Pharma is taking adherence seriously. A recent report showed that 71 per cent of companies now have dedicated in-house adherence departments – with the vast majority of these teams established in the last three years – and the average adherence budget has increased by 331 per cent from 2009 to 2012, and nearly doubled from 2011 to 2012. In Europe this is currently reported to be $1m, whereas in the US it is $1.5m.
The growing focus on adherence can be attributed to mounting pressures from healthcare systems to optimise the use of medicines and limit waste in medical spending. A report from the IMS Institute for Healthcare Informatics published in 2012 showed that approximately five per cent of global health expenditure, or $269bn, could be saved through better adherence to treatments.
More importantly, there’s now strong evidence that better adherence to treatment and lifestyle guidance will ultimately deliver better health outcomes for the patient. To put this in context, the five year survival rate for breast cancer patients who were over 85 per cent adherent to treatment was 77 per cent – this dropped to just 48 per cent in those who were under 65 per cent adherent.
An evidence-based approach
“The evidence clearly shows that simply providing information or reminders is not enough to encourage adherence,” explained Prof John Weinman, a prominent researcher in the field of patient adherence, speaking at the Patient Adherence Seminar in Brussels earlier this year. According to the Cochrane review, there are a number of reasons why adherence interventions typically fail: “Current methods of improving adherence are mostly complex and not very effective, so that the full benefits of treatment cannot be realised. High priority should be given to fundamental and applied research concerning innovations to assist patients to follow medication prescriptions for long-term disorders.”
In order to tackle the problem, it’s necessary to understand the varying types and causes of non-adherence. Interventions should then be tailored accordingly.
According to Prof Weinman, there are two types of non-adherence: unintentional non-adherence – where there are practical barriers, such as poor communication between the patient and their healthcare professional, or financial barriers to purchasing treatment – and intentional non-adherence, which is when the patient’s perceptions, such as illness and treatment beliefs and motivations, lead to non-adherence.
A broad range of factors can influence a person’s decision not to take treatment as prescribed. However, research clearly shows the key beliefs that influence adherence to treatment are a patient’s perceptions of illness and his or her perception of their treatment.
In order to create a framework to measure and identify unhelpful health beliefs in patients, Professor Weinman and his fellow researchers developed the Illness Perception Questionnaire – a method for assessing the cognitive representation of illness. This pioneering new method was first published in 1996. The thinking in this area continued to evolve and subsequent research showed that illness beliefs per se were not strong predictors of treatment adherence alone, and that other more proximal predictors needed to be considered, such as the beliefs patients hold about their treatment. This led to the creation of the Beliefs about Medicines Questionnaire (BMQ), a novel method for assessing cognitive representations of medication, published by Robert Horne, John Weinman and Matthew Hankins in 1999.
The BMQ is now widely recognised as the industry standard framework for predicting non-adherence, and is being applied at the outset in a growing number of patient support programmes.
Designing a patient support programme that works
To put the theory into practice and to illustrate how an effective patient support programme should be designed, the Understand.Connect.Change methodology was developed:
Understand
The first step is to set objectives for the programme. For example, disease management programmes that span multiple treatment types have very different goals from risk management programmes that are designed to manage and report on patient safety for specific treatments. Programmes are often driven by very different goals, including improving treatment adherence, improving the patient experience while on treatment, increasing brand awareness – not to mention differentiation, ROI and managing patent expiry. The design of the programme will vary depending on the priority objective.
Once objectives have been clearly defined, key performance indicators (KPIs) can be set, along with a measurement framework, so that outcome reports can be issued to measure the impact of the programme.
At the start of the project, patient research is usually required to better understand the patients the programme is targeting. Too often, research focuses on demographic factors, such as a patient’s gender, income age and race. Evidence clearly shows that in order to drive healthier behaviours, patient research must delve much deeper into the psychology of a person’s health beliefs about his or her condition and treatment. It’s crucial to understand this level of research before any effective intervention can be designed.
It’s also essential to understand the legal and regulatory frameworks that govern the rules of adverse event reporting and data protection laws. This is particularly important when working across markets, as governance will vary widely. Regional industry bodies all have strict guidelines for how adverse events should be reported, so a clear reporting strategy must be implemented.
Patient data collected in the context of a patient programme is considered by default as a sensitive personal data, so robust standards must be in place to safeguard the privacy of this information.
Connect
The way in which support is delivered to patients is an exciting arena of change. For example, there are currently more than 40,000 healthcare apps available for download from Apple iTunes. The majority of these apps are designed to provide health instructions, but as we know, information alone does not change behaviour. This is why the content delivered by any channel – such as a nurse call, traditional print media or an app – must be geared towards that person’s individual beliefs. And they must, of course, be engaging enough for them to want to use.
Change
Outcomes are no longer a ‘nice to have’ but an essential element of any health initiative. Any patient support programme worth its salt will have a measurement framework to track the number of patients enrolled, persistence to product and satisfaction with the programme. Measuring adherence shifts, treatment discontinuation rates, quality of life and long-term changes in health beliefs and behaviours are key areas to assess – but it can take a number of years to build a robust dataset.
In order to demonstrate these outcomes, it is important to be clear on what you can and can’t measure. It is very easy to tie yourself in knots if the measurement strategy is too ambitious or not practically achievable.