Pharmacogenomics Implementation at the National Institutes of Health Clinical Center.

The National Institutes of Health Clinical Center (NIH CC) is the largest hospital in the United States devoted entirely to clinical research, with a highly diverse spectrum of patients. Patient safety and clinical quality are major goals of the hospital, and therapy is often complicated by multiple cotherapies and comorbidities. To this end, we implemented a pharmacogenomics program in 2 phases.

Integrating pharmacogenetic information and clinical decision support into the electronic health record.

Pharmacogenetics (PG) examines gene variations for drug disposition, response, or toxicity. At the National Institutes of Health Clinical Center (NIH CC), a multidepartment Pharmacogenetics Testing Implementation Committee (PGTIC) was established to develop clinical decision support (CDS) algorithms for abacavir, carbamazepine, and allopurinol, medications for which human leukocyte antigen (HLA) variants predict severe hypersensitivity reactions. Providing PG CDS in the electronic health record (EHR) during order entry could prevent adverse drug events.

Improving adherence to research protocol drug exclusions using a clinical alerting system.

Objective: To develop a general method for using the alerting function of an electronic health record (EHR) system to warn prescribers when a drug order may be in conflict with the restrictions of a patient's research protocol.

Methods: We examined a sample of clinical research protocols at the National Institutes of Health (NIH) to identify the frequency with which drugs were excluded by protocols. We analyzed two protocols and modeled the exclusions they contained.

Use of clinical alerting to improve the collection of clinical research data.

Data errors in electronic health records have been shown to have the potential to adversely impact the conclusions drawn from clinical research. We prospectively studied the efficacy of a new alert to infer errors in previously stored data and to decrease the frequency of data entry errors, in an attempt to improve the quality of data for clinical trials. For the purpose of this study, we monitored data entry errors in height or weight measurements.