Use of Laboratory and Use of Laboratory and Other Simulations in Other Simulations in

Assessing Drug Name Assessing Drug Name ConfusionConfusion

Tony Grasha (dec)University of Cincinnati

Kraig SchellAngelo State University

The Current State As We See It…

Current means of assessing drug

name confusion are primarily

rational and reductionistic FMEA/RCA Computer phonological analysis Expert teams and committees

Careful consideration must be paid to drug name confusion to avoid patient injury and to avoid financial loss by companies

Our Approach to the Problem The problem of name confusability is broader

and less rational than might be assumed In addition to the physical characteristics of the

name, other factors may play a role such as: Workplace stress and fatigue Outside of the workplace stress and tension Time of day Frequency of prescriptions Workload and work rate Complex and conflicting information Personality characteristics/individual differences

Our Approach to the Problem…

Major assumptions and observations Drugs that look similar, sound similar, and are

spelled in similar ways are not confused with each other or misfilled 100% of the time

Phonological and perceptual factors are important contributors to the problem and are “necessary” but are not “necessary and sufficient” explanations for why the problem exists

The process of human error is not a rational process and cannot be completely reduced to rules and formulae

The Use of Simulations

Simulating all or part of a

dispensing or drug distribution

process can yield important

information about:

• “human factors” that interact with the physical characteristics of a drug name

• work environments within whichparticular drug names are more

confusable than others

A Hierarchy of Simulations

Lab Simulation

Full Scale Pharmacy Simulation“Movie Set Metaphor”

Simulations in Pharmacy Schools

Error MonitoringStations Around the Country

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NT

RO

L

RE

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SM

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L

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Characteristics of Simulations Both objective errors and subjective errors can

be observed Subjective errors include the drug name’s ability

to create “process errors”or “process deviations” that may contribute sporadically to actual errors

Process errors represent mistakes made and corrected but also are indicative of our cognitive system moving into an “error mode.”

A 6:1 average ratio of process errors to those that get by normal verification processes has occurred across a number of settings: laboratory, retail pharmacy, outpatient hospital pharmacy

Characteristics of Simulations

Safe environment for assessing effects of drug names on performance

Allow the use of controlled experimental designs, quasi-experimental designs, case studies of individuals and teams, naturalistic observations of performance

Provide opportunities to insert drug names to be evaluated into a mix of normal products dispensed

Three Laboratory ApproachesFull-scale dispensing task

Simulated products are dispensed from mock scripts

Verification task Simulated prescriptions are checked for

accuracy against “pharmacy records”

Drug name perception task Following the methods of Lambert and

colleagues, drug name confusion can be connected to specific individual difference factors

Examples of Laboratory Simulations

Simulated Prescription Verification Lab

Drug Name Confusion Task

Computer-based simulation (currently under construction)

Names are presented to participants, who must navigate through a “virtual shelf” to retrieve the correct product

Many parameters of the task are modifiable (i.e., duration of name presentation, inclusion of informational context such as dosage, feedback conditions, etc.)

Laboratory Simulation

Pros Strict control over

IVs/DVs Name testing can be

tailored as necessary Other factors (work

pace/workload, etc.) can be varied systematically

Customizable products

Cons Lack of realism Shorter versions of

the task tend to be overly simplistic

Some causes of name confusion may be controlled for in the experimental design

“Movie Set” Simulation Pharmacists/technicians would fill/check scripts in a fluid

and dynamic environment resembling actual pharmacy or variations on it

Emphasis on duplicating the workflow and other likely conditions under which prescription filling/checking would occur

Both objective (errors) and subjective (observational) data collected

“Movie Set” Simulation

The name would be tested in a simulated environment that includes estimable factors that could impact performance: Phone calls/interruptions Customer complaints Insurance paperwork Working with multiple scripts at once Induced stress/fatigue

“Movie Set” Simulation Name confusion could be tested using several

“exercises” based around these potential confounding factors: The “insurance fiasco” exercise The “multiple script” exercise The “similar preceding name” exercise The “frequent prescription” exercise The “stressed out” exercise The “irate customer” exercise, etc.

Exercise creation would be informed by the drug name confusion laboratory task described previously

Simulations in Colleges of Pharmacy

Use of existing simulated environment Possible to do some of the things done in the

“movie set” simulation” May not be as flexible for manipulating some

psychosocial factors

The Error Monitoring Station

Especially in automated pharmacies, the pharmacist’s role has largely switched from filling to verification

This test would insert the new drug into an existing pharmacy strategically placed around the United States

Controls in place to insure that the new drug is not actually dispensed to a customer

Two types of data: pharmacist/technician self-monitoring, objective (end-result) data

The Error Monitoring Station

Advantages: No conflicts of interest Actual “real-world” environment Marketing ramifications

Disadvantages: Slight risk of accidental dispensation but

correctable with observers on site Use of self-report data Possible lack of sample size