Bruce W. Chaffee

Recommendations to Improve the Usability of Drug-Drug Interaction Clinical Decision Support Alerts

OBJECTIVE To establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts. MATERIALS AND METHODS A DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs. We addressed three key questions: (1) what, how, where, and when do we display DDI decision support? (2) should presentation of DDI decision support vary by clinicians? and (3) how should effectiveness of DDI decision support be measured? RESULTS Our recommendations include the consistent use of terminology, visual cues, minimal text, formatting, content, and reporting standards to facilitate usability. All clinicians involved in the medication use process should be able to view DDI alerts and actions by other clinicians. Override rates are common but may not be a good measure of effectiveness. DISCUSSION Seven core elements should be included with DDI decision support. DDI information should be presented to all clinicians. Finally, in their current form, override rates have limited capability to evaluate alert effectiveness. CONCLUSION DDI clinical decision support alerts need major improvements. We provide recommendations for healthcare organizations and IT vendors to improve the clinician interface of DDI alerts, with the aim of reducing alert fatigue and improving patient safety.

Developing and implementing clinical decision support for use in a computerized prescriber-order-entry system

PURPOSE The development and implementation of clinical decision support (CDS) in a computerized prescriber-order-entry (CPOE) system in a large, tertiary care, academic health care system are described. SUMMARY CDS is generally considered to be a key factor in promoting successful system adoption, patient safety, and positive patient outcomes for CPOE implementation. The impact of CDS depends on the methods used by the institution to implement CPOE using both passive and active system design features. At the University of Michigan Health System, interdisciplinary project teams were assembled to plan, build, and implement the CDS component of CPOE using several underlying fundamental principles to ensure the usability and safety of the system, including standardization of system configuration, workflow design, and prioritization of the number and types of interruptive alerts that would be deployed. Passive CDS rules were established for nomenclature, links to information, relevant results, and order sets. Active CDS rules were developed for noninterruptive alerts (patient list alert flags and form-called medical logic modules) and interruptive alerts, including alerts for allergies, dose checks, drug-drug interactions, drug-food interactions, and drug-disease interactions. The institution provided sufficient staffing and institutional governance to implement and sustain CDS. CONCLUSION Through an interdisciplinary collaboration, an academic health care system planned, designed, and implemented institution-specific, CPOE-integrated CDS to improve clinical efficiency and facilitate the compliance with regulatory policies and guidelines.

Pharmacoeconomic evaluation of flumazenil for routine outpatient EGD

BACKGROUND Flumazenil is a benzodiazepine antagonist indicated for reversal of the sedative effects of benzodiazepines. Previous studies suggest that flumazenil may shorten recovery time after endoscopy, but there are few data on actual recovery room times and charges. METHODS Fifty patients undergoing routine upper endoscopy were sedated with midazolam alone in the usual titrated manner. Patients were randomized in a double-blind fashion to receive either flumazenil or saline immediately after procedure. Assessments of responsiveness, speech, facial expression, and ptosis (Observers Assessment of Alertness/Sedation [OAA/S] scale) were made before procedure, immediately after procedure and every 15 minutes thereafter. The patient was discharged from the recovery room when vital signs and OAA/S scale reached preprocedure levels. Recovery room times and charges were recorded. RESULTS The flumazenil group demonstrated shorter recovery room times and recovery room charges than the placebo group (p < 0.001). The difference in recovery room charges was not statistically different when flumazenil charges were included (p = 0.09). CONCLUSIONS The routine use of flumazenil after midazolam sedation for upper endoscopy significantly shortened recovery time and charges but did not statistically reduce overall charges.

Guidelines for the safe handling of hazardous drugs: Consensus recommendations

Determining the proper precautions that employees should take to reduce their exposure to potentially hazardous drugs is very difficult due to the many risk factors that must be considered. Some of these risk factors include the inherent toxicity of the drug, the drug’s mechanism of action, the

Maintaining the enterprisewide continuity and interoperability of patient allergy data

PURPOSE The efforts, results, and challenges of a large tertiary care, academic health care system to standardize and integrate allergy information across clinical information systems are discussed. SUMMARY The University of Michigan Health System and its Information Technology Strategic Advisory Committee recognized the necessity for storing and maintaining allergy information in a single repository; therefore, the clinical data repository (CDR) was named as the central database for coded allergens and reactions for the University of Michigan Hospitals and Health Care Centers (UMHHC) electronic medical record. The Enterprise Allergy Project (EAP) began in June 2005 with the formation of a steering committee that included representatives from clinical departments with order-entry systems. The initial phase of the EAP consisted of several components. One component was a one-time conversion of existing free-text allergy information into coded allergens and reactions. Before the implementation of the EAP, the order-entry system only supported the entry of uncoded allergen and reaction information. An initial process of allergy matching reduced the list of un-coded allergens from 272,519 to 29,500 by using terms that indicated no allergies were present and trimming and modifying free-text strings that closely matched or easily translated to a coded allergen counterpart. Another component of the EAP consisted of the interface and technical build to support allergy information processing between the CDR and University of Michigan (UM)-Carelink. One goal of the EAP was to transfer data bidirectionally, but that goal could not safely be accomplished. CONCLUSION Implementing a strategy for enterprise allergy integration at UMHHC has improved the quality of allergy information documented as measured by a significant decrease in the amount of uncoded allergens.

Clinical decision support for atypical orders: detection and warning of atypical medication orders submitted to a computerized provider order entry system.

The specificity of medication-related alerts must be improved to overcome the pernicious effects of alert fatigue. A systematic comparison of new drug orders to historical orders could improve alert specificity and relevance. Using historical order data from a computerized provider order entry system, we alerted physicians to atypical orders during the prescribing of five medications: calcium, clopidogrel, heparin, magnesium, and potassium. The percentage of atypical orders placed for these five medications decreased during the 92 days the alerts were active when compared to the same period in the previous year (from 0.81% to 0.53%; p=0.015). Some atypical orders were appropriate. Fifty of the 68 atypical order alerts were over-ridden (74%). However, the over-ride rate is misleading because 28 of the atypical medication orders (41%) were changed. Atypical order alerts were relatively few, identified problems with frequencies as well as doses, and had a higher specificity than dose check alerts.

The need for collaborative engagement in creating clinical decision-support alerts.

Clinical decision support (CDS) encompasses a broad array of technology and approaches, all of which involve the provision and use of clinical information in medical processes. [1][1] Medication-focused CDS is frequently used in the context of inpatient computerized prescriber order entry (CPOE) and

Future of clinical decision support in computerized prescriber order entry.

In the defunct ABC television series Life on Mars , Jason O’Mara plays Sam Tyler, a modern-day New York City police detective thrust back in time to 1973. Upon arriving in the past, Sam finds none of the technological advances available in modern-day society—items we now take for granted—such

ASHP Guidelines on the Design of Database-Driven Clinical Decision Support: Strategic Directions for Drug Database and Electronic Health Records Vendors.

ASHP believes that use of clinical decision support (CDS) tools can make patient care more efficient and effective.[1][1] Currently available pharmacotherapy CDS systems are not as effective as they need to be at helping all practice settings achieve the goal of safe and effective pharmacotherapy.

National standards for computerized prescriber order entry and clinical decision support: The case of drug interactions

T o say that health information technology is a hot topic in health care is an understatement. The American Recovery and Reinvestment Act (ARRA) of 2009 has made elec tronic health record (EHR) and computerized provider order entry (CPOE) everyday terms for health care practitioners. CPOE was first