How can we improve patient retention in clinical trials?

Maintaining high levels of patient recruitment, adherence and retention is essential for the successful completion of a clinical trial, yet it remains a significant challenge faced by researchers.  Poor patient adherence and retention can adversely affect a trial by lengthening timelines, adding cost and risk to the validity of the data and delaying product approval.

There are numerous factors which contribute to the slow process of attracting the patient to consider participating in clinical research studies. These include  lack of awareness of the critical role that clinical trials play, limited access to knowledge about clinical trials, lack of understanding about rights, safety and benefits and which are among the most common reasons for low participation. In terms of retention in the trial these include (i) patient-centred factors: such as demographic and psychosocial including beliefs, attitudes and motivation, severity; (ii) therapy-related factors: such as treatment complexity adverse reactions, lack of therapeutic impact; (iii) social and economic factors : including inability to take time off works, lifestyle patterns etc. (iii) Other factors: including clinical trial site location, frequency of clinic visits, clinic staff etc.

Development and integration of patient retention strategies that address the issues of patient perceived benefits, barriers and burden by leveraging both technology and communication is essential for addressing patient dropout. However, traditional thinking would have us believe that an individual’s decision to stay in or drop out of a clinical trial is based solely on the patient acting rationally.

At DHP Research we are bringing to our clients an approach which to quote Jules Berry “…shines a light on the factors that influence our actions” in an attempt to understand more the subtle and complex mechanisms that influences patient behaviour whether to stay or pullout of a clinical trial. It is to paraphrase Jules Berry,  viewing the solutions through the prism of behavioural economics.

What is behavioural economics (BE)?

BE is a multi-factor approach to the understanding of human behaviour that represents a paradigm shift in the traditional thinking that our behaviour is rational. Rather the principles of BE are that our behaviour is to a large extent unconscious, irrational and socially driven. Therefore, for any clinical trial retention strategy to be truly patient-centric it must  take account of these influences on patient behaviour throughout the different phases of a clinical trial.

The key characteristics of human behaviour outlined in BE are:

  • Personal factors: We don’t like change, we live in the here and now, we are averse to loss, we want a positive and consistent self-image
  • Social factors: We are heavily influenced by others
  • Local and choice environment: The environment matters, it’s hard work to think and choices are guided by salience of information and mental shortcuts

Lets illustrate how these might apply in a real world setting.

Personal factors: We think short term and avoid loss rather than achieve gain (loss-aversion).In other words we feel loss more keenly than gain. For example, offering an amount of points at the start of an exercise programme which could be exchanged for items or money on programme completion – but would be withdrawn for failure to adhere to aspects of the programme – is likely to be more effective in achieving adherence than accumulating points from zero.

Social factors: In addition to our need to retain a positive self-image, individual decision making is heavily influenced by others – the power of the messenger – rather than the message itself. It is certainly true our behaviour can be be influenced by experts and authority, but the people like us (our peers) have tremendous influence over what we do.

Knowing which groups of people are likely to be be influential is a key question in developing a patient retention strategy and one that only research can address but, patient groups and their communications for example through social media and mobile phone apps could have a significant  influence on trial participants to stay in.

Choice environment factors: When it comes to making a decision or choice as humans we don’t like to think too much. We can’t attend to and process all available information. Too much information, too many messages leaves us unable to cope and our system 1 thinking – perceptual, intuitive, influenced by emotion – kicks in to help us make decisions on judgements that come easily to mind.

When it comes to choice things that come to mind easily are considered important and decisions are often influenced by the salience of the information readily available. For example, we are less likely to participate in a clinical trial  because we know someone who had a bad experience and withdrew. This is known as as the availability heuristic which results in the individual giving too much emphasis to small probabilities.

As individuals we priorities information that supports our existing beliefs and will filter information that supports those beliefs. Related to this is anchoring and occurs when we are presented with a piece of information we then use as an anchor for all subsequent information. For example, if patients are told that in previous studies that chances of adverse reactions was 8% this will serve as an anchor for the expected adverse reactions in the current study whether this is high or low.

Information such as this can be communicated in different ways and which can have a profound effect on choice For example, at a trial recruitment stage patients are told there’s a one in 25 chance of having an adverse reaction it’s more than likely the majority of patients will think this as extremely risky. However, informing patients the treatment is 96% reliable will more than likely be considered as very safe. Neither of these values is strictly “the truth” but they provide a perspective which is known as framing where the salience of information is created by presenting the more positive side of the problem.

Salience can also effect what we remember which is usually shaped not by the average way we felt about an experience but, rather at the peak and end of the experience. We use a mental shortcut to remember the most salient aspect of the experience. For example, having met interesting people at a party might be the salient thought about the party and will have significant impact on your choice to accept another invitation from the host. For trial participants this would not be the overall experience of participating in the trial to that point that comes to mind, but for example, how they were made to feel the last time they attended the trial site or experienced an adverse reaction.

The effect of salience can be seen in our everyday lives such as the most popular/expensive  coffee and tea placed on the front of shelves, chocolate and crisps next to the till.

Ensuring trial participants have a positive experience at the trial site is critical for ongoing patient participation not only for increasing the salience of that positive experience for example through 1 to 1 discussions with patients about their well-being and attitudes and experiences of participating in  the trial but, also as an opportunity to reinforce the salience of positive aspects of the trial.

This post has described just some of the key aspects to illustrate how BE can provide an added dimension to understanding behaviour. Through the careful assessment of these behavioural factors using different research techniques we can build a framework that helps us explain how these factors relate to behaviour in different situations. There are however, questions still to be answered such as the importance of each factor.  Do the factors work together? How do the factors work at the individual level? Are the factors equally important for different disease groups and trial? Yet despite this and as yet not  being able to make accurate predictions, behavioural economics does have the potential to be a real game changer in understanding some of the subtle and complex mechanisms that influences patient participation in clinical trials.



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