Role of Artificial Intelligence in polypharmacy and medication nonadherence in Saudi Arabia

Polypharmacy and medication nonadherence are growing global challenges in healthcare, especially among the older population. The rate of both is relatively high worldwide and in Saudi Arabia, with about 50% of chronic disease patients failing to comply with their treatment regimen. These issues should be countered to improve healthcare delivery systems and quality of life. AI integration into the patient care plan may assist prevent Polypharmacy's negative consequences and encourage patients to follow their prescribed course of action. In order to provide better patient care, numerous AI initiatives have been established both domestically and outside in Saudi Arabia. For maximum use, however, the introduction of AI presents ethical and technical issues that need to be resolved. Saudi Arabia has made strides toward integrating AI into healthcare through improved rates of AI literacy and easy accessibility. To get the most out of AI, more work is necessary to get over its constraints.


INTRODUCTION
Polymorbidity is an emerging global phenomenon among immunocompromised individuals, which has led to the rise in Polypharmacy.Several factors contribute to multiple drug intake, such as the multiple medication-promoting guidelines and the easy availability of drugs in developed countries (Pazan and Wehling, 2021).Polypharmacy refers to the concurrent usage of multiple drugs within a particular span.Though controversial, the intake of ≥5 medicines are generally categorized under Polypharmacy, whereas another approach considers the usage of 2 to 11 drugs as Polypharmacy.The lack of polypharmacy standards Polypharmacy can be beneficial in certain cases, but it could lead to harmful drug interactions and side effects of a drug on other concurrent diseases.It can also result in therapeutic failure in almost 50% of individuals taking four or more drugs (Guillot et al., 2020;Mair et al., 2020).Adherence, persistence, or compliance with the treatment is critical for its success.Medical adherence has emerged as a silent epidemic as WHO has reported a significantly lower (50%) adherence to chronic illnesses treatments.Approximately 21-37% of nonadherence cases are associated with preventable adverse drug impacts that negatively affect the treatment cost, efficacy, and safety.This phenomenon has been observed in various chronic conditions such as diabetes, asthma, HIV, hypertension, and rheumatic diseases (Chan et al., 2020;Lee et al., 2022).Improved treatment adherence is considered more effective than modifications in medical treatments of diseased individuals.
The initial term 'compliance' was supposed to have a negative connotation of patients' obedience to the physicians.However, the prescription is now considered a mutual decision of a physician and patient (Alsanosi et al., 2023).Therefore, the WHO has updated the definition of medical adherence to "the extent to which a person's behavior of taking medication, following a diet and lifestyle changes, corresponds with the agreed recommendations from a healthcare provider".Multifactorial medical adherence issues can be further categorized into disease, therapy, patient, economic and social, and healthcare system-related problems (Shahin et al., 2019).An in-depth understanding of nonadherence reasons is important for the identification of high-risk populations and removable potential barriers, as well as the development of individual adherence-promoting interventions.

GLOBAL AND LOCAL (KSA) PREVALENCE OF POLYPHARMACY
The global prevalence of Polypharmacy can range from 10% to 90% depending on the patients' age, considered definition, geographical area, and healthcare system.A study revealed that 20% of the old-age European population (70-74 years), particularly the deprived individuals, are simultaneously prescribed ≥10 drugs (Midão et al., 2021).Scotland-based investigations have revealed that the ratio of individuals simultaneously taking ≥5 medications has doubled, whereas 16.9% of the adult population was found to take 4-9 medicines.
Similarly, a threefold rise has been noted in patients taking ≥10 medications from 1995 (5.8%) to 2010 (20.8%).Higher polypharmacy rates were observed in individuals with lower literacy and females.The study also depicted lower polypharmacy rates in the Western European population than in immigrants from the Middle Eastern countries (Payne, 2016;Khezrian et al., 2020).
A study in South Korea (≥90 days and ≥180 days) deduced a steady increase in polypharmacy prevalence among elderly patients reported Polypharmacy among 27.2% of the participants, which ranged from 16.4% to 60.8% in Geneva and Coimbra, respectively.
Polypharmacy was found to be linked with higher comorbidities, BMI, and age (Zhang et al., 2020).A study in Saudi Arabia analyzed the profiles of 3009 patients and found Polypharmacy in 55% of individuals where, on average, 6.4 medicines were prescribed per patient.The study further noticed a linear relationship between Polypharmacy, patient's age, and comorbidity (Cho et al., 2022).AlJawadi et al., (2022) have reported the prescription of multiple drugs to 51.5% of older Saudi Arabian adults, which raised the risks in diabetic, pain, hypertension, and suggestive depression patients.
The patients from the central regions had more multiple prescriptions than patients from the Northern and Southern regions (Aljawadi et al., 2022).Another investigation reported up to 4 prescriptions in 54% and ≥ five prescriptions in 46% of participants.The prevalence of Polypharmacy has almost doubled in diabetes and hypertension patients, whereas dementia patients experienced five times the increase in Polypharmacy in comparison to the general population.A study in the Al-Ahsa region of Saudi Arabia has reported an 18% prevalence of Polypharmacy (Balkhi et al., 2021).The prevalence of Polypharmacy differs in various countries; however, the convenience of medication availability has led to a continuous increase in prescription rates.

Global and local (KSA) prevalence of medication nonadherence
A study revealed self-reported non-compliance with the treatment regimen in 19.9% of the Chinese population.Multiple factors contributed to this self-reported non-compliance, including gender, disease duration, and perception of medication adherence among patients (Alnaim et al., 2023).Approximately 60% of chronic disease patients in Singapore are medication non-adherent.The discontinuation of the medication generally happens in response to complicated regimens and side effects (Xu et al., 2020).Similarly, 30% of Indian epilepsy patients are known to not adhere to their treatment regimen due to negative effects, treatment duration, and polytherapy.An investigation in Missouri reported non-compliance in 1 in 4 hypertension patients and 1 in 3 diabetes patients, whereas age was noted to be the key influential factor (Kumar et al., 2021).

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Medical Science 28, e24ms3321 (2024) A study demonstrated that the majority (96.2%) of Saudi Arabian chronic illness patients do not adhere to treatment regimens.
Medical adherence was affected by various factors such as dosage regimen, comorbidity type, and type of medication (Heflin et al., 2022).Another study reported that 48.2% of the patients stopped their medication without the permission of physicians, and forgetfulness was noted to be the main reason (60%) for non-compliance.Mobile applications were used by 38.5% of patients to track their prescriptions, whereas 50% of the patients used reminders to take ≥4 pills/day.Heart failure patients were more compliant with the treatment regimen, followed by chronic kidney disease patients.Contrarily, patients with Vitamin D deficiency most frequently missed their medication, followed by patients with hyperlipidemia (Kurdi et al., 2021).
A study in Riyadh depicted medical adherence in 81.6% of epilepsy patients (Almwled et al., 2022).Contrarily, the data of geriatric patients in Madinah-Al-Munawwara revealed poor adherence in 67.9% of patients, and only 32.1% of patients exhibited medication adherence.Forgetfulness was the most common factor of non-compliance, followed by the stopping of medication after feeling better, Polypharmacy, and concerns regarding side effects (Fadil et al., 2023).During a study in Khobar, Saudi Arabia, only one-third of the Type 2 Diabetes Mellitus patients were found compliant with the prescription.The patients with better knowledge of the disease showed 4 to 5 times more compliance with the medication regimen (AlQarni et al., 2019).

Current technologies and developmental status of healthcare in KSA
A significantly high incidence of non-communicable diseases (NCDs), such as obesity and diabetes, is one of the major issues in the Saudi Arabian healthcare system.Polypharmacy, particularly in the aging population with health complications, is another rising concern (Nobili et al., 2011).A cross-sectional study of heart failure patients in a Saudi Arabian tertiary hospital setting demonstrated a dangerously high prevalence (39.88%) of Polypharmacy.The increased Polypharmacy and medical nonadherence have urged healthcare practitioners to adopt innovative technologies (Alsultan et al., 2023).KSA is undergoing a transformative developmental phase in all sectors, including the healthcare system.The key objectives are to improve healthcare service quality at reduced cost and better access to healthcare services by improving the healthcare infrastructure, inducting novel healthcare technologies, and increasing the number of healthcare providers (Saeed et al., 2023).

AI-BASED HEALTHCARE TRANSFORMATION IN SAUDI VISION 2030
Saudi Arabia's "Vision 2030" encompasses a multidimensional strategy for economic and national growth.To implement this vision, a national transformation program (NTP) was launched in June 2016, with healthcare transformation among one of the eight themes (Chowdhury et al., 2021).The new model of care (MOC) is anticipated to promote public health and health awareness in society.
Moreover, the model will improve health services through impartial geographical distribution, optimal coverage, digital solutions, and expanded comprehensive e-health services.It will also facilitate sustained improvement of healthcare services to achieve better satisfaction and experience of beneficiaries according to international standards (Chowdhury et al., 2021; Alkhamis and Miraj, 2021).
The role of Artificial Intelligence (AI) is rapidly expanding in the field of medicine.AI's capability of large-scale data interpretation can help in better clinical decision-making.It can revolutionize the healthcare system via more personalized measures according to the individual needs of the patients (Patel et al., 2009).Currently, AI is used to diagnose and recommend appropriate disease management steps.AI could be more autonomous in the future to perform complicated tasks such as patient triage.However, AI-associated potential risk factors should be carefully handled to ensure optimal healthcare delivery.

Prediction of adverse drug interaction
AI-developed systems can predict potential drug interactions by effectively analyzing major databases based on patient-related factors such as genetics, age, allergies, and ethnicity.These predisposing factors can facilitate the analysis of existing health status, prescribed medications, and medical history to foresee the occurrence of certain diseases (Yang and Kar, 2023).Collectively, the information could improve the decision-making regarding medication combinations to alleviate polypharmacy-linked adverse reactions, particularly in older individuals under multiple treatments for different diseases.Sema4 signal is a patient health-centered transformative product of a healthcare intelligence development company, Sema4 (Kureczka, 2020).
It employs AI, digital tools, and innovative exome-based genetic testing to reveal the genetic profile and clinical history of the patient.The information helps to evaluate and predict adverse risks of medications and enables healthcare practitioners, particularly oncologists, to vigilantly evaluate multiple treatment options for better patient care (Donnard et al., 2014).Elsevier's Pinpoint suite provides evidence-based literature by utilizing machine learning and AI, which assist healthcare providers in considering contraindications and adverse drug interactions during treatment.Moreover, it facilitates making inclusive decisions to ensure patient safety in complicated cases (Vidhya et al., 2023).

Precise prescription for personalized treatments
AI-driven systems can effectively utilize existing databases to assist in precise, personalized alterations in medications and doses for various diseases based on the patients' profiles.This comprehensive strategy acknowledges the existing health situation of an individual, leading to patient satisfaction and acceptability (Roski et al., 2019).The luxury of personalized treatments for everyone in society could improve the overall quality of life for all social classes, which can be achieved by developing relevant AI algorithms.The AI-powered system known as IBM Watson for Oncology is specifically designed to select the best treatment regimen for cancer patients (Somashekhar et al., 2018).The database of this system includes all the updated literature, similar patient records, and clinical trial results to assist oncologists and patients in adopting the optimum treatment procedure among various complicated options while considering the associated factors (Liu et al., 2018).

Adherence strategies and continuous monitoring
AI tools can conveniently improve medication adherence by reshaping the previous approaches according to the patient's preferences and behaviors.AI can also suggest personalized adherence options, including educational materials, adaptive schedules for dosing, and reminders (Bohlmann et al., 2021;Al-Sharo et al., 2023;Nordin et al., 2024).AiCure is an AI-based interactive mobile app that monitors the patient and confirms his medications as prescribed.It employs facial recognition and a mobile phone camera to visually confirm a patient's medication intake and transmits the feedback to healthcare providers.Moreover, the AiCure app alerts the patient through personalized reminders to timely take the prescribed drug and provides educational interactive videos for proper intake of the medication (Bain et al., 2017;Xu et al., 2021).The app also ensures the patient's constant monitoring and medical adherence while keeping the doctor constantly informed for timely amendments in doses and medication.
The interactive features of this app significantly improve patient's adherence to the prescribed dosages and medication (Verma and Naaz, 2022).A similar app, "Tadawi", has been developed in Saudi Arabia that sends constant personalized reminders and dosage alerts to users for enhanced medical adherence (Saeed et al., 2023).The scope of this app is still limited, but future AI tools can incorporate the notifications for the patient's healthcare team further.Sehhaty Wa Daghty, an iPhone-linked Arabic health app, monitors blood pressure, food consumption, and physical activity.This app mainly focuses on developing a mobile phone-based selfmonitoring of HTN to achieve improved fitness and health levels among Saudi adults (Alzahrani et al., 2023).
Sustainable medical adherence can be attained by educating patients about adverse drug reactions and enhancing awareness regarding medication adherence.The interactive AI-assisted tools can also answer the patient's queries in a user-friendly manner (Liu and Xiao, 2021; Upadhyay & Gupta, 2023).AI-based Your.MD healthcare assistant offers personalized advice and information regarding potential side effects and benefits of medication adherence.This user-friendly platform can be operated through a mobile application or surface web.It has significantly contributed to enhancing the community's awareness and scientific knowledge of medication adherence (Xu et al., 2021;Bekbolatova et al., 2024).Sehhaty app, developed by the government of Saudi Arabia, offers various healthcare services such as telemedicine, appointment booking, and interaction with health providers.It has also helped to enhance health awareness among the Saudi Arabian population (Alkhalifah et al., 2022).

PROSPECTS AND CHALLENGES
Despite the revolutionary AI potential in patient care through the mitigation of complex polypharmacy impacts and enhancing medical adherence, there are various ethical, technical, and legal challenges associated with its large-scale applications.The development of a broad-range AI program that can integrate into multiple healthcare systems with convenient utility for patients and healthcare providers is a complicated task (Bekbolatova et al., 2024).It requires extensive medical and personal data of numerous variable parameters for better polypharmacy management without affecting the patient's treatment.The induction of AI systems could be

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Medical Science 28, e24ms3321 (2024) 5 of 8 limited by the existing healthcare infrastructures' data processing and storage potential.The extent of AI integration and education through government curricula could determine its level of applicability (Paul et al., 2021).
Quality-independent AI data might lead to discriminatory results against minority and marginalized groups, whereas inaccurate, missing, and poor data could compromise patient safety by negatively impacting AI algorithms.Moreover, AI algorithms (big data analytics and machine learning) require sensitive medical and personal data of the patients, which could raise questions regarding patient anonymity, confidentiality, and information safety (Bouhouita-Guermech et al., 2023; Chen et al., 2023).Therefore, issues related to patient consent and privacy must be addressed through data owner identification and legal and ethical considerations.The legislation should also be carried out to ensure the accountability of AI developers, program owners, and healthcare providers in handling medical accidents (Paul et al., 2021).
Saudi Arabian Vision 2030 anticipates embracing and integrating AI at all levels of patient care.Recent efforts have focused on enhancing AI literacy through e-learning and aiding healthcare professionals in the multidimensional diagnosis process.This article highlights the characteristics of polypharmacy and medical adherence issues in Saudi Arabia, which can be tackled by effective AI induction in pharmacy (Al-Jehani et al., 2021).Current investigations should focus on overcoming the AI program-associated limitations while concurrently exploring diverse utilities of AI-platforms for improved patient treatments.For instance, have reported a high efficiency of AI integrations for better medical adherence in non-communicable disease patients (Vora et al., 2023).

CONCLUSION
Polypharmacy and nonadherence are growing global challenges in healthcare, especially among the older population.The polypharmacy rate is quite high in Saudi Arabia, and 50% of chronic disease patients fail to comply with their treatment regimen.These issues should be countered to improve healthcare delivery systems and quality of life.AI incorporation into the patient care plan could help avoid the adverse effects of Polypharmacy and promote patient adherence to the treatment plan.Several AI programs have been developed internationally and locally in Saudi Arabia for better patient care.However, the induction of AI raises technical and ethical concerns that should be solved for its optimum applicability.Saudi Arabia has taken progressive steps to promote AI integration in all aspects of healthcare through enhanced AI literacy rates and convenient accessibility.However, further efforts are needed to overcome AI-posed limitations for maximum benefits.