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Updated: Jul 25, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Pharmacist comprehensive review of fall-risk-increasing drugs and polypharmacy in elderly Spanish community patients
Silvia González-Munguía1,2, Obdulia Munguía-López3, Esther Sánchez Sánchez3
1Hospital Universitario Nuestra Señora de la Candelaria. Servicio de Farmacia. Carretera General del Rosario, 145 Santa Cruz de Tenerife, 38010 Tenerife, Spain.
Objective:
The aim of this study is to identify and analyze adults aged ≥65 years living in the Canary Islands, Spain, who are prescribed medications that increase the risk of falls and are polymedicated. To do so we have made use of the electronic prescription and the RStudio®.
Method:
For the detection of Fall-Risk-Increasing Drugs (FRIDs), outpatient electronic prescription dispensing data were used in two pharmacies. A total of 118,890 dispensations grouped into 15,601 treatment plans for 2,312 patients were analyzed. The FRIDs analyzed were antipsychotics (APSI), benzodiazepines (BZPN), antidepressants (DEPR), opioids (OPIO) and Z-hypnotics (ZHIP). For the development of the algorithms for the construction of tables and data screening, the statistical programming language RStudio® was used.
Results:
Of the total number of patients and prescriptions analyzed, 46.6% were polymedicated and 44.3% had prescribed an FRID. 28.7% of the patients presented both factors, had a dispensation from an FRID and were polymedicated. Of the 14,278 dispensations with FRID, 49% had a benzodiazepine, 22.7% opioids, 18% antidepressants, 5.6% hypnotics, and finally 4.4% antipsychotics. At least 32% of the patients had been dispensed a benzodiazepine together with another FRID and 23% an opioid together with another FRID.
Conclusions:
The method of analysis developed and applied in RStudio® allows to detect and determine in a simple and fast way polymedicated patients, as well as the number and therapeutic class of drugs in their treatment plan and identify prescriptions that can increase the risk of falls. Our results show a high number of prescriptions for benzodiazepines and opioids.
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