Development, implementation and outcome analysis of semi-automated alerts for metformin dose adjustment in hospitalized patients with renal impairment.

PURPOSE: Overdosing of the oral antidiabetic metformin in impaired renal function is an important contributory cause to life-threatening lactic acidosis. The presented project aimed to quantify and prevent this avoidable medication error in clinical practice. METHODS: We developed and implemented an algorithm into a hospital's clinical information system that prospectively identifies metformin prescriptions if the estimated glomerular filtration rate is below 60 mL/min. Resulting real-time electronic alerts are sent to clinical pharmacologists and pharmacists, who validate cases in electronic medical records and contact prescribing physicians with recommendations if necessary. RESULTS: The screening algorithm has been used in routine clinical practice for 3 years and generated 2145 automated alerts (about 2 per day). Validated expert recommendations regarding metformin therapy, i.e., dose reduction or stop, were issued for 381 patients (about 3 per week). Follow-up was available for 257 cases, and prescribers' compliance with recommendations was 79%. Furthermore, during 3 years, we identified eight local cases of lactic acidosis associated with metformin therapy in renal impairment that could not be prevented, e.g., because metformin overdosing had occurred before hospitalization. CONCLUSIONS: Automated sensitive screening followed by specific expert evaluation and personal recommendations can prevent metformin overdosing in renal impairment with high efficiency and efficacy. Repeated cases of metformin-associated lactic acidosis in renal impairment underline the clinical relevance of this medication error. Our locally developed and customized alert system is a successful proof of concept for a proactive clinical drug safety program that is now expanded to other clinically and economically relevant medication errors. Copyright © 2016 John Wiley & Sons, Ltd.

Second-generation antipsychotics in a tertiary care hospital: prescribing patterns, metabolic profiles, and drug interactions.

We carried out an observational study that analyzed population characteristics, metabolic profiles, potentially interacting pharmacotherapy, and related adverse events in second-generation antipsychotics (SGAs) users of a tertiary care hospital. Within our pharmacoepidemiological database derived from electronic medical records of 82,358 hospitalizations, we identified 1136 hospitalizations contributing 9165 patient-days with exposure to SGA. Blood pressure, blood glucose, lipids, and BMI had been documented in 97.7, 75.7, 24.6, and 77.4% of hospitalizations, respectively. Among these, the prevalence of hypertension, hyperglycemia, dyslipidemia, and BMI 30 kg/m or more was 36.9, 22.6, 61.1, and 23.1%, respectively. A total of 63.4, 70.8, and 37.1% of SGA users with hyperglycemia, dyslipidemia, and hypertension, respectively, received no pharmacotherapy for these conditions. We identified 614 patient-days with SGA plus formally contraindicated comedication and another 1066 patient-days with other high-risk combinations for QTc prolongation. Among those there was one case with associated neutropenia and four cases with abnormal QTc interval. However, specific monitoring for such adverse events was not documented in 45.5% of hospitalizations with contraindicated and 89.8% with high-risk QTc-prolonging combinations. Our study identified targets for improved monitoring and management in SGA users. These may be implemented as automated alerts into electronic prescribing systems and thereby efficiently support safer pharmacotherapy in clinical practice.