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Updated: Dec 20, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Development of a screening tool to identify patients likely to benefit from clinical pharmacist review in a
Objective:
To create a novel screening tool that identified patients who were most likely to benefit from pharmacist in-home medication reviews.
Design:
Single-center, retrospective study.
Setting And Participants:
A total of 25 homebound patients in Forsyth County, NC, aged 60 years or older with physical or cognitive impairments and enrolled in home-based primary care or transitional and supportive care programs participated in the study. Pharmacy resident-provider pairs conducted home visits for all patients in the study. Pharmacy residents assessed the subjective risk (high, medium, low) of medication nonadherence using information obtained from home visits (health literacy, support network, medications, and detection of something unexpected related to medications). An electronic medical record-based risk score was simultaneously calculated using screening tool components (i.e., electronic frailty index score, LACE+ index [length of stay in the hospital, acuity of admission, comorbidity, emergency department utilization in the 6 months before admission], and 2015 American Geriatric Society Beers Criteria).
Outcome Measures:
The electronic medical record-based screening tool numerical risk scores were compared with pharmacy resident subjective risk assessments using tree-based classification models to determine screening tool components that best predicted pharmacy residents' subjective assessment of patients' likelihood of benefit from in-home pharmacist medication review. Following the study, satisfaction surveys were given to providers and pharmacy residents.
Results:
The best predictor of high-risk patients was an electronic frailty index score greater than 0.32 (indicating very frail) or LACE+ index greater than or equal to 59 (at high risk for hospital readmission). Pharmacy residents and providers agreed that homebound patients at high-risk for medication noncompliance benefited from pharmacist time and attention in home visits.
Conclusion:
In homebound older persons, this screening tool allowed for the identification of patients at high-risk for medication nonadherence through targeted in-home pharmacist medication reviews. Further studies are needed to validate the accuracy of this tool internally and externally.
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