HealthBeacon
Nominated Award: Best Application of AI in a Startup
Website of Company: https://healthbeacon.com/
Patients with chronic conditions often self-administer their injections at home. In its 2003 report on medication adherence, the World Health Organization (WHO) quoted the statement by Haynes et al that as many as 1-in -2 patients fail to adhere to their medication schedule. The effects of poor medication adherence are well documented in both the clinical trial and real-world setting, contributing to treatment failures with resultant increases in hospitalizations and healthcare costs. Staying on track with medication for chronic conditions is a challenge and there is inadequate data available to accurately measure the adherence to the medication.
Health Beacon is a medication adherence technology company which develops smart tools for managing medication. HealthBeacon’s Injection Care Management System (ICMS) provides an innovative alternative to traditional methods by accurately measuring patient’s adherence. HealthBeacon’s FDA cleared smart sharps bin tracks patient injection history, provides personalized interactive reminders and safely stores used injectables. It encases a traditional waste bin and provides patients with an easy, elegant, safe, and connected way to dispose of their used needles, syringes, vials or injectors. HealthBeacon uses customized reminders and provides real time support to individual patients with the help of a dedicated customer care team to help patients start and stay on track with their medication. HealthBeacon tech enables us to identify patients around the globe who miss their inject ion on the scheduled day and initiates targeted outreach by our Customer Support team.
The HealthBeacon was designed using customer feedback with patient empowerment as the top priority, leading to 90% patient acceptance and documented improvements in adherence and persistence to therapy. HealthBeacon has been globally adopted and regulatory approved on the market since 2014 and has tracked > 500,000 injections in over 14 countries to date. Addressing the needs of individuals who self-inject medications at home is critically important. Through our experience and research, we are leading the delivery of digital health solutions to this growing and vulnerable population.
To improve the patient experience, we opened the HB Labs which facilitates extensive collaboration between the data and product teams. Once devices have been tested in the user lab and are released for patient use, the data team constantly monitors and identifies new behaviours and insights from the actionable data that we capture using the devices in the market. The data also helps us to understand the relationship between different treatments and the patient outcomes and this in turn helps us to design the most effective and optimized patient support programs. The use of Artificial Intelligence in combination with the data that we collect has also led to significant improvements in areas such as automated clinical decision-making.
Reason for Nomination:
The customized reminder system is personalized and programmed to keep people on track and is aimed at those who administer their medication on a schedule regularly (e.g., daily, weekly, monthly). The SMS reminder system is somewhat unoptimized, in an ideal scenario, to make the reminder system more effective and to support patients stay on track, the SMS would be sent closer to the date & time of the day when the patient is most likely to take the injection. This is achieved by observing the behaviour of the patient for past injection events and subsequently making prediction for future events.
Objective: The primary aim was to map the reminder timings with patients own behaviour by looking at their historical data and then making predictions about their likely future medication taking behaviour. The secondary aim was to build the smart reminder system which will remind the patient to take the medication only if patient does not take it at the predicted time. In summary, the goal was to predict when exactly the patient will take the medication using the historical data of the user.
Methods: After analyzing the historical data thoroughly, we observed that most patients follow a specific trend for their historical injections which is likely the outcome of their own medication taking behaviour in combination with the impact of the HealthBeacon device which helps them to form a habit. This was also confirmed by looking at the variability in the inject ion hour of the day for individual patients by calculating the standard deviation around their own mean.
This standard deviation or the variance is nothing but the measure of the patient’s variability. The lower variance in the data suggests that patients tend to follow their own trend. This led to the concept of building an Artificial Intelligence platform, to make the prediction for an hour of the day when a patient will most likely take the next scheduled injection based on the data available for last ‘n’ injections. Another branch of this platform is to make the real time behavioural predictions of the patient and assign a behavioural tag to the patient’s profile from the set of defined behavioural tags. Behavioural analytics focuses on understanding how consumers/users act and why, enabling accurate predictions about how they are likely to act in the future.
Challenges:
Challenge #1 – Making Predictions for New Patients: It is very difficult to make accurate predictions for a completely new patient using historical data from similar patients as the patients behaviours tend to vary quite a lot. To overcome this challenge, we developed an optimized algorithm which only requires data f or a small number of historic injections to make a prediction.
Challenge #2 – Unusual Patient Behaviour
In certain events the patient may do something unexpected, the algorithm identifies these cases by calculating the standard deviation around their own mean and smartly excludes these events from the prediction calculation.
Impact:
(1) Patient Empowerment
By predicting the hour of the day that the patient will take their next injection, the smart reminder system will wait for the patient to take the injection at that time and if the injection is still not reported by the patient at the predicted hour then we intervene by sending the reminder. This reminder system driven by AI which is optimized based on the observed patient behaviour will be more effective than just notifying the patient at a scheduled time on their injection day.
(2) SMS Cost Reduction
This solution will also reduce the issuance of unnecessary reminders where patients are likely to report the injection just before the predicted time.
(3) Precision Outreach
Tagging the patients real time using behavioural analytics, helps the customer care team to provide more targeted support to the group of patients that are behaving irregularly.
As a result, more vulnerable and irregular patients will get the support that they require to stay on track with their scheduled injections leading to more adherence and persistence to the medication. Additionally, patients who behave as expected for their injection events will be left alone as they do not require and additional support and for the patients identified to be going through a period of behavioural change our system will automatically identify them and adapt to align with their new behaviour.
This is revolutionary in the field of healthcare as the data along with the AI is leading us to make a positive impact on both patients’ experience and their wellbeing.
Additional Information:
HealthBeacon is a major catalyst for change in the Healthcare industry by connecting patients, medical practitioners, and drug development companies through data. HealthBeacon is deploying smart devices in patient homes that connect patients real time to its platform and is a radical paradigm shift in traditional healthcare pathways.
From the previous research studies, we have seen that the overall adherence of patients drops drastically after initiation and is being reported in the range of 46% to 66% over the treatment duration with variation in adherence due to gender, age and therapeutic area. By enhancing patient support programs and mapping those with the individual patient’s routine and behaviour, HealthBeacon aims to improve the adherence further. The HealthBeacon’s Injection Care Management System is helping to improve not only adherence but also the persistence across multiple therapeutic areas with overall adherence rates of >80% being reported.
Prior to the HealthBeacon, there was inadequate independent data available to prove that patients had actually taken their medication. As such, a key feature of the HealthBeacon is the ability to independently track and record the different types of medications that are taken by patients and disposed of in the smart sharps bin.
Our in-house image detection platform is us ed to accurately detect injection devices from images. Our innovative AI platforms along with the technology running in the backend are built based on the robust data analytics and understanding of the patient journey and the relevant factors. The extensive use of AI integrated technologies is benefitting both the patients and the system. All components connected together are helping us to digitally monitor the patients’ health more effectively and to intervene smartly at the right time.