Optimizing Patient Safety

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The University of Nairobi *

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Course

430

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Health Science

Date

Nov 24, 2024

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docx

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3

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1 Optimizing Patient Safety: Leveraging Predictive Analytics to Mitigate Medication Errors in Hospital Pharmacies Student’s Name Instructor’s Name Course Date
OPTIMIZING PATIENT SAFETY 2 ABSTRACT Research Purpose: This study focuses on the application of predictive analytics to enhance patient safety by proactively mitigating medication errors in hospital pharmacy settings. It aims to explore the utility of predictive analytics in identifying and preventing medication errors through the use of historical data and predictive models, empowering healthcare providers to take preemptive measures. Background : Patient safety is fundamental in healthcare, and medication errors remain a significant challenge. This research study addresses this challenge by leveraging predictive analytics to anticipate and prevent medication errors before they occur, thereby fortifying patient safety within hospital pharmacies. Methods: The study employs a comprehensive literature review methodology, with a specific focus on existing literature related to predictive analytics in healthcare, its applications in medication safety, and its potential to mitigate medication errors. The articles were accessed through databases such as PubMed, Web of Science, and CINAHL with the help of various keywords which were directly related to the question research. Results: The findings emphasize the potential of predictive analytics to proactively mitigate medication errors, supplying actionable insights to healthcare providers. This approach aligns with the broader goals of data-driven healthcare and patient safety, advancing the understanding of how data-driven methods can optimize medication safety in healthcare practices. Conclusion : Predictive analytics has the potential to play a pivotal role in enhancing patient safety by proactively mitigating medication errors. By leveraging historical data and predictive models, healthcare providers can anticipate potential errors and take preemptive measures. (Word Count: 242)
OPTIMIZING PATIENT SAFETY 3 Keywords: Patient Safety, Medication Errors, Predictive Analytics, Hospital Pharmacies, Healthcare Technology, Medication Safety, Healthcare Quality Improvement, Pharmacy Management, Data-driven Healthcare, Medication Adverse Events.
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