Search

RATIONALE, AIMS, AND OBJECTIVES Long-term exposure to glucocorticoids can cause adverse drug reactions of long latency (ADRLLs), including glucocorticoid-induced diabetes mellitus (GID). Providers can monitor for GID using the glycosylated haemoglobin blood (HbA1C) test. This study examined the utility of decisional support to improve HbA1C-based screening for GID. US veterans were identified as chronic users of oral glucocorticoids (>120 days of oral glucocorticoids in the last 2 years). The primary care providers caring for these patients were the target of the intervention. Providers were randomized to receive automatic HbA1C orders for their patients receiving chronic glucocorticoid or usual care. METHODS This study was a pilot two-arm, group-randomized, controlled trial (n = 12 providers, n = 38 patients). Data collection occurred from 5 May 2013 until 10 January 2014. A pharmacist generated the order for an HbA1C through the electronic medical record. The time between the intervention start date and the date on which an HbA1C order was signed were compared using Cox proportional and hierarchical linear regression. RESULTS The time to sign HbA1C orders (mean 12.0 days for the intervention arm; 104.0 days for control arm) was associated with significant differences favouring the intervention [HR (Hazard Ratio) 50.2, P

Objective: To assess the accuracy of International Classification of Diseases, Ninth Revision, and Current Procedural Terminology codes for identifying cardiovascular (CV) events (myocardial infarction [MI], stroke, coronary artery bypass graft [CABG], and percutaneous coronary intervention [PCI]) in enrollees of the Veterans Affairs Rheumatoid Arthritis (VARA) registry.Design: We performed a validation study from VARA enrollment until 6/1/2010 to compare the accuracy of CV events in those with and without CV-event coding in inpatient and outpatient records to evaluate for CV events +/- 3 months of the coding. The positive predictive value (PPV) was calculated, and codes with a PPV ≥50% were included in a composite coding algorithm.Results: We evaluated 107 individuals for 21 CV-event codes and 60 individuals without CV-event coding. The PPV varied between 0-100%. Composite coding algorithms’ PPV ranged from 70-100%.Conclusions: Validation of these algorithms allows for identification of acute CV events with known accuracy. The sensitivity and PPV of coding algorithms for CABG and PCI exceed that of stroke and MI.