Patient preferences – does offering choice improve treatment outcomes?

If you had a condition that could be treated with a single operation that carries risks, or with a series of physiotherapy sessions, which has fewer risks but will take longer, which would you choose?

A post last week on our blogs looked at participatory medicine and what the meaning of ‘participation’ in this context is. Clearly, an element of patient participation is their ability to express a choice in the type of treatment they’re offered.

The choice is down to individual preference, personal needs, circumstances and motivation. These perspectives are becoming increasingly recognised by clinical and policy decision makers and should pave the way for improved patient satisfaction, in addition to outcome and cost-effectiveness of medical care.

The implementation of strategies for involving patients in decision making does not come without costs or complexities. It is important to identify exactly which criteria should be used to label a decision as preference-sensitive, and how guidelines should be adapted to support patients’ and healthcare professionals’ shared decision making.

Discrete choice experiments (DCEs) have often been used to elicit patient preferences for health care, and to quantify the trade-offs that respondents make between the various attributes that characterise a treatment e.g. efficacy, side-effects, costs, mode and frequency of administration.

One such study, which presented patients with hypothetical osteoporosis drug treatments, found that respondents were willing to pay a personal contribution of $19.53 per month or to give up 13.52% of a drug’s efficacy to have an injection every six months rather than a weekly oral tablet.

In terms of side-effects, participants expressed greater concern with the risk of developing gastrointestinal disorders than with the risk of skin reactions and flu-like symptoms. Lead author Mickael Hiligsmann commented, “This evidence demonstrates that maximising treatment efficacy and safety is not unequivocally important to all patients, particularly if at the cost of less convenient administration attributes.”

Understanding patient preferences for treatment can help clinicians administer treatments that patients like (and presumably will take). According to NICE, between 30-50% of medicines prescribed for long-term conditions are not used as prescribed. Intentional non-adherence, such as under-dosing, of analgesics, in particular, appears to be driven by factors including the fear of addiction and the burden of increased pill loads.

The Medication Decisions in Osteoarthritis Study (MEDOS) assessed the factors that influence the decision to continue with a medication, in a clinical trial population symptomatic for this chronic disease. 24% of participants reported intentionally stopping or altering the dose of their treatment, despite having a high level of trust in their primary care physician. Again, treatment efficacy did not significantly influence patient choices; costs, side effects and treatment schedule were more important. It’s clearly important, therefore, that patient medication decision-making is supported through the provision of explicit risk/benefit information to the patients.

With the wealth of information already available on the internet and social media websites, patients are starting to take control of their health. As Hood and Auffrey discuss in their recently published editorial on participatory medicine, patients are beginning to question whether they want to have physicians who do not know anything about their ‘data cloud’; their genomes, or nutrition or wellness. Bringing all the necessary participants into alignment around P4 medicine (predictive, preventative, personalised and participatory) is an enormous challenge.

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