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How to measure conversations - evaluation and analytics for a healthcare chatbot service

Presentation from Measurecamp Manchester 2019 on chatbot analytics. It covered: a specific (scripted) chatbot service and how this was evaluated; a discussion on other techniques and tools. Enjoy!

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How to measure conversations - evaluation and analytics for a healthcare chatbot service

  1. 1. Evaluation and analytics for a healthcare chatbot service Measurecamp Manchester, 2019 How to measure conversations
  2. 2. •  The challenge •  Evaluation approaches for: •  Usage •  Commercial value •  Clinical value •  Future opportunities What we’ll cover: This is a session is about chatbots and possible ways to evaluate them
  3. 3. We developed a chatbot support app for people starting a new weekly T2D treatment Challenge: People with type 2 diabetes (T2D) starting a new treatment needed the most support over the first 12 weeks Solution: We developed a scripted chatbot app for iOS and Android smartphones to provide support around starting, titrating and monitoring their treatment 3
  4. 4. The potential to learn more through the app was huge… If done accurately and compliantly, the app could allow us to: •  Spot and understand patterns in how people start and stay on treatment* •  Feed these insights back into the organisation to improve the service and future products •  Improving the experience and outcomes of patients on Drug Y •  Combine with real world studies on adherence and patient health outcomes * based on opted-in, aggregated, anonymised usage data
  5. 5. 5 How do you track when different things are discussed each time? …but first we had to work out what to track and how to evaluate a chatbot How do you define a “successful” conversation? How do we demonstrate the value of the service? Measuring and optimising a chatbot presents several challenges:
  6. 6. Usage Commercial value Clinical support To tackle these we evaluated the service at three levels •  Understand user preferences and behaviours •  Leading indicator for treatment uptake •  Assess completion of treatment initiation •  Support patient adherence / outcomes 1 2 3
  7. 7. Level 1: Usage
  8. 8. We evaluated app usage by focusing on the four core service areas ii) Record Tracking a patient’s progress with the app iii) Inform Providing treatment and safety information in a variety of formats (text, photo, video) iv) Remind Providing reminders to the patient about treatment and reinforcing adherence i) Acquire Finding, installing and setting up the app
  9. 9. To monitor promotion, installs and on-boarding, we set up a conversion funnel within the app App promotion through patient / physician support materials App store views App store downloads App installs Registration starts Registration completions Weekly active users How well are we informing people about the app? How many go on to set up the app? How many become active app users? i) Acquire
  10. 10. This would help us identify how to better promote and help people register on the app Types of question this would answer: •  Which promotional activities materials drive the most app store views / downloads? •  Where do people drop out of the set up process? •  How many people start and then continue to use the app? i) Acquire
  11. 11. To help users manage their health, we gave them optional tools to track their progress Initial setup •  Injection reminder preferences •  Dosing settings •  Weight tracking & starting weight (optional) Treatment initiation process •  Adherence and dosing information •  Weekly weight loss (optional) On-going treatment management •  Weekly weight loss (optional) •  Satisfaction level with app ii) Record
  12. 12. The chatbot also provided support content on T2D and managing the treatment Dialogue User feedback App opens Notification Conversation tree followed Educational content interactions Alerts Frequency & recency iii) Inform
  13. 13. We wrote a feedback loop into conversations… 13 First time a user accesses each support content element User taken to start of conversation Conversation ended iii) Inform
  14. 14. …and tracked net promoter score among users after 15 days of registering with the app To evaluate app satisfaction we used the Net Promoter Score (NPS) framework to evaluate the overall satisfaction level of users Rules •  NPS question would only be available to users who had unlocked the app (and provided) •  Unique product ID (to confirm the were a patient-on-treatment) •  Login credentials •  Accept terms and conditions •  15 days after successful app unlock, the NPS survey would be activated •  The NPS survey would be included within the app exit dialogue (see right): “How likely are you to recommend this app to a friend? 1 being not at all likely, 10 being extremely likely” 14 iii) Inform
  15. 15. This helped us get users’ perspectives on the chatbot service and the information provided Types of question this would answer: • What are the top 3 topics or conversations for patients during the first 12 weeks of treatment? • How engaged and satisfied patients are with programmed content? • How users navigate and interact with the app and the conversations? iii) Inform
  16. 16. Key to the chatbot was reminding users when it was time to take their treatment Schedule Reminder Injection Outcome iv) Remind
  17. 17. We were able to learn how well the reminder functionality worked and for which user groups Types of question this would answer: • What patient / behavioural characteristics correlate with adherence? • How effective are reminders at keeping patients on track with their treatments? • What can be learned about their likelihood to adhere to treatment week by week? • At which point-in-time of the treatment are the users most engaged with the app? When does that trail of? How could we proactively engage users with relevant information?
  18. 18. Level 2: Commercial
  19. 19. The chatbot supported the business strategy of delivering a rewarding treatment experience Strategic action (3) Deliver a rewarding patient experience • Set patients and physicians up for success through treatment initiation • Help build patient encouragement and motivation to stay on treatment Strategic focus Establish Drug Y as the unparalleled treatment for T2D
  20. 20. To assess the commercial value of the chatbot we needed to demonstrate four things 1. What was the level of uptake? 2. What level of completion? 3. How satisfied were users with the service? 4. What was the cost saving/potential return for healthcare providers? 20 Inspired by the GDS service standard and mandatory KPIs. See: - -
  21. 21. Three of these were addressed through our measurement of chatbot usage 1.  Uptake - # new app registrations; # weekly active users 2.  Completion - % users completing the 12 week initiation period 3.  Satisfaction - net promoter score 4.  Financial saving/return 21
  22. 22. Measuring the financial value of the chatbot required wider collaboration We needed to answer the following questions: •  What percentage of patients complete titration on the app vs. those not using the app? •  How many additional injections are taken by patients on the app vs. those not using the app? •  What is the patient lifetime value of a Drug Y app user vs. a Drug Y non-app user? To answer these we worked with: •  Medical affairs team – set up a separate study are / integrate within the planned RW •  Forecasting team – understand: •  The actual cost of an injection •  Completion rate of patients over first 12 weeks; average number of injections taken per patient (non- app users) 22
  23. 23. Level 3: Clinical
  24. 24. Via the app What was tracked to deliver the app’s functionality: Outside the app What could only be tracked outside of the app •  Dose achieved •  Reminders fulfilled •  Satisfaction level with treatment •  Completion of initiation period •  Change in patient reported weight (optional) •  Behaviour of people on treatment who are not using the app •  Clinical outcomes beyond weight reduction (HbA1C, clinically recorded weight loss, cardiovascular health) •  Quality of life To understand clinical outcomes, we needed to go beyond what we could track through the app
  25. 25. Integration with real-world study 25 •  Created a separate arm of the real world study to evaluate app usage and health outcomes of patients who start using the app: •  How do app user health outcomes differ from those not using the app? •  How does successful completion of the titration period differ between app users and non app users? •  How does the previous T2D medication affect outcomes among app and non-app user? •  How does number of weeks of app usage correlate with health outcomes? •  Why do patients who start using the app stop using it? •  Advantages: ensures that a minimum sample size of app users is recruited •  Disadvantages: may involve additional resource, delay of >6 months for initial study results The app was integrated into an observational study to learn its impact on adherence
  26. 26. So, what do think? •  What else could we have evaluated to assess the service? •  How have you evaluated chatbot / voice assistant tools in other industries? •  What tools have you used to do this? 26