Evaluation of context-specific alerts for potassium-increasing drug-drug interactions: A pre-post study

Highlights

• Clinical decision support systems are associated with high override rates and alert fatigue

• Potassium-increasing drug-drug interactions occur frequently and can be life-threatening

• Alerts for low-risk patients were suppressed which led to a 92.8% reduction in alert burden

• The intervention increased the alert acceptance from 5.7% to 86.5%

• There was no significant difference in occurrence of hyperkalemia, thus preserving patient safety

Abstract

Objective

To investigate whether context-specific alerts for potassium-increasing drug-drug interactions (DDIs) in a clinical decision support system reduced the alert burden, increased alert acceptance, and had an effect on the occurrence of hyperkalemia.

Materials and Methods

In the pre-intervention period all alerts for potassium-increasing DDIs were level 1 alerts advising absolute contraindication, while in the post-intervention period the same drug combinations could trigger a level 1 (absolute contraindication), a level 2 (monitor potassium values), or a level 3 alert (informative, not shown to physicians) based on the patient’s recent laboratory value of potassium. Alert acceptance was defined as non-prescription or non-administration of the interacting drug combination for level 1 alerts and as monitoring of the potassium levels for level 2 alerts.

Results

The alert burden decreased by 92.8%. The relative risk (RR) for alert acceptance based on prescription rates for level 1 alerts and monitoring rates for level 2 alerts was 15.048 (86.5% vs 5.7%; 95% CI 12.037–18.811; P < 0.001). With alert acceptance for level 1 alerts based on actual administration and for level 2 alerts on monitoring rates, the RR was 3.597 (87.6% vs 24.4%; 95% CI 3.192–4.053; P < 0.001). In the generalized linear mixed model the effect of the intervention on the occurrence of hyperkalemia was not significant (OR 1.091, 95% CI 0.172–6.919).

Conclusion

The proposed strategy seems effective to get a grip on the delicate balance between over- and under alerting.

Introduction

One key cause of preventable adverse drug events (ADEs) are drug-drug interactions (DDIs) [1]. Computerized physician order entry (CPOE) with built-in clinical decision support systems (CDSS) have the potential to prevent medication errors and consecutive ADEs at the very moment of prescribing [[2], [3], [4], [5], [6], [7]]. Yet, the evidence on the impact of CDSS on patient outcomes remains scarce [8,9]. It is well established that CDSS for DDI checking are often overly sensitive generating excessive alerts with low specificity leading to alert fatigue and high override rates, often exceeding 80% [[10], [11], [12], [13], [14], [15], [16]]. The main problems are the low specificity of the alerts and their perceived lack of clinical importance [4,12,16,17]. This makes it difficult for clinicians to distinguish between clinically significant and insignificant alerts leading to both types of alerts being overridden which compromises the primary objective of patient safety [4,13,18,19]. Integration of patient characteristics in the clinical decision support (CDS) logic was suggested to improve alert specificity [20,21]. Specifically, linkage and follow-up of laboratory values with the CDS rules was proposed [[22], [23], [24], [25], [26], [27]]. However, just displaying laboratory values in the alert did not significantly improve the alert adherence in high-risk patients [28].

We have encountered the same problem of low specificity and high override rates in our hospital [29,30]. Of all DDI alerts generated by the CDSS from the 1 st of January 2010 till the 30th of June 2011, 72.1% were alerts for the risk of hyperkalemia due to the interaction between potassium-sparing diuretics and potassium supplements, with an override rate of 85.7% [31]. Hyperkalemia is a serious and potentially life-threatening electrolyte disorder caused by an imbalance in potassium homeostasis and is associated with increased mortality and adverse cardiovascular effects such as cardiac arrhythmia and cardiac arrest [[32], [33], [34]]. Uijtendaal et al. found that DDI-induced hyperkalemia occurred in 10% of hospitalized patients who were prescribed at least one potassium-increasing drug [24].

Context-specific alerts for potassium-increasing DDIs with patient-specific risk assessments for hyperkalemia were developed as part of our CDSS. Alerts for low-risk patients were not shown to the physicians to improve the specificity, as suggested by Duke et al. [28]. The main objective of this study was to investigate whether these context-specific alerts reduced the alert burden and had a higher alert acceptance compared to alerts without context-specific rules. Because it is important to improve the efficiency of the DDI alerting system without compromising patient safety, the effect of the optimized CDSS on the patient outcome, occurrence of hyperkalemia, was also examined.