Personalizing adherence support with Patient Support Programs

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Personalizing adherence support with Patient Support Programs



Patient Support Programs are behavioral interventions designed to improve adherence

The World Health Organization has identified medication non-adherence as a priority, preventable global healthcare problem that affects more than 60% of patients with cardiovascular disease and exacerbated by socioeconomic conditions in less-industrialized countries. Previous articles in this series discuss patient decision-making, behavioral drivers, and other factors that influence treatment adherence. There are a variety of frameworks healthcare providers can use to evaluate a patient’s risk of non-adherence and to identify effective strategies for assisting patients in following their treatment plans.

Wrap-around interventions have been developed to support patients, encourage them to be comfortable with their treatments, and correctly adhere to their prescribed therapy. Commonly called Patient Support Programs, or PSPs, these solutions can include simply labeled pill boxes or blister packaging to routinize medications or more intensive services rooted in behavioral science frameworks.1,2 PSPs can either be provided directly by a healthcare provider’s office or via sponsored off-site programs. With the prevalence of digital technology, mobile health solutions (mHealth) are increasingly included in PSPs. Approximately 95% of the global population lives in areas covered by a mobile-cellular network.3 Some evaluations have found that PSPs4 coupled with mobile solutions1 have a significant effect on adherence and improve health outcomes. However, such programs often lack a personalized approach.5,6 Personalization uses artificial intelligence (AI) and is increasingly popular in online marketing to anticipate customers’ needs and tailor recommendations.11 Similarly, the latest PSPs are digital solutions incorporating behavioral science to provide personalized support. These programs represent a significant opportunity to improve adherence and patient outcomes.


The latest Patient Support Programs incorporate mobile health solutions for broad adherence support

The development of mobile technology over the last decade has made broad dissemination of medical and public health support both possible and cost-effective. Mobile phone subscriptions are estimated at 7 billion globally;3 particularly in developing countries, simple text message interventions are an important tool for quickly and easily reaching a broad patient population. This allows healthcare providers to more easily interact with a greater number of patients.2 Texting elements have become a common component of effective PSPs; however, SMS messaging is still subject to privacy regulations. mHealth solutions enable improved remote patient monitoring, education, reminders, and other forms of adherence support.7 Text messaging has already been used with positive results in behavior change communication such as appointment and medication reminders; health promotions, such as smoking cessation, contact tracing, and community mobilization; and can improve adherence among patients with chronic diseases.3

Evidence that text messaging improves adherence for cardiovascular disease medications has been promising, but further research is required.8, 9 These interventions are generally centered on reminders addressing forgetfulness, which is only one facet of improving adherence. Digital interventions also present a major opportunity for patient education,10 which can be enhanced by personalization to reflect the rapport between patients and their providers. To optimize the patient’s experience and overall program effectiveness, digital PSPs must include a degree of personalization that can address individual risk levels and various behavioral drivers.2

Effective Patient Support Programs are personalized to the patient

The application of behavioral science theories to personalize adherence interventions and PSPs remains a significant area of opportunity to improve patients’ health and outcomes.5, 6  Solutions can be customized to the individual patient according to the nature of their needs and non-adherence drivers.2

However, PSPs still face a number of challenges to effective personalization:

  • Existing adherence models are not digitally compatible. Most PSPs do not have the capacity to collected frequent, real-time, and reliable information about patients’ behavior – a requirement for effective decision-making and AI customization. However, the latest personalization research is building on various behavioral science models using questionnaires to profile patients and generate an actionable, digitally compatible model of patient adherence.2
  • Additional effort by the patient is required. Personalization models require patients to report data about their health and behavior more frequently. This is  a burden that patients may not be willing to undertake, especially if they do not recognize the added benefit of the PSP.

Despite these challenges, PSPs and personalization can have significant potential, as illustrated by the following example of a patient with hypertension at a clinic for a regular checkup: By following the frameworks previously discussed and making theory-driven inquiries, the healthcare provider recognizes that the patient is not managing their diet and salt intake properly and is not taking their medication as directed. The provider also learns that the patient does not see himself as being responsible for managing hypertension, i.e. he has low activation. The healthcare provider recommends that the patient enroll in the Atlas Clinic Hypertension Support Program to learn more about managing their symptoms, the importance of healthy lifestyle behaviors, and the value of adhering to hypertension treatment. With the patient’s consent, the healthcare provider immediately enrolls the patient via text message in the 90-day program provides him with printed educational materials on diet and the benefits of various treatments. A few days later, the patient receives an enrollment call from a program specialist who asks questions, again based on the behavioral science frameworks previously discussed, to assess the patient’s beliefs, attitudes, confidence, behaviors, and knowledge. A digital profile is automatically generated for the patient with suggestions for the type and timing of support to be provided. During the program, the patient receives regular text messages with coaching and information on managing hypertension and his treatment, as well as telephone counseling. As a result of the PSP, the patient develops a better understanding of his condition and the importance of adhering to treatment and is empowered and supported in his efforts to follow the treatment recommended by his provider.

Patient Support Programs help healthcare providers support their patients

Enhancing the effectiveness of the provider-patient relationship using behavioral science theories and extending the impact of the provider’s influence into the patient’s daily life can significantly improve outcomes. Using the methods covered in this series to assess their patients’ risk of non-adherence and provide targeted support, providers can improve their interactions with patients; digital adherence solutions and PSPs can enhance these efforts even further while alleviating provider time constraints. Value is created for patients through more tailored education, reminders, and other forms of support. Personalized digital tools and “nudge” techniques engage patients and increase the effectiveness of PSPs. While nudge techniques presented cannot replace a direct and informed therapeutic approach, they can be used to supplement provider/patient interactions. Healthcare providers are uniquely positioned to educate patients and encourage them to take advantage of the benefits offered by engagement with PSPs.  The final article in this series, << How do Patient Support Programs impact adherence? >> , will discuss in more detail different strategies employed by PSPs, their benefits for patients, and their effect on adherence.


1. Yousel Gandapur et al. (2016). “The role of mHealth for improving medication adherence in patients with cardiovascular disease: A systematic review,” European Heart Journal – Quality of Care and Clinical Outcomes, (2):4, pp. 237–244. https://doi:10.1093/ehjqcco/qcw018

2. Kevin Dolgin (2020). “The SPUR Model: A framework for considering patient behavior,” Patient Preference and Adherence, 14, pp. 97–105. https://doi:10.2147/PPA.S237778

3. Sarah J. Iribarren, Sarah et al. (2017). “Scoping review and evaluation of SMS/text messaging platforms for mHealth projects or clinical interventions,” International Journal of Medical Informatics, 101, pp. 28–40. https://doi:10.1016/j.ijmedinf.2017.01.017

4. Arijit Ganguli, Jerry Clewell, & Alicia C. Shillington (2016). “The impact of patient support programs on adherence, clinical, humanistic, and economic patient outcomes: A targeted systematic review,” Patient Preference and Adherence, 10, p. 711. https://doi:10.2147/PPA.S101175

5. Bart J.F. van den Bemt et al. (2012). “Medication adherence in patients with rheumatoid arthritis: A critical appraisal of the existing literature,” Expert Review of Clinical Immunology, (8):4, pp. 337–351. https://doi: 10.1586/eci.12.23

6. Susan Michie et al. (2011). “The behaviour change wheel: A new method for characterising and designing behaviour change interventions.” Implementation Science, (6):42. https://doi:10.1186/1748-5908-6-42

7. Sven Meister, Wolfgang Deiters, & Stefan Becker (2016). “Digital health and digital biomarkers – Enabling value chains on health data,” Current Directions in Biomedical Engineering, (2):1.

8. Alma J. Adler et al. (2017). “Mobile phone text messaging to improve medication adherence in secondary prevention of cardiovascular disease,” Cochrane Database of Systematic Reviews, (4):4. https://doi: 10.1002/14651858.CD011851.pub2

9. Melissa J. Palmer et al. (2018). “Mobile phone‐based interventions for improving adherence to medication prescribed for the primary prevention of cardiovascular disease in adults,” Cochrane Database of Systematic Reviews, (6):6. https://doi:10.1002/14651858.CD012675.pub2

10. Roderick W. Treskes et al. (2018). “Implementation of smart technology to improve medication adherence in patients with cardiovascular disease: Is it effective?” Expert Review of Medical Devices, (15):2, pp. 119–126. https://doi:10.1080/17434440.2018.1421456

11. Shabana Arora (2016). “Recommendation engines: How Amazon and Netflix are winning the personalization battle,” MarTech Advisor, June 2016. Accessed 25 May 2020.