Publications by authors named "Michael A Krall"

Objective: The United States Office of the National Coordinator for Health Information Technology sponsored the development of a "high-priority" list of drug-drug interactions (DDIs) to be used for clinical decision support. We assessed current adoption of this list and current alerting practice for these DDIs with regard to alert implementation (presence or absence of an alert) and display (alert appearance as interruptive or passive).

Materials And Methods: We conducted evaluations of electronic health records (EHRs) at a convenience sample of health care organizations across the United States using a standardized testing protocol with simulated orders.

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Anesthesia information management systems (AIMS) are sophisticated hardware and software technology solutions that can provide electronic feedback to anesthesia providers. This feedback can be tailored to provide clinical decision support (CDS) to aid clinicians with patient care processes, documentation compliance, and resource utilization. We conducted a systematic review of peer-reviewed articles on near real-time and point-of-care CDS within AIMS using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols.

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Background: Many computerized provider order entry (CPOE) systems include the ability to create electronic order sets: collections of clinically related orders grouped by purpose. Order sets promise to make CPOE systems more efficient, improve care quality and increase adherence to evidence-based guidelines. However, the development and implementation of order sets can be expensive and time-consuming and limited literature exists about their utilization.

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Most computerized physician order entry (CPOE) systems have built-in support for order sets (collections of orders grouped by a clinical purpose). Evidence and experience suggest that order sets are important tools for ordering efficiency and decision support and may influence ordering. Developing and maintaining order sets is costly, so hospitals often must prioritize which order sets can be created.

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Background: Real-time clinical decision support (CDS) integrated into clinicians' workflow has the potential to profoundly affect the cost, quality, and safety of health care delivery. Recent reports have identified a surprisingly low acceptance rate for different types of CDS. We hypothesized that factors affecting CDS system acceptance could be categorized as relating to differences in patients, physicians, CDS-type, or environmental characteristics.

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We tested whether off-line data analysis, instead of event monitoring, was a viable method for initiating a clinical quality alert. A cohort of patients eligible for an alert was identified by off-line data analysis and a flag was set in their ambulatory Electronic Medical Records. One hundred clinicians were randomly assigned either to a control group or to a group that received the alert when viewing the electronic medical record of eligible patients.

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Electronic medical record alerts and reminders are increasingly employed as a means of decreasing medical errors and increasing the quality and cost-effectiveness of care. However, clinicians indicate that alerts and reminders can be either help or hindrance. Discerning the elements that determine which they will be, and the requirements of a helpful alert or reminder, was the focus of this study.

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