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A Guide to Boosting Reporting Productivity in 2021

There are many contributing factors to widespread burnout, but several studies have labeled rising imaging volumes and greater turnaround expectations as leading causes.1

There is a single-word solution to this and that is—Automation.

Ok, I lied.  That by itself is not the answer.  The real answer is “Smart Automation.”  That is to say, automation that is meaningful, simple, and reliable.    More specifically, smart automation is automation that… 

  1. has impact
  2. is easy to execute without upheaving the whole workflow
  3. won’t need the help of tech support every other week.

Luckily, it’s 2021, and there are many great examples of smart automation that are being used to increase reporting productivity. In fact, if automation is done right, it not only increases productivity, but also eliminate stressors and gives the team more time to provide quality care.

Here are 7 examples of smart automation that will meaningfully increase RVUs and decrease report turnaround time without increasing feelings of burnout.


1.  Automatic Caseload Assignment & Workflow Orchestration

Let’s talk about what happens before the radiologist even opens an exam.

The radiologist comes in, sits down and they are ready to read some exams, but when they log in they see this…

Having to sift through 50+ exams to find the specific exam you are supposed to be reading wastes time.  Normally what practices will do to mitigate this is to display certain types of exams for a particular radiologist.  As a result, the radiologist is served with a list like this instead…

Q/ris 3000,radiology workflow,automation,streamline,efficiency,save time,improve patient care,structured reporting,DICOM SR,CDS,peer learning,CTR management,automatic workload assignment,imaging workflow,virtual check-in,patient registration,exam ordering,scheduling,automated tech workflow,dose,supply,auto-capture

The downside to this method is that it can be time-consuming to curate these lists and the number of lists can start to balloon as new sorting criteria and filters accumulate over time.

The more effective and efficient method is automatic caseload assignment.

An “assignment engine” continuously checks the pending exams and automatically matches them up with reading radiologists based on priority, availability, specialty, credentials, and other customized parameters.

What’s more, an assignment engine can also update the priority of an exam based on the preliminary findings of a diagnostic AI.

Now, instead of doctors spending valuable time trying to figure out which study they should read, they are served the correct exam at the right time, every time.  Automating this process can lower stress, raise confidence, and easily save your imaging team 30 minutes per day.

 

2. DICOM SR and Multi-Layered Macros

DICOM structured reporting is not new, but it is essential to the radiologist in order to efficiently create reports.  Radiologists can easily save 1-2 minutes (or more) per exam just by having DICOM SR data prepopulated in the report when they begin to dictate.

As a little side note, if you are making use of medQ’s Q/ris Tech Workflow, DICOM SR data is automatically captured from the modality during the imaging procedure.  The Technologist can then validate the data before it is prepopulated for the radiologist.

As a little side note, if you are making use of medQ’s Q/ris Tech Workflow, DICOM SR data is automatically captured from the modality during the imaging procedure. The Technologist can then validate the data before it is prepopulated for the radiologist.

Macro templates have also been around for a while, however, the macros you should be looking for are multi-layered or “nested” macros.  Nested macros, like the ones available in medQ’s Reporting PLUS+ allows the radiologist not only to quickly format their report but also populate that report using only a few keywords and phrases.  Let’s observe what that looks like.

The doctor opens the exam and selects the appropriate macro template.  Now we see that the report is not only formatted but also an additional dialogue box has opened allowing the radiologist to insert entire sentences to the different parts of the report and with simple, single-word prompts.

Each of these macros can be easily customized to fit the dictation style of each individual doctor.

Using customizable nested macros can also make it much easier to include patient-friendly terminology in your reports.  One can simply preprogram the macro responses to always include extra explanatory phrases and simplified language in addition to the standard diagnostic terminology.

Radiologist Vocal Input: Pre-Coded Macro Response:
"[Usual Keyword or Phrase]"
"[Diagnostic Terminology] + [Patient Friendly Explanation]"

Using nested macros in this way, radiologists join the growing movement of providing easy-to-read reports while continuing to dictate in the way that’s most comfortable for them.

Seen in this light, it is easy to see that thoughtfully programmed nested macro sequences can save radiologists 3-5 minutes per patient while vastly improving the patient experience.

 

3. Integrate your Diagnostic AI with your reporting solution

Diagnostic AI has been among the most exciting innovations to come to radiology in recent years.  For the most part, these AI algorithms have been limited in their capacity to affect the productivity of the radiologist beyond the initial interpretation.

A solution like medQ’s AI Navigator allows radiologists to drop AI-generated findings directly onto a final report by establishing a connection between the reporting solution and the diagnostic AI program.

When selecting an exam to read, a visual indicator lets the radiologist know that there are relevant AI findings to review.  The radiologist can then navigate quickly through the various findings, select the ones they would like to include, and with a simple click, add them to the report.

Productivity gains would obviously be dependent on how frequently your team uses diagnostic AI, but it’s easy to see how an AI-integrated reporting workflow can help radiologists provide a more data-rich report while saving 3-5 minutes per patient by not having to re-dictate or retype AI-generated findings.

5. Use a Customizable Reporting Quality Checker

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With every workflow step and manual process, comes an opportunity that some tiny detail will get mistyped, or misread.  In imaging, the consequences for such minor errors can result in significant patient morbidity—especially when surgery is involved.

The medQ Quality Checker can help lower your error rate by automatically checking reports as they are dictated for basic discrepancies regarding laterality, gender, and many other customizable criteria.

For example, if as a part of your group’s peer learning discussion, it was determined that your doctors were making a particular mistake, or that there was certain terminology used in reports that is difficult for the patients to understand, the quality checker could be used to check for and highlight those issues before the report is finalized.

Used this way, medQ’s Quality Checker doubles as a training and improvement tool while also saving your team time due to a declining need for rigorous, manual proofreading.

6. Integrating and Streamlining Peer Learning/Review

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Even though radiologists are being called upon to create more reports per hour than ever, peer review requirements have not lessened in the slightest.

Under such pressure, it’s understandable that peer review can sometimes be seen as a burden and met with something less than enthusiasm.

To mitigate these feelings and more effectively achieve your desired improvement outcomes, it is important to streamline and integrate the peer review process to the point where it becomes a natural, non-interruptive part of the reporting workflow.

As an example, medQ’s Peer Review program is integrated directly into the Reporting PLUS+ platform, automatically selects cases for the review pool, and makes it easy for doctors to both identify relevant priors and review cases when it’s most convenient.  medQ’s Peer Review can also be configured to submit cases to Radnet automatically.

By making peer review a natural part of the workflow and by automating the case selection and submission process, practices can save 2-8 hours a month depending on your exam volume.

7. Automating your Critical Findings Protocol

Closing the communication loop for critical findings has proved a challenge for imaging teams for decades.  Even though technology has improved, it has remained a challenge because everyone’s schedule has gotten that much busier.

That being said, there is a solid way to save about 15 minutes per critical finding while also closing more communication loops. That methodology is integrating a semi-automated critical finding communication protocol directly into your reporting solution.

Using medQ’s Q/ris Critical Test Result Management system (Q/ris CTRM), and before even finishing the report, a radiologist can open the CTRM tab, create a critical finding notification, and assign follow-up responsibility in just a few clicks.  If a case needs to be communicated directly, the referring physician’s contact information will also be listed.

Here is where the automation kicks in.  Immediately after closing the CTRM tab, the system automatically sends a text alert to the referring physician, notifies an administrator for follow-up, logs the critical test results in the patients’ file, and notes your communication attempts on the final report.

All this, and the radiologist never had to leave the reporting solution or even the exam they were working on.

By integrating a streamlined critical findings workflow into the reporting solution itself, and by automating several of the communication and follow-up tasks, the radiologist is closing more communication loops while also saving themselves up to 15 minutes per critical test result.

 

Total Productivity Gains

There are several ways that an imaging team can significantly boost their reporting productivity.  Let’s take a look at a quick breakdown.

Automating the radiologist caseload selection process with an assignment engine speeds up the process of getting the right exam to the right doctor and can save the team 30 minutes per day or 15 hours per month.

Automatically prepopulating DICOM SR data onto the final report saves a practiced radiologist 2 minutes per patient.

Using multi-layer nested macros to not only format a report, but also populate the entire report using a few single-word prompts and phrases can save 3-5 minutes per patient.

Dropping AI-generated findings onto final reports (instead of re-typing or dictating them) can save radiologists 3-5 minutes per patient.

Using a customizable quality checker while your doctors dictate can save you from exhaustive proof reading.

By integrating a streamlined peer review program to automate the case selection and submission process, you can save your team anywhere from 2-8 hours per month, depending on your volume.

By automating your critical findings protocol with something like the Q/ris CTRM you could save your team 15 minutes per critical finding.  However, seeing as incidental findings can be found in anywhere from 5% to 33% of exams (depending on the procedure)2 for the sake of this exercise we’re going to round that down to 2 minutes per patient.

Feature Potential Time Savings
Automated Caseload Assignment
30 min/day (approx. 15 hrs/month)
Automated DICOM SR
2 min/patient
Multi-layered Nested Macros
3–5 min/patient
Drop AI-generated Findings onto Reports
3–5 min/patient
Integrating Streamlined Peer Review
2–8 hrs/month
Automating Critical Finding Processes

15 min/incidental finding
(works out to about 2 min/patient) 2

Total

10–14 min/patient + 17–23 hrs/month

That brings us to an estimated grand total of 10–14 minutes per patient plus 17-23 hours per month of time saved for your imaging team.  To calculate that using FTEs, let’s once again take a generic practice that is open 6 days a week, 8 hours a day, and sees 50 patients a day.

At 50 patients a day you would be saving your team approximately 1.35–1.88 FTEs.

Factoring in the average salary of a radiologist (which was over $400,000 in 2020)3 and a radiology admin staff (which was over $40,000 in 2020) and it’s easy to see how an investment of this nature pays for itself very quickly.  

Obviously, the actual results will vary depending on your team’s personnel, volume, and tech stack, but we can clearly see that applying a few of these methodologies can yield immensely valuable productivity gains for your team.

If you want to know how these numbers would stack up for your team, one of medQ’s workflow automation specialists would be happy to calculate your team’s specific time savings.  

Next Steps?

We get it. Making process changes isn’t easy; however,  if you are looking for a single solution that provides all of these automation tools, productivity gains, and more, then please take a look at medQ’s Reporting PLUS+™.  We save 100s of teams 1000s of hours every year by automating their imaging workflows, and we would love to do the same for your team.

So, schedule a demo or get a free productivity potential analysis from one of our specialists and see if the numbers add up for yourself.

(An analysis can be as short as 15 minutes)

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Sources:

[1] Chetlen, A., Chan, T., Ballard, D., Frigini, L., Hildebrand, A., & Kim, S. et al. (2019). Addressing Burnout in Radiologists. Academic Radiology26(4), 526-533. doi: 10.1016/j.acra.2018.07.001

[2] O’Sullivan, J., Muntinga, T., Grigg, S., & Ioannidis, J. (2018). Prevalence and outcomes of incidental imaging findings: umbrella review. BMJ, k2387. doi: 10.1136/bmj.k2387

[3] Collins, J. (2021). Radiologist $alary Update 2020: Show Me The Money! – The Reading Room. Retrieved 28 June 2021, from https://thereadingroom.mrionline.com/2020/11/radiologist-alary-update-2020-show-me-the-money