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

Understanding responses to a renal dosing decision support system in primary care

Renal dosing clinical decision support (CDS) systems have demonstrated clinical effectiveness and potential benefits for patient outcomes. However, the high override rates consistently reported are problematic and undesirable. To understand providers' use patterns of renal dosing CDS, we investigated the override reasons obtained from primary care practices affiliated with two teaching hospitals. We selected a stratified random sample of 300 alerts and reviewed electronic medical records. Appropriateness criteria and an inter-rater reliability process were used. We found that two thirds of alerts were overridden inappropriately, and this proportion was similar for frequent over-riders as compared to the remainder of physicians. These findings imply that strategies are needed to convince providers to accept more clinically appropriate suggestions, though they need to be broadly targeted

Understanding Physicians' Behavior toward Alerts on Nephrotoxic Medications in Outpatients: A Cross-Sectional Analysis

Background: Although most outpatients are relatively healthy, many have chronic renal insufficiency, and high override rates for suggestions on renal dosing have been observed. To better understand the override of renal dosing alerts in an outpatient setting, we conducted a study to evaluate which patients were more frequently prescribed contraindicated medications, to assess providers' responses to suggestions, and to examine the drugs involved and the reasons for overrides. Methods: We obtained data on renal alert overrides and the coded reasons for overrides cited by providers at the time of prescription from outpatient clinics and ambulatory hospital-based practices at a large academic health care center over a period of 3 years, from January 2009 to December 2011. For detailed chart review, a group of 6 trained clinicians developed the appropriateness criteria with excellent inter-rater reliability (kappa = 0.93). We stratified providers by override frequency and then drew samples from the high- and low-frequency groups. We measured the rate of total overrides, rate of appropriate overrides, medications overridden, and the reason(s) for override. Results: A total of 4120 renal alerts were triggered by 584 prescribers in the study period, among which 78.2% (3,221) were overridden. Almost half of the alerts were triggered by 40 providers and one-third was triggered by high-frequency overriders. The appropriateness rates were fairly similar, at 28.4% and 31.6% for high- and low-frequency overriders, respectively. Metformin, glyburide, hydrochlorothiazide, and nitrofurantoin were the most common drugs overridden. Physicians' appropriateness rates were higher than the rates for nurse practitioners (32.9% vs. 22.1%). Physicians with low frequency override rates had higher levels of appropriateness for metformin than the high frequency overriders (P = 0.005). Conclusion: A small number of providers accounted for a large fraction of overrides, as was the case with a small number of drugs. These data suggest that a focused intervention targeting primarily these providers and medications has the potential to improve medication safety

Are we heeding the warning signs? Examining providers' overrides of computerized drug-drug interaction alerts in primary care

Background: Health IT can play a major role in improving patient safety. Computerized physician order entry with decision support can alert providers to potential prescribing errors. However, too many alerts can result in providers ignoring and overriding clinically important ones. Objective: To evaluate the appropriateness of providers’ drug-drug interaction (DDI) alert overrides, the reasons why they chose to override these alerts, and what actions they took as a consequence of the alert. Design: A cross-sectional, observational study of DDI alerts generated over a three-year period between January 1st, 2009, and December 31st, 2011. Setting: Primary care practices affiliated with two Harvard teaching hospitals. The DDI alerts were screened to minimize the number of clinically unimportant warnings. Participants: A total of 24,849 DDI alerts were generated in the study period, with 40% accepted. The top 62 providers with the highest override rate were identified and eight overrides randomly selected for each (a total of 496 alert overrides for 438 patients, 3.3% of the sample). Results: Overall, 68.2% (338/496) of the DDI alert overrides were considered appropriate. Among inappropriate overrides, the therapeutic combinations put patients at increased risk of several specific conditions including: serotonin syndrome (21.5%, n=34), cardiotoxicity (16.5%, n=26), or sharp falls in blood pressure or significant hypotension (28.5%, n=45). A small number of drugs and DDIs accounted for a disproportionate share of alert overrides. Of the 121 appropriate alert overrides where the provider indicated they would “monitor as recommended”, a detailed chart review revealed that only 35.5% (n=43) actually did. Providers sometimes reported that patients had already taken interacting medications together (15.7%, n=78), despite no evidence to confirm this. Conclusions and Relevance: We found that providers continue to override important and useful alerts that are likely to cause serious patient injuries, even when relatively few false positive alerts are displayed

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

A cross-sectional observational study of high override rates of drug allergy alerts in inpatient and outpatient settings, and opportunities for improvement

Objectives: To evaluate how often and why providers overrode drug allergy alerts in both the inpatient and outpatient settings. Design: A cross-sectional observational study of drug allergy alerts generated over a 3-year period between 1 January 2009 and 31 December 2011. Setting: A 793-bed tertiary care teaching affiliate of Harvard Medical School and 36 primary care practices. Participants: Drug allergy alerts were displayed for a total of 29 420 patients across both settings. Main outcome measures: Proportion of drug allergy alerts displayed and overridden, proportion of appropriate overrides, proportion of overrides in each medication class, different reasons for overriding and types of reactions overridden. Results: A total of 158 023 drug allergy alerts were displayed, 131 615 (83%) in the inpatient setting and 26 408 (17%) in the outpatient setting; 128 157 (81%) of which were overridden. A random sample of inpatient (n=200, 0.19%) and outpatient (n=50, 0.25%) alert overrides were screened for appropriateness, with >96% considered appropriate. Alerts for some drug classes, such as ‘non-antibiotic sulfonamides’, were overridden for >81% of prescriptions in both settings. The most common override reason was patient has taken previously without allergic reaction. In the inpatient setting alone, 70.9% of alerts that warned against the risk of anaphylaxis were overridden. Conclusions: The information contained in patients’ drug allergy lists needs to be regularly updated. Most of the drug allergy alerts were overridden, with the majority of alert overrides in the subsample considered appropriate. Some of the rules for these alerts should be carefully reviewed and modified, or removed. Further research is needed to understand providers’ overriding of alerts that warned against the risk of ‘anaphylaxis’, which are more concerning with respect to patient safety