Just Culture Meets AI: How Pharmacists Are Leading Safer Transitions of Care

As artificial intelligence (AI) continues to expand its reach and impact new areas, health care professionals search for safe and effective ways to incorporate it into practice. For pharmacists in the transitions of care space, AI can help improve safety while assisting in the implementation of Just Culture—a practice model that emphasizes empathy and balanced accountability.

Artificial intelligence must be incorporated safely into health care | Image credit: Suriyo | stock.adobe.com

Just Culture is based on the idea that “organizations are accountable for the systems they have designed and for responding to the behavior of their employees in a fair and just manner. Employees are accountable for the quality of their choices and for reporting errors and system vulnerabilities.”¹ This system of shared accountability facilitates a shift from blame to systems thinking and helps foster psychological safety, which increases error reporting rates and ultimately leads to continuous improvement. By creating an environment where mistakes are viewed as opportunities for learning rather than reasons for punishment, health systems can address root causes of problems, implement more effective preventive measures, and build a stronger culture of transparency and collaboration.

This is especially important as patients transition from hospital to home care, an exceptionally risky time. One study examining patients discharged from hospital to home found that 89% of patients had at least 1 medication discrepancy.² Several factors contribute to this high incidence of errors. Some occur because of poor communication between health care providers or inadequate medication counseling at discharge. Others are due to failures in properly reconciling medications during transitions. Still others can be attributed to patient factors—complex regimens, multiple comorbidities, cognitive impairments, and more. Though these risks are well-established, transitions of care pharmacists and technicians often feel a pressure to do more with less. A 2023 report published in New England Journal of Medicine Catalyst noted that workforce shortages place significant strain on acute, post-acute, and long-term care institutions, contributing to transition backlogs and increased medication errors.³

Artificial Intelligence Case Studies

To address these challenges, some health systems have turned to AI to reduce manual burdens and improve accuracy during transitions of care. Carle Health in Illinois has recruited the help of AI to combat such shortages. In 2021, Carle integrated AI into their Epic electronic health records to relieve some of the workload for their medication reconciliation staff.⁴ The AI retrieves medication history from community pharmacies, converts prescription instructions into plain language, and imports data into the appropriate fields, reducing the amount of manual entry required and freeing pharmacists and technicians up for more involved tasks like interviewing patients to resolve discrepancies, providing targeted discharge counseling, and coordinating care with post-acute providers. Since implementation, external medication histories are consulted in 99% of their high-risk patients.⁴

AI can also be used to reduce potential medication errors by predicting adverse drug reactions and recognizing drug-drug interactions, patient-specific documented adverse effects, and patterns of non-adherence.^5,6 These technologies can help detect and prevent issues that may otherwise go unnoticed in a time-sensitive discharge workflow.

Limitations of AI

Still, AI cannot function independently. Although it can assist in flagging potentially unsafe orders, it does not yet possess the clinical judgment required to operate on its own. The pharmacist’s role remains critical, with some necessary adaptations. Pharmacists must continue to review discharge plans, catch errors that escape AI filters, and communicate with informatics teams and developers to improve AI design and functionality.

Once implemented, AI tools can also expose system-level gaps that create error-prone situations. For example, if data reveal that discharge medications are consistently being dosed in mg instead of mg/kg, medication safety teams can review order sets and defaults to correct this issue. In addressing these findings, institutions must stay grounded in the principles of Just Culture, recognizing that both system design and individual actions contribute to safety. Data should drive learning and improvement, not punitive oversight.

The Future of AI

As we look to the future, AI’s role in transitions of care is best viewed not as a replacement for pharmacists but as an enhancer of their capabilities. AI can handle repetitive and time-consuming tasks, but it is the pharmacist who interprets context, exercises judgment, and applies empathy. The future will be defined by this relationship: a tech-savvy workplace where pharmacists can spend more time with patients and less time on data entry.

This holds exciting potential. Imagine a transitions of care space where AI flags high-risk patients, generates an initial discharge plan, and alerts pharmacists to areas needing clinical attention. With AI support, the pharmacist is more available to focus on patient counseling, social determinants of health, and coordination with primary care teams. Rather than replacing the human element, AI creates space for more of it.

Ultimately, integrating AI into pharmacy practice, especially in high-risk areas like transitions of care, will only succeed if it is guided by ethical leadership. Pharmacists must engage boldly with these tools, continuing to develop designs that enhance safety, equity, and transparency. Collaboration between frontline practitioners, developers, and administrators will be essential to ensure that AI assists in the pursuit of better patient outcomes.

As we move forward, the most transformative innovations will come not from machines alone, but from pharmacists who know how to use them. The future is not one or the other; it is both AI and humans working together toward safer, smarter, and more compassionate care.

REFERENCES

1. What Is Just Culture? Changing the way we think about errors to improve patient safety and staff satisfaction. Mass General Brigham. Accessed June 25, 2025. https://www.brighamandwomensfaulkner.org/about-bwfh/news/what-is-just-culture-changing-the-way-we-think-about-errors-to-improve-patient-safety-and-staff-satisfaction

2. Corbett CF, Dupler AE, Smith S, Balogh EM, Bolkan CR. Advances in patient safety and medical liability. Agency for Healthcare Research and Quality. Updated August 2017. Accessed June 25, 2025. https://www.ahrq.gov/es/patient-safety/reports/liability/corbett.html

3. Lam K, Blauwet C. Silos and shortages challenge transitions between care settings. NEJM Catal Innov Care Deliv. 2023;4(5). doi:10.1056/CAT.23.0095

4. Siwicki B. AI-powered med history system improves care, reduces work at Carle Health. Healthcare IT News. July 17, 2024. Accessed June 25, 2025. https://www.healthcareitnews.com/news/ai-powered-med-history-system-improves-care-reduces-work-carle-health

5. Yang S, Kar S. Application of artificial intelligence and machine learning in early detection of adverse drug reactions (ADRs) and drug-induced toxicity. Art Intel Chem. 2023;1(2):100011. doi:10.1016/j.aichem.2023.100011

6. Alsanosi SM, Padmanabhan S. Potential application of artificial intelligence (AI) in managing polypharmacy in Saudi Arabia: a narrative review. Healthcare (Basel). 2024;12(7):788. doi:10.3390/healthcare12070788