The Powerful Relationship Between Hospital Pharmacists, the Care Providers They Serve, Their Patient-Customers, and Artificial Intelligence (AI)
This week, a short but impactful comment on the previous AIHG Blog, “Courage Is Not the Absence of Fear—The Relationship Between Personal Courage and Personal Authenticity,” prompted me to recall my interactions over the past two decades with Md. Rezaul Islam, a hospital-based pharmacist. During that time, I have watched him grow into a highly competent example of a 21st-century leader-manager. From the beginning, his passion for personal and professional knowledge has distinguished him. More importantly, I continue to appreciate his willingness to share what he knows with others.
Sharing knowledge—and creating synergy through it—is central to hospital-based pharmacy. A practical example from about forty years ago illustrates that principle and frames the exceptional relationship among hospital-based pharmacists, the care providers they serve, and patient-customers. It also shows how artificial intelligence (AI) can support those relationships.
What Hospital-Based Pharmacy Is and How It Works
A few decades back, as a new hospital administrator, I assumed responsibility for “Support Services,” which included activities that occurred “behind the scenes,” such as pharmacy operations. At the time, I knew little about pharmacies, much less about how a hospital-based pharmacy worked. Fortunately, the Chief of Pharmacy (William), who held a doctorate in pharmacology, was a serious educator. He taught everyone in the hospital what distinguished his “Pharmacy Service” and how that distinction affected the quality of customer care and patient outcomes. Through his example, I came to understand the pharmacy in a hospital or healthcare delivery system as a bona fide care provider.
Once, while I was participating in a Morbidity and Mortality Committee meeting of the medical staff, the group faced a serious patient-care and outcome issue involving a complex case of comorbidity. After considerable back-and-forth among committee members without a conclusion, someone suggested, “Let’s call William in; he’ll have an answer.” William was called in, and he cogently shared his answer with everyone. Around the table, I saw great respect for him and for the treatment course he suggested. I realized then that this kind of pharmacist was a true care provider and an asset to every other provider within his Sphere of Influence and Control. So, I began to pay attention to William and his Tribe of Followers.
What I saw was the power of information and process management. William was a master at providing the information others needed to deliver excellent care. More than that, he offered clear process steps for others to follow to achieve the outcomes (Intended Results) he predicted. As I reflected on his success, I realized that access to AI would have given him exponentially more information to draw upon as he developed and shared his products.
With that context, I offer some thoughts on how hospital-based pharmacists can begin using AI from the “bottom up” today to improve customer satisfaction and patient outcomes. News and social media reports describe almost daily the benefits AI may bring to healthcare delivery. Major developments will come from the “top down,” but meaningful changes can happen—and are already happening—now. Let’s consider what pharmacists, especially hospital-based pharmacists, can do with AI today.
Hospital-based pharmacy is the organized practice of pharmacy within a hospital or health system, supporting patient care across inpatient, emergency, procedural, ambulatory, and transitional settings. Its pharmacists work as members of the care team who manage medication-use systems, contribute clinical expertise, promote safety and quality, and help achieve patient and organizational outcomes.
Key distinction: Hospital-based pharmacy is embedded in the delivery of coordinated clinical care and is accountable to the hospital or health system’s patient-care mission. Commercial pharmacy operates primarily as a customer-facing distribution and service business. The categories may overlap—for example, a health system may own outpatient or specialty pharmacies—but the principal distinction is the practice’s primary purpose, setting, and relationship to the care team.
Examples include an inpatient pharmacy that prepares and distributes medications for hospitalized patients; a clinical pharmacist who participates in intensive care rounds and adjusts medication therapy with the care team; an emergency-department pharmacist who supports urgent medication decisions; and a health-system pharmacy that coordinates discharge medications and follow-up care.
A hospital-based pharmacist is a care provider who collaborates with the clinical team to optimize medication therapy, prevent harm, educate patients, and coordinate care across transitions. By applying medication expertise to patient-specific decisions, the pharmacist contributes directly to safe, effective, and patient-centered outcomes (ASHP, 2019).
Within hospital-based pharmacy, the pharmacist serves as an accountable clinical integrator who coordinates medication-use practices across pharmacy operations, care providers, patient-customers, and artificial intelligence (AI).
The pharmacist contributes medication expertise to interdisciplinary decisions, incorporates patient goals, and circumstances, and uses AI to organize information, identify patterns, and support evidence-informed recommendations. Because AI supplements rather than replaces professional judgment, the pharmacist remains responsible for evaluating its relevance, reliability, potential bias, and privacy implications and for translating all available inputs into safe, individualized medication therapy.
Five Ways AI Can Support These Relationships
Shared clinical decision support: AI can synthesize medication histories, laboratory findings, diagnoses, and current therapies to identify risks and present evidence-informed options for pharmacist and care-team review.
Medication-safety surveillance: AI can help pharmacists and other care providers detect potential interactions, contraindications, dosing concerns, duplicate therapies, and emerging adverse-drug-event patterns.
Patient-centered communication: AI can help pharmacists prepare clear, individualized medication instructions and educational materials that reflect a patient-customer’s language, health literacy, treatment goals, and care setting.
Care coordination and transitions: AI can reconcile information across care settings, flag discrepancies, and identify follow-up needs, enabling pharmacists to coordinate more effectively with prescribers, nurses, case managers, and patients during admission, transfer, and discharge.
Knowledge sharing and workflow support: AI can summarize guidelines, organize relevant evidence, document routine information, and prioritize high-risk cases, giving pharmacists more time for clinical consultation and direct patient engagement.
Across all five applications, AI should augment—not replace—professional judgment; pharmacists remain responsible for validating outputs, protecting confidential information, recognizing bias, and ensuring that recommendations are clinically appropriate and patient-centered.
Pharmacist Oversight of AI Tools
The pharmacist’s oversight role extends across the AI tool’s lifecycle. Before implementation, pharmacists should help define the clinical purpose, assess evidence and workflow fit, and ensure that data use complies with privacy, security, and equity requirements (ASHP, 2024; FIP, 2025; WHO, 2021).
During use, they must interpret AI outputs within the patient’s full clinical context, verify recommendations against authoritative evidence, communicate uncertainty to care providers and patient-customers, and retain authority to modify or reject inappropriate suggestions (ASHP, 2024; FIP, 2025).
Pharmacists should also monitor performance for errors, bias, alert fatigue, and unintended effects; document significant decisions; report safety concerns; and participate in periodic governance reviews (NIST, 2023; WHO, 2021). Although technical teams and organizational leaders share responsibility for system design and control, the pharmacist remains professionally accountable for medication-related judgments and for ensuring that AI supports safe, transparent, and patient-centered care (ASHP, 2024; FIP, 2025).
Call to Action: Lead the Responsible Use of AI
Now is the time to help shape how AI supports medication use and patient care. Begin with a specific problem, define the intended benefit and risks, secure organizational support, and establish measures of safety, quality, efficiency, and patient experience. Advocate for a limited pilot with pharmacist review before broader adoption, and approach AI not as a stand-alone technology but as a tool for strengthening coordinated relationships.
1. Mobilize Your Hospital Pharmacy Colleagues - Bring operational, clinical, informatics, and pharmacy leaders together around one focused use case, such as identifying high-risk medication orders or prioritizing patients for review. Map the current workflow, assign responsibility for validating AI outputs, establish escalation procedures, and prepare colleagues to recognize both the tool’s value and its limitations. Review pilot results, overrides, errors, and workload effects as a team before recommending expansion.
2. Partner with Care Providers - Invite physicians, nurses, and other care providers to determine when AI-supported medication information should enter clinical decisions and how recommendations should be communicated. Agree on evidence standards, response expectations, documentation requirements, and situations requiring direct pharmacist consultation. Use interdisciplinary review of early cases to confirm that AI improves the timeliness, clarity, and clinical value of decisions without increasing alert fatigue.
3. Engage and Protect Patient-Customers - Choose patient-facing applications that meet a clear need, such as individualized medication education, language support, adherence planning, or discharge follow-up. Tell patients when AI contributes to communication or recommendations, preserve direct access to a pharmacist, and provide a dependable way to correct inaccurate information. Review every application for clinical accuracy, comprehensibility, accessibility, cultural appropriateness, and privacy, and use patient feedback to improve the process.
4. Lead with AI, Informatics, and Governance Partners - Work directly with informatics, information security, quality, legal, compliance, and vendor teams to scrutinize data provenance, validation evidence, access controls, privacy protections, bias testing, system reliability, and fallback procedures. Insist on governance that defines who may use the tool, which decisions require human confirmation, how performance will be monitored, and how incidents will be reported and corrected. Exercise your authority to question, override, or suspend medication-related AI use whenever outputs are unreliable or unsafe.
Act now:
Select one low-complexity, measurable use case; establish baseline performance;
Complete rigorous technical and clinical validation;
Prepare every participating group;
Launch a time-limited pilot under direct pharmacist oversight;
Measure outcomes, investigate unintended effects, refine the workflow, and expand only when evidence demonstrates that the benefits outweigh the risks.
Do not remain a passive user of AI—help govern it. In every use of AI, establish continuous monitoring, periodic revalidation, transparent accountability, and meaningful patient and staff feedback as defining standards of safe, equitable, and patient-centered AI-enabled pharmacy care. Above all, pharmacists must ensure that every AI-supported medication decision begins with the patient’s needs, reflects the patient’s goals and values, and advances outcomes that matter to the patient (Agency for Healthcare Research and Quality [AHRQ], n.d.).
References and Citations
Agency for Healthcare Research and Quality. (n.d.). Six domains of healthcare quality. AHRQ: Six Domains of Healthcare Quality
American Society of Health-System Pharmacists. (2019). Long-range vision for the pharmacy workforce in hospitals and health systems. https://www.ashp.org/-/media/assets/policy-guidelines/docs/endorsed-documents/pharmacy-workforce-long-range-vision.pdf
American Society of Health-System Pharmacists. (2024). ASHP statement on the use of artificial intelligence in pharmacy. ASHP statement on AI in pharmacy
International Pharmaceutical Federation. (2025). An artificial intelligence toolkit for pharmacy: An introduction and resource guide for pharmacists. https://www.fip.org/file/6202
National Institute of Standards and Technology. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). NIST AI Risk Management Framework
World Health Organization. (2021). Ethics and governance of artificial intelligence for health: WHO guidance. https://www.who.int/publications/i/item/9789240029200
Author’s Disclosure on the Use of AI
The author controlled the use of artificial intelligence tools to support the development and refinement of the author’s original ideas and content. AI assistance was used selectively and under the author’s direction; the author reviewed, evaluated, and approved the final content and retains responsibility for its accuracy, integrity, and conclusions.
Comments