There was acceptable representation of the data from 10 observational databases in the OMOP CDM using the standardized terminologies selected, and a range of analytic methods was developed and executed with sufficient performance to be useful for active safety surveillance.

Although sickle cell disease (SCD) is marked by high utilization of medical resources, the full cost of care for patients with SCD, including care not directly related to SCD, is unknown. The purpose of this study was to estimate the total cost of medical care for a population of children and adults with SCD. We used data from individuals diagnosed with SCD enrolled in the Florida Medicaid program during 2001-2005 to estimate total, SCD-related, and non-SCD-related cost per patient-month based on patient age at the time of health care use. Across the 4,294 patient samples, total health care costs generally rose with age, from $892 to $2,562 per patient-month in the 0-9-and 50-64-year age groups, respectively. Average cost per patient-month was $1,389. Overall, 51.8% of care was directly related to SCD, the majority of which (80.5%) was associated with inpatient hospitalizations. Notably, non-SCD-related costs were substantially higher than those reported for the general US population. These results suggest a discounted (3% discount rate) lifetime cost of care averaging $460,151 per patient with SCD. Interventions designed to prevent SCD complications and avoid hospitalizations may reduce the significant economic burden of the disease. Am. J.

The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks of marketed drugs and other medical products. The Observational Medical Outcomes Partnership is a public-private partnership among the FDA, academia, data owners, and the pharmaceutical industry that is responding to the need to advance the science of active medical product safety surveillance by using existing observational databases. The Observational Medical Outcomes Partnership's transparent, open innovation approach is designed to systematically and empirically study critical governance, data resource, and methodological issues and their interrelationships in establishing a viable national program of active drug safety surveillance by using observational data. This article describes the governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated.

A methodological study was performed in 1992 to evaluate the accuracy of self-reported use of nonsteroidal antiinflammatory drugs (NSAIDs) and noncontraceptive estrogens that had been dispensed during the previous 12 years. A sample of 560 individuals dispensed NSAIDs or estrogens, and 140 individuals without NSAID/estrogen dispensations were selected from the Group Health Cooperative pharmacy database. Demographic, behavioral, and drug information was ascertained by telephone interview for 356 persons with and 98 persons without NSAID/estrogen dispensations. Of those with only a single NSAID dispensation, 41% (95% confidence interval (CI) 32-50%) were able to recall any NSAID use compared with 85% (95% CI 76-94%) for those with multiple NSAID dispensations. Thirty percent (95% CI 24-36%) recalled the NSAID name, and 15% (95% CI 10-20%) recalled both the name and dose. For estrogens, 78% (95% CI 70-86%) recalled the name, but only 26% (95% CI 17-34%) recalled the name and dose. Age, but not sex, appeared to influence recall accuracy: Persons 50-65 years of age recalled the NSAID name more accurately than those aged 66-80 (odds ratio (OR) = 1.8, 95% confidence interval (CI) 1.0-3.4). A similar advantage was noted for 50- to 65-year-old women in recalling the estrogen name (OR = 1.5, 95% CI 0.6-3.9). Drug name was recalled more frequently for exposures stopped 2-3 years prior to interview than for those stopped 7-11 years prior (OR = 3.0, 95% CI 1.6-5.7, and OR = 2.4, 95% CI 0.9-6.7, for NSAIDs and estrogens, respectively). Specificity was consistently high, ranging from 92% to 100%. This study suggests significant underascertainment of self-reported prescription drug exposure but little evidence that exposures are overreported.

Systematic processes for risk identification can provide useful information to supplement an overall safety assessment, but assessment of methods performance suggests a substantial chance of identifying false positive associations.

Clinical studies that use observational databases to evaluate the effects of medical products have become commonplace. Such studies begin by selecting a particular database, a decision that published papers invariably report but do not discuss. Studies of the same issue in different databases, however, can and do generate different results, sometimes with strikingly different clinical implications. In this paper, we systematically study heterogeneity among databases, holding other study methods constant, by exploring relative risk estimates for 53 drugoutcome pairs and 2 widely used study designs (cohort studies and self-controlled case series) across 10 observational databases. When holding the study design constant, our analysis shows that estimated relative risks range from a statistically significant decreased risk to a statistically significant increased risk in 11 of 53 (21%) of drug-outcome pairs that use a cohort design and 19 of 53 (36%) of drug-outcome pairs that use a self-controlled case series design. This exceeds the proportion of pairs that were consistent across databases in both direction and statistical significance, which was 9 of 53 (17%) for cohort studies and 5 of 53 (9%) for self-controlled case series. Our findings show that clinical studies that use observational databases can be sensitive to the choice of database. More attention is needed to consider how the choice of data source may be affecting results. database; heterogeneity; methods; population characteristics; reproducibility of results; surveillanceThe increasing use of large-scale observational clinical databases underlies the recent rapid growth in the number of epidemiologic database studies. Such studies seek to use administrative claims data or electronic health records to address important questions about the effects of medical products by using observational study designs. Many potential biases and sources of variability threaten the validity of such studies, and a substantial literature documents these concerns (1-3). Although published studies typically discuss various limitations, such studies rarely discuss alternative databases that could have been used and how the choice of database might have affected results. Indeed, most reports simply identify the data source and provide no discussion about the process used to select it. The literature provides several important examples wherein different studies that used different data sources arrived at contradictory conclusions (4-7). Recent meta-analyses of observational studies have shown that individual studies of the same drug effect yielded conflicting results ranging from statistically significant decreased risk to statistically significant increased risk. Specific examples of meta-analyses wherein individual studies provide conflicting results include a meta-analysis (8) that considered the association between oral contraceptives and endometriosis, a meta-analysis (9) of the effects of proton pump inhibitors on mortality in patients receiving clopidogrel, and a meta-a...

A reference set of test cases can be established to facilitate methodological research in drug safety. Creating a sufficient sample of drug-outcome pairs with binary classification of having no effect (negative controls) or having an increased effect (positive controls) is possible and can enable estimation of predictive accuracy through discrimination. Since the magnitude of the positive effects cannot be reliably obtained and the quality of evidence may vary across outcomes, assumptions are required to use the test cases in real data for purposes of measuring bias, mean squared error, or coverage probability.

Background and aims Medication persistence, defined as the time from drug initiation to discontinuation of therapy, has been suggested as a proxy for real-world therapeutic benefit and safety. This study seeks to compare the persistence of biologic drugs among patients with inflammatory bowel disease (IBD). Methods Patients with newly diagnosed IBD were included in a retrospective study using Truven MarketScan database. Treatment persistence and switching was compared among biologic medications including infliximab, adalimumab, certolizumab, golimumab, and vedolizumab. Predictors for discontinuation and switching were evaluated using time-dependent proportional hazard regression. Results In total, 5612 patients with Crohn’s disease (CD) and 3533 patients with ulcerative colitis (UC) were included in this analysis. Less than half of the patients continued using their initial biologic treatment after 1 year (48.48% in CD cohort; 44.78% in UC cohort). In the first year, adalimumab had the highest persistence and lowest switching rates for both CD (median survival time: 1.04 years) and UC (median survival time: 0.84 years). In subsequent years, infliximab users were more likely to persist in the use of biologic. Combination therapy with immunomodulators significantly decreased the risk of discontinuation, especially when immunomodulator therapy was started more than 30 days before the biologic (hazard ratio [HR], 0.22; CI, 0.16, 0.32). The major predictors for noncompliance included infection and hospitalization. Conclusion Overall, the persistence profiles of biologics suggest a high rate of dissatisfaction or adverse disease outcomes resulting in discontinuation and switching to a different agent. Early initiation of immunomodulators will substantially increase the persistence of biologic treatment.