#MEAction + Mayo Algorithm’s Effect on ME/CFS Care
- #MEAction
- Apr 21
- 3 min read
We have a new research paper out, and it marks an important milestone in a collaboration that set out to improve care for people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The paper is co-first-authored by Jaime Seltzer, Scientific Director at #MEAction, and Dr. Stephanie Grach, an Assistant Professor of Medicine at Mayo Clinic Rochester, and a clinician-researcher specializing in ME/CFS care. They were joined by co-authors Scott Eggers, Melissa Redetzke, Katie J. Mau, Tony Y. Chon, and Ravindra Ganesh.
Through a small grant from the Society to Improve Diagnosis in Medicine (SIDM), #MEAction worked side-by-side with Mayo Clinic clinician-researchers to build practical, point-of-care tools for medical providers. That grant ended up punching far above its weight! Together, we produced:
A Concise Clinical Review of ME/CFS in Mayo Clinic Proceedings (with an attendant CME)
An updated public-facing Mayo Clinic page on ME/CFS
And now, this new paper evaluating what happened after the algorithm went live
The new study asks: was the introduction of this new tool associated with improved diagnostic accuracy of ME/CFS?
What we studied
Clinical algorithms are interactive, step-by-step pathways clinicians can follow while they’re seeing patients. In this case, the ME/CFS care process algorithm lives in Mayo Clinic’s AskMayoExpert, Mayo’s internal knowledge platform that clinicians use for conditions outside their usual specialty.
Our team wanted to understand whether introducing the ME/CFS algorithm was associated with better outcomes in two practical ways:
Did referrals to Mayo Clinic’s ME/CFS specialty clinic increase in a meaningful way?
Were referrals more likely to “match” the specialty clinic’s expert diagnosis of ME/CFS?
In other words: were more people getting to the right place, and were they getting there with a more accurate working diagnosis?
What the study found
This is a study using “real world data”, and a quality improvement study. It compared referral behaviors before and after the AskMayoExpert ME/CFS care process algorithm was made available to providers at Mayo.
It’s important to note that we report an association between introduction of the algorithm and improvements in the outcomes we measured, rather than claiming the algorithm caused these changes.
After the algorithm was introduced, we found that:
Referrals to Mayo Clinic’s ME/CFS Specialty Clinic did increase overall.
Referrals were also more likely to be concordant: referrals more likely to “match” the specialty clinic’s expert diagnosis of ME/CFS.
That pattern is consistent with improved diagnostic accuracy and more appropriate referral to specialty ME/CFS care. These findings were statistically significant (p<0.01) and showed a moderate effect using Cohen’s d. That means the separation between the behaviors of the pre-algorithm and post-algorithm referral groups were practically meaningful, not just statistically significant.
Why this matters for people with ME and for systems
Better diagnostic accuracy can mean:
Less time lost, less money spent by both the patient and the hospital system
Earlier recognition of hallmark features like post-exertional malaise (PEM)
More appropriate management (including pacing, and avoiding recommendations of graded exercise and other potentially harmful management approaches)
More targeted referrals and fewer dead ends
Many people with ME/CFS spend years cycling through appointments, tests, and referrals, losing critical time for supportive treatment and management, leading to preventable harm.
For hospital systems, diagnostic delays can translate into repeat visits, duplicative workups, preventable escalations, and inefficient referral. Point-of-care guidance that helps clinicians recognize ME/CFS sooner can ensure the right care is delivered more rapidly– and doing so with a system-specific care process creates clearer expectations for evaluation and management.
Collaboration done right
This project also reflects what’s possible when advocacy organizations and clinical systems collaborate in good faith. We are deeply grateful to the Mayo Clinic collaborators who invested time, thought, and institutional support into making these tools real, and to everyone who helped translate ME/CFS expertise into something actionable at the point of care.
These positive results could go on to influence other medical systems. The creation and introduction of point-of-care tools, provided they are created with the input of people with lived experience, is a very inexpensive way to improve diagnosis and reduce the cost inherent in a cycle of referrals and unnecessary testing while cutting down on inappropriate advice that may lead to harm.
ME/CFS care has been shaped for far too long by under-recognition, stigma, and outdated assumptions. Building tools that clinicians actually use—tools that reflect what patients experience—requires lived experience leadership at the table from day one. When people with lived experience of ME/CFS have a strong and central role in clinical research, our perspectives change what gets built and what gets prioritized.
Can we review the algorithm without being employees of Mayo?