The frequency of inappropriate nonformulary medication alert overrides in the inpatient setting

Background Experts suggest that formulary alerts at the time of medication order entry are the most effective form of clinical decision support to automate formulary management. Objective Our objectives were to quantify the frequency of inappropriate nonformulary medication (NFM) alert overrides in the inpatient setting and provide insight on how the design of formulary alerts could be improved. Methods Alert overrides of the top 11 (n = 206) most-utilized and highest-costing NFMs, from January 1 to December 31, 2012, were randomly selected for appropriateness evaluation. Using an empirically developed appropriateness algorithm, appropriateness of NFM alert overrides was assessed by 2 pharmacists via chart review. Appropriateness agreement of overrides was assessed with a Cohen’s kappa. We also assessed which types of NFMs were most likely to be inappropriately overridden, the override reasons that were disproportionately provided in the inappropriate overrides, and the specific reasons the overrides were considered inappropriate. Results Approximately 17.2% (n = 35.4/206) of NFM alerts were inappropriately overridden. Non-oral NFM alerts were more likely to be inappropriately overridden compared to orals. Alerts overridden with “blank” reasons were more likely to be inappropriate. The failure to first try a formulary alternative was the most common reason for alerts being overridden inappropriately. Conclusion Approximately 1 in 5 NFM alert overrides are overridden inappropriately. Future research should evaluate the impact of mandating a valid override reason and adding a list of formulary alternatives to each NFM alert; we speculate these NFM alert features may decrease the frequency of inappropriate overrides

The effect of provider characteristics on the responses to medication-related decision support alerts

Background Improving the quality of prescribing and appropriate handling of alerts remains a challenge for design and implementation of clinical decision support (CDS) and comparatively little is known about the effects that provider characteristics have on how providers respond to medication alerts. Objectives To investigate the relationship between provider characteristics and their response to medication alerts in the outpatient setting. Design and participants Retrospective observational study using a prescription log from the automated electronic outpatient system for each of 478 providers using the system at primary care practices affiliated with 2 teaching hospitals, from 2009 to 2011 for six types of alerts. Provider characteristics were obtained from the hospital credentialing system and the Massachusetts Board of Registration in Medicine. Main measures Override rates per 100 prescriptions and 100 alerts. Results The providers’ mean override rates per 100 prescriptions and per 100 alerts were 0.52 (95% confidence interval (CI), 0.46–0.58) and 0.42 (95% CI, 0.38–0.44) respectively. The physicians (n = 422) on average overrode drug alerts with rates of 0.48 per 100 drugs and 0.44 per 100 warnings. Univariate analysis revealed that six physician characteristics (physician type, age, number of encounters, medical school ranking, residency hospital ranking, and acceptance of Medicaid) were significantly related to the override rate. Multiple regression showed that house staff were more likely to override than staff physicians (p < 0.001), physicians with fewer than 13 average daily encounters were more likely to override than others with more than 13 encounters (p (range), <0.001–0.05), and graduates of the top 5 medical schools were more likely to override than the others (p = 0.04). All six predictors together explained 30% and 50% of the variance in override rates, respectively. Conclusions Consideration of six specific physician characteristics may help inform interventions to improve prescriber decision-making

Overrides of medication-related clinical decision support alerts in outpatients

Background: Electronic prescribing is increasingly used, in part because of government incentives for its use. Many of its benefits come from clinical decision support (CDS), but often too many alerts are displayed, resulting in alert fatigue. Objective: To characterize the override rates for medication-related CDS alerts in the outpatient setting, the reasons cited for overrides at the time of prescribing, and the appropriateness of overrides. Methods We measured CDS alert override rates and the coded reasons for overrides cited by providers at the time of prescribing. Our primary outcome was the rate of CDS alert overrides; our secondary outcomes were the rate of overrides by alert type, reasons cited for overrides at the time of prescribing, and override appropriateness for a subset of 600 alert overrides. Through detailed chart reviews of alert override cases, and selective literature review, we developed appropriateness criteria for each alert type, which were modified iteratively as necessary until consensus was reached on all criteria. Results: We reviewed 157 483 CDS alerts (7.9% alert rate) on 2 004 069 medication orders during the study period. 82 889 (52.6%) of alerts were overridden. The most common alerts were duplicate drug (33.1%), patient allergy (16.8%), and drug–drug interactions (15.8%). The most likely alerts to be overridden were formulary substitutions (85.0%), age-based recommendations (79.0%), renal recommendations (78.0%), and patient allergies (77.4%). An average of 53% of overrides were classified as appropriate, and rates of appropriateness varied by alert type (p<0.0001) from 12% for renal recommendations to 92% for patient allergies. Discussion: About half of CDS alerts were overridden by providers and about half of the overrides were classified as appropriate, but the likelihood of overriding an alert varied widely by alert type. Refinement of these alerts has the potential to improve the relevance of alerts and reduce alert fatigue