Multiple morbidity is increasing, especially in elderly people, with a corresponding increase in polypharmacy and inappropriate prescriptions. According to different evaluations, between 25 and 75% of patients aged 75 or older are exposed to 5 or more drugs. There is increasing evidence that polypharmacy can cause more harm than good, especially in elderly people, due to factors such as drug-drug and drug-disease interactions. Many strategies were proposed to reduce polypharmacy and inappropriate prescribing, but there is little evidence to show benefit. There is an urgent need to implement effective strategies. The application methodology must be simple so that it does not fail in daily practice. For the current plan, an electronic medical record, named "DrApp", will be used, which will include a drug interaction program, (Interax-AI), which will automatically indicate the medication prescriptions that involve a risk for the patient. All outpatient indications followed by physicians using the DrApp electronic history will be registered. The indications will be compared in the 4 months prior to the incorporation of the Interax-AI program with the 4 months after the incorporation of the program. Between both stages a period of 2 weeks will be established in which the data will not be recorded. The minimum \& maximum number of patients that will be included in each stage are 100 \& 200. The primary end point is to compare the total number of indications per inpatient, before the availability of the Interax-AI program and after the application of this program. The objective is to evaluate if the computer program of detection of drug interactions allows to limit the polypharmacy in outpatients.
Multiple morbidity is increasing, especially in elderly people, with a corresponding increase in polypharmacy and inappropriate prescriptions. According to different evaluations, between 25 and 75% of patients aged 75 or older are exposed to 5 or more drugs. There is increasing evidence that polypharmacy can cause more harm than good, especially in elderly people, due to factors such as drug-drug and drug-disease interactions. Many strategies were proposed to reduce polypharmacy and inappropriate prescribing, but there is little evidence to show benefit. There is an urgent need to implement effective strategies. The application methodology must be simple so that it does not fail in daily practice. For the current plan, an electronic medical record, named "DrApp", will be used, which will include a drug interaction program, (Interax-AI), which will automatically indicate the medication prescriptions that involve a risk for the patient. All outpatient indications followed by physicians using the DrApp electronic history will be registered. The indications will be compared in the 4 months prior to the incorporation of the Interax-AI program with the 4 months after the incorporation of the program. Between both stages a period of 2 weeks will be established in which the data will not be recorded. The minimum \& maximum number of patients that will be included in each stage are 100 \& 200. The primary end point is to compare the total number of indications per inpatient, before the availability of the Interax-AI program and after the application of this program. The objective is to evaluate if the computer program of detection of drug interactions allows to limit the polypharmacy in outpatients.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
PREVENTION
Masking
QUADRUPLE
Enrollment
200
Interax-AI is a drug interactions detection module for the electronic clinical history software DrApp
Hospital de Clínicas José de San Martín
Buenos Aires, Buenos Aires F.D., Argentina
Centro de Vigilancia y Seguridad de Medicamentos
Ciudad Autonoma de Buenos Aire, Buenos Aires F.D., Argentina
Instituto de Investigaciones Cardiológicas Prof. Dr. Alberto C. Taquini
Ciudad Autonoma de Buenos Aire, Buenos Aires F.D., Argentina
Prevalence of polypharmacy cases detected in outpatients of outpatient clinics of doctors using the electronic medical record application DrApp
Through the electronic medical record called DrApp, the quantity of medicines prescribed to each patient is quantified and used for calculation of polypharmacy prevalence in tha basal period (pre-introduction of Interax-AI) and late period (Post introduction of Interax-AI).
Time frame: 1 year
Interax-AI associated change in the number of total prescribed drug per patient
Change in total prescribed drug per patient will be calculated as the differene between basal total prescribed drug per patient (Pre-Interax-AI) minus resulting total prescribed drug per patient (Post-Interax-AI)
Time frame: 1 year
Number of total drug interactions per patient and subclassification by severity (in post-Interax-AI period).
The addition of the application called Interax-AI, will allow detecting the presence of drug interactions and their severity in the second phase. These will be reported as the total number of interactions reported per patient, and subclassificated into number of mild (no need to take action), moderate (require patient monitoring), and severe (possible contraindication) interactions detected per patient.
Time frame: 1 year
Difference between Number of total drug interactions per patient in the local environment with those reported in the literature at the international level.
The difference will be calculated as the number of total drug interactions per patient minus the value (number of drug interaction per patient) reported in the bibliography at international level in similar populations.
Time frame: 1 year
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