How can AI support Medicines Optimisation and Adherence?

Medicines optimisation is an essential component of healthcare that aims to ensure that patients receive the right medication at the right time, in the right dose, for the right condition, and with the appropriate support to ensure adherence. It is an ongoing process that involves the careful selection, prescribing, dispensing, and monitoring of medications to achieve the best possible outcomes for patients.

Adherence, on the other hand, is a patient's willingness and ability to follow the prescribed treatment regimen as instructed by their healthcare provider. Adherence is crucial in ensuring the effectiveness of the prescribed medication, reducing the risk of complications, and improving patient outcomes.

In this blog, we will explore how AI can support medicines optimisation and adherence.

How can AI support medicines optimisation?

There are several ways that AI can help with medicines optimisation:

1. Medication reconciliation
   Medication reconciliation is the process of creating an accurate and complete list of a patient's medications, including prescription medications, over-the-counter medications, and herbal supplements. AI can support this process by using natural language processing (NLP) to extract medication information from electronic health records (EHRs) and patient data. This can help identify medication discrepancies and reduce the risk of adverse drug events.
   
   
2. Decision support systems
   AI-powered decision support systems can provide clinicians with real-time information and recommendations based on patient data, such as medication allergies, drug interactions, and contraindications. These systems can also provide guidance on dosage, administration, and monitoring, helping to ensure that patients receive the most appropriate medication regimen.
   
   
3. Predictive analytics
   Predictive analytics can help identify patients at risk of adverse drug events, non-adherence, or medication-related complications. By analysing patient data, such as medical history, laboratory results, and medication use, AI can predict the likelihood of adverse events and provide clinicians with early warnings, allowing for timely intervention and prevention.
   
   
4. Patient education and engagement
   AI-powered patient education and engagement tools can help improve patient understanding of their medications and treatment regimen. These tools can provide patients with personalised information, reminders, and alerts, helping them stay on track with their medications and reducing the risk of non-adherence.

How can AI support medication adherence?

Medication adherence, or the extent to which patients take their medications as prescribed, is affected by a multitude of factors. One significant factor is the complexity of the medication regimen, which includes factors such as the number of medications, the frequency of dosing, and the timing of doses. AI can help to develop interventions that promote medication adherence and improve patient outcomes, for example:

1. Personalised medication reminders
   AI-powered medication reminder systems can send personalised reminders to patients via email, text, or app notifications. These reminders can include specific instructions on medication administration, dosage, and timing, helping to ensure that patients take their medications as prescribed.
   
   
2. Behavioural nudges
   AI can use behavioural nudges, such as positive reinforcement, to encourage medication adherence. For example, patients can earn rewards or incentives for taking their medication on time, adhering to their treatment regimen, or achieving specific health goals.
   
   
3. Medication adherence monitoring
   AI-powered medication adherence monitoring systems can track patient medication use in real-time, providing clinicians with information on patient adherence and identifying patients who may need additional support or intervention.
   
   
4. Predictive analytics
   Predictive analytics can also be used to identify patients at risk of non-adherence and provide clinicians with early warnings, allowing for timely intervention and support.

Conclusion

AI has the potential to revolutionise medicines optimisation and adherence by providing clinicians with real-time information and recommendations, identifying patients at risk of adverse events and non-adherence, and improving patient engagement and understanding of their medications.

However, it is essential to consider the ethical implications of using AI in healthcare, such as data privacy and security, algorithm bias, and the potential for AI to replace human clinicians. As such, it is crucial to ensure that AI is used responsibly and ethically in healthcare, with a focus on patient safety and outcomes.

MedAdvisor Medication Management App

When it comes to managing medication, the MedAdvisor solution is a popular choice. 

To book a call and find out more click here.