Article

The value of effective worklist prioritization in Radiology

Diagnostic radiology is a dynamic and changing landscape. Emergency Departments are now more crowded than ever, with the use of diagnostic imaging growing at an exponential rate. Here we’ll outline the current landscape and share steps you can take to efficiently manage workloads without compromising quality and patient care.

Increased Volume & Workload

Imaging volume from 1999 to 2010 grew 10x, while the number of radiologists remained largely the same. The radiologist’s workload has increased significantly, where the average number of images interpreted have increased from 2.9 to 10.1 per minute.

Imaging volume is increasing due to increased demand from both providers and patients. In a recent study of Emergency Medicine Physicians, 97% admitted to ordering medically unnecessary CT or MRI scans. An aging patient population, increased health insurance coverage, and the practice of defensive medicine, are expected to contribute to even greater image volume in the years to come.

Increased Complexity

Many medical facilities operate on a “first in, first out” workflow (with certain exceptions) and there is risk here that time sensitive diagnoses will be delayed when internal processes hit their edge cases. These processes are especially strained when there are multiple geographically-distributed institutions contributing to a single worklist. We’ve seen that COVID-19 has amplified the trend of remote readings, and we expect to see this continue.

What Does This Mean?

  • As study volume increases, worklists grow, and emergent cases may sit idle.
  • Internal processes are likely to require more manual intervention due to the increasing dispersion of imaging centers and radiologists.
  • Communication between sites/departments are prone to be delayed, leading to errors and misdiagnoses.

What Can Be Done?

A key starting point is to assess and audit key metrics within your department or practice now to establish a baseline.

What are the discrete steps that take place within your end-to-end workflow? 

How long do studies sit in different portions of your radiology workflow? Here, you can understand where your “long-tail” comes from and where the most impact (for efficiency and error reduction) can be made. 

How do you assign priorities to studies in the worklist currently?

Have there been misdiagnoses, miscommunications, or other adverse events? Relate this back to your long-tail assessment to assess the impact of addressing these particular situations.

RadiLens can help

We’ve developed a behind-the-scenes process to audit and develop a baseline related to prioritization and workflow efficiency. Reach out to us below to learn more. We’ve also built a machine learning model to automate the prioritization of a Radiology worklist – you can download our White Paper here:

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