Anil K. Dubey

Clinical inertia in the management of Type 2 diabetes metabolic risk factors.

Aims  Delays in the initiation and intensification of medical therapy may be one reason patients with diabetes do not reach evidence‐based goals for metabolic control. We assessed intensification of medical therapy over time, comparing the management of hyperglycaemia, hypertension, and hyperlipidaemia.

Instrumenting the health care enterprise for discovery research in the genomic era

Tens of thousands of subjects may be required to obtain reliable evidence relating disease characteristics to the weak effects typically reported from common genetic variants. The costs of assembling, phenotyping, and studying these large populations are substantial, recently estimated at three billion dollars for 500,000 individuals. They are also decade-long efforts. We hypothesized that automation and analytic tools can repurpose the informational byproducts of routine clinical care, bringing sample acquisition and phenotyping to the same high-throughput pace and commodity price-point as is currently true of genome-wide genotyping. Described here is a demonstration of the capability to acquire samples and data from densely phenotyped and genotyped individuals in the tens of thousands for common diseases (e.g., in a 1-yr period: N = 15,798 for rheumatoid arthritis; N = 42,238 for asthma; N = 34,535 for major depressive disorder) in one academic health center at an order of magnitude lower cost. Even for rare diseases caused by rare, highly penetrant mutations such as Huntington disease (N = 102) and autism (N = 756), these capabilities are also of interest.

Rapid identification of myocardial infarction risk associated with diabetes medications using electronic medical records.

OBJECTIVE To assess the ability to identify potential association(s) of diabetes medications with myocardial infarction using usual care clinical data obtained from the electronic medical record. RESEARCH DESIGN AND METHODS We defined a retrospective cohort of patients (n = 34,253) treated with a sulfonylurea, metformin, rosiglitazone, or pioglitazone in a single academic health care network. All patients were aged >18 years with at least one prescription for one of the medications between 1 January 2000 and 31 December 2006. The study outcome was acute myocardial infarction requiring hospitalization. We used a cumulative temporal approach to ascertain the calendar date for earliest identifiable risk associated with rosiglitazone compared with that for other therapies. RESULTS Sulfonylurea, metformin, rosiglitazone, or pioglitazone therapy was prescribed for 11,200, 12,490, 1,879, and 806 patients, respectively. A total of 1,343 myocardial infarctions were identified. After adjustment for potential myocardial infarction risk factors, the relative risk for myocardial infarction with rosiglitazone was 1.3 (95% CI 1.1–1.6) compared with sulfonylurea, 2.2 (1.6–3.1) compared with metformin, and 2.2 (1.5–3.4) compared with pioglitazone. Prospective surveillance using these data would have identified increased risk for myocardial infarction with rosiglitazone compared with metformin within 18 months of its introduction with a risk ratio of 2.1 (95% CI 1.2–3.8). CONCLUSIONS Our results are consistent with a relative adverse cardiovascular risk profile for rosiglitazone. Our use of usual care electronic data sources from a large hospital network represents an innovative approach to rapid safety signal detection that may enable more effective postmarketing drug surveillance.

Current state of information technologies for the clinical research enterprise across academic medical centers.

Information technology (IT) to support clinical research has steadily grown over the past 10 years. Many new applications at the enterprise level are available to assist with the numerous tasks necessary in performing clinical research. However, it is not clear how rapidly this technology is being adopted or whether it is making an impact upon how clinical research is being performed. The Clinical Research Forum’s IT Roundtable performed a survey of 17 representative academic medical centers (AMCs) to understand the adoption rate and implementation strategies within this field. The results were compared with similar surveys from 4 and 6 years ago. We found the adoption rate for four prominent areas of IT‐supported clinical research had increased remarkably, specifically regulatory compliance, electronic data capture for clinical trials, data repositories for secondary use of clinical data, and infrastructure for supporting collaboration. Adoption of other areas of clinical research IT was more irregular with wider differences between AMCs. These differences appeared to be partially due to a set of openly available applications that have emerged to occupy an important place in the landscape of clinical research enterprise‐level support at AMC’s. Clin Trans Sci 2012; Volume #: 1–4