Related Experiment Video
Updated: Jun 25, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A pilot study testing a medication algorithm to reduce polypharmacy
L A Mistler1, T A Mellman, R E Drake
1Department of Psychiatry, Dartmouth Medical School, Hanover, New Hampshire, USA. lisa.a.mistler@dartmouth.edu
Background:
Polypharmacy is common in the treatment of persons with severe mental illness, yet it is not an evidence-based practice. To address this, an attempt was made to reduce medications for patients already receiving polypharmacy during an episode of acute psychiatric hospitalization.
Methods:
A medication-reduction algorithm was developed , based on the best available evidence regarding indications for and efficacy of medications and principles of collaborative care. A feasibility pilot study was conducted using a matched case-control design for 12 patients treated with the algorithm and 12 patients treated as usual.
Results:
The intervention patients were discharged on significantly fewer medications than controls; symptom reduction and length of stay did not differ significantly.
Conclusion:
A collaborative approach to reducing polypharmacy may reverse the trend to add medications during hospitalization.
Related Concept Videos
Drug Dosing: Geriatric Patients
Drug Therapy
Antianxiety Medications
Pharmacokinetic–Pharmacodynamic Relationship: Problems
Dosage Regimens: Designs and Approaches
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
Pharmaceutical Poisoning: Potential Scenarios