Failure to adhere to prescribed-medication regimens is one of the principal reasons patients don’t achieve the expected outcomes from their treatment. Solving this challenge has been a major goal for pharmaceutical and healthcare organizations for decades. Studies show that 50 to 60 percent of patients with chronic illnesses miss doses, take the wrong doses, or drop off treatment in the first year. An estimated 125,000 lives are lost annually in the United States and additional healthcare expenditures of $290 billion are driven by nonadherence. An estimated 10 percent of hospitalizations in older patients are considered avoidable through improved medication adherence. Beyond the primary goal of healthier and longer lives for patients, improved adherence also has a direct impact on pharmaceutical-industry revenues.

In this article we delve into insights from a McKinsey study that examined differences in adherence across diseases, and among branded medications treating the same disease. We find interesting variations among diseases and drugs that we will explore further in this article. The study applied a 360-degree approach to examine factors that may influence patient adherence (see “A 360-degree approach to patient adherence”). We analyzed select patterns in adherence data for the top branded medications in eight disease categories. The study principally examined patients in the United States, looking at pharmacy (prescription) data and medical claims using a data set covering millions of patients from Crossix Solutions, a data-analytics company. The data contain a host of patient characteristics, including psychographics, socioeconomic indicators, and consumer-purchase patterns, which are referenced in examples throughout.

There are three principle measures of adherence:

• Persistence. How long patients take a drug before either switching to a new drug or stopping treatment entirely. This is measured by how many patients continue to fill their prescriptions.
• Compliance. How closely patients follow the prescribed treatment plan. This is measured by how many persistent patients fill their prescribed doses on schedule, based on the approved product label. We have considered patients to be compliant if at least 80 percent of doses, according to approved product label, were filled within the study period.
• Adherence. Combined view of compliance and persistence, measured by the share of all patients, who fill their prescribed doses on schedule, based on the approved product label. Similar to compliance, we have considered patients to be adherent if at least 80 percent of doses, according to approved product label, were filled within the study period.

We explored two of these dimensions in our analysis: persistence and adherence.

Adherence varies widely among medications treating the same disease

As might be expected, adherence rates varied noticeably among the disease categories examined. Exhibit 1 shows adherence and persistence rates across diseases.

The data show a significant lack of adherence across disease categories, all of which are chronic in nature. Across diseases, 26 to 63 percent of patients do not adhere to the treatment regimen indicated by the approved product label. Further, after one year, 50 percent or fewer patients remained on their treatment across all the diseases analyzed.

Contrary to studies that suggest severe conditions tend to have worse adherence rates, our analysis showed that diseases with greater severity, measured by average disability-adjusted life years, tended to have higher median adherence rates. For example, two of the most severe diseases in the study—HIV and multiple sclerosis—had significantly higher median adherence levels than other diseases.

Interestingly, our analysis also showed that adherence variations can be greater among medications for a specific disease category than the median variations across disease categories. Exhibits 2 and 3 show the range of adherence and persistence rates, respectively, for medications in each of the studied disease categories.

Within disease categories, adherence rates differed by about 20 to 50 percentage points based on the medication being prescribed (Exhibit 2). For example, in ulcerative colitis, the medication with the highest adherence rate had about 65 percent adherence, while the one with the lowest was approximately 20 percent, a 45-percentage-point gap.

Persistence shows a similar trend (Exhibit 3), although variations within disease categories are even wider. More than half of the diseases analyzed had a range of more than 40 percentage points in persistence rates across medications. Psoriasis showed the largest variation, a 45-percentage-point gap between the best performer, 53 percent, and the worst, 8 percent.

A multitude of factors specific to individual brands could be affecting adherence. This is apparent even for brands in the same drug class with similar efficacy, cost, and delivery mechanism. For example, interferons in multiple sclerosis showed a 13-percentage-point difference in adherence between the best- and worst-performing medications.

These findings highlight the importance of identifying specific drivers of adherence for each individual medication or brand—indicating that it is important to understand the specifics of each medication or brand beyond just understanding the broad factors related to the disease category.