1. Decision Support for Quality Improvement
Unit 6.3: Alerts and Clinical Reminders
Welcome back to Decision Support for Quality Improvement. This unit is designed to provide you with a deeper understanding of the role of alerts and clinical reminders, their benefits, and potential hazards.
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2. Health IT Workforce Curriculum
Objectives
Analyze the benefits and shortfalls of alerts and clinical reminders
After completing unit 6.3, the learner should be able to analyze the benefits and shortfalls of alerts and clinical reminders.
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3. Health IT Workforce Curriculum
Reminders and Alerts
“…the burden of reminders and alerts must not be too high…or alert fatigue may cause clinicians to override both important and unimportant alerts, in a manner that compromises the desired safety effect of integrating decision support into CPOE.”
While decision support in the form of alerts and reminders has the potential to improve patient safety, reality is that, according to the current literature, these alerts are overridden by clinicians % of the time. This is a real concern for HIT professionals.
van der Sijs H, Aarts J, Vulto A, Berg M (2006) Overriding of drug safety alerts in computerized physician order entry. Journal of the American Medical Informatics Association, 13(2),
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4. Health IT Workforce Curriculum
Alerts and Reminders
Nuisance Alert
Alert Fatigue
“…provides little perceived benefit to the prescriber at the time of the alert”
“…arise when clinicians, either consciously or unconsciously, begin to systematically bypass CDS alerts without regard to their importance, enabling the possibility that a clinically important alert is missed”
One of the main reasons given for over-riding alerts is perceived lack of relevance. The so-called Nuisance alerts provide little perceived benefit to the prescriber at the time of the alert. This causes great frustration on the part of clinicians and leads to a phenomenon called alert fatigue. Alert fatigue can result in the clinician systematically bypassing the alert, either consciously or subconsciously. The potential for missing a clinically important alert is high.
Chaffee, BW (2010). Future of clinical decision support in computerized prescriber order entry. American Journal of Health System Pharmacists, 67:
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5. Responses to Clinical Reminders
Tendency to perform an action when a warning system instructs the user to do so
Compliance
Tendency to refrain from performing an action when the warning system does not indicate that it is necessary
Reliance
There have been 4 types of responses identified with respect to clinicians and clinical reminders. Compliance is the tendency to perform an action when a warning system instructs the user to perform a corrective or preventive action, such as checking a hospitalized patient’s status when a clinical monitor issues an alert in the EHR. Reliance, on the other hand, is the tendency to refrain from performing an action when the warning system does not indicate that it is necessary, e.g., assuming that the patient’s status is normal and thus not checking the patient, when the monitor does not generate an alert in the EHR.
Vashitz G, Meyer J, Parmet Y, Peleq R, Goldfarb D, Porath A, Gilutz H. (2009).
Defining and measuring physicians' responses to clinical reminders.
Journal of Biomedical Informatics; 42(2): Epub 2008 Oct 26.
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6. Responses to Clinical Reminders
Clinician performs an action even when not prompted by the reminder system
Spillover
Clinician refrains from performing an action due to a perceived threat to professional autonomy
Reactance
Two additional types of responses include Spillover and Reactance. Spillover can occur when there is a spread of responses merely due to increased awareness of the need for an action, even when the clinician is not prompted by the reminder system. For example, Zanetti’s research team found that reminders for intra-operative drugs increased re–dosing even in a control group which did not receive these reminders and concluded that this spillover occurred because of increased awareness to the importance of re-dosing. Reactance is the tendency for clinicians to experience a threat to their autonomy or freedom of choice in the presence of these systems. The clinician may consciously or unconsciously react by either ignoring the reminders or choosing a different course of action, trying to regain their sense of freedom and autonomy.
Vashitz G, Meyer J, Parmet Y, Peleq R, Goldfarb D, Porath A, Gilutz H. (2009).
Defining and measuring physicians' responses to clinical reminders.
Journal of Biomedical Informatics; 42(2): Epub 2008 Oct 26.
G. Zanetti, H.L. Flanagan, L.H. Cohn, R. Giardina and R. Platt, Improvement of intraoperative antibiotic prophylaxis in prolonged cardiac surgery by automated alerts in the operating room, Infect Control Hosp Epidemiol 24 (1) (2003), pp. 13–16.
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7. Four Types of Alerts/Reminders
Drug Alerts
Lab Test Alerts
Practice Reminders
Administrative Reminders
For the purpose of this discussion, we will look at experience with 4 types of alerts or reminders: drug alerts, lab test alerts, practice reminders, and administrative reminders.
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8. Health IT Workforce Curriculum
Basic Drug Alerts
Drug allergy warnings
Drug-drug interactions
Duplicate medication or therapeutic duplication alert
Basic medication order guidance
Kuperman and colleagues identify 4 types of basic drug alerts. Drug allergy warnings are generated on ordering a drug to which the patient has a documented drug allergy. Drug-drug interactions are generated when the mode of action of one drug is known to be affected by simultaneously prescribing a second drug. Duplicate medication or therapeutic duplication alerts are generated when the patient is already receiving the medication just ordered or a different drug in the same therapeutic category. Basic medication order guidance is an alert that provides dosing information with default dosing being the most appropriate initial dosing.
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Advanced Drug Alerts
Drug-Lab alerts
Drug-Condition interactions
Drug-Disease Contraindication alerts
Drug-condition alerts aimed at appropriate prescribing
There are 8 identified types of advanced drug alerts. Drug-lab alerts are generated when drug administration requires close monitoring of laboratory results before and/or after administration. Drug-condition interactions are generated to raise awareness of specific prescribing for particular clinical conditions. Drug-disease contraindication alerts are generated to warn against prescribing a certain drug in a specific disease or condition. Drug-condition alerts aimed at appropriate prescribing are generated to encourage prescribing a certain drug in a specific clinical condition.
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Advanced Drug Alerts
Drug-age alerts
Drug-formulary alerts
Dosing guidelines
Complex prescribing alerts
Drug-age alerts are generated to discourage prescribing of a certain drug in the elderly or in children. Drug-formulary alerts are generated to notify the prescriber that a particular brand or drug is neither included nor recommended in the formulary at the prescribing location. Dosing guidelines are alerts that take into account complex patient characteristics such as age, renal/liver function, pregnancy or female of childbearing potential, pediatric weight-based dosing, drug utilization restrictions, or clinical indication. Finally, complex prescribing alerts are generated with combined features of basic and advanced alerts.
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11. Evidence to Support Drug Alerts
Systematic review examined 20 studies that evaluated the impact of efficacy of computerized drug alerts and prompts
23 of 27 alert types identified demonstrated benefit
Improving prescribing behavior
Reducing error rates
Greatest potential for affecting prescribing
Drug-drug interaction alerts
Drug-disease contraindication alerts
Dosing guidelines based on age
Angela Schledlbauer and her colleagues performed a systematic review of the evidence that supports use of computerized alerts and prompts to improve drug prescribing behaviors. Most of the studies reviewed showed positive benefits. 23 of 27 drug alert types that were identified demonstrated benefits in terms of improving prescriber behavior and reducing error rates. They found that the greatest potential for benefit was with drug-drug interaction and drug disease contraindication alerts, and age-related dosing guidelines.
Schedlbauer, A, Prasad V, Mulvaney C, Phansalkar S, Stanton W, Bates DW, Avery AJ (2009).
What evidence supports the use of computerized alerts and prompts to improve clinicians' prescribing behavior?
Journal of the American Medical Informatics Association;16(4): Epub 2009 Apr 23.
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12. Improving Adoption of Drug Alerts
Shah and colleagues studied way to improve clinician acceptance of drug alerts in ambulatory care settings
Designed a selective set of drug alerts for the ambulatory care setting using a criticality leveling system
Minimized workflow disruptions by designating only critical to high-severity alerts to be interruptive to clinician workflow
Alert levels:
1: clinician could not proceed with the prescription without eliminating the contraindication;
2: clinicians could proceed if provided an over-ride reason
3: alert displayed at top of screen in red; did not hinder workflow
A group of northeastern researchers wanted to find a way to improve clinician acceptance of drug alerts in ambulatory care settings. They designed a selective set of drug alerts using a criticality leveling systems. Level 1 alerts were the most critical and a clinician could not proceed with the prescription without eliminating the contraindication. Level 2 alerts were very important, but the clinician could proceed if he or she provided a reason for overriding the alert. Level 3 alerts were designed to not disrupt workflow, but to provide important information for the clinician to take into consideration. Through this research, Shah’s team was able to demonstrate that by designating only critical to high-severity alerts to be interruptive of clinician workflow they were able to minimize workflow disruptions and improve clinician acceptance of drug alerts.
Shah NR, Seger AC, Seger DL, Fiskio JM, Kuperman, GJ, Blumenfeld B, Recklet EG, Bates DW, & Gandhi TK (2006).
Improving Acceptance of Computerized Prescribing Alerts in Ambulatory Care. Journal of the American Medical Informatics Association; 13(1): 5–11.
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13. Basic Laboratory Alerts
Drug-laboratory alerts
Duplicate laboratory testing alert
Basic laboratory test order guidance
Public health situational awareness
Basic laboratory alerts include: drug-lab alerts, which as stated previously, are generated when drug administration requires close monitoring of laboratory results before and/or after administration. Duplicate laboratory testing alerts are generated when the patient has already had the lab test ordered. Basic laboratory test order guidance is an alert that provides ordering information with respect to the particular lab test being ordered. Finally, alerts can be generated to notify clinicians of public health alerts so that they can initiate appropriate laboratory testing during local disease outbreaks.
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14. Evidence to Support Lab Alerts
Research examined the impact of a clinical decision support system that generated reminders of previous lab test results
Found that the proportion of unnecessarily repeated tests dropped significantly
Features of the Alert
Alert was automatically prompted and was part of the clinician workflow
User could not deactivate the alert output
Most recent laboratory result for viral serology test an its date was automatically retrieved from the patient’s EHR
Alert was displayed at the time and location of decision making (before the user ordered an unnecessarily repeated test
French researchers recently examined the impact of a serology-clinical decision support system providing point of care reminders of previous existing blood test results. These reminders were embedded in a Computerized Physician Order Entry at a university teaching hospital. The clinical decision support system was implemented in the Cardiovascular Surgery department of the hospital in order to decrease inappropriate repetitions of viral serology tests (specifically, Hepatitis B Virus). The researchers found that the proportion of unnecessarily repeated tests immediately dropped after implementation of the alert and remained stable.
Features of the alert that enhanced its success were: the alert was automatically prompted and was part of clinician workflow, the user could not deactivate the alert output, the most recent laboratory result for viral serology tests and its date was automatically retrieved from the patient's EHR, and the alert was displayed at the time and location of decision making (ie, before the user ordered an unnecessarily repeated test).
BMC Health Services Research, 9;10:70.
Nies J, Colombet I, Zapletal E, Gillaizeau F, Chevalier P, Durieux P. (2010) Effects of automated alerts on unnecessarily repeated serology tests in a cardiovascular surgery department: a time series analysis.
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Practice Reminders
Provides recommended treatment
Guiding
Checks prescriptions against clinical practice guidelines
Critiquing
Helps provider follow the patient
Monitoring
There are three ways in which practice reminders can be used as clinical decision support. They can guide the clinician to provide the recommended treatment. They can critique the clinicians course of action by comparing it against guideline recommendations, and they can help with patient follow-up.
Lami JB, Ebrahiminia V, Riou C, Seroussi B, Bouaud J, Simon C, Dubois S, Butti A, Simon G, Favre M, Falcoff H, Venot A. et al. (2010). How to translate therapeutic recommendations in clinical practice guidelines into rules for critiquing physician prescriptions? Methods and application to five guidelines. BMC Medical Informatics and Decision Making May 28;10:31.
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16. Practice Reminders Challenges
Incorrect Guidelines
Too generic guideline
Patient data inconsistency
Inappropriate action
Potential Risk
There are a number of known challenges to incorporating clinical practice guidelines into clinical decision support systems. These were identified over 10 years ago, and are still applicable today. First, reminders can be false alarms, given as a result of an incorrectly implemented guideline. Next, reminders can be false due to the fact that the guideline is not specific enough to address the particular patient’s condition. For example, a guideline may not specify exceptions and a patient who falls within the exception may have the guideline inappropriately applied. Third, patient data in the EHR can be incomplete or inconsistent, resulting in the reminder either firing inappropriately or not firing at all. Fourth, the actions that the reminder generates may not be clinically appropriate for the particular patient, and finally, the reminder itself may generate risk to the patient.
De Clercq PA, Blom JA, Hasman A, Korsten HHM. A strategy for
developing practice guidelines for the ICU using automated knowl-
edge acquisition techniques.
Journal of Clinical Monitoring; 15:
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17. Administrative Reminders
Guides prescribers to document to support appropriate medical coding
Medical Coding
Guides the collection of QI indicator data
Quality Improvement
Decision support can also be used to provide administrative reminders such as use of suggested coded problems for particular patient populations to support billing and specific guidance on documentation to support collection of QI indicator data.
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18. Success Factors: Alerts
Specificity
Alert clinically important for the patient
Sensitivity
Alert generated in all dangerous cases
There are several success factors that have been identified to aid in gaining clinician acceptance of alerts and reminders.
Alerts should be specific. That is they should be clinically important for the patient. Action should follow the alert and the alert should be accurate for the right patient (taking patient characteristics such as age, clinical condition, and gender into account).
Alerts should also be sensitive. They should fire in all dangerous cases.
van der Sijs H, Aarts J, Vulto A, Berg M (2006) Overriding of drug safety alerts in computerized physician order entry. Journal of the American Medical Informatics Association, 13(2),
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19. Success Factors: Alerts
Information Content
Clear, concise, unambiguous
Justification noted
Further information accessible
Alternative actions presented
Information contained in the alert should be clear and concise. Justification should be noted and additional information should be readily accessible. Alternative actions should be presented
van der Sijs H, Aarts J, Vulto A, Berg M (2006) Overriding of drug safety alerts in computerized physician order entry. Journal of the American Medical Informatics Association, 13(2),
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20. Success Factors: Alerts
Workflow
Directed to right person at right time
Specialty-specific; Knowledge-specific
Avoid repetition
Safe, efficient handling
High threshold
Reasons for non-compliance
Promotes action
Speed; Screen design; minimize work
Alerts should be directed to the right person at the right point in their workflow. Specialists should not receive alerts that tell them what they already know. Physicians in training should receive more alerts than specialists. Annoying repetition should be prevented. In addition, overriding fatal alerts should never be easy. Reasons for over-riding the alert should be requested. Alerts should promote action rather than stopping intended actions. Alerts should not slow the system down and the user should not be required to scroll endlessly or perform multiple keystrokes to accomplish a task. Screen design should be logical.
van der Sijs H, Aarts J, Vulto A, Berg M (2006) Overriding of drug safety alerts in computerized physician order entry. Journal of the American Medical Informatics Association, 13(2),
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Summary
Alerts and reminders have the potential to improve patient safety
Types of alerts and reminders include: drug and lab test alerts, practice reminders, and administrative reminders
Nuisance alerts provide little perceived benefit to the prescriber at the time of the alert, causing clinician frustration and alert fatigue
Successful alerts are specific, sensitive, clear and concise.
Successful alerts support clinical workflow and allow for safe, efficient responses.
In summary, alerts and reminders have the potential to improve patient safety. Types include drug and lab test alerts, practice reminders, and administrative reminders. Alerts and reminders also have the potential to compromise patient safety. Nuisance alerts provide little perceived benefit to the prescriber at the time of the alert and can cause frustration ad alert fatigue, which can , in turn, result in medical error. Successful alerts are specific, sensitive, clear and concise, support clinical workflow and efficiency.
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