ASSESSING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON PRESCRIPTION ACCURACY AND MEDICATION ERRORS IN COMMUNITY PHARMACIES IN UYO LOCAL GOVERNMENT.

CHAPTER ONE INTRODUCTION 1.1 Background to the Study The integration of Artificial Intelligence (AI) into healthcare systems has marked a paradigm shift in clinical decision-making and pharmaceutical practices globally. In particular, community pharmacies, which serve as the first point of contact for many patients in Nigeria, are increasingly adopting AI technologies to enhance prescription accuracy and minimize medication errors (Okonkwo & Adepoju, 2022). AI-powered systems, including decision-support tools and machine learning algorithms, are being deployed to validate prescriptions, detect drug interactions, and flag potential errors before medications are dispensed. This evolution aligns with the broader trend of digital health transformation, which emphasizes precision, efficiency, and patient-centered care (Ngene & Mbata, 2023). Prescription errors—ranging from incorrect drug selection to inappropriate dosages—have been longstanding concerns in community pharmacies, contributing significantly to adverse drug events (ADEs) and preventable morbidity (Ezeh, 2021). These errors often stem from factors such as illegible handwriting, high workload, polypharmacy, and insufficient drug knowledge. AI, with its capability to analyze vast datasets in real-time, offers a potential solution by acting as a safeguard against human fallibility. It does so by automatically checking prescriptions against patient histories, allergies, and current medication regimes (Lawal & Okechukwu, 2024). In contexts like Uyo Local Government, where community pharmacies are under pressure to deliver fast and accurate service, AI holds promise as a transformative tool. The adoption of AI technologies in Nigerian community pharmacies is, however, still nascent and uneven. While some urban pharmacies have begun integrating electronic prescribing and AI-based validation tools, others continue to rely on manual processes. This disparity presents both a challenge and an opportunity: a challenge in terms of system standardization and equitable access, and an opportunity to study AI's practical impact in diverse operational settings (Etim & Okon, 2021). Uyo, as a growing urban center in Akwa Ibom State, provides a suitable case study due to its mix of technologically progressive and traditionally operated pharmacies. Recent studies indicate that AI interventions can reduce prescription-related errors by as much as 30% when effectively implemented (Chukwu et al., 2022). However, these findings are predominantly based on hospital settings, leaving a knowledge gap in the context of community pharmacies. Community pharmacists often operate without the immediate oversight of prescribing physicians, making them more reliant on accurate documentation and robust validation systems. As such, understanding the real-world impact of AI on prescription workflows in these environments is crucial to optimizing its benefits and guiding policy formulation. Moreover, the ethical and professional implications of AI use in healthcare remain hotly debated. Concerns about data privacy, algorithmic bias, and the erosion of human judgment persist, necessitating careful implementation strategies (Obasi & Mohammed, 2023). For instance, if AI tools are not contextually adapted or if pharmacy staff lack adequate training, these technologies may introduce new errors rather than resolve existing ones. Therefore, beyond technological adoption, there is a need to examine user competence, infrastructural readiness, and regulatory frameworks to ensure the safe and effective use of AI. In light of these developments, the present study seeks to evaluate the impact of AI on prescription accuracy and medication errors in community pharmacies in Uyo Local Government. This inquiry is particularly timely given Nigeria’s increasing digitalization of health services, and the imperative to ensure that technological innovations translate into measurable improvements in patient safety and pharmaceutical care quality. 1.2 Statement of the Problem Medication errors constitute a significant public health concern in Nigeria, with community pharmacies often being the epicenter of these incidents due to fragmented communication between prescribers and dispensers. In Uyo Local Government, anecdotal reports and preliminary studies reveal persistent cases of wrong dosages, drug duplication, and contraindicated prescriptions—most of which are preventable with the application of intelligent technologies. Despite the global push towards AI adoption, there is limited empirical data on how AI interventions have shaped outcomes in non-hospital pharmacy settings within Nigeria, creating a critical knowledge gap. While AI is often promoted as a panacea for prescription-related issues, its actual implementation in community pharmacy practice has been met with varied success. Some pharmacy professionals remain skeptical about its reliability, while others struggle with infrastructural limitations such as internet connectivity, power supply, and lack of technical training (Udo & Nkereuwem, 2022). Furthermore, the regulatory environment is yet to catch up with technological advancements, resulting in minimal guidance on standards and protocols for AI integration in pharmaceutical services. These inconsistencies raise questions about the true efficacy and safety of AI in improving prescription accuracy in local contexts. Another pressing concern is the dearth of localized research examining AI’s influence on medication safety in Nigerian pharmacies. Most available studies are foreign and contextually inapplicable. As such, without systematic evaluation within Nigerian community settings like Uyo, it is difficult to ascertain whether AI tools are mitigating or exacerbating existing challenges. This study, therefore, addresses a critical void in understanding the nuanced effects of AI implementation on prescription accuracy and medication error rates in a typical Nigerian urban community. 1.3 Objectives of the Study 1. To assess the extent of AI adoption in community pharmacies in Uyo Local Government. 2. To evaluate the impact of AI systems on prescription accuracy in selected community pharmacies. 3. To determine the relationship between AI implementation and reduction in medication errors. 4. To identify challenges affecting the effective use of AI in prescription and dispensing processes. 1.4 Research Questions 1. To what extent have community pharmacies in Uyo adopted AI technologies? 2. How has the use of AI influenced prescription accuracy in these pharmacies? 3. What is the relationship between AI application and the incidence of medication errors? 4. What barriers exist in the implementation of AI tools in community pharmacy settings? 1.5 Research Hypotheses H₁: There is a significant relationship between the use of AI and prescription accuracy in community pharmacies in Uyo. H₂: The implementation of AI systems significantly reduces medication errors in community pharmacies in Uyo. 1.6 Significance of the Study This study will contribute significantly to the professional discourse on the role of digital technologies in modern pharmaceutical practice. By focusing on AI integration, it provides empirical evidence that can guide pharmacists and health IT experts in designing context-appropriate interventions. The study will also help in updating pharmaceutical curricula to incorporate AI literacy, thereby fostering a more digitally competent workforce. For health providers, the findings offer insights into how AI can improve safety protocols and streamline prescription workflows. This is especially vital in community pharmacies where access to physicians is limited and the burden of medication verification falls squarely on pharmacists. AI tools can act as an additional layer of scrutiny, thus enhancing clinical decision-making and reducing liability risks. At the societal level, the study underscores the public health implications of safe medication practices. By reducing medication errors, AI contributes to improved therapeutic outcomes, greater trust in health systems, and decreased healthcare costs related to drug-related complications. The study will therefore be useful to policymakers, health regulators, and civil society organizations advocating for safer pharmaceutical practices in Nigeria. 1.7 Scope of the Study The study focuses on community pharmacies within Uyo Local Government Area of Akwa Ibom State. It investigates AI adoption, prescription accuracy, and medication errors, targeting pharmacists, pharmacy technicians, and support staff as the primary population. Both AI users and non-users will be sampled to allow comparative analysis. The study also considers contextual factors such as infrastructural support, staff training, and regulatory environment. Key variables include AI adoption (independent variable), prescription accuracy and medication error rates (dependent variables), and moderating variables such as pharmacist experience and infrastructure availability. The geographical scope is limited to Uyo, chosen due to its urban character and growing healthcare service needs. The findings, however, may have broader implications for similar settings in Nigeria. 1.8 Operational Definition of Terms Artificial Intelligence (AI): Computer-based technologies, including algorithms and machine learning tools, used to support clinical decisions and validate prescription data in community pharmacies. Prescription Accuracy: The degree to which prescribed medications match patient needs in terms of drug selection, dosage, and duration, as verified through pharmacy dispensing records and AI support systems. Medication Errors: Preventable events that may cause or lead to inappropriate medication use or patient harm, particularly involving incorrect drug, dose, or administration in the pharmacy context. Community Pharmacy: A privately owned retail pharmacy outlet within a community setting in Uyo Local Government, responsible for the dispensing of prescribed drugs and provision of pharmaceutical care.