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Nurses’ mental models of smart infusion pumps

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Presentation on theme: "Nurses’ mental models of smart infusion pumps"— Presentation transcript:

1 Nurses’ mental models of smart infusion pumps
Steven J. Landry, Ph.D. School of Industrial Engineering School of Aeronautics and Astronautics (by courtesy) Regenstrief Center for Healthcare Engineering Purdue University

2 Motivation

3 Past work: Survey of nurses
When you override the warning, what is your estimate/perception of the percentage of the time that the override is necessary? When you reprogram the warning, what is your estimate/perception of the percentage of the time that reprogramming the pump is necessary?

4 Poor mental models can result in frustration and improper responses.
The problem We don’t know what mental models nurses have for infusion pumps, where those mental models will affect a nurses’ decision to override or reprogram an alarm that goes off due to violating a soft limit. Poor mental models can result in frustration and improper responses. Unfortunately, there is no definitive way to elicit a mental model.

5 Do different models exist?
Research questions Do different models exist? Alert occurs when programmed limit is exceeded. Alert occurs when entered data does not match prescription. Alert occurs when adverse drug reaction will occur. If so, what effect does it have on responses? What forms of the alert (or training) can mediate any misperception?

6 Method Model 1: Alert occurs when threshold is exceeded.
Model 2: Alert occurs when entered data does not match prescription. Model 3: Alert occurs when adverse drug reaction will occur if dose is applied.

7 I need your help! Q7 Your patient is a white male, approximately 50 years of age, who has just undergone hip surgery to remove a chondroid.  The doctor has prescribed morphine for the patient to relieve pain.  You select "Guardrail Infusion" and "Non Critical Care."  You enter "Morphine" as the drug, but when you enter "4" as the "Dose," you get the following error message:

8 Survey Definitely would cause the alert. (1)
Definitely would cause the alert. (1) Probably would cause the alert. (2) Unsure whether it could cause the alert or not. (3) Probably would not cause the alert (4) Definitely not cause the alert (5) There is an issue with the pump hardware. (1) There is an issue with the infusion settings. (2) There is an issue with the pump drug library. (3) There are other pump software issues. (4) The pump is not aware in which ward we are. (5) The programmed dosage/rate/volume exceeds the library threshold. (6) The programmed dosage/rate/volume does not match the doctor's prescription. (7) The programmed dosage/rate/volume is not what the nurse intended to program. (8) The programmed dosage/rate/volume is unsafe for the patient. (9) There is an issue with the order the nurse got from the doctor. (10)

9 Steven J. Landry, Ph.D. slandry@purdue.edu 765-494-6256
Yuval Bitan (Ben Gurion University) Jeong Joon Boo (undergraduate/graduate)


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