Patient retention and engagement with healthcare technology

Health technologies are becoming increasingly well-established and have been shown to improve patient treatment. However, effective user engagement and retention for these technologies remains a challenge. Understanding the drivers of app usability may prove crucial in improving retention and long-term use of health technologies.

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The difference between engagement and retention

     Mobile health (mHealth) technologies are increasingly being used to improve the delivery of healthcare to patients.1 The application potential of mHealth is extensive and includes remote monitoring of patients, treatment adherence assessment, medical record access and virtual diagnosis.1

     But when we consider the use of health technology applications, we must consider both the way in which users interact with the technology (engagement), and the regularity with which they do so (retention). Low app engagement or low retention may both be a recipe for failure.2 Industry benchmarks for retention vary but can be defined as the percentage of users who return to the application (app) within three months of their first session.2 The goal is to ensure that users are not only engaged, but also use their health technology with regularity.

User retention is a problem

     Average mobile app retention rates are estimated to be as low as 20% after 90 days across all industries.2 Healthcare is no exception; only 7% of mHealth apps have more than 50,000 active users.3 Moreover, when considering those users who return to their apps regularly, 62% of mHealth app publishers report fewer than 1,000 monthly active users (defined as a user who has used their app at least once in a month).3

     So why do users abandon their health technology apps? A study by Murnane and colleagues, using the Google Consumer Survey, investigated the reasons why users abandoned their mHealth technologies.4 Reported reasons were varied and included functionality issues, phone incompatibility, mistrust of the app developer, lack of desired features (e.g. absence of push notifications) or abandonment of a particular health goal itself.4

     Adherence to treatment regimens is an already established challenge for patient health outcomes (the percentage of patients who are still taking their statin medications 90 days after their prescription, is approximately only 60%)5 and uptake of health technologies seemingly faces similar barriers. So, what does that mean for the retention levels of health-related technologies?

     In a competitive market, health technology retention is an important focus for developers and is further complicated when considering technologies that engage multiple parties. Finding ways to ensure that doctors, patients and administrators continue to use a particular app means combining features that appeal to multiple stakeholders which may incur its own challenges.5 Finally, a unique consideration for technology retention within healthcare involves anticipating patient engagement based on their current health status. When they are feeling good, patients may feel they do not need to use their health technology as frequently compared with when they are feeling unwell. Innovative solutions to address these challenges are crucial to boost user engagement and retention. 

Improving retention and engagement

     Despite these hurdles, there is good progress being made; a proportion of health technology solutions have reported considerable market penetration, with rising numbers of monthly active users.3

     What are the secrets to good user retention? Studies suggest that those technologies most likely to retain users include those that are individualized, easy to use and offer real value to patients.3 In healthcare, the language used can be an issue. Conversa, a mobile platform for virtual healthcare, has tackled retention through a strategic use of language that is relatable, succinct and engages patients without complicated terminology and use of easy-to-understand chat-bot features. Moreover, collaboration between Conversa and psychologists aims to incorporate wording that is synonymous with patients’ self-determination to further encourage regular use of the app.5

     Making access simple may be another key to improving retention. Allowing carers to access patient health solutions may further improve usability and encourage technology uptake. Additionally, personalization of technologies is important; content, communication, functionality and notifications should ideally be personalized in line with a patient’s diagnosis, health status and preferences.5

     In summary, health technologies must not only engage patients but also ensure they return to use them regularly. Solutions to improve user retention such as personalization and easy to use interfaces5 will further strengthen the use of technology in the healthcare space. To find out more about the potential for digital health initiatives, explore our article on mHealth, and to stay informed on the latest in healthcare innovation. Sign up for our monthly updates too here.

References

  1. Lebied M. 12 examples of big data analytics in healthcare that can save people. 2018. Available at: https://www.datapine.com/blog/big-data-examples-in-healthcare/. [Accessed October 2020].
  2. Brown T. Pros and Cons of artificial intelligence in healthcare. 2018. Available at: https://www.jamasoftware.com/blog/pros-and-cons-of-artificial-intelligence-in-health-care/. [Accessed October 2020].
  3. Medica magazine. Diagnosing disease with big data. 2018. Available at: https://www.medica-tradefair.com/en/News/Topic_of_the_Month/Older_Topics_of_the_Month/Topics_of_the_Month_2018/Big_data_in_diagnostics/Diagnosing_diseases_with_big_data. [Accessed October 2020].
  4. Dilsizian SE and Siegel EL. Current Cardiology Reports 2014; 16: 441.
  5. Ives J. Study shows how AI can improve physician’s diagnostic accuracy. Available at: https://www.news-medical.net/news/20190319/Study-shows-how-AI-can-improve-physicians-diagnostic-accuracy.aspx. [Accessed October 2020].
  6. Daley S. Surgical robots, new medicines and better care: 32 examples of AI in healthcare. 2020. Available at: https://builtin.com/artificial-intelligence/artificial-intelligence-healthcare. [Accessed October 2020].
  7. Sanyal S. 4 ways in which AI is revolutionizing respiratory care. 2018. Available at: https://www.forbes.com/sites/shourjyasanyal/2018/11/26/4-ways-in-which-ai-is-revolutionizing-respiratory-care/#3234717b318d. [Accessed October2020].
  8. Available at: https://www.fluidda.com/. [Accessed October 2020]
  9. Deloitte Insights. Predictive analytics in healthcare: emerging value and risks. 2019. Available at: https://www2.deloitte.com/us/en/insights/topics/analytics/predictive-analytics-health-care-value-risks.html. [Accessed October 2020].

October 2020 RESP-42184

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