We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The risks of polypharmacy can be far greater than the benefits, especially in the elderly. Comorbidity makes polypharmacy very prevalent in this population; thus, increasing the occurrence of adverse effects. To solve this problem, the most common strategy is to use lists of potentially inappropriate medications. However, this strategy is time consuming.
Methods:
In order to minimize the expenditure of time, our group devised a pilot computer tool (Polimedication) that automatically processes lists of medication providing the corresponding Screening Tool of Older Persons’ potentially inappropriate Prescriptions alerts and facilitating standardized reports. The drug lists for 115 residents in Santa Marta Nursing Home (Fundación San Rosendo, Ourense, Spain) were processed.
Results:
The program detected 10.04 alerts/patient, of which 74.29% were not repeated. After reviewing these alerts, 12.12% of the total (1.30 alerts/patient) were considered relevant. The largest number of alerts (41.48%) involved neuroleptic drugs. Finally, the patient's family physician or psychiatrist accepted the alert and made medication changes in 62.86% of the relevant alerts. The largest number of changes (38.64%) also involved neuroleptic drugs. The mean time spent in the generation and review of the warnings was 6.26 minute/patient. Total changes represented a saving of 32.77 € per resident/year in medication.
Conclusions:
The application of Polimedication tool detected a high proportion of potentially inappropriate prescriptions in institutionalized elderly patients. The use of the computerized tool achieved significant savings in pharmaceutical expenditure, as well as a reduction in the time taken for medication review.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.