Everyone is talking about artificial intelligence (AI) and machine learning (ML) technologies, and many health systems are adding them to their software. Forward-thinking people suggest that using these technologies in the medical field has the potential to improve patient care, streamline clinical workflows, and advance medical research.1,2 Approximately 80% of clinically relevant healthcare information is unstructured data, and AI and ML can rapidly analyze such data.3,4 of table3-10 List some areas where healthcare is adopting AI and ML.
However, medical ethicists point out that ethical considerations regarding the use of AI and ML are multifaceted.5
Basics of medical ethics
Three ethical principles should be emphasized in all healthcare11, 12:
- charity This means that patient needs and preferences drive all clinical decisions. All healthcare providers must do their best to maximize positive outcomes and reduce suffering as much as possible.
- non-malicioussimply put, means do no harm. Although medical procedures can carry risks and cause adverse events, healthcare providers must share decision-making with patients and respect their autonomy.
- justice It means distributing resources fairly and addressing inequality.
ethical concerns
Ethical concerns regarding AI and ML arise from the aforementioned principles. First and foremost, ethicists are concerned about patient privacy.13,14 AI and ML can access electronic health records (EHRs), imaging data, and genomic data, raising the potential for data privacy and breaches. Data security protocols used in the pre-AI era will be inadequate once AI and ML are adopted. Organizations will need sensitive encryption techniques, access controls, and authentication mechanisms. If healthcare providers use AI, they must also communicate to patients that they are using AI and explain how it will be used.13,14
About the author
Jeannette Y. Wick, MBA, RPh, FASCP, is director of the Office of Pharmacy Professional Development at the University of Connecticut School of Pharmacy in Storrs.
Second, we need to proactively address bias and fairness. Although we tend to associate bias with humans and their beliefs, AI and ML algorithms can also be biased.15 For example, if an algorithm uses data that has too few people in a certain demographic, or too many people in a certain socio-economic group, the actions it recommends will be biased. Applying the proposed measures may delay diagnosis or initiate treatment cascades that are inappropriate for ethnic minority populations.16 This violates the principles of justice.
Drug side effects and adherence
Current EHR systems already use AI to predict and detect side effects, notifying staff when a prescriber attempts to order two drugs that are known to interact. New AI-assisted systems may recommend dosage adjustments or drug switches.17 Clinicians should be aware that false positives and false negatives can occur independently and should not rely solely on these alerts.
AI can also create patient-specific message alerts, such as medication update reminders for both pharmacists and patients. Wearable devices (such as smartwatches and smartphones) also integrate AI technology that can suggest behavioral changes (such as messages that it’s time to get up and move) and strengthen adherence.2 Few pharmacy employees would object to using AI technology to request and process prior authorizations, manage the supply chain, optimize the pharmacy’s revenue cycle, or track financial performance.18
AI and pharmacy
Many pharmacy professionals are concerned that AI will replace them. However, the cost of automation technology, labor market trends, and regulatory and societal acceptance pose major barriers to widespread adoption of AI. Actual job losses may be mitigated.2 The integration of AI should help pharmacists expand their scope of practice.18,19 AI can imitate certain human behaviors, but it is not a human. Pharmacists and technicians will continue to use their interpersonal skills to build relationships. Ultimately, AI will complement pharmacists by streamlining repetitive tasks, addressing workforce shortages, and allowing pharmacists to leverage uniquely human intelligence.8,18
conclusion
Will AI technologies revolutionize healthcare? Will they enhance clinical decision-making, improve patient outcomes, and streamline workflows? In many ways, they already are. As healthcare continues to evolve, all healthcare providers must be aware of significant barriers. They need to understand algorithmic transparency (or lack thereof) and understand bias, cost, and accountability concerns. Most important is collaboration between healthcare providers, policy makers, and AI developers. Establishing clear guidelines and verification procedures will help ensure that AI technology is safe and used appropriately. With proper implementation and education, AI can be a powerful tool to reduce the workload and improve the capabilities of healthcare professionals.
