating PCP was 72.0% (95% CI 65.0% to 79.0%). The estimated PPV for an inpatient principal diagnosis O9A.2-O9A.4 to capture injuries was 90.7% (95% CI 82.0% to 99.4%) and the PPV for capturing injuries complicating PCP was 88.4% (95% CI 78.4% to 98.4%). The estimated PPV for any mention of O9A.2-O9A.4 in emergency department data to capture injuries was 95.2% (95% CI 90.6% to 99.9%) and the PPV for capturing injuries complicating PCP was 81.0% (95% CI 72.4% to 89.5%).DiscussionThe O9A.2-O9A.4 codes captured high percentage true injury cases among pregnant and puerperal women.

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