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Role of the Novel Integrated Clinical Pharmacist Menu Software in Improving Medication Therapy Management
Author(s) -
Muhammad Tahir Aziz,
Tofeeq Ur-Rehman,
Sadia Qureshi,
Kashif Sajjad
Publication year - 2021
Publication title -
journal of pharmaceutical research international
Language(s) - English
Resource type - Journals
ISSN - 2456-9119
DOI - 10.9734/jpri/2021/v33i32b31749
Subject(s) - medication therapy management , clinical decision support system , medicine , pharmacist , clinical pharmacy , pharmacy , identification (biology) , decision support system , medical physics , medical emergency , computer science , nursing , data mining , botany , biology
Background: Medication therapy management (MTM) continues to offer pharmacists the opportunity to use their knowledge, assist patients and caregiver in improving therapeutic outcomes, however the change is slow. Health information technology has been noted as an important driver in the success of MTM and has a potential role in improving therapeutic outcomes and reducing medication errors. Objective: This research aimed to design an integrated clinical pharmacist menu (CPM) software along with clinical decision support tools, optimizing MTM services and reducing medication errors. Methods: The integrated CPM software was designed abridged with decision support tools. A comparative study was conducted in a setting of integrated CPM software versus paper-based clinical pharmacy services (P-CPS) for the evaluation of MTM services. Clinical decision support systems (CDSS) and automated significant laboratory and medication alerts were analyzed for the improvement of MTM and impact on the identification and resolution of medication errors. Results: MTM improved after the application of the CPM software with a difference of 100% in “medication history generation” and “patient care plan,” with a reduction in medication errors by 39.8%. The identification of medication errors and verification of medication order significantly improved from 49% to 82% (p = 0.00) and from 4.5% to 7.0% (p = 0.00), respectively, in the CPM setting. The CDSS tool in the CPM software generated 730, 1802, and 198 auto alerts for “drug–drug interaction,” “inappropriate dose,” and “dose adjustment in an abnormal clinical laboratory test,” respectively, which improved the resolution and identification of medication errors. Conclusion: The CPM is user-friendly, which improved the MTM services. Medication error identification and resolution were significantly improved by the CPM software.

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