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Updated: Aug 5, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Conducting Screenings and Determining Primary Healthcare Provider Follow-Up for Heart, Muscle, and Brain Health in
Jayme Steig1, Jacob Kieser2, Ryan McGrath2
1Department of Pharmacy Practice, North Dakota State University, Fargo, ND 58102, USA.
Background:
Frequently visited community pharmacies can serve as sites for additional healthcare, including screenings for unknown conditions. Our implementation-oriented pilot study sought to evaluate the proportions of older adults that followed-up with their primary healthcare provider about a positive cardiac arrhythmia, weakness, or cognitive impairment screening performed in a community pharmacy.
Methods:
A cross-sectional design was used and screenings occurred at a well-visited community pharmacy inside a clinic. Possible cardiac arrhythmias were identified with a mobile electrocardiogram. Weakness status was examined with a hydraulic handgrip dynamometer. A paper-and-pencil based cognitive assessment determined cognitive impairment status. Participants screening positive were advised to visit their healthcare provider, and follow-up for determining if such visits occurred was performed approximately 3-months later.
Results:
Of the 106 participants, 51 were referred to their healthcare provider for any positive screening. At follow-up, 12 (23.5%) participants reported visiting their primary healthcare provider about the positive screening performed at the community pharmacy.
Conclusions:
Our implementation-oriented pilot study showed promise for kindling healthcare provider follow-up regarding positive screenings performed at a community pharmacy. Conducting such screenings may reengage patients with their primary healthcare providers when appropriate, and support the identification of unknown conditions.
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