Errors made while prescribing medication constitute the most common type of medication errors in hospitalized patients (7-15%) and result in significant morbidity, mortality and costs. However, many errors are preventable. Electronic prescriptions with computerized physician order entry systems (CPOE) and integrated computerized clinical decision support systems (providing online alerts) could resolve Drug Related Problems (DRP) at the point of care and reduce prescription errors by approximately 50%. CDSS includes drug-allergy, dosing and renal adjustment, duplicate therapy and drug–drug interaction checking.

Clinicians have to deal on a daily basis with a flood of data and information that they need to make decisions upon; mistakes are more likely to happen. CDSS helps clinicians to easily identify areas that need attention. Examples like drug-drug interactions, drug-allergy interactions, high doses and duplicate therapy, or labs that need to be checked before prescribing medication. Possibilities are endless, and here lies the problem.

Due to the fact that there is so much information to present to the clinicians, and while everything is important, nothing is important anymore! Here is where the alert fatigue starts to take place.

The introduction of CDSS is often met by opposition due to the flood of alerts, and most prescribers eventually ignore even crucial alerts (“alert fatigue”).

How many is too many?While in healthcare systems, alert fatigue has been observed for clinicians presented with as little as 12 alerts per day in a busy clinic seeing almost 40 patients a day. That means that 1 alert every 3 patients, was enough to kill the concept of CDSS, cause alert fatigue, and drive the override rate all the way >90% for all types of alerts. Why?

Relevance is the key!

The more we look into alert fatigue cases, the more we realize; it’s mainly around alerts relevance rather than numbers. There are many factors that can lead clinicians to override alerts, but relevance is the most important one.

Once we present clinicians with multiple irrelevant alerts that they have to override without a positive impact on their current plan of care, their perception of the CDSS will shift down. We (as humans) are programmed to filter unimportant information.

Ignoring crucial alerts (“alert fatigue”), reducing the CDSS’s effectiveness. Therefore, optimizing and customization of the CDSS to a hospital department’s specific needs is necessary, reducing the alerts to “actionable alerts” that are likely to result in a change of prescription or follow-up instructions.

Not all alerts are stopping alert!

To fight this phenomenon called “alert fatigue”, we must categorize our alerts according to number of factors. For example; before you accept an alert in the system, ask yourself:

1. Does the clinician need to take an action NOW?
2. Should the alert stop the clinician’s current workflow or notifying the clinicians unobtrusively achieve the same goal?
3. Are there any valid reasons to override the alert? What’s the acceptable override rate?

Going through such process for every type of alert you have will help you achieve your objective with as little disruption as possible to the clinicians, which is a main factor in compliance with your CDSS.

Improving CDSS

CDSS systems provide reports on the number of fired alerts, clinicians’ response to the (Override rate, override reasons, changes), triggers, trends, etc. These reports should drive us to continuously change our design and review our alerts system, and provide feedback to clinicians on their behavior. It’s critical to regularly evaluate these data and look closely for trends like:

1. Rise or fall of alerts fired (Especially the top 10)
2. Rise or fall of override rate (%)
3. Significant changes in the type of fired alerts by customization tools
4. Clinical outcomes related to these alerts

Clinical Decision Support systems should support your decisions in their design, as much as they support clinicians in providing better and safer care for the patients.

The main purpose our study is to examine the impact of multilevel factors affecting drug prescribing errors in inpatients, and how implementation and customization of CDSS affect the safety of medication treatment, with the purpose of reducing the number of alerts to minimize alert fatigue. Moreover, we aim to examine the mediating role of alert fatigue rate in the effect of CDSS implementation on drug prescribing errors.