An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records

AbstractWe describe a two-stage analytical approach for characterizing morbidity profile dissimilarity among patient cohorts using electronic medical records. We capture morbidities using the International Statistical Classification of Diseases and Related Health Problems (ICD-9) codes. In the first stage of the approach separate logistic regression analyses for ICD-9 sections (e.g., “hypertensive disease” or “appendicitis”) are conducted, and the odds ratios that describe adjusted differences in prevalence between two cohorts are displayed graphically. In the second stage, the results from ICD-9 section analyses are combined into a general morbidity dissimilarity index (MDI). For illustration, we examine nine cohorts of patients representing six phenotypes (or controls) derived from five institutions, each a participant in the electronic MEdical REcords and GEnomics (eMERGE) network. The phenotypes studied include type II diabetes and type II diabetes controls, peripheral arterial disease and peripheral arterial disease controls, normal cardiac conduction as measured by electrocardiography, and senile cataracts

Rates and Reasons for Early Change of First HAART in HIV-1-Infected Patients in 7 Sites throughout the Caribbean and Latin America

BACKGROUND: HAART rollout in Latin America and the Caribbean has increased from approximately 210,000 in 2003 to 390,000 patients in 2007, covering 62% (51%-70%) of eligible patients, with considerable variation among countries. No multi-cohort study has examined rates of and reasons for change of initial HAART in this region. METHODOLOGY: Antiretroviral-naïve patients >or= 18 years who started HAART between 1996 and 2007 and had at least one follow-up visit from sites in Argentina, Brazil, Chile, Haiti, Honduras, Mexico and Peru were included. Time from HAART initiation to change (stopping or switching any antiretrovirals) was estimated using Kaplan-Meier techniques. Cox proportional hazards modeled the associations between change and demographics, initial regimen, baseline CD4 count, and clinical stage. PRINCIPAL FINDINGS: Of 5026 HIV-infected patients, 35% were female, median age at HAART initiation was 37 years (interquartile range [IQR], 31-44), and median CD4 count was 105 cells/uL (IQR, 38-200). Estimated probabilities of changing within 3 months and one year of HAART initiation were 16% (95% confidence interval (CI) 15-17%) and 28% (95% CI 27-29%), respectively. Efavirenz-based regimens and no clinical AIDS at HAART initiation were associated with lower risk of change (hazard ratio (HR) = 1.7 (95% CI 1.1-2.6) and 2.1 (95% CI 1.7-2.5) comparing neverapine-based regimens and other regimens to efavirenz, respectively; HR = 1.3 (95% CI 1.1-1.5) for clinical AIDS at HAART initiation). The primary reason for change among HAART initiators were adverse events (14%), death (5.7%) and failure (1.3%) with specific toxicities varying among sites. After change, most patients remained in first line regimens. CONCLUSIONS: Adverse events were the leading cause for changing initial HAART. Predictors for change due to any reason were AIDS at baseline and the use of a non-efavirenz containing regimen. Differences between participant sites were observed and require further investigation

Measuring the Quality of Observational Study Data in an International HIV Research Network

Observational studies of health conditions and outcomes often combine clinical care data from many sites without explicitly assessing the accuracy and completeness of these data. In order to improve the quality of data in an international multi-site observational cohort of HIV-infected patients, the authors conducted on-site, Good Clinical Practice-based audits of the clinical care datasets submitted by participating HIV clinics. Discrepancies between data submitted for research and data in the clinical records were categorized using the audit codes published by the European Organization for the Research and Treatment of Cancer. Five of seven sites had error rates >10% in key study variables, notably laboratory data, weight measurements, and antiretroviral medications. All sites had significant discrepancies in medication start and stop dates. Clinical care data, particularly antiretroviral regimens and associated dates, are prone to substantial error. Verifying data against source documents through audits will improve the quality of databases and research and can be a technique for retraining staff responsible for clinical data collection. The authors recommend that all participants in observational cohorts use data audits to assess and improve the quality of data and to guide future data collection and abstraction efforts at the point of care

The eMERGE Network: A consortium of biorepositories linked to electronic medical records data for conducting genomic studies

<p>Abstract</p> <p>Introduction</p> <p>The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record (EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors.</p> <p>Organization</p> <p>The five sites are supported by an Administrative Coordinating Center. Setting of network goals is initiated by working groups: (1) Genomics, (2) Informatics, and (3) Consent & Community Consultation, which also includes active participation by investigators outside the eMERGE funded sites, and (4) Return of Results Oversight Committee. The Steering Committee, comprised of site PIs and representatives and NHGRI staff, meet three times per year, once per year with the External Scientific Panel.</p> <p>Current progress</p> <p>The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in ≈2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped. Funded by ARRA supplements, secondary phenotypes have been added at all sites to leverage the genotyping data, and hypothyroidism is being analyzed as a cross-network phenotype. Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site.</p> <p>Future activities</p> <p>Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care.</p> <p>Summary</p> <p>By combining advanced clinical informatics, genome science, and community consultation, eMERGE represents a first step in the development of data-driven approaches to incorporate genomic information into routine healthcare delivery.</p

Cross-Sectional Analysis of Late HAART Initiation in Latin America and the Caribbean: Late Testers and Late Presenters

Background: Starting HAART in a very advanced stage of disease is assumed to be the most prevalent form of initiation in HIV-infected subjects in developing countries. Data from Latin America and the Caribbean is still lacking. Our main objective was to determine the frequency, risk factors and trends in time for being late HAART initiator (LHI) in this region. Methodology: Cross-sectional analysis from 9817 HIV-infected treatment-naive patients initiating HAART at 6 sites (Argentina, Chile, Haiti, Honduras, Peru and Mexico) from October 1999 to July 2010. LHI had CD4$^+$ count $\leq$200cells/mm$^3$ prior to HAART. Late testers (LT) were those LHI who initiated HAART within 6 months of HIV diagnosis. Late presenters (LP) initiated after 6 months of diagnosis. Prevalence, risk factors and trends over time were analyzed. Principal Findings: Among subjects starting HAART (n = 9817) who had baseline CD4$^+$ available (n = 8515), 76% were LHI: Argentina (56%[95%CI:52–59]), Chile (80%[95%CI:77–82]), Haiti (76%[95%CI:74–77]), Honduras (91%[95%CI:87–94]), Mexico (79%[95%CI:75–83]), Peru (86%[95%CI:84–88]). The proportion of LHI statistically changed over time (except in Honduras) ($p\leq0.02$; Honduras p = 0.7), with a tendency towards lower rates in recent years. Males had increased risk of LHI in Chile, Haiti, Peru, and in the combined site analyses (CSA). Older patients were more likely LHI in Argentina and Peru (OR 1.21 per +10-year of age, 95%CI:1.02–1.45; OR 1.20, 95%CI:1.02–1.43; respectively), but not in CSA (OR 1.07, 95%CI:0.94–1.21). Higher education was associated with decreased risk for LHI in Chile (OR 0.92 per +1-year of education, 95%CI:0.87–0.98) (similar trends in Mexico, Peru, and CSA). LHI with date of HIV-diagnosis available, 55% were LT and 45% LP. Conclusion: LHI was highly prevalent in CCASAnet sites, mostly due to LT; the main risk factors associated were being male and older age. Earlier HIV-diagnosis and earlier treatment initiation are needed to maximize benefits from HAART in the region