Click frustration

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Click Frustration

Click frustration, a little known phenomenon closely related to alert fatigue, has blossomed with the development of the electronic medical record (EMR). While alert fatigue tends to be related to clinical decision support (CDS), click frustration deals more with the entire electronic medical record.

In order to understand click frustration, a basic understanding of alert fatigue is necessary. Alert warnings, reminders, and recommendations have been well defined in CDS [1][2]. Alert fatigue is related to the barrage of message provided by a CDS which can overwhelm a provider and cause them to ignore messages. Stelle et al showed that providers will adhere to some alerts, which can be used to improve patient care and ensure that proper corollary orders are also input [3]. Corollary orders have been shown an improvement of provider adherence to guidelines and a decrease in errors of omission [4]. While disabling drug-drug interactions alerts is one potential method of dealing with the problem of alert fatigue, there seems to be no consensus on which alerts are needed and how to safely disable the alerts [5]. Other studies show positive effects of alerts [6]. There are other studies that show alert threshold can affect provider attitudes [7]. Regardless, CDS with alerts and reminders can improve patient safety and the quality of care [8].

Alert fatigue deals with actions that are needed by the user, responses and messages are generated by the decision support system. Users must act on those alerts and reminders by taking action, whether that action be to implement the support recommendations or to ignore them, a user must react to the system. Click frustration also incorporates user input. Alert fatigue is an active response to CDS and system function. Click frustration is a passive medium from an event driven approach to the EMR. Unlike the active support provided by the CDS, all electronic records are based on the event driven programming paradigm. This paradigm requires users to take an active approach to information management. The user must make decision for system interactions, namely, use the mouse and keyboard for input and decision making tasks. While in this course of events, the mouse click becomes an event which drives the system. While this concept is well known to all who use any type of windows based user interface, the problem is multiplied by the complexity of the electronic medical record.

Click frustration is therefore the psychiatric and psychological manifestations of repetitive clicks to the mouse button with the hopes of accomplishing some task in an electronic medical record, for which the task should not require repetitive mouse button clicks. For example, most prominent electronic medical record systems use a prescription writing program for ePrescribing. In one such system, to refill a medication, the following step must be taken:

1. Login to the EMR

  a.	1 mouse click to launch the application
  b.	1 click to type a user name
  c.	1 click to type a password, 
  d.	1 click to login
  e.	Total:  4 clicks

2. Select the patient

  a.	1 click to launch the search box
  b.	1 click to enter the medical record number
  c.	1 click to search
  d.	1 click to select the patient
  e.	1 click to select an encounter
  f.	Total:  5 clicks

3. Patient chart is open, find the medication

  a.	1 click to find the medication list
  b.	1 click to find the medication
  c.	Total: 2 clicks

4. Refill the medication

  a.	1-3 clicks to override alerts/reminders about …printers, inpatient vs outpatient, vs expired med, etc, 
  b.	1 click to view the details tab 
     i.	0 clicks to medication order – assume refill, no other changes like changing the number of refills, quantity or frequency, 
     ii.	1 click to open printer tab
     iii.	1 click to select the printer [this system does not allow a default printer]
     iv.	1 click to hit OK button,)
  c.	Total 5-7 clicks (assuming refill only)

5. Sign order

  a.	 1click to go to order signature page
  b.	1 click to sign
  c.	Total: 2 clicks

6. Now the prescription is printed and must be manually signed.

This example, for refilling one medication, took a minimum of 16-18 click of the mouse. That does not account for time it took to load the application, no allergy alerts, no drug-drug interaction alerts, no changes to the original prescription. What was once a simple signature by the provider on the paper-chart, has now become a process, with a minimum of 16 clicks by the provider. This is by definition – click frustration.

While the process described above is the process currently used, it must be expressed that it is not an optimal process. There are a number of steps that could be streamlined to avoid click frustration, however, the goal of this article is not manage processes, but to define the frustrations that providers suffer while using the mouse clicks to interact with the electronic medical record. It should also be noted that paper based charts have a separate process for refills, one which allowed charts to be brought to the provider, a refill request on the top of the chart and only a signature or initials were needed to provide the refill. There are distinct differences between the paper-based and electronic processes which account for some of the frustrations that provider encounter. It must be recognized that click frustration is not entirely a technical problem, but a frustration that occurs when inefficient electronic processes replace relatively time insensitive paper-based system. A relatively simple manual process becomes a time and labor intensive adventure with clicks. It is recognized that there are many more examples of click frustration in the current electronic medical records that exist and that many more click frustration processes will be implemented in the future, neither which offer excuses for the use who suffers from click frustration.


[1] Vashtz G (sp), Meyer J, Parmet Y, Peleg R, Goldfarb D, Porath A, Gilutz H. Defining and measuring physicians' responses to clinical reminders. J Biomed Inform. 2008 Oct 26.

[2] Varonen H, Kortteisto T, Kaila M; EBMeDS Study Group. What may help or hinder the implementation of computerized decision support systems (CDSSs): a focus group study with physicians. Fam Pract. 2008 Jun;25(3):162-7.

[3] Steele AW, Eisert S, Witter J, Lyons P, Jones MA, Gabow P, Ortiz E. The effect of automated alerts on provider ordering behavior in an outpatient setting. PLoS Med. 2005 Sep;2(9):e255.

[4] Overhage JM, Tierney WM, Zhou XH, McDonald CJ. A randomized trial of "corollary orders" to prevent errors of omission. J Am Med Inform Assoc. 1997 Sep-Oct;4(5):364-75.

[5] van der Sijs H, Aarts J, van Gelder T, Berg M, Vulto A. Turning off frequently overridden drug alerts: limited opportunities for doing it safely. J Am Med Inform Assoc. 2008 Jul-Aug;15(4):439-48.

[6] Ko Y, Abarca J, Malone DC, Dare DC, Geraets D, Houranieh A, Jones WN, Nichol WP, Schepers GP, Wilhardt M. Practitioners' views on computerized drug-drug interaction alerts in the VA system. J Am Med Inform Assoc. 2007 Jan-Feb;14(1):130-1.

[7] Weingart SN, Toth M, Sands DZ, Aronson MD, Davis RB, Phillips RS. Physicians' decisions to override computerized drug alerts in primary care. Arch Intern Med. 2003 Nov 24;163(21):2625-31.

[8] Coiera E, Westbrook J, Wyatt J. The safety and quality of decision support systems. Yearb Med Inform. 2006:20-5.

--Trevorrohm 15:11, 18 February 2009 (CST)

Submitted by Trevor Rohm