Katie J. Mau
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Katie J. Mau has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Jaime Seltzer
The Myalgic Encephalomyelitis Action Network, Santa Clara, CA 90403, USA
1 shared publication - Melissa M. Redetzke
Health Education and Content Services, Mayo Clinic, Rochester, MN 55905, USA
1 shared publication - Ravindra Ganesh
Mayo Clinic
1 shared publication - Scott D. Z. Eggers
Department of Neurology, Mayo Clinic, Rochester, MN, USA
1 shared publication - Stephanie L. Grach
Mayo Clinic
1 shared publication - Tony Y. Chon
Advisor to residents and Consultant in General Internal Medicine, Mayo Clinic, Rochester, MN
1 shared publication
Latest Publications
- Open Access
- 3 April 2026
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 23 (4) , 460
Improving Diagnostic Accuracy of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Through a Point-of-Care Clinical Algorithm
Despite the increasing prevalence and median severity of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), medical education on the disease is scant, leading to a diagnostic crisis in which the majority of people with ME/CFS are undiagnosed. We created a care process algorithm in AskMayoExpert accessible to all Mayo Clinic medical providers as a source for information on diagnosis and management of ME/CFS. To evaluate whether the algorithm was associated with improved diagnostic accuracy, we compared concordance before versus after the algorithm was introduced, where concordance was defined as agreement between an appropriately coded referral to Mayo Clinic’s Chronic Fatigue Specialty Clinic and the specialty clinic with an expert diagnosis of ME/CFS. Referrals to the Chronic Fatigue Specialty Clinic increased overall and were more likely to show concordance between specialist diagnosis and referral after the introduction of the ME/CFS AskMayoExpert algorithm. Particularly in diseases that are prevalent and poorly understood, a point-of-care clinical tool may offer just-in-time opportunities to improve diagnosis and management.
- 3 April 2026
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 23 (4) , 460
Open AccessImproving Diagnostic Accuracy of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Through a Point-of-Care Clinical Algorithm
Despite the increasing prevalence and median severity of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), medical education on the disease is scant, leading to a diagnostic crisis in which the majority of people with ME/CFS are undiagnosed. We created a care process algorithm in AskMayoExpert accessible to all Mayo Clinic medical providers as a source for information on diagnosis and management of ME/CFS. To evaluate whether the algorithm was associated with improved diagnostic accuracy, we compared concordance before versus after the algorithm was introduced, where concordance was defined as agreement between an appropriately coded referral to Mayo Clinic’s Chronic Fatigue Specialty Clinic and the specialty clinic with an expert diagnosis of ME/CFS. Referrals to the Chronic Fatigue Specialty Clinic increased overall and were more likely to show concordance between specialist diagnosis and referral after the introduction of the ME/CFS AskMayoExpert algorithm. Particularly in diseases that are prevalent and poorly understood, a point-of-care clinical tool may offer just-in-time opportunities to improve diagnosis and management.