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Development and Implementation of the Hdc.DrApp.la and SIMDA Programs to Reduce Polypharmacy and Drug-drug
Ricardo Enrique Barcia1,2, Guillermo Alberto Keller3, Francisco Azzato1
1Facultad de Medicina, Universidad de Buenos Aires, Hospital de Cliìnicas "Joseì de San Martiìn", 6o Caìtedra de Medicina Interna, Argentina.
Objectives:
We evaluated polypharmacy and possible drug-drug interactions (p-DDIs) in hospitalized patients before and after using the SIMDA Computerized Medical Decision Support System (CMDSS).
Materials And Methods:
We included the prescriptions of ≥ 18 years hospitalized patients in the internal medicine department. We developed and implemented the Hdc.DrApp Physician Order Entry System and the CMDSS SIMDA, which detects p-DDIs and signals dosage adjustment based on renal function. To evaluate the impact of the CMDSS, we made a comparison Before (Survey) / After (Intervention): Survey between Oct/22/2019, and Mar/21/2020, and Intervention between Apr/4/2020 and Sep/3/2020. We analyze prescriptions from the first day and after the first day. We compared the number of drugs, polypharmacy (≥ 5 drugs), excessive polypharmacy (≥ 10 drugs), and p-DDIs. We evaluated differences with the X2 test, Yates correction, Fisher's exact test, ANOVA, and post hoc tests according to their characteristics.
Results:
We evaluated 2,834 admissions: Survey 1,211 and Intervention 1,623. The number of drugs per patient was 6.02 (± 3.20) in Survey and 5.17 (± 3.22) in Intervention (p < 0.001) on the first day and 9.68 (± 5.60) in Survey and 7.22 (± 4.93) in Intervention (p < 0.001) throughout the hospitalization. Polypharmacy was present in 64% of the Survey and 53% of Interventions (RR: 0.83 (0.78-0.88); and excessive polypharmacy in 14% of the Survey and 10% of Intervention (RR: 0.73, 0.60-0.90). The frequency of total p-DDIs was 1.91/patient (± 4.11) in Survey and 0.35 (± 0.81) in the Intervention (p < 0.001).
Conclusions:
We developed and implemented the Hdc.DrApp and SIMDA systems that were easy to use and allowed us to quantify and reduce polypharmacy and p-DDIs.
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