Low Rx Adherence Brings High Costs

The concept is simple. Low adherence to prescription medication brings higher overall medical costs. When patients fail to take their medications as prescribed, consequences can include a worsening of health and an increase in further medical expenses. Despite this fact, studies have shown that more than 50% of patients in numerous disease categories are not adherent to their medications. So how can we combat this trend? 

Targeted Analytics 
Plans can benefit from a tailored approach to managing the member population through targeted analytics. Using targeted analytics, plan sponsors analyze their population data to pinpoint at-risk areas. 

Populations can be targeted based on disease state (diabetes, hepatitis C, etc.), drug/category (opioids, drug-drug interactions, etc.) or age/gender. For example, when looking at your cost and utilization data, are there certain disease states that have runaway costs? Are there certain drugs or therapeutic categories putting people at risk or causing a spike in spending? What about age groups or gender – can you drill into your data to determine if certain groups are not behaving as expected?

Once those high risk populations are determined, the plan can then benefit from targeted clinical programs.

Population-Specific Clinical Programs 
Using what is known about the high-risk member population, plan sponsors can implement tailored health outreach through population-specific clinical programs. Commonly, we recommend clinical programs that focus on:

  • Education: how to use medications, avoiding drug-drug interactions, managing side effects, importance of adherence
  • Changing behavior: using preferred drugs versus non-preferred drugs, brand versus generic, refills, etc.
  • Saving money: less expensive alternative options for high-cost drugs such as over-the-counter medications
  • Programs should be not limited to the member – it may help to engage prescribers or pharmacies as appropriate to achieve the results. After the clinical program is implemented, plan sponsors should re-evaluate the data to see how the outreach worked.

Non-Adherence and Diabetes: An Example 
There’s no better illustration of the impact of non-adherence and ways to address it than the diabetes disease category. Diabetes is one of the most costly and concerning conditions for employers and plan sponsors, with more than 114 million Americans – or 1 in 3 – diagnosed with diabetes or are pre-disposed to diabetes and an average of $9,000 per person spent by employers.

Patients who were adherent to their diabetes medications avoided more than $210 million in healthcare spending in 2016. Likewise, non-adherent patients face more diabetes-related complications, resulting in 9.4% higher healthcare costs.

When analyzing diabetes adherence within your population, factors for adherence like age, gender, and pharmacy channel may come into play. For example, you would be able to identify the age and gender with the lowest adherence and establish recommended changes that will improve adherence within that group, such as providing a 90-day supply of medication and perhaps having that 90-day supply delivered through mail rather than retail. Then, after conducting your targeted outreach, plan sponsors can review newer analytics to see results, make adjustments, or begin a new outreach with a new population target.

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