Mount Sinai Medical Center: Implementation of Decision Support for Radiology Orders

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Screen Shot 2014-02-10 at 6.01.04 PM.png - Mount Sinai Medical Center: Implementation of Decision Support for Radiology Errors

The rapid deployment of EMRs—in parallel with the extensive penetration of digital systems into radiology—has produced an environment that will enable many new technologies, including clinical decision support, to be introduced into the health-care system. There has long been interest in clinical decision support, especially at the time of order entry, but a lack of systems (and credentialed guidelines) has limited clinical use. In the realm of imaging, it is hoped that the implementation of radiology decision support will have an impact on inappropriate utilization and will thereby increase the quality (and diminish the cost) of imaging within the overall health-care system. Such solutions are now moving into commercially available systems. While we might expect growing pains, we simultaneously should look for enhancements in the quality of care that we can deliver to our patients. New opportunities have arrived; we need to take our new tools and put them to use. At MSMC, our first efforts to implement a radiology decision-support system made us early adopters of commercial offerings. MSMC encompasses both the Mount Sinai Hospital and the Mount Sinai School of Medicine. The Mount Sinai Hospital, founded in 1852, is a 1,171-bed tertiary- and quaternary-care teaching facility and is one of the nation’s oldest, largest, and most respected voluntary hospitals. Nearly 60,000 people were treated at MSMC as inpatients in 2011, and approximately a million outpatient visits took place. Due to MSMC’s location on the Upper East Side of New York City, the hospital is at the intersection of some of the wealthiest and poorest zip codes in the United States; it has the responsibility of meeting the unique medical needs of both patients from affluent backgrounds and those requiring indigent care. MSMC’s focus is on seamless care coordination across all ambulatory, inpatient, and emergency-department settings—as well as on providing access to patients’ records to their clinicians. This is being supported using a well-known, broadly deployed integrated EMR at MSMC. In addition, MSMC is also implementing a wide array of advanced clinical processes that are made possible by the EMR. The primary drivers are quality, safety, and efficiency. We spent approximately two years exploring potential decision-support solutions for radiology. In parallel, the ACR® had made a decision to make its well-known ACR Appropriateness Criteria® available (in a format that can easily be consumed by downstream systems) via ACR Select—the Web-service version of the appropriateness criteria and exclusive distributor of the guidelines. We were positioned to purchase a solution concurrent with the release of the ACR Select product; simultaneously, our EMR vendor adopted the approach of establishing a transparent means of importing and integrating credentialed rule sets for clinical decision support for radiology. These two converging strategies have facilitated our current approach. The ACR provides an authoritative source of clinical decision-support rules, meant to be consumed as a Web service by multiple EMRs, so the solution is vendor agnostic. In fact, this approach makes initial implementation fairly straightforward, requiring little technical effort (on the order of 40 hours of work). This implementation represents a first version and an early effort of the EMR vendor to integrate the ACR Select rule set, and as such, it had many constraints. The ACR Select product provides the vendor with lists of indications. The EMR then needs to orchestrate the presentation of these indications. In this first version, there was little flexibility regarding the structure and presentation of these indication lists. The lists were provided as groups, and one could combine these groups to build a list that would be presented to the ordering provider at the time of order entry. In essence, a site had a choice of providing long lists—quite inclusive of every possible indication for an exam—versus short lists of common indications (excluding rarer indications). As an academic institution with many specialty providers, we initially elected to provide the long, granular lists of indications. We had a small group of radiologists and clinicians review the lists and decide which to include and which to exclude. Our local EMR team then did the work to integrate these indications with our EMR. The Data-collection Phase Phase 1 of radiology decision support was implemented in March