Artificial Intelligence (AI) in Pharmacy Certificate
ACPE Numbers: Various - see below Release Date: April 16, 2025 Expiration Date: April 16, 2028 Activity Type: Application-based CE Credit Hours: 18.75 contact hours |
Overview
The evolution of artificial intelligence (AI) is changing how pharmacy is practiced. From administrative tasks to clinical duties, AI uses algorithms and software to analyze, interpret, and comprehend data. What is AI’s impact on patient care and pharmacy workload? What are the different types of models used? How does AI fit into the different practice sites of pharmacy? The Artificial Intelligence (AI) in Pharmacy Certificate answers these questions along with looking at the ethical consideration of AI and its governance.
Artificial Intelligence (AI) in Pharmacy Certificate Requirement
Once a learner has completed the educational curriculum, they will have the opportunity to complete an online comprehensive exam. Once the learner completes the exam (minimum 80% passing rate; unlimited attempts permitted), they will earn the professional certificate.
Accreditation
The American Society of Health-System Pharmacists is accredited by the Accreditation Council for Pharmacy Education as a provider of continuing pharmacy education with Commendation.
Target Audience
This certificate is intended for pharmacists and pharmacy technicians who would like to grow their knowledge and skills for artificial intelligence use in the pharmacy setting.
Course Modules
Learning Activity |
ACPE Number |
Contact Hours |
Fundamentals of AI |
0204-0000-25-752-H04-P&T |
2.5 |
AI Applications in Hospital Operational and Clinical Pharmacy |
0204-0000-25-753-H04-P&T |
4.0 |
AI Applications in Research, Academia, and Industry |
0204-0000-25-754-H04-P&T |
2.25 |
AI Applications in Outpatient Pharmacy and Telehealth |
0204-0000-25-755-H04-P&T |
2.0 |
Ethical Considerations for AI in Pharmacy |
0204-0000-25-756-H04-P&T |
3.0 |
Administrative Aspects for Establishing Successful AI in Pharmacy |
0204-0000-25-757-H04-P&T |
3.0 |
AI Governance |
0204-0000-25-758-H04-P&T |
2.0 |
→ Final Assessment: (80% passing score required) |
Learning Objectives
Fundamentals of AI
ACPE #: 0204-0000-25-752-H04-P&T
Application-based
2.5 contact hours
Learning Objectives:
- Define key terms related to AI, such as machine learning, neural networks, and natural language processing.
- List historical milestones in the development of AI in healthcare.
- Compare predictive analytics versus generative AI.
- Describe at least one key benefit and limitation of AI application in healthcare.
- Evaluate the differences between supervised and unsupervised learning models for use in pharmacy applications.
- Use critical thinking to train and assess models with pharmacy data, ensuring accurate and relevant classifications.
- Summarize the signs and impact of model drift in AI.
- Identify strategies to retrain and maintain model accuracy.
- Combine knowledge of simple and complex AI techniques to assess large language models (LLMs) that enhance data interpretation in pharmacy.
- Compose effective prompts for generating high-quality images.
AI Applications in Hospital Operational and Clinical Pharmacy
ACPE #: 0204-0000-25-753-H04-P&T
Application-based
4 contact hours
Learning Objectives:
- Analyze suggestions from an Inventory Management data model.
- Explain potential benefits of a Drug Shortage AI model.
- Compare aspects of an AI model as it relates to software as a medical device.
- Interpret potential issues with Machine Learning suggestions for prescribing.
- Identify key patient elements to be validated for Electronic Prospective Medication Order Review (EPMOR).
- Design an EPMOR checklist.
- Evaluate the impact of AI used to enhance medication safety within the dispensing process.
- Develop data-driven processes using machine learning (ML) to continuously refine pharmacy operations and support real-time decision-making based on automation.
- Interpret the benefits of medication administration technologies leveraging AI to prevent adverse drug events (ADE) and streamline workflows.
- Apply ML algorithms that automate real-time monitoring of medications and patient transitions of care using predictive modeling.
- Analyze how patient-specific data can support pharmacy monitoring through generative AI.
- Recommend a framework for continuous quality improvement that includes regular assessment of AI applications with a focused balance of human insight in pharmacy practice.
- Identify quality improvement metrics and methods for monitoring the use of natural language processing and pharmacy clinical documentation tools for maintaining professional integrity.
AI Applications in Research, Academia, and Industry
ACPE #: 0204-0000-25-754-H04-P&T
Application-based
2.25 contact hours
Learning Objectives:
- Analyze existing big data platforms and large-scale data sources.
- Examine the applications of AI in enhancing clinical trial matching procedures and advancing pharmacogenomic efforts for personalizing patient care and improving healthcare outcomes.
- Outline the key steps and considerations in implementing AI systems in healthcare settings from a research consideration.
- Identify options in which pharmacy educators can effectively utilize AI in their teaching methods that grow AI literacy for students.
- Assess applications of AI that can benefit pharmacy learners in their studies and skill development.
- Evaluate the potential of AI in revolutionizing drug discovery and development processes in the pharmaceutical sector.
- Describe how AI is utilized for post-market surveillance, including supply chain support, and monitoring of existing pharmaceutical molecules.
AI Applications in Outpatient Pharmacy and Telehealth
ACPE #: 0204-0000-25-755-H04-P&T
Application-based
2 contact hours
Learning Objectives:
- Apply AI technologies in outpatient pharmacy and ambulatory settings to enhance patient care and operational efficiency.
- Analyze the role of AI in remote patient monitoring.
- Assess strategies to implement AI effectively in pharmacy practice.
- Evaluate how patients use and experience AI in healthcare.
- Identify pharmacy reimbursement opportunities related to AI applications, including Medication Therapy Management and CMS provisions.
Ethical Considerations for AI in Pharmacy
ACPE #: 0204-0000-25-756-H04-P&T
Application-based
3 contact hours
Learning Objectives:
- Define key ethical principles relevant to the use of artificial intelligence (AI) in pharmacy practice.
- Explain the impact of data quality and bias in AI models on social determinants of health (SDOH) and patient outcomes.
- Identify regulatory considerations, including privacy laws such as HIPAA, applicable to AI integration in pharmacy.
- Recommend strategies to mitigate bias and promote equitable access and inclusion in AI-driven pharmacy solutions.
- Assess the importance of transparency, accountability, and explainability in AI-assisted decision-making.
- Apply ethical frameworks to evaluate real-world scenarios involving AI use in pharmacy practice.
Administrative Aspects for Establishing Successful AI in Pharmacy
ACPE #: 0204-0000-25-757-H04-P&T
Application-based
3 contact hours
Learning Objectives:
- Describe the various roles in a data team.
- Identify AI in pharmacy workflow components and infrastructure requirements.
- Evaluate performance metrics to measure the impact of AI.
- Analyze an AI in pharmacy business case.
- Calculate return on investment.
- Create a business case to build c-suite buy-in for AI in pharmacy.
- Identify AI’s impact on pharmacy labor.
AI Governance
ACPE #: 0204-0000-25-758-H04-P&T
Application-based
2.0 contact hours
Learning Objectives:
- Assess policies within a health system that would benefit from incorporation of artificial intelligence (AI)-related verbiage.
- Recommend at least one strategy for identifying and maintaining policies associated with AI.
- Evaluate applications of AI ethical considerations within pharmacy practice.
- Describe ways to streamline health system policies and procedures to prepare for expansion of AI into mainstream practice.
- Identify methods for supporting compliance of regulatory and legislative changes.
- Design local resources for expanding AI principles into pharmacy residency training.
Faculty
Ghalib Abbasi, PharmD, MS, MBA
System Director of Pharmacy Informatics
Houston Methodist Health System
Houston, Texas
Benjamin Anderson, PharmD, MPH, FASHP, FMSHP
Medication Management Informaticist
Mayo Clinic
Rochester, Minnesota
Timothy Aungst, PharmD
Professor of Pharmacy Practice
Massachusetts College of Pharmacy and Health Sciences
Worcester, Massachusetts
Jay Dorris, PharmD
Assistant Professor
Lipscomb University, College of Pharmacy
Nashville, Tennessee
Emmanuel Enwere, PharmD, MS, CPHIMS
System Director of Pharmacy and Oncology Informatics
City of Hope National Cancer Center
Duarte, California
Hesham Mourad, PharmD, EMBA, BCPS, BCCCP, FASHP
Senior Pharmacy Manager of Acute and Ambulatory Care Systems
Mayo Clinic
Scott Nelson, PharmD, MS, ACHIP
Associate Professor
Vanderbilt University Medical Center
Nashville, Tennessee
Khoa Nguyen, PharmD
Clinical Assistant Professor
University of Florida, College of Pharmacy
Gainesville, Florida
Alex Rodriguez, CPhT, MHIIM
Lead Data Analyst
St. Jude Children’s Research Hospital
Memphis, Tennessee
Relevant Financial Relationship Disclosure
In accordance with our accreditor’s Standards of Integrity and Independence in Accredited Continuing Education, ASHP requires that all individuals in control of content disclose all financial relationships with ineligible companies. An individual has a relevant financial relationship if they have had a financial relationship with an ineligible company in any dollar amount in the past 24 months and the educational content that the individual controls is related to the business lines or products of the ineligible company.
An ineligible company is any entity producing, marketing, re-selling, or distributing health care goods or services consumed by, or used on, patients. The presence or absence of relevant financial relationships will be disclosed to the activity audience.
The following persons in control of this activity’s content have relevant financial relationships:
Timothy Aungst, PharmD
- Otsuka Pharmaceuticals: consultant
Hesham Mourad, PharmD, EMBA, BCPS, BCCCP, FASHP
- Pfizer: Health IT leadership advisory panel
All other persons in control of content do not have any relevant financial relationships with an ineligible company.
As defined by the Standards of Integrity and Independence in Accredited Continuing Education definition of ineligible company. All relevant financial relationships have been mitigated prior to the CE activity.
Methods and CE Requirements
Each activity consists of audio, video, and/or PDFs and evaluations. Learners must review all content and complete the evaluations to receive continuing pharmacy education credit for each activity.
Follow the prompts to claim, view, or print the statement of credit within 60 days after completing the activity.
Important Note – ACPE 60 Day Deadline:
Per ACPE requirements, CPE credit must be claimed within 60 days of being earned. To verify that you have completed the required steps and to ensure your credits have been reported to CPE Monitor, check your NABP profile account to validate that your credits were transferred successfully before the ACPE 60-day deadline. After the 60-day deadline, ASHP will no longer be able to award credit for this activity.
The ASHP PROFESSIONAL CERTIFICATES℠ educational product line contains learning activities that are ACPE-accredited knowledge and application-based continuing education. This is not an ACPE Certificate Program. Upon successful completion of the activities, the learner will be able to download an ASHP Professional Certificate.