Radiology

Estimated reading time: 3-4 minutes

What if the right radiologist were automatically chosen to read the right case at the right time?

Imagine putting the power of AI algorithms to work for radiologists to address the worklist management burden of their workflow.

Prioritizing cases is a delicate operation for radiologists and administrators. In an ideal scenario, cases would be distributed among the radiology team based on urgency, clinical expertise and prior experience with particular patients.

Radiologists checking patient data on a monitor

At a glance

Challenge

Matching the right case to the right radiologist at the right time in multi-site imaging operations for efficient reading and enhanced patient care.

Solution

Philips Radiology Workflow Orchestrator

Results

Offers providers the ability to better manage the delivery of reports by matching radiologist strengths to the needs of the patient. This helps address both quality standards and volume of work so that service level agreements can be efficiently met.

Case Study

Orchestrating radiology workflow in a large, distributed reading environment

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Knowing exactly which exam to read next can free up radiologist time and attention

In complex, multi-site radiology enterprises, where different locations generate an ongoing stream of imaging cases – some urgent, some less urgent, and some highly specialized – it can be a challenge to manage the prioritization and delegation of cases to the radiologist best suited to read a particular exam, based on expertise or prior history.

64% of radiologists’ time is spent on non-interpretive tasks, according to the American College of Radiology¹

Streamlining workflow is imperative, not only to deliver a high level of patient care, but also to address the very real challenge of radiologist burnout.

Burnout is a concern for radiologists …greater for diagnostic radiologists than all other physicians. Risk factors for burnout include inadequate training, work overload, lack of control, severe time constraints for work output, prolonged stress, introduction of many changes quickly….”²

How do we balance radiologist workload and provide continuity of care?

Intelligent algorithms that automatically determine the best match can help deliver the right case to the right radiologist, based on their area of expertise, availability and current workload, including for academic and research institutions.

The ability to index multiple archives stored on disparate servers to automatically deliver the most urgent studies to the most qualified available radiologists can expedite reading and reporting so that appropriate treatment can be given as quickly as possible. This helps with balancing workload among radiologists, allowing the most relevant cases to be read first by the appropriate available subspecialist. It also helps with continuity of care since, when possible, the case can be routed to the radiologist who has already reviewed the prior exams for a given patient.

Meeting the increased demand for imaging

Addressing the imaging backlog caused by the COVID-19 pandemic will increase the number of studies that must be read. Prioritizing those studies is essential.

For example, when a patient with a sudden and acute headache is rushed into the emergency department, the CT scan demands immediate attention. AI algorithms* can detect an intracranial hemorrhage, which triggers the worklist to prioritize the case.

A smart worklist will move the exam to the top of the worklist for the most appropriate neuroradiologist. While the patient is still in the scanner, the radiologist reading the image can remotely connect to another specialist using native chat and screen-sharing to discuss the case in a secure digital environment.

A head of radiology has this to say about Radiology Workflow Orchestrator:

The radiologist is not only an ‘interpreter’ of images, but also a consultant for clinical activity. Freeing up useful and precious time for the radiologist means you can not only double the number of exams to be reported, but more and more allows radiologists to grow and also improve their professional life …. allowing for space and time with multidisciplinary teams; the role of the radiologist will be fundamental.”

How Philips can support you

Philips Radiology Workflow Orchestrator

Offers the ability to index multiple archives stored on disparate servers to automatically deliver the most urgent studies to the most relevant radiologists.

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See the Philips Radiology Workflow Orchestrator in action.

Demonstration of Philips Radiology Workflow Orchestrator for diagnostic image reading

Philips Radiology Workflow Orchestrator brochure for diagnostic image reading

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Interested in learning more about how this solution can help address your workflow orchestration challenges?

Download the brochure (2.24MB)

*Philips Radiology Workflow Orchestrator can be connected to external AI algorithms in order to prioritize worklists. Workflow Orchestrator itself has no AI internal algorithms.

Results presented are for illustrative purposes only and are not predictive of actual results for your business.

¹ Dhanoa D, Dhesi T, Burton D, Nicolaou S, Liang T. The evolving role of the radiologist: the Vancouver Workload Utilization Evaluation Study. 2013;10(10):764-769. DOI: doi.org/10.1016/j.jacr.2013.04.001.

² Harolds J, et al. Burnout of radiologists: frequency, risk factors, and remedies: a report of the ACR commission on human resources. JACR. 2016;13(4):411-416. DOI: 10.1016/j.jacr.2015.11.003.

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At a glance

Challenge
Matching the right case to the right radiologist at the right time in multi-site imaging operations for efficient reading and enhanced patient care.

Solution

Philips Radiology Workflow Orchestrator

Results
Offers providers the ability to better manage the delivery of reports by matching radiologist strengths to the needs of the patient. This helps address both quality standards and volume of work so that service level agreements can be efficiently met.

Case Study

Orchestrating radiology workflow in a large, distributed reading environment

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