June 12, 2023

Tackling polypharmacy challenges with conversational AI: Enhancing patient engagement and personalised care

Prof. Nick Barber
Head of Clinical Outcomes

Polypharmacy, the concurrent use of multiple medications, is increasingly common and presents a range of challenges for healthcare professionals and patients alike. Effective management in long-term conditions is crucial in ensuring optimal patient outcomes.

What follows are four challenges we believe conversational AI can help solve by engaging in short, daily patient interactions that provide opportunities for in-the-moment support and insight.

1. Enabling patient education

Medication non-adherence is a significant challenge in polypharmacy, especially for those with comorbidity. Among patients aged 65 and older, those with two conditions received an average of 5.5 prescribed medications, and those with five or more comorbidities were prescribed an average of 10.1. Managing these complex regimens is a leading cause of non-adherence.

Alongside providing timely, personalised reminders, conversational AI can also educate patients about their medicines and empower them to make informed decisions about their health. Through the use of structured, clinically-designed natural language that knows the patient record, we can:

  • Address concerns or misconceptions a person may have about their medicine
  • Help a patient better understand their medicines and reasons for their prescription
  • Provide in-the-moment guidance on how to take medicine for optimal effect

These conversations can be highly personalised and initiated without additional clinical time. By fostering a deeper understanding of medicines alongside tools to help medicines fit more naturally into their day, patients will be more likely to adhere to their treatment plans.

2. Limited evidence for effectiveness

The challenge of limited evidence on drug combinations in polypharmacy can make it difficult for healthcare professionals to choose the best treatment for their patients. It also places a high dependence on the patient's symptom recall ability which the clinician must navigate during a review.

Through continuous interaction, which includes monitoring patient progress and medicine effectiveness, conversational AI can help gather real-time data on patient outcomes, enabling providers to make evidence-based decisions and tailor treatment plans accordingly.

The service must find the right tone — one that’s not paternalistic or judgemental, but more ‘critical friend’ — and provide daily utility that makes the patient’s condition management easier. Once the patient welcomes the system into their life, this data can help clinicians adjust medication regimes and reduce the risk of adverse effects.

3. Deprescribing challenges

Reducing or stopping medications can be difficult due to concerns about withdrawal, symptom recurrence, or negative patient-clinician interactions. Specifically designed conversations that can recur as needed (e.g. weekly, monthly or every three months) can guide patients through this process by monitoring symptoms, signposting, and capturing any concerns that arise along the way.

Consistent engagement of conversational AI means that deprescribing can be approached cautiously, systematically, and in real-time, without long gaps between interactions with the healthcare system.

4. Ownership of one’s health

We are often told by people in our patient panels and from users of Aide that their biggest concern is being treated as ‘one of many’. This is particularly true of those with comorbidity.

Since the introduction of the iOS App Store in 2008, highly individualised technology has been placed within reach of millions of people. This technology has fundamentally changed how health can be managed. As with any technology, there must be a balance between personalisation and burden.

Many reminder apps require a patient to make 50+ interactions to create a personalised schedule for their prescription. They must cycle through each medicine, each dose and set times and methods of reminder.

Using conversational AI, Aide discovers the patient's wake, sleep and meal times and automatically creates reminders for their medicines and monitoring. Interactions like these that are tailored to individual needs and foster a sense of ownership, build trust and encourage patients to take an active role in their care. But only when balanced with the path of least effort.

Where this leads

A patient experience led by conversational AI offers a promising solution to address the myriad challenges associated with polypharmacy. By providing personalised support, improving medication adherence, and offering more continuous communication between healthcare system and patient, this technology has the potential to change the management of polypharmacy radically.


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