Reports From the Field

Using Clinical Decision Support to Reduce Inappropriate Imaging: A Health Care Improvement Case Study


 

References

From the Office of Science Policy and Communications, National Institute on Drug Abuse, National Institutes of Health, Rockville, MD, and George Washington University, Washington, DC (Dr. Jones), Office of the National Coordinator for Health Information Technology, US Department of Health and Human Services, Washington, DC (Mr. Swain), and Banner Health, Phoenix, AZ (Ms. Burdick).

Abstract

  • Objective: Clinical decision support (CDS) can be a useful tool to decrease inappropriate imaging by providing evidence-based information to clinicians at the point of care. The objective of this case study is to highlight lessons from a health care improvement initiative using CDS to encourage use of ultrasound rather than computed tomography (CT) scans as an initial diagnostic tool for suspected appendicitis in pediatric patients.
  • Methods: The percentage of suspected pediatric appendicitis cases receiving ultrasounds and CT scans was calculated using electronic health record data. Four steps for implementing health information technology were identified in a literature scan that guided data collection and analysis: planning, software customization and workflow design, training and user support, and optimization.
  • Results: During the fourth quarter of 2010, 1 in 7 pediatric patients with suspected appendicitis received an ultrasound and almost half received a CT scan. By the first quarter of 2012, ultrasounds were performed in 40.8% of these cases and the use of CT scans declined to 39.9% of suspected pediatric appendicitis cases.
  • Conclusion: Four lessons emerged. First, all levels of staff should be involved in the planning process to make organizational priorities actionable and build buy-in for each healthcare improvement initiative. Second, it takes time to design and test the alert to ensure that clinical guidelines are being properly applied. Third, re-engineering the workflow is critical for usability; in this case, ensuring the availability of ultrasound staff was particularly important. Finally, the effectiveness of CDS depends on applying relevant evidence-based practice guidelines to real-time patient data.

Diagnostic imaging is a useful tool for identifying and guiding the treatment of many health conditions, but evidence indicates that health care providers do not always use imaging appropriately. In fact, a substantial proportion of diagnostic imaging procedures performed in hospital and ambulatory settings are not supported by clinical guideline recommendations [1,2]. Spending on diagnostic imaging is rapidly increasing, and some patients receive unnecessary radiation exposure that can lead to adverse health impacts [3]. Inappropriate imaging falls into 3 broad categories: imaging that does not conform to clinical guidelines, imaging that is contraindicated due to an allergy or implantable medical device, and imaging that might be clinically indicated but is duplicative of prior imaging services.

Clinical decision support (CDS) functionality supports health care improvement initiatives to narrow the gap between evidence-based practices and routine care [4]. CDS merges patient-specific clinical information with relevant information about evidence-based practices, providing health care providers with timely information to guide decisions at the point of care [5]. Decision support is most commonly delivered in the form of alerts and reminders [6]. CDS can be effective in reducing adverse drug events [7], sepsis [8,9], and other conditions in hospital [10–12] and ambulatory settings [13,14].

For the evaluation of suspected appendicitis in children, ultrasound is the preferred initial consideration for imaging examination [15]. Evidence suggests that CDS can increase the use of ultrasound for suspected pediatric appendicitis [16,17] and has affirmed the utility of ultrasound as a first-line diagnostic tool for suspected appendicitis [18,19]. In the Choosing Wisely campaign, the American College of Surgeons and the American College of Radiology have both endorsed ultrasound as an option to consider prior to conducting a CT scan to evaluate suspected appendicitis in children [15].

Banner Health, a large health system headquartered in Phoenix, Arizona, implemented a health care improvement initiative using CDS functionality to encourage providers to use ultrasound instead of CT as a first-line diagnostic tool for suspected pediatric appendicitis. We conducted a site visit to Banner Health, an organization who had had attained a high score on the EMR Adoption Model [20] to examine their implementation process. We sought to build on previous research examining the use of health information technology to improve performance in large health systems [21–23].

Methods

Setting

Banner Health is a large not-for-profit health system that is comprised of 24 acute care hospitals across several states, as well as ambulatory medical practices, behavioral health, home care, and ambulatory surgery centers [24,25]. The health system is the largest employer in Arizona and one of the largest in the United States with over 50,000 employees. Banner Health has been nationally recognized for clinical quality [26], an innovative leadership team [27], and using health IT to improve quality [20]. The health system was also selected as one of the Centers for Medicare & Medicaid Services (CMS) Pioneer Accountable Care Organizations.

Site Visit

The first 2 authors conducted a 2-day site visit to the Banner Health headquarters in Phoenix, Arizona in November 2013. The team conducted discussions with over 20 individuals, including health system leadership, frontline clinicians in several units of an acute care hospital, staff members in 2 telehealth hubs—including a tele-ICU hub—and trainers in a simulation facility that is used for staff training. The discussions were conducted with groups of staff or on an individual basis, as appropriate. At the outset of the project, an environmental scan of relevant grey and peer-reviewed literature was conducted under contract on behalf of the authors to guide data collection and analysis [28]. An interview protocol was created to guide the discussions. The protocol contained modules that were used during each discussion, if relevant. The modules addressed topics such as technical issues with designing and deploying health information technology functionalities such as clinical decision support systems, the organizational processes and structures needed to launch health care improvement initiatives, and using health information technology care coordination. Within each module, questions probed about the challenges that arose and the solutions to these challenges, with a focus on the four phases of implementing a health information technology intervention: functionality planning, software customization and workflow design, training and user support, and optimization. To assist with interpreting the qualitative findings, an evolving outline of the findings was maintained. Salient themes and conceptual categories were tracked, which helped the researchers organize, synthesize, and interpret the information collected during the site visit. Once the authors chose to focus on clinical decision support, summary notes from the discussions were reviewed for relevant information, and this information was compiled and organized under the rubric of the four implementation phases. The findings and key themes from the discussion notes were distilled into key lessons for the field.

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