Burnout is a global health problem affecting physicians across all medical specialties. Radiologists in particular experience high rates of burnout and this trend is continuing to worsen. Case In point, according to Medscape's 2019 National Physicians Burnout & Depression Report, 54% of radiologists Indicated they felt burned out or depressed.[1]
Numerous studies have reported that increasing workload is one of the leading sources of job-related stress leading to burnout.2-6 In radiology, workloads have steadily increased over the last 20 years due to the increased utilization of imaging, the growing complexity of exams with much larger sets of data to analyze, and an overall increase in the number of imaging studies read.
"This is probably why many Imaging leaders indicate one of their top priorities is to assist their radiologists in dealing with this growing volume and complexity of exams by continually ensuring they have the latest productivity tools," explains Pete Eggleston, Director, Global Product Marketing at GE Healthcare Digital. However, it was also interesting to note that another top cause of burnout cited In the Medscape study was “increasing computerization of practice." The reason being is that learning new software can be in itself time-consuming and frustrating. In fact, over half of the institutions report being flat-out terrible at getting personnel to train and adopt.7 Thus, in attempting to alleviate radiologist burnout, adding more productivity tools may actually be adding to their burnout level!
Therefore, Eggleston notes that caution is needed when deploying new software-based productivity tools. In the case of Artificial Intelligence (AI) based clinical applications, this may be even more relevant given the large and rapidly growing number of third-party applications flooding into the market to assist radiologists with triaging and reading exams. When deployed In the PACS (Picture Archiving and Communication System), these AI-based applications have the promise to act as intelligent assistants to assist radiologists in increasing their productivity. But implemented incorrectly, this very technology that promises to assist them can Itself cause an increase in cognitive workload, thus further contributing to burn out.
To combat this, what is needed, according to Eggleston, are ways to effectively orchestrate the application of these new assistive technologies in the radiology reading workflows, in a seamless and uniform fashion, thus reducing effort and cognitive overload. It needs to be done in a way that reduces clicks and the number of UX interactions rather than adding to them and not requiring new applications or workflows to be learned. Technology should work with us, not against us.
This is the reason why GE Healthcare is leveraging its extensive global industry partnerships and integration expertise to provide a single vendor contact for implementing AI-based clinical applications into PACS and reading workflows. Our goal is to enable quick deployment of new applications, easy configuration of workflows and parameters, and the ability to easily experiment, measure and optimize results. This will also allow our team of workflow and application specialists to work with imaging organizations to ensure they maximize their investment in new applications through an understanding of not just their current workflows, but also to re-map their workflows in support of achieving their organizational KPIs.
“The challenge is real. Today’s organizations must balance the ongoing challenges of personnel issues such as burn out with IT and operational issues such as a growing complexity and volume of their work and tools,” according to Eggleston. By leveraging AI-based applications with an understanding of how to do so, and with proper tools to seamlessly incorporate these applications into existing workflows, we are working with healthcare organizations to orchestrate the radiology reading workflows of the future. The end result will be to provide a new, integrated, and unified user experience to help empower radiologists with the right information at the right time to guide diagnosis and speed of treatment. This can, in turn, elevate patient care as well as the satisfaction level of clinicians.
- Medscape National Physician Burnout, Depression & Suicide Report 2019, Leslie Kane, MA, January 16, 2019
- Magnavita N, Fileni A, Magnavita G, et al. Work stress in radiologists. A pilot study. Radiology Med. 2008; 113:329–346.
- Graham J, Ramirez AJ, Field S, et al. Job stress and satisfaction among clinical radiologists. Clin Radiology 2000; 55:182–185
- Chew FS, Mulcahy MJ, Porrino JA, et al. Prevalence of burnout among musculoskeletal radiologists. Skeletal Radiology 2017; 46:497–506.
- Harolds JA, Parikh JR, Bluth EI, et al. Burnout of radiologists: frequency, risk factors, and remedies: a report of the ACR commission on human resources. J Am Coll Radiology 2016; 13:411–416.
- Nicola R, McNeeley MF, Bhargava P. Burnout in radiology. Current Problems in Diagnostic Radiology, 2015; 44:389–390.
- Brian P. Watson, The State of Enterprise Software Adoption, CIO Insight, October 21, 2009.
