Introduction: Mobile health (mHealth) apps have been involved in contemporary clinical practice in potential drug-drug interactions (pDDIs) research. However, available pDDIs information may differ between apps, which could impact the success of patient's drug therapy. This study analyzed the performance of the mHealth apps in a context of pharmacotherapy prescribed to HIV/AIDS hospitalized patients. Methods: Cross-sectional study was conducted in a referral hospital for infectious diseases, central Brazil. Drug prescriptions were selected randomly by census. A pDDIs prevalence, severity classification as well the agreement of information and performance of different mHealth checkers were analyzed. Free access mHealth apps were selected: Drugs®, EpocratesRx®, and Micromedex® (considered as reference app). Analysis of sensitivity, specificity, positive or negative predictive values (PPV or NPV) was conducted. Results: The majority of 33 HIV/AIDS hospitalized patients was males, young adults, with opportunistic infections despite of a recent HIV diagnosis. 373 drugs were prescribed with 461 pDDIs identified by mHealth checkers. The pDDIs prevalence was 13.9% (12.4-15.6), 22.2% (20.1-24.5) and 24.8% (22.9-26.8) in Micromedex®, EpocratesRx® and Drugs®, respectively. Micromedex® classified most of pDDIs (71.2%) as major, while Drugs® (67.6%) and EpocratesRx® (84.8%) classified most of them as minor. In comparison with Micromedex®, Drugs® or EpocratesRx® showed none (K<0.00) or little (K=0.11) agreement in identification of pDDIs, respectively. Performance analyzes showed that Drugs® presented greater sensitivity (75.4%), however, the results of specificity, PPV, NPV, and accuracy were similar by both apps when compared to the reference. Conclusion: The mHealth drug interaction checkers presented important divergences in the results of identification, classification of severity and prevalence rate of pDDIs.
Introduction: Information on potential drug interactions (PDI) are obtained from databases available on the web or through mobile healthcare applications (mHealth), and can prevent unfavorable clinical outcomes for patients. This study compared PDI information available in Micromedex® drug interaction checker, its web version and its mHealth app. Method: A cross-sectional study realized based on a retrospective review of drug prescriptions in a reference hospital in infectology in the Midwest Region of Brazil, 2018. We selected all prescriptions containing two or more drugs. Drugs were classified according to the first level of the Anatomical Therapeutic Chemical (ATC) classification, according to the route of administration and the number of drugs prescribed. PDIs were classified according to the severity system and four-level evidence classification system. Results: This study selected 72 patients, predominantly male, median age of 38 years, average length of stay of 15.8 days, and most diagnosed with HIV/AIDS. The most frequently prescribed anatomical groups according to ATC were digestive system and metabolism (22.1%) and general anti-infectives for systemic use (21.6%). The average number of drugs per prescription was 10.8 (SD±6.7). The Micromedex® mHealth app found 381 PDIs while its web version detected 502 PDIs, with an average of 5.3 and 7.0 and frequency of 61.1% and 72.2%, respectively. According to the severity classification in mHealth and web versions, the following stood out, respectively: 221 and 321 severe; 139 and 149 moderate. The majority (>65%) of identified PDIs had their documentation classified as reasonable. Conclusion: Digital tools although they aid decision-making, are not unanimous and consistent in detecting such interactions.
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