Providing Access to Genomic Variant Knowledge in a Healthcare Setting: A Vision for the ClinGen Electronic Health Records Workgroup.

The Clinical Genome Resource (ClinGen) is a National Institutes of Health (NIH)-funded collaborative program that brings together a variety of projects designed to provide high-quality, curated information on clinically relevant genes and variants. ClinGen's EHR (Electronic Health Record) Workgroup aims to ensure that ClinGen is accessible to providers and patients through EHR and related systems. This article describes the current scope of these efforts and progress to date. The ClinGen public portal can be accessed at www.clinicalgenome.org.

The association between use of a clinical decision support tool and adherence to monitoring for medication-laboratory guidelines in the ambulatory setting.

BACKGROUND: Stage 2 Meaningful Use criteria require the use of clinical decision support systems (CDSS) on high priority health conditions to improve clinical quality measures. Although CDSS hold great promise, implementation has been fraught with challenges, evidence of their impact is mixed, and the optimal method of content delivery is unknown. OBJECTIVE: The authors investigated whether implementation of a simple clinical decision support (CDS) tool was associated with improved prescriber adherence to national medication-laboratory monitoring guidelines for safety (hepatic function, renal function, myalgias/rhabdomyolysis) and intermediate outcomes for antidiabetic (Hemoglobin A(1c); HbA(1c)) and antihyperlipidemic (low density lipoprotein; LDL) medications prescribed within a diabetes registry. METHODS: This was a retrospective observational study conducted in three phases of CDS implementation (2008-2009): pre-, transition-, and post-Prescriptions evaluated were ordered from an electronic health record within a multispecialty medical group. Adherence was evaluated within and without applying guideline-imposed time constraints. RESULTS: Forty-thousand prescriptions were ordered over three timeframes. For hepatic and renal function, the proportion of prescriptions for which labs were monitored at any time increased from 52% to 65% (p<0.001); those that met time guidelines, from 14% to 21% (p<0.001). Only 6% of required labs were drawn to monitor for myalgias/rhabdomyolysis, regardless of timeframe. Over 90% of safety labs were within normal limits. The proportion of labs monitored at any time for LDL increased from 56% to 64% (p<0.001); those that met time guidelines from 11% to 17% (p<0.001). The proportion of labs monitored at any time for HbA(1c) remained the same (72%); those that met time guidelines decreased from 45% to 41% (p<0.001). CONCLUSION: A simple CDS tool may be associated with improved adherence to guidelines. Efforts are needed to confirm findings and improve the timeliness of monitoring; investigations to optimize alerts should be ongoing.