Suneeta Kumari, MD

The impact of nonadherence is staggering. It is estimated that at least 50% of patients with chronic health conditions are nonadherent; 20% to 30% of prescriptions are 

 In the US, nonadherence is responsible for an estimated 125,000 deaths and between $100 to $300 billion in medical costs annually.

Treatment nonadherence in patients with psychiatric disorders is similar or higher than with other chronic conditions. At least 61% of patients with schizophrenia, 57% of patients with bipolar disorder, and 52% of patients with depression had problems with adherence.

 Even with depot medications, many patients are treatment nonadherent within one year.

Measuring adherence is tricky. Adherence to treatment occurs on a spectrum from total adherence to total nonadherence. It is also a dynamic process-patients can be selective in their adherence, and their adherence levels can change over time. The definition of adherence also varies: nonadherence is defined as patients missing medications from 20% to 50% of the time.

Adherence is almost always overestimated. Most studies use pharmacy prescription claims data as a proxy for adherence. Most commonly used measures are Medication Possession Ratio (MPR) and the Proportion of Days Covered (PDC). MPR is the ratio of the number of days for which a patient has medications on hand divided by the total number of days the patient was observed. Because the assumption is that nonadherent patients are unlikely to fill their prescriptions, MPR is likely to overestimate adherence for patients who fill their prescriptions. The Proportion of Days Covered (PDC) can be more accurate. It uses several “covered” days for which patients have medications on hand. However, neither MRP nor PDC measure actual ingestion of medications.

Technology-based solutions are available that can closely approximate patients’ adherence. The Medication Event Monitoring System (MEMS) uses microtechnology to detect when a medication container is opened. This technology can be applied to smart pillboxes labeled with the day and time of each medication. The data are transferred via the patient’s cell phone to providers. MEMS can also send text messages to remind patients to take their meds.

Another approach is edible digital sensors embedded in the medication. The sensors are activated by gastric acid and send a signal to a remote monitoring system. In 2018, the FDA approved the first use of this technology for mental health disorders. A tablet formulation of aripiprazole was approved with a small (1 mm x 1 mm) sensor. Activated in the stomach it sends a signal to a wearable sensor worn on the chest. The data are then transmitted to a cloud server via a smartphone app, and can be accessed by the treating clinician.

Multiple factors play a role in nonadherence (

); most is attributable to patients’ perceptual factors. Findings from a 

 of patients with chronic health conditions indicate that 62% of patients forgot to take their medications, 37% reported running out of medications, and 23% were careless about taking medications.

Three themes of medication adherence came to light in a review of the literature on schizophrenia: perceived lack of control, risk of dependence on medications or provider, and stigma associated with medication use. Self-efficacy and an internal locus of control are positively correlated with medication adherence. While poor insight into illness is associated with higher rates of previous admissions and nonadherence.

Another predictor of adherence is physician related-the therapeutic alliance plays a key role in treatment adherence. A collaborative relationship, agreement on treatment tasks, and stability of the alliance are necessary elements of better treatment adherence. The patient needs to be involved in the decision-making process for treatment because factors such as medication dosage, pill burden, and regimen complexity influence adherence. Practical and financial issues also affect adherence: how difficult is it for the patient to get to appointments or pharmacies for prescriptions? Can the patient afford the copays for medications? An analysis of comprehensive Medicaid claims shows that the increase in medication copayment is directly related to nonadherence.

As expected, stigma and perceived criticism about mental health issues can have a negative impact on adherence. In a large study, self-stigma highly correlated with rates of nonadherence: patients with bipolar disorder had the highest rates of medication discontinuation at 65%, but living with a partner lowered the rates of self-stigma and decreased nonadherence.

 Symptom severity and overall level of disability also negatively affect adherence. Patients with depression and substance use disorders are less likely to be adherent.

Most of the research in treatment adherence targets barriers to treatment and relies on self-reported estimates of adherence. Studies have generally shown that improved engagement with patients results in greater adherence. Overall, multilevel interventions are likely to be more effective (

Psychoeducation has been the mainstay of intervention. Other interventions include family/peer support, pharmacist interventions, reminders to fill prescriptions by phone or text, even payment for medication adherence. However, the effect size of these interventions is small, and the relationship to clinical outcomes is unclear.

 found 182 intervention studies published between 2007 and 2013.

 These studies were extremely heterogeneous, and even the best quality studies that used multiple interventions demonstrated only small results. Five studies reported clinical outcome measures but did not show significant improvement; 60% of the studies were underpowered.

In a review of multiple studies, the results were mixed. The most frequent intervention was patient education and counseling, with positive results seen in half the studies. Interventions delivered by nurses and pharmacists had better results than those provided by physicians.

There are no studies that are specific to nonadherence in patients with psychiatric disorders. However, there have been reports of mobile health (mHealth) interventions that target nonadherence. mHealth uses smartphones and other wireless technology. Increasingly popular, a report from the Pew Research Center indicates that in 2017, 46% of patients used their cell phones or tablets to access health information.

 The most common way mHealth is being used is for education via smartphones apps. There are hundreds of thousands of health-related apps available for download.

The apps can be a useful and easy way to get information and measure certain behaviors; however, privacy is not assured, and they can be inaccurate. In a review of 571 mental health apps, 60% did not use validated screening tools and two-third of the apps did not provide a privacy policy. One exception is the app designed by the US Department of Veterans Affairs for the treatment of PTSD, which is of high quality and does not collect or share patient data.

Over the last decade, there has been a lot of interest in using Short Messages Service (SMS) for behavioral interventions. There are an estimated 300 million cell phones in the US, and most of the people use text messaging. Text messaging has been one of the most common interventions used to enhance adherence. A systematic review found that reminders such as phone calls were most effective.

Treatment nonadherence is highly prevalent with significant negative consequences, yet it is rarely addressed in routine clinical care. A high index of suspicion is needed to identify nonadherence and when identified, use evidence-based interventions address nonadherence.

Nonadherence should be addressed at multiple levels. Recent technological advances have made it possible to leverage mobile communications to improve adherence; however, a great need still exists for adequately powered studies to elucidate the mechanisms of and interventions for treatment nonadherence.

This article was originally posted on February 3, 2020, and has since been updated.

 is Clinical Professor, Johns Hopkins University, Baltimore, MD; 

 is Associate Professor, Howard University, Washington, DC.

The authors report no conflicts of interest concerning the subject matter of this article.

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 Patient adherence and medical treatment outcomes: a meta-analysis

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Interventions for enhancing medication adherence

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A number of factors affect treatment adherence, including the therapeutic alliance, perceived perceived lack of control, risk of dependence on medications, stigma associated with medication use, and more.

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