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Utilization of diagnostic imaging in the Emergency Department has increased dramatically over the past two decades, driven by an increased availability of advanced imaging, legal pressures to exclude serious diagnoses in low-risk patients, patient expectations, and the tendency to associate more testing with a higher quality of care. However, this rise in the use of diagnostic imaging, particularly in low-risk patients, may not be taking into account the risk of radiation exposure to patients, or the impact on finite health system resources. The objective of this project is to improve the appropriateness of CT imaging in Alberta Emergency Departments by advancing awareness of, and adherence to, evidence-based guidelines for CT imaging of patients with mild traumatic brain injury (MTBI) and suspected pulmonary embolism (PE). These two clinical scenarios have been selected because of evidence of significant variation in imaging practices across Alberta, and the robust evidence base that exists to guide CT imaging decisions such as the Canadian CT Head Rule and the Pulmonary Embolism Rule Out Criteria.
Full description
Background:
Imaging technology for the rapid diagnosis of medical conditions is an indispensable tool in the emergency department (ED). However, increasing and inappropriate use of costly and potentially dangerous imaging is a growing healthcare concern. The long-term health risks of radiation exposure, and the resources consumed by increased use, pose serious threats to the integrity of the investigators' health care system and the population at large. Computed tomography (CT) is frequently used in the emergency department setting to evaluate patients with mild traumatic brain injury (MTBI) and suspected pulmonary embolism (PE) to eliminate diagnostic uncertainty by either confirming or ruling out serious injury and illness. However, these tests are often used in lieu of alternate and safer strategies with equivalent accuracy and effectiveness. Fortunately, well-validated decision-support tools exist that can safely identify low risk patients who are unlikely to benefit from CT imaging, avoiding unnecessary diagnostic imaging and radiation exposure, and making better use of limited health system resources. However, decision-support is under-used in clinical practice, and research to optimize their uptake has yielded mixed results.
Study Objectives:
The investigators will conduct a cluster-randomized trial to evaluate whether the implementation of decision-support into standard clinical practice for ordering CTs will (a) decrease the number of CTs ordered, (b) increase the appropriateness of the CTs that are ordered (e.g. by increasing diagnostic yield but avoiding any missed diagnosis).
Scope:
The scope is to focus on two conditions for which validated decision-support exists: MTBI and PE.
These conditions were selected because internal AHS data shows significant variability (15-90%) in the ordering of CTs for patients presenting with these conditions, and because validated decision-support exists for these conditions (e.g. Canadian CT Head Rule, Well's Score, Pulmonary Embolism Rule-Out Criteria).
The scope includes all hospitals in Alberta with an ED and in-house CT. There are 17 of these hospitals in Alberta from Fort McMurray to Medicine Hat. The investigators have obtained operational approvals to conduct the researchers' study in all 17 hospitals from the Emergency Chief at each site, and from ED and Diagnostic Imaging leadership at the level of each Zone as well as the Province. The scope is limited to patients presenting to the ED.
Methods:
The study design is a cluster randomized trial. In the Calgary Zone, the investigators will randomize half of the investigators' ED physicians to receive decision-support for MTBI, and half to receive decision-support for PE.
Outside of the Calgary Zone, the investigators will randomize by site, so half of sites will receive decision-support for MTBI, and half will receive decision-support for PE. Each half of the randomization will serve as a control for the other group. The reason the investigators are randomizing by physician in the Calgary Zone is because the Computerized Physician Order Entry system in Calgary allows us to implement such a randomization, whereas outside of the Calgary Zone the heterogeneity of order entry systems does not make it feasible to randomize by physician, but it is feasible to randomize by site.
The implementation of decision-support for CT ordering will be mandatory and is supported by operational and clinical leadership. By integrating decision-support into the existing systems to order CTs, a physician (or site) randomized to MTBI or PE decision-support will have to consider those tools prior to ordering a CT. However, decision-support does not make decisions about who receives a CT; it merely provides additional information about how likely a CT is to be diagnostically useful. All decisions regarding diagnostic or therapeutic interventions are the sole responsibility of the physician in consultation with the patient. The primary outcomes measured by this study will be (a) the percentage of MTBI and PE patients receiving a CT scan, and (b) the "appropriateness" of CT scans ordered. This last point can be measured in a variety of ways, such as the percentage of low-risk patients (as defined by decision-support) receiving CT, as well as the diagnostic yield of the CTs that are ordered.
Procedure:
This study will be supported by several strategies including the integration of decision-support into CT ordering procedures in consultation with participating sites. This will also be supported by a voluntary pre-intervention Physician Survey to measure knowledge and attitudes towards CT ordering and decision-support, as well as the perceived barriers to implementing decision-support in their practice. Finally, throughout the intervention physicians and sites will be provided with "audit and feedback" (clinical informatics) on their CT ordering practices in relation to their peers. This feedback will be provided through existing AHS data systems through the Department of Data Integration, Measurement, and Reporting.
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52,058 participants in 2 patient groups
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Daniel W. Grigat
Data sourced from clinicaltrials.gov
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