The impact of Patient Support Programs on adherence: enhancing engagement and improving effectiveness
- PSPs are designed to boost adherence; some have significant impact, however, other programs have been shown to have limited success
- PSPs should have their basis in behavioral science theories and incorporate a mixture of informative and behavioral strategies to enhance their effectiveness
Patient Support Programs are designed to boost adherence
Patient Support Programs (PSPs) employ a variety of techniques to help patients follow their treatment and deal with their conditions.1
Some are purely informative and provide practical information to patients on topics such as disease management and drug management (especially for complex drugs), etc. The channels through which patients receive this information might be limited to printed or electronic materials, but may include web-based interventions.1 While it is crucial to provide important information to patients, the impact on non-adherence of PSPs that limit themselves to information provision and patient education is often low; it is not sufficient in isolation.2
Other PSPs are purely behavioral, involving individually tailored adherence-focused sessions and nurse-assisted patient support programs.1
Reaching patients who would otherwise be non-adherent can be best achieved by PSPs that are based on a mix of both informative and behavioral strategies, based on the principles of behavioral science. This approach was supported by a meta-analysis conducted in 2015 of 17 PSPs (covering inflammatory and immunologic diseases, such as rheumatoid arthritis, osteoporosis, ulcerative colitis or multiple sclerosis) which employed information strategies, behavioral strategies or mixed strategies (behavioral and informative strategies).1
The results showed that patient programs increased adherence compared with standard of care, and that combination programs using both informational and behavioral strategies were superior in improving adherence vs. programs using only informational or only behavioral approaches.1
While this study was restricted to certain pathologies, these results lead to the conclusion that a careful mix of informational and behavioral strategies may be a means by which to generate significant impact and avoid the mixed results of less structured interventions.1
The current evidence supports the use of text-messaging programs and smartphone apps in cardiovascular disease (CVD) care; studies have demonstrated reduced CVD risk and improved medication adherence with text-messaging programs.3 In a review of seven trials of patients with cardiovascular disease, six of the trials found a beneficial effect of interventions with text messaging; however, the included studies were small, and the quality of evidence was considered to be low.3 As an evolving area of investigation, more evidence is needed to confirm the benefits of smartphone apps, for example.3
The future of PSPs: will personalization through behavioral sciences and digitalization increase adherence?
In 2003, the WHO cited RB Haynes in saying that “increasing the effectiveness of adherence interventions may have a far greater impact on the health of the population than any improvement in specific medical treatments”.4 However, we have seen that these interventions, in the form of PSPs, must be carefully constructed to add value.
One promising design approach is PSP personalization. This allows the mixture of information communication and more coaching-oriented approaches to be determined on an individual basis, tailoring the specific information and behavioral content, as well as the tone of these interventions, to each individual.5 Screening questionnaires are available to assist in profiling patients.6 The SPUR (Social, Psychological, Usage, Rational) framework is a holistic profiling tool with detailed, quantitative outputs that describe a patient’s behavioral risks and the drivers of that risk.5
A personalized approach can now be applied on a larger scale thanks to advances in digital and mobile technology. Mobile technology has the potential to make healthcare better, faster, less costly and more accessible.7
Mobile health has shown promising results in improving medication adherence, allowing monitoring and real-time analysis of health data, while also enabling patients become more engaged in managing their condition through highly personalized tools.7
Recent developments in the behavioral sciences allow greater understanding of the decision- making process of each patient, and, therefore, can be far more effective in determining individual “nudges” for patients on the basis of their behavioral profiles.5 Digital technologies that leverage behavioral-science techniques effectively can enhance patient experience.5,8
The effectiveness of personalized approaches using digital technologies has already been demonstrated in consumer-based industries such as e-commerce; Companies like Amazon thrive thanks to the personalization approaches they use.9
The same principles can be applied to patients: for example, a “chat-bot” with a virtual “patient-coach” that helps the patient manage their disease and treatment and is always available via their smartphone, tablet or computer.10 These chat-bots may potentially improve communication between patients and healthcare professionals, and allow medication adherence to be monitored remotely.8
Such chat-bots have only recently been launched in the healthcare sphere, and their acceptability is yet to be determined.8 However, they offer new possibilities for PSPs in addressing non-adherence, allowing the positive influence of healthcare providers to be extended into the patient’s daily life.8
- Burudpakdee C, et al. Impact of patient programs on adherence and persistence in inflammatory and immunologic diseases: a meta-analysis. Patient Prefer Adherence 2015;9:435–48.
- Jackson C, et al. Applying COM-B to medication adherence: a suggested framework for research and interventions. Eur Health Psychol 2014;16(1):7–17.
- Santo K and Redfern J. Digital Health Innovations to Improve Cardiovascular Disease Care. Current Atherosclerosis Reports 2020;22:71.
- World Health Organization. Adherence to Long-Term Therapies: Evidence for Action. 2003.
- Dolgin K. The SPUR Model: A Framework for Considering Patient Behavior. Patient Prefer Adherence 2020;14:97–105.
- Weinman J, et al. Pilot Testing Of A Brief Pre-Consultation Screener For Improving The Identification And Discussion Of Medication Adherence In Routine Consultations. Patient Preference and Adherence 2019;13:1895–98.
- Gandapur Y, et al. The role of mHealth for improving medication adherence in patients with cardiovascular disease. Eur Heart J Qual Care Clin Outcomes 2016;2(4):237–44.
- Nadarzynski T, et al. Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digit Health 2019;5:2055207619871808.
- Arora S (Martech Advisor). “Recommendation Engines: How Amazon and Netflix are Winning the Personalization Battle”. Available at: https://www.martechadvisor.com/articles/customer-experience-2/recommendation-engines-how-amazon-and-netflix-are-winning-the-personalization-battle/ [Accessed Jan 21, 2020].
- Chaix B, et al. When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot. JMIR Cancer 2019;5(1):e12856.