Chronic conditions  impact 6 in 10 Americans, according to estimates by the Centers for Disease Control and Prevention (CDC). Many of those patients are prescribed medication to treat their condition; however, medication non-adherence in patients with chronic conditions remains a significant healthcare challenge. 

The consequences of non-adherence can be costly in more ways than one. Non-adherence to chronic disease medications not only costs  around $290 billion each year in avoidable healthcare spending, but also leads to increased hospitalizations, worsening health conditions, and even mortality.

Certain conditions have unique barriers that make them more prone to non-adherence. What’s more, the conditions with the lowest adherence rates tend to be those with the greatest  consequences when patients don’t properly follow drug regimens. In this article, we discuss the conditions with the biggest adherence challenges:

Which Conditions Have the Lowest Adherence Rates?

5 Health Conditions with the Lowest Medication Adherence Rates

  1. Mental Health

Mental health conditions are some of the most difficult to manage—and it shows in adherence rates. A 2020 study showed that adherence rates to  psychotropic medications were 56 percent for schizophrenia, 50 percent for major depressive disorder, and 44 percent for bipolar disorder.

Non-adherence to mental health medications  is associated with poor outcomes, such as psychiatric hospitalization, substance abuse relapse, negative social outcomes (e.g., arrest, job loss), and an increased risk of suicide.

  1. Hypertension

Medication adherence is critical to the success of hypertension management for patients with high blood pressure. However, Million Hearts reports that  only 51 percent of Americans treated for hypertension follow the long-term medication therapies prescribed to them. In addition to uncontrolled hypertension, poor adherence is  linked to adverse cardiovascular events, including coronary syndromes, stroke and transient ischemic attack, chronic heart failure, and mortality.

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  1. Diabetes

Research by the Behavioral Diabetes Institute indicates that  poor medication adherence is very common among patients with diabetes. In fact,  nearly 50 percent of patients with diabetes struggle (and ultimately fail) to reach their glycemic goals.  Diabetes medication non-adherence can have significant negative consequences, ranging from inadequate glycemic control to increased emergency room visits, hospitalizations, and mortalities.

  1. Asthma

Asthma is another condition with poor adherence rates. Barriers to asthma medication adherence range from not knowing how to use an inhaler and fearing insulin injections to struggling with complex dosing regimens and denying one’s condition. As such,  preventing non-adherence in asthma patients is difficult for many healthcare organizations.

  1. Cancer

Adherence is an unmet challenge for oral anticancer medications (OAMs). There are a myriad of reasons for non-adherence to cancer medications, from rising out-of-pocket drug costs to limited access. Whatever the reason, deviation from 100% adherence is serious and can result in  significant treatment failures for patients with various cancers. 

Improving Medication Adherence Interventions with Smart Data

Despite the significant challenges posed by non-adherence to medications for chronic conditions, there are still steps that pharmaceutical companies, pharmacies, payers, and prescribers alike can take to drive improvements. 

Artificial intelligence (AI) has emerged in recent years as a highly effective tool for  improving patient support programs and overcoming barriers to adherence. How? The answer lies in  smart data, predictive analytics, and personalization. 

Using an  AI engine like AllazoHealth’s helps healthcare organizations identify the right patients—who are both high risk and most likely to be influenced—and the optimal intervention channel, messaging, timing, and frequency for each of them. 

The result? 

Better engagement, better adherence, and better outcomes.

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