View source for Comprehensive Analysis of a Medication Dosing Error Related to CPOE

This is a systematic review of the article entitled “Comprehensive Analysis of a Medication Dosing Error Related to CPOE” by Jan Horsky <ref name= “Horskey 2005”> Comprehensive Analysis of a Medication Dosing Error Related to CPOE. [J Am Med Inform Association 2005;12:377–382. DOI 10.1197/jamia.M1740]  http://dx.doi.org/10.1197/jamia.M1740 </ref>.

==Introduction==
New drugs that manage or relieve previously untreated diseases have come about due to new innovations in pharmacology research. These advancements in drug therapy have led to increased incidence of [[Adverse drug event]] (ADEs) due to avoidable causes such as prescribing errors. 
[[Computerized physician order entry]] (CPOE) systems are known to drastically minimize the incidence of ADEs by confirming legibility of orders and integrating clinical decision support ([[CDS]]) such as checking for allergies.

However, the progressive effect of CPOE on prescribing safety can be compromised by the advent of new forms of errors. These errors are related to the intricacy of the human-computer interaction and may be a consequence of poor user training or inadequate understanding of data handling by a CPOE application. 

Understanding the acuity of users at crucial stages of an incident that occurred during the use of CPOE is extremely beneficial to the process of characterizing cognitively based errors.
In this article, the case of a serious medication error that occurred at a large academic medical institution is described and a synopsis of how the error was analyzed is discussed. The authors hope that characterization of the entire process of the error will provide key insight and recommendations for improving CPOE systems and clinical ordering procedures.

==Case Description==
*An elderly man was admitted to a medical intensive care unit with septic shock and respiratory failure then transferred to a pulmonary service unit.
*On a Saturday morning, Provider A diagnosed the patient as hypokalemic after observing a low serum KCL in the setting of renal insufficiency.
*Provider A decided to replete the patient’s KCL by providing 40 mEq of KCL via an IV route over a period of 4 hours as indicated by institutional guidelines.
*After the order was entered, Provider A realized that the patient already had an IV fluid line and subsequently decided to provide KCL as an additive to the currently running IV fluid.
*Provider A then entered a new order for infusion of 100 mEq of KCL in 1 liter of D5W solution at a rate of 75ml/hr. 
*The order for 40 mEq of KCL through IV was supposed to be discontinued at this point but Provider A mistakenly discontinued a similar order entered by another clinician from two days earlier.
*Provider A then received notification from the pharmacy department that the dose of 100 mEq of KCL in 1 liter of D5W was higher than the maximum allowed for the facility. 
*Provider A discontinued the order for 100 mEq of KCL in 1 liter of D5W and wrote a new order for 80mq/L KClr.
*This new order for 80mq/L KClr was supposed to deliver 1L of fluid however the order did not specify stop time or maximum volume of fluid to be delivered.
*As a result, the fluid continued to be administered for 36 hours. Unfortunately, Provider A unintentionally caused the patient to receive a total of 256 mEq KCL over 36 hours.
*On Sunday morning, there was a change in coverage. Provider A asked Provider B to check the patient’s KCl level.
*Provider B reviewed the patient’s most recent serum KCl which was taken on Saturday morning (before the infusion of potassium). The value was 3.1 mEq/ L which indicated that the patient was hypokalemic. Provider B did not  realize that the lab result was indicative of the patient’s potassium status prior to unnecessary KCl repletion.
*Provider B then ordered 60mEq KCl by injection to be given even while the previous potassium drip was still running.
*Order entry logs revealed that another dose of 40mEq KCl IV injection was also ordered by Provider B but no clear evidence from sources indicate that it was actually given.
*Therefore, the patient received a total volume of 316 mEq KCl over 42 hours.
*On Monday, when the patient’s potassium levels were checked, the patient was found to be dangerously hypokalemic with a serum potassium level of 7.8 mEq/L.
*Once the errors were discovered, immediate measures were taken and the patient was treated.

==Methods and Examples==
The case was reviewed by the hospital Significant Event Committee and experts in cognitive evaluation of information systems. The mission was to identify possible cognitive errors in the chain actions that led to the [[medication error]] and make suggestions to change system interface design and user training in order to eliminate the chance of a similar event. Three significant methods were used in order to create a reconstruction of events that took place.
===Analysis of Order Entry Logs===
All medication orders for the patient over the three days that the incident took place were evaluated. From this analysis, it was discovered that Provider A interacted with the order entry system on three occasions within a 2-hour period. Provider B interacted with the system on three separate occasions, manipulating four orders within the span of an hour. Inappropriate use of CPOE application was also uncovered, such as the use of free-text comment field to limit total fluid volume to 1 liter.
===Visual and Cognitive Evaluation of Ordering Screens===
Unfortunately, the data captured by computer entry logs did not have any information regarding what values were visible on the screen at the time the orders were being filled. Six orders were identified as being potentially erroneous but it was uncertain what the users’ motives were for activating and discontinuing them. Other inconsistencies in visual layout, screen control behavior, and ordering clarity were examined.
===Semi-structured Interviews with Clinicians===
The purpose of these interviews was to integrate the collected data with personal observations and to discover how clinicians interpreted information available to them while using the order entry system. Also, any verbal exchanges with the patient and an explanation for the changes in the order were examined. 

==Results and Discussion==
It was found that this medication error occurred as a result of several factors:
*Misconceptions about the relation between intravenous volume and time duration
*Sub-optimal display of IV bolus injection and medicated fluid drip orders
*Misconception of latest and “dated” laboratory results
*Lack of certain automated checking functions in the order entry system
*Inadequate training of safe and efficient ordering practices

===Specific Recommendations for System and Ordering Procedure Changes===
The hospital’s Medication Safety and Informatics Committee made the following recommendations for changes:
*Screens for ordering continuous IV fluid drips and drips of limited volume need to be clearly distinct so that the ordering of each is unambiguous.
*Screens that list active medication orders also should list IV drip orders.
*Laboratory results review screen needs to clearly visually indicate when the most recent results are not from the current day.
*Add an alert that would inform users, ordering potassium (drip or bolus) when the patient already has another active order for potassium.
*Add an alert informing users ordering potassium when there has not been a serum potassium value recorded in the past 12 hours or the most recent potassium value is greater than 4.0. This would reduce the likelihood of ordering potassium when the patient is hyperkalemic.
*Make other minor changes to increase the consistency of ordering screen behavior.
*Training for the order entry application should not be limited to procedural knowledge but should emphasize conceptual understanding and safe entry strategies.

==Conclusion==
The basis of this medical error was as a result of failures in interaction among human and system agents. The classes of errors that we described are likely to occur in similar systems at other institutions. Sophisticated information systems require comprehensive analyses of human errors for design changes that accentuate clarity of communicated information and employ useful safeguards against patient injury.

==Comments==
This article is very useful for understanding medical errors based on user cognition while using order entry systems. Extensive research needs to be done in order to enhance visual display, cognition-friendly functions and decision support in health information technology systems.

==References==
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==Related Articles==
[[Medication errors: prevention using information technology systems]]

[[Category: CPOE]]
[[Category: Medication Errors]]
[[Category: Drug-drug interaction]]
[[Category: Reviews]]
[[Category: HI5313-2015-FALL]]
[[Category: Medication Error]]