Can we use the pharmacy data to estimate the prevalence of chronic conditions? a comparison of multiple data sources

<p>Abstract</p> <p>Background</p> <p>The estimate of the prevalence of the most common chronic conditions (CCs) is calculated using direct methods such as prevalence surveys but also indirect methods using health administrative databases.</p> <p>The aim of this study is to provide estimates prevalence of CCs in Lazio region of Italy (including Rome), using the drug prescription's database and to compare these estimates with those obtained using other health administrative databases.</p> <p>Methods</p> <p>Prevalence of CCs was estimated using pharmacy data (PD) using the Anathomical Therapeutic Chemical Classification System (ATC).</p> <p>Prevalences estimate were compared with those estimated by hospital information system (HIS) using list of ICD9-CM diagnosis coding, registry of exempt patients from health care cost for pathology (REP) and national health survey performed by the Italian bureau of census (ISTAT).</p> <p>Results</p> <p>From the PD we identified 20 CCs. About one fourth of the population received a drug for treating a cardiovascular disease, 9% for treating a rheumatologic conditions.</p> <p>The estimated prevalences using the PD were usually higher that those obtained with one of the other sources. Regarding the comparison with the ISTAT survey there was a good agreement for cardiovascular disease, diabetes and thyroid disorder whereas for rheumatologic conditions, chronic respiratory illnesses, migraine and Alzheimer's disease, the prevalence estimates were lower than those estimated by ISTAT survey. Estimates of prevalences derived by the HIS and by the REP were usually lower than those of the PD (but malignancies, chronic renal diseases).</p> <p>Conclusion</p> <p>Our study showed that PD can be used to provide reliable prevalence estimates of several CCs in the general population.</p

Global correlation of genome and transcriptome changes in classical Hodgkin lymphoma

To identify genes involved in the pathogenesis of classical Hodgkin lymphoma (cHL), we performed serial analysis of gene expression (SAGE) and array-based comparative genomic hybridization (aCGH). Comparison of SAGE libraries of cHL cell lines L428 and L1236 with that of germinal centre B cells revealed consistent overexpression of only 14 genes. In contrast, 141 genes were downregulated in both cHL cell lines, including many B cell and HLA genes. aCGH revealed gain of 2p, 7p, 9p, 11q and Xq and loss of 4q and 11q. Eighteen percent of the differentially expressed genes mapped to regions with loss or gain and a good correlation was observed between underexpression and loss or overexpression and gain of DNA. Remarkably, gain of 2p and 9p did not correlate with increased expression of the proposed target genes c-REL and JAK2. Downregullation of many genes within the HLA region also did not correlate with loss of DNA. FSCN1 and IRAK1 mapping at genomic loci (7p and Xq) that frequently showed gain were overexpressed in cHL cell lines and might be involved in the pathogenesis of cHL. Copyright (c) 2006 John Wiley & Sons, Ltd

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited