Unfortunately, providers across the specialties are notorious for this behavior, relying on their own clinical judgment to deliver care and ignoring clinical alerts, such as drug-drug interactions or overdue order reminders...and why not?
That’s why you have a license to practice medicine, right?
The Human Condition
But aren’t we all human? We all make mistakes, forget things. EHR adoption is supposed to be an aid to help support us, to remind us when we may forget something —or even if a patient forgets. Mistakes, forgotten orders, or ignored orders were almost impossible to track on paper, or were too time consuming for those “keepers of the charts” who were responsible for tracking all the orders, medication lists, and the like.
A great example of the tracking efficiency EHR offers is the email I received the other day from my daughter’s provider. “Bridget, Allscripts is telling me that Leah hasn’t had the urine culture that I ordered.” I hate to admit it, but he was right, and the next day I had her urine sample at the lab, along with my son, who still hadn’t had his blood drawn (his doctor had sent me a reminder, too!). Although an EHR system can be cumbersome and time consuming (especially at first), the reality is that in the end, providers are delivering better care….that is, unless they start ignoring the system.
An EHR Casualty
The phenomenon is known as “alert fatigue.” Providers see so many alerts , notices, and reminders that they tend to ignore them, including alerts for meaningful use: reconciling meds, documenting smoking status, recording vitals, etc. According to accessmedicine.com, “Studies within and outside health care show that the beneficial effect of an alert, such as a pop-up box in a software system, is rapidly extinguished if the alert becomes a routine part of using the system. . .If a clinical decision support system provides an ‘alert’ to the drug-drug interaction of two medications routinely used together safely, such as enoxaparin and warfarin, in the same way as to unfamiliar but dangerous interactions, such as theophylline and fluoroquinolones, clinicians become desensitized to the alerts and dismiss critically important guidance when it does appear.”
In the next few weeks, another alert will have to be implemented in order to attest to Core Measure 11: “Implement one clinical decision support rule relevant to specialty or high clinical priority along with the ability to track compliance with that rule.”
“Another alert?” you may be thinking. “Isn’t your point that we’re already tired of them?”
Patient-Centered Data
True, you may be tired of them, but the reality is that they do improve patient care….if used correctly. CMS requires that the clinical decision support rule be based on “general and person-specific information, intelligently filtered and organized, at appropriate times, to enhance health and health care.” Our system, as a certified EHR product, generates alerts based on patient-specific data. An example of this would be an alert reminding the provider to ask the patient if he/she has had his/her Pneumovax, driven by individual patient immunization status and patient demographics (such as age or problem list information). For users, this means that information needs to be entered correctly and updated regularly.
Accurate Data
As we have been looking over charts the past few months for quality improvement, there have been numerous instances where patient records have not been updated (i.e. a patient with an active pregnancy who aborted three months previously). Using our Pneumovax example, if the administration of a previously given Pneumovax was not documented, then the number of false alerts could hinder rather than help.
Steps to Follow
The following are some steps to help avoid alert fatigue and ensure that Meaningful Use data is reported accurately.
1. When an alert pops up, don’t just click out of it. Read the alert and make sure that what is being “alerted” should be. If the alert shouldn’t be generated, question why.
2. If the alert was generated based on incorrect information entered in the system, correct that data. For example, if medications are still on the current medication list that shouldn’t be, then fix it.
3. If an alert generates that shouldn’t based on information you know to be clinically incorrect, let your support team know. Alerts are supposed to generate on evidence-based medicine and the latest national standards of care.
If all of our users in our clinics work together to make sure that data is accurate in the patients’ chart and that the system is functioning correctly, then the alerts that generate should be less frequent and clinically relevant.