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John Pagliuca is Vice President for Business Development at SCIO Health Analytics.
Consumers of life sciences products are reluctant customers, and this reluctance can turn into non-compliance. Organizations and providers need to understand patients at a human level, and what will motivate them to stay with a treatment plan, writes John Pagliuca.
Most modern marketing is built on the premise of satisfying a desire or unmet need in the target audience. Whether it’s the momentary pleasure drawn from indulging in a sweet or salty snack, the prestige of owning a deluxe home, being seen in an upscale car, or gaining the admiration/envy of friends and family by becoming the first in one’s circle to own the latest technology gadget, there is already a built-in affinity for those products.
This is one of the aspects that makes life sciences unique – and challenging. No one wants to be placed on medication for hypertension, diabetes, or some other condition. No one wants to interrupt their day at regular intervals to take biometric readings. No one wants to be permanently hooked up to an oxygen tank. And they certainly don’t want to spend their hard-earned money on a specific medication rather than invest in that cool tech gadget.
The reality is, consumers of life sciences products are reluctant customers. They use medications and devices because they must, not because they want to. Eventually, this reluctance can turn into resistance, and ultimately into full or partial non-compliance. At that point no one is served – not the life sciences organizations whose products appear to be ineffective, not the physicians who prescribed them and are being held accountable for value-based outcomes, and not the patients themselves whose quality of life or even survival is threatened.
Often it is a question of motivation. To improve compliance, life sciences organizations and providers need to understand who patients are at a human level, and what will motivate them to stay with a treatment plan. That’s a complex challenge under the best of circumstances, much less in a healthcare culture where patient office visits are often schedule in 15-minute increments.
This is where life sciences organizations can take a cue from other consumer products marketers, who use sophisticated data analytics to develop personas that represent large segments of their customer base.
Personas are used to group individuals together based on key, shared characteristics. For example, a snack manufacturer will determine its product mix in a particular store or neighborhood based on factors such as median age, income, ethnicity, education, the types of homes in that area, and other information. It will then compare that information to models that show which products sell best in areas that match that profile and use predictive analytics to determine the optimal mix for stores in that area.
The predictive analytics technology is now available for life sciences organizations to use a similar approach to determine the barriers to compliance, and the triggers to use to improve it. The challenge is in obtaining the proper data to feed into the analytics.
The typical clinical or claims data that is readily available to life sciences organizations is not enough. Building powerful, accurate personas requires outside data, such as zip+4, credit card, socioeconomic, psychographic, and attitudinal data as well. Following is an example of what this data can do to improve the situation.
Physicians will often tell patients with uncontrolled diabetes that they need to “eat healthier and get more exercise” in addition to taking their medication. While this is sound advice, it may not be practical given a particular set of patients’ circumstances, leading to non-compliance.
Personas can get to the “why” behind non-compliance. For example, zip code data may show that there is a high density of fast food restaurants near a patient’s home, and few stores that sell healthier choices. It also shows the patient lives in an urban area where transportation is challenge. These factors demonstrate the difficulty the patient will have in changing diet, which will limit the effectiveness of medications.
If the commercial effectiveness team can show physicians in that area what these challenges are, and use personas to suggest ways to overcome them, they can improve compliance and performance for all.
Life sciences organizations can use personas to uncover compliance issues around prescribed medications as well. In this case, zip code and demographic data may show that patients live in a high population density area, leading to a high probability they live in an apartment building with a small mailbox. As a result, prescribing bulk mail order medications for a chronic condition will likely result in a need for the patient to go to the post office to pick up the medications.
If the nearest post office is several blocks away and the patient has mobility and/or transportation challenges, there is a high likelihood the patient will not pick it up right away, especially given any reluctance or resentment around taking the medication in the first place. If the physician understands these issues, however, they can be addressed through social services or other means in order to improve compliance.
Credit card information can be used to pull purchase histories that show whether patients who fit a particular persona tend to purchase store brands or generic products over name brands. This pattern can be an indicator of financial concerns – consumers tend to prefer store brands when they can afford them – which commercial effectiveness teams can take into account when calling on physicians.
Attitudinal data can also be of great value when creating plans to improve compliance. Personas that are built with attitudinal data can again help uncover barriers to as well as motivations for compliance.
In some cases, patients may be reluctant to take a particular medication because it would mean they are admitting they have a chronic condition, and they are not ready to face that yet. In these cases, professional or peer counseling could be arranged to help overcome it.
In others, it may be cultural. For example, parents who fit a persona within an area where American football dominates the youth sports landscape may try to hide the fact their son has asthma so it doesn’t hurt his chances of making the team or becoming a starter.
Understanding attitudes as well as empirical factors can help overcome these types of issues and drive compliance even higher.
Life sciences organizations face unique challenges in getting consumers to use their products. It’s generally not something anyone would choose – but definitely necessary for their own good.
By using personas to gain a peek behind the curtain, life sciences organizations can help physicians create strategies that overcome that natural reluctance and ensure patients become actively engaged in their own care.
John Pagliuca is Vice President, Life Sciences at SCIO Health Analytics.
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