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medication-related decision-support alerts

Posted: 03 May 2014, 15:19
by jerome
This is an excerpt from this article (freely available online): Zachariah, Marianne, Shobha Phansalkar, Hanna M Seidling, Pamela M Neri, Kathrin M Cresswell, Jon Duke, Meryl Bloomrosen, Lynn A Volk, and David W Bates. “Development and Preliminary Evidence for the Validity of an Instrument Assessing Implementation of Human-Factors Principles in Medication-Related Decision-Support Systems--I-MeDeSA.” Journal of the American Medical Informatics Association: JAMIA 18 Suppl 1 (December 2011): i62–72. doi:10.1136/amiajnl-2011-000362.

In my last post about drug-drug interaction alerts, I suggested changing the appearance of alerts in FreeMedForms. Here is the reference to support my claims. If you read the article, you'll see that the authors tested their principles on real life CPOE (computerized order entry) systems.

Please give me feedback as to how we could implement the missing features in FMF.

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Summary of the 11 key human-factors principles for use in medication-related decision-support alerts, compiled by Phansalkar et al.

Human-factors principle & Summary of principle

Alarm philosophy
Defined as the logic used to classify alert priority levels. A catalog of all alert level categories should be made available to users, clearly indicating how priority levels are set (eg, based on the severity of patient harm). The goal of this philosophy should be to minimize the overall number of alerts. Additionally, the alert should seek to capture the user's acknowledgment and response. Ideally, the user's acceptance or rejection of the alert would also serve as an acknowledgment of having seen the alert. Less desirable would be alert designs in which these functions are separated, and users would need to first acknowledge an alert and subsequently indicate their response in a separate window.

False alarms
May arise when the alert logic is incorrect or out of date, or the alert is calibrated too sensitively, setting off alarms that are essentially irrelevant to clinical care. False alarms may disrupt workflow and unnecessarily increase workload. Evidence suggests that users will decrease their response to alerts in general as the false-alarm rate increases. Recommendations are to move away from alarm strategies that follow a one-size-fits-all approach and toward intelligent alarm monitoring that considers the multi-dimensional relationship between clinical interactions and patient health.

Placement
Alerts and the information within should take into consideration users' viewing habits to optimize visibility. Alerts should be located in the visual field in order of their importance. Additionally, the proximity compatibility principle of Wickens and Carswell14 should be employed—for example, as a user orders medications, alerts should appear in close proximity to the location on the screen where a user enters medications in the ordering window.

Visibility
Considers overall size of the alert on the screen (target size), luminance, background contrast, and lettering characteristics. The size of the target should be increased as viewing distance increases or contrast decreases. Additionally, letter heights should be larger when reading from a visual display; a mixture of upper and lower cases should be used for easier reading; and visibility is optimized when dark text is presented on a light background.

Prioritization
Prioritization of alerts through visual characteristics is necessary and should utilize hazard matching. This is the process of matching the appearance of the warning to the level of hazard associated with the clinical implications of the alert. For example, colors such as red and orange typically imply a higher level of hazard, while green, blue, and white imply a lower hazard level. It is also important to consider the limitations of color for indicating the level of hazard for color-blind users. To address color-blind users' needs, signal words and shapes can be used to communicate the level of hazard and priority in addition to the use of color. Signal words demonstrating high priority are: ‘lethal,’ ‘deadly,’ ‘danger;’ and words demonstrating low priority are: ‘warning,’ ‘caution,’ etc. Shapes can also be used for conveying levels of priority: angular shapes represent high priority while regular shapes such as circles represent low priority

Color
May be utilized not only to indicate severity but also to communicate the type of alert (eg, drug–drug, drug–allergy, etc) or the response required. However, colors should be kept to a minimum (<10), since, with more colors, it may be difficult for users to remember what each color indicates.

Learnability and confusability
Refers to the ability of the user to learn and distinguish between different types of visual alerts. Color, shapes, and size can be used to lend a distinct appearance to different types of alerts. The fewer features that alerts share with each other, the more distinct they appear, making it easier for users to remember and quickly recognize different types of alerts.

Textual information
Demands as much consideration in the designing of medication-related decision support alerts as the alerts' visual characteristics. The text of visual alerts should possess the following four components for effective communication of information: (1) a signal word to indicate the severity of the alert, (2) a statement of the nature of the hazard (eg, specify interacting drug names or drug classes), (3) an instruction statement providing recommended actions, and (4) a consequence statement that indicates the potential harm to the patient. Of these four components, the nature of the hazard and instruction statements carry the most importance. Additionally, textual information should be explicit, rather than non-explicit (eg, ‘smoking causes lung cancer’ rather than ‘smoking is damaging to health’).

Habituation
Refers to a decrease in response to stimulus due to repeated and inconsequential exposure. Habituation predicts that repeated exposure to an alert that does not require that a meaningful response will result in a decrease, and eventual elimination, of responding to the alert. This risk highlights the importance of reducing the rate of false alarms, as well as the importance of an alarm philosophy that minimizes alerts overall. Habituation also highlights the importance of different types of alerts being visually distinct from one another, since alerts that are not visually distinct can be perceived as the same.

Mental model
Represents the understanding individuals have about a particular topic. Given that mental models govern users' behavior, alerting systems should adequately support pervading mental models. For example, since users generally perceive red to mean ‘stop’ and green to mean ‘go,’ alerting systems should follow the same model, rather than using green to signal ‘stop’ and red to signal ‘go.’


Proximity of task components being displayed
Incorporates Wickens and Carswell's proximity compatibility principle,14 as does the Placement principle. With respect to Proximity of Task Components Being Displayed, tools for decision-making should be integrated into the body of the alert or found within close temporal and spatial proximity to the alert. For example, a link to a medical reference website should be located within the alert, not in a window that is multiple clicks away.
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Re: medication-related decision-support alerts

Posted: 04 May 2014, 22:12
by eric
This is a very interesting summary of what an alert system consist.
The FreeMedForms alert system is already answering to some of the problematics. And there are still was to improve the alert system.
We should take some times to describe the current engine and all its potential improvements in a way that contributors will find the main ideas for the code.

Re: medication-related decision-support alerts

Posted: 16 May 2014, 04:29
by eric

Re: medication-related decision-support alerts

Posted: 13 December 2014, 12:33
by Aliraza149
YYYYEEEESSSSS !!!! :D
Please, create a wiki page to explain the role and organisation of the SC (scientific committee).
Until you finish your PhD or MD ?

Re: medication-related decision-support alerts

Posted: 13 December 2014, 14:10
by jerome
hi!

The interactions committee page already exists: https://freemedforms.com/en/interaction-committee/start

You seem very enthusiastic. :-)