The Importance of Effective Measurement for Fostering Change
Abstract and Keywords
This essay examines issues relevant to the accurate assessment of patient adherence to recommendations for health behavior change and/or the management of medical conditions, including long-term chronic diseases. Both conceptual and methodological issues are discussed. The importance of accurate assessment in both clinical practice and research is examined, as well as the consequences of conceptual and measurement biases. The role of assessments of current adherence in predicting future behavior is examined, as is the essential distinction between assessing adherence as a behavior and assessing the predictors and consequences of adherence. The potential challenges of various approaches to assessing adherence accurately are examined, focusing particularly on self-report; measurement scales for adherence are presented; and innovative techniques are discussed for assessing adherence using technologically based formats. Effective communication is emphasized as the most important and salient element relevant to adherence assessment, linking patient adherence assessment with effective communication in the clinical setting.
Patient adherence (or compliance) to the recommendations given by health professionals is clearly one of the major challenges of healthcare delivery today. The failure of individuals to enact, and persist in, essential health habits such as eating a healthful diet, exercising for strength and fitness, and faithfully taking medication appears to be a widespread and serious problem, with nonadherence rates at or above 50% in many disease conditions (e.g., Sabaté, 2003; Laufs et al., 2011).
The negative effects of nonadherence to medical recommendations can be seen in multiple domains: healthcare system costs, suffering and death of individual patients, scientific misunderstandings, and the toll taken on medical professionals. With regard to the first, nonadherence is extremely taxing to the healthcare system. As many as 275 million medical visits for the prevention and/or treatment of chronic conditions are wasted annually when patients do not follow the advice they are given (DiMatteo, Haskard-Zolnierek, & Martin, 2012). Nonadherence-related losses to the US healthcare system have been estimated at $290–$300 billion per year, resulting from poor outcomes including avoidable complications, emergency department visits, and hospitalizations (DiMatteo, 2004; NEHI, 2009).
The costs in human suffering are notable as well. Cutler and colleagues (2007) report that medication nonadherence for hypertension alone results in 89,000 premature deaths in the United States each year. Nonadherence to clinical treatment also jeopardizes the effective management of long-term chronic diseases, interfering with patients’ quality of life and expected survival.
Nonadherence to treatment has equally devastating effects on the accuracy of scientific research, the results of which are threatened by nonadherence (p. 371) of patients to treatment protocols. It has been estimated that as many as 30% of individuals participating in clinical trials to test medications may, in fact, not be taking what is prescribed to them, which may result in an underestimation of side effects and an overestimation of the doses necessary for clinical efficacy (Smith, 2012). Nonadherence in this context represents a particularly serious problem because the degree to which future patients may be able to effectively adhere—and indeed whether they are prescribed an appropriate regimen in the first place—may be influenced by inaccurate findings from research studies that are contaminated by nonadherence.
Finally, the job satisfaction of health professionals is also affected when patients are nonadherent because of the frustration and hopelessness associated with caring for patients who could improve health wise, but do not (DiMatteo et al., 1993b). It can be difficult to continue to pour time, energy, and empathy into patients who are not committed or don’t believe in the importance of the protocol, or simply cannot overcome the personal barriers to their own healthy behaviors.
Why Effective Adherence Assessment Is Valuable and Important
It may seem obvious that the delivery of effective clinical care requires a clinician to know, with a fair degree of certainty, whether his or her patients are following clinical directives. Knowing which exercises are being done, which foods avoided, and how much medication is being regularly ingested or injected by the patient is essential to the understanding of a treatment’s efficacy and to decisions about possible dosing adjustments, medication changes, or other shifts in recommendations. Former Surgeon General of the United States, C. Everett Koop, has often been quoted as saying, “Drugs don’t work in people who don’t take them.” This statement highlights the possibility that, if an individual’s health is not improving, one explanation may be that the actions required for improvement are not being taken.
Accurate knowledge of what a patient is doing, in the context of what he or she is supposed to be doing, offers a wealth of information. First, as noted, with the possible exception of some placebo interventions, medication that does not enter the human body generally does not affect it physiologically. Similarly, exercises that are not done cannot burn calories, strengthen weak muscles, or maintain bone mass. Furthermore, with regard to placebo effects, just the knowledge that one has taken a medication or fulfilled a medical directive can have its own special boost in outcomes. As outlined in several recent reviews (Bingel, Collaca, & Vase, 2011; Linde, Fässler, & Meissner, 2011; Horowitz, 2012), patients who adhere often have better health outcomes than patients who do not, even when the medication in question is itself a placebo and even when patients know that they are taking a placebo. It is suggested, then, that the process of adhering might have its own beneficial effects on health, perhaps through positive expectations for better outcomes, reductions in patient anxiety, enhanced self-efficacy that prompts additional healthy behavior, or improvements in relationships with providers and others.
Providers gain important information about treatment efficacy and the accuracy of diagnoses from the effects of prescriptions on patients’ conditions. Without clear evidence to the contrary, providers usually assume that their patients have taken medication as prescribed, and they respond to clinical parameters such as symptoms or blood work results accordingly. Providers may adjust medication doses, rethink possible differential diagnoses, or consider comorbidities as the available data indicate. Without accurate information about what the patient has actually done, the provider can easily make suboptimal choices for treatment based on that incorrect knowledge.
Clinicians also gain information about the patient him- or herself. Knowing how well or poorly the patient has adhered to a given directive tells the provider much about what the patient can handle in terms of future required behavior change. The clinician can determine whether the patient might be capable of following a complex medication schedule with little room for error or whether a simpler approach should be chosen, one to which the patient probably can adhere. Long-term management of chronic disease, in particular, requires an honest evaluation of the trajectory of treatment progress, and accurate knowledge of the patient’s adherence is central to that evaluation. Targeting desired health outcomes involves not only the efficacy of medications but also the influence of the disease management regimen on the patient’s life as a whole. Effective targeting of desired outcomes requires knowing what the patient can and cannot do.
A patient’s failure to adhere to recommended treatments can occur intentionally or unintentionally, depending on what the patient understands that (p. 372) he or she is to do, what he or she is willing to do, and what he or she is capable of doing (Lindquist et al., 2012). A patient might fully intend to take her medication in the evening before bed, but be so tired from work and meeting her family’s needs that she falls deeply asleep before ingesting her pill; and, in the morning, she may be so busy that she does not even realize she has failed to take her medication. (A blister pack would certainly help with this!) On the other hand, a patient might experience “motivated forgetting”—that is, she may let herself fall asleep without attempting to take her medication because she does not really believe that the medication is good for her or worth the cost. She might “fail to remember” to take the medication because she does not really think she needs it, or she may find the side effects intolerable. The distinction between intention and unintentional nonadherence is a meaningful one and has important implications for how nonadherence can best be addressed (Wroe, 2002).
Primary nonadherence, that is, failing to fulfill the prescription from the outset or failing to initiate a behavioral regimen, might result from the patient’s failure to understand the need for treatment, from his or her lack of commitment to or desire for the regimen, or from the inability to pay for prescribed drugs or equipment. Perhaps a patient’s medical visit is covered (or mostly subsidized) by an insurance plan but his costly medications are not—in this case, he may make and keep an appointment, and receive a prescription, but be unable to fill it. Or, he may be prescribed a medication the side effects of which prompt “horror stories” on the internet. The patient might read these and decide that he would rather take his chances with the disease itself rather than subject himself to side effects that he believes to be an almost certain outcome. Primary nonadherence is often, although not always, intentional; it represents a choice on the part of the patient. As can be seen from these examples, however, different tactics for addressing individual cases may be required (e.g., financial help, additional explanations of drug efficacy, or discussion of likely side effects).
Nonpersistence involves the patient’s failure to follow treatment over time, an action that may be intentional—such as making a decision that the benefits no longer outweigh the costs, deciding that symptoms have been addressed and the remaining medication can be “saved” for another time, or becoming discouraged with difficulties in organizing disease management behaviors and giving up. Nonpersistence may, however, also be unintentional. It may result from poor communication and the failure, from the time of the initial prescription, to fully inform and train the patient. For example, providers might tell the patient to take pills “three times per day” instead of being clear that this means “every 8 hours”). Nonpersistence might result from chaos in the patient’s life that intermittently interferes with his or her ability to effectively remember or carry out desired behaviors. Knowing the type of nonadherence offers the chance to intervene, to assess the reasons that adherence is not being maintained, and to make appropriate changes to regimens.
Inconsistencies across types of adherence can communicate a great deal of information to the clinician. For example, a patient may be nonadherent to a medication, but persistent in adherence to exercise and diet; or the patient might accurately take a medication with simple dosing but inaccurately take a medication with a more complex dosing requirement. Present adherence not only affects current treatment, but is a significant predictor of future adherence (DiMatteo et al., 1993a; Turner, Weiner, Yang, & TenHave, 2004). Thus, if clinicians know about the details of (non)adherence, they will be better able to provide effective care.
Finally, as previously noted, adherence is not only important in clinical settings, but also in the research (clinical trials) context (Smith, 2012). Research on the effectiveness of any treatment requires that the treatment be carried out, otherwise those in the “treatment group” are really not in the treatment group but are instead in the “intent to treat condition.” In these cases, just as in cases where individuals in the control group (who should not be receiving the designated treatment) nonetheless engage in the protocol, outcomes become suspect. Techniques to mitigate biases of this sort (e.g., intent-to-treat analysis, randomized encouragement designs, etc.) do exist (e.g., West et al., 2008) but, of course, it is best to assess adherence to clinical trial regimens and gather accurate knowledge of what patients (research subjects) are actually doing.
Effective Communication Is Essential for Adherence Assessment
One thing we are fairly sure of is that patients do not regularly tell their providers of their intentions not to adhere, nor do they readily admit nonadherence when it occurs (Turner & Hecht, 2001; Lapane, Dubé, Schneider, & Quilliam, 2007; Jerant, DiMatteo, Arnsten, Moore-Hill, & Franks, 2008). Research also shows that health professionals, (p. 373) particularly physicians, often tend to overestimate the degree to which their patients are adherent, and many believe that most or all of their patients have perfect, or near perfect, adherence (Lapane et al., 2007). In addition to a great deal of nonadherence going unrecognized by clinicians, most clinicians have difficulty accurately identifying which of their patients are having adherence difficulties (Mason, Matsuyama, & Jue, 1995). This assessment problem can have serious implications for the outcomes of clinical practice.
Some clinicians make an effort to ask about adherence, although their questions are usually not precise enough to really learn whether the patient is taking the appropriate action toward fulfilling the treatment. If the clinician asks: “You’re doing okay with the medicine, right?” few patients will volunteer that they are having difficulty or that they are not adhering at all. Such general questions also fail to identify those who may believe they are adherent but are actually carrying out their treatment recommendations incorrectly. This type of approach makes it quite possible that essential information about the patient’s adherence will be missed by the clinician and the chance to adjust the treatment to something the patient can live with will be missed (Hahn, 2009).
Why do patients fail to admit their nonadherence? After all, it is in their best interest to do so, to enhance treatment outcomes. Patients often fear ridicule or reprimand by their physician if they admit to nonadherence; some may not want to disappoint a provider they care for. The social power of the provider–patient relationship is a very salient issue as well (Parsons, 1951; Goodyear-Smith & Buetow, 2001), making honesty particularly challenging. Patients do not want to question the authority of their physicians, and thus they may do their best to hide the truth (Hahn, 2009).
A healthy interpersonal relationship and effective communication are central to distinguishing between intentional versus unintentional nonadherence and to addressing both types of problems. Unintentional failures to adhere are often caused by poor communication about the treatment and about the disease condition, coupled with poor health literacy on the part of the patient. The net result may be that the patient does not understand what needs to be done to care for him- or herself (Lindquist et al., 2012). Sometimes, patients are unintentionally nonadherent because they do not have the skills or resources they need to follow the treatment correctly or a clear plan for modifying and managing their behavior. Conversely, when a patient is intentionally nonadherent, he or she holds beliefs that do not support the treatment; the patient may believe that the treatment is dangerous, ineffective, or not worth the trouble to carry out, and, as a result, the patient makes a conscious choice not to follow it. Trust in the provider–patient relationship is essential to an open and honest discussion about these beliefs and about adherence (Dowell & Hudson, 1997; Kerse et al., 2004; Hahn, 2009). Discussing and identifying patient nonadherence early in treatment can help clinicians and patients to talk with one another about the challenges of treatment and eventually improve adherence (Hahn, 2009). Communication and collaboration are not things that come easy to all clinicians, but one recent meta-analysis by Zolnierek and DiMatteo (2009) showed that training in effective communication can significantly improve patient adherence. Rosenbaum and Silverman (in press) provide a detailed review and recommendations for “best practices” when it comes to training for effective medical communication.
Assessing Adherence in Clinical Practice
It is important to make a distinction between assessment of adherence in research and assessment in clinical practice. The assessment of patients’ adherence in the context of clinical practice can be done in a number of ways. Some assessment methods are likely to also promote and improve adherence, and some approaches have potential pitfalls. Similarly, there are benefits and costs associated with various methods when applied in a research context. For example, in research, adherence assessments sometimes use such methods as electronic pill bottle monitoring (more commonly referred to as “medication event monitoring systems” or MEMS). These might be special medicine bottle caps that have a built-in computer chip to record precisely each time the bottle is opened (Feinn, Tennen, Cramer, & Kranzler, 2003; de Bruin, Hospers, van den Borne, Kok, & Prins, 2005). This approach can be expensive, but the precise and standardized protocols of research can make such techniques essential. In clinical practice, however, electronic pill dispensers can sometimes interfere with a patient’s own pill organizing system. Electronic monitoring might even convey to the patient that he or she is not trusted, thus undermining the clinician–patient partnership necessary for effective long-term chronic disease management (Jerant et al., 2008). Some research does suggest (p. 374) however that, in many cases, patients seem to be accepting of MEMS (Hamilton, 2003).
Research approaches also include the use of data from prescription databases. Although useful in some cases, medication possession information tends to be an even more indirect measure of adherence than is a MEMS record. Medication might be possessed by the patient but still not used, or it may not be used correctly. Indirect methods also do not work for other health behaviors, such as exercise or dietary management (Jerant et al., 2008).
The approach of pill-counting (counting the patient’s medication remaining in the bottle) is a technique borrowed from early adherence research (DiMatteo, 2004) in which patients are asked to take their medication bottles to the visit and someone (e.g., the nurse, the medical assistant) counts the remaining medication or weighs the canister (e.g., for inhaler-administered drugs). Again, this approach can be useful for research, but is also associated with several problems. Patients might discard unused medication before their visit in order to appear adherent, or patients might feel that they are not trusted to respond directly and honestly to questions, thus compromising the trust and partnership within the clinician–patient relationship.
Of course, asking patients to bring in their pill bottles in order to talk about their various medications can be a positive step. Given the challenges of more indirect methods, including MEMS, pill counts, and pharmacy data, however, it has been suggested that the most accurate assessments will be those that use multipronged measurement strategies (Bova et al., 2005).
Multifaceted Approaches to Assessment
Multifaceted, personalized approaches work best to assess patient adherence, and effective communication is essential. No single assessment approach, questionnaire, or instrument is “the best,” because assessment is complex. There does exist, however, a manageable set of issues that must be understood and applied effectively to each patient (DiMatteo et al., 1993a; Roter et al., 1998; van Dulman, Sluijs, van Dijk, de Ridder, Heerdink, & Bensing, 2007). An adherence assessment strategy needs to be tailored to each patient for maximum benefit. Assessing Mr. Jenson’s adherence might be challenging because he does not really understand what he is supposed to do. He thinks he is doing everything correctly and thus reports that his adherence is excellent—not really understanding why the treatment needs to be carried out in a particular way in order to be truly “correct.” Another patient, Ms. Smith, might know what she is supposed to do, but she doesn’t entirely trust her provider’s recommendations. Furthermore, she believes she will be charged higher insurance premiums if she is nonadherent. So, she does her best to deceive the provider. A third patient, Mr. Hardy, cannot organize his life well enough to adhere properly; he has no idea what he did yesterday; he lost his cell phone and calendar; and he was interrupted when he was filling his medication organizer, so he did it wrong. He can’t remember what he’s done, and he certainly cannot reliably report to his healthcare provider about his actions. Finally, there is Ms. Cameron, who has a large family. The needs of her children come first, and so she has little time to pick up her medications at the pharmacy and can barely afford to pay for them. She also has trouble keeping appointments and is always in a rush, with no time to discuss the challenges she is facing with regard to her adherence. For each of these patients, the reasons for nonadherence are different and the factors affecting the accuracy of their self-reported adherence vary; thus, the approaches for improving the measurement of their adherence will also vary. Assessing adherence via multiple means can be expensive, time-intensive, and inefficient, although it is likely to give the most accurate reading. Given the observed associations between self-report and other adherence measures, there is strong and consistent evidence that patients’ self-reports are the most practical way to estimate adherence (Turner & Hecht, 2001; Simoni et al., 2006; Jerant et al., 2008; Garfield, Clifford, Eliasson, Barber, & Willson, 2011).
The purpose of this essay is to link the assessment of patient adherence with effective communication in the clinical setting. It could be argued that, all things considered, the most effective and efficient approach to assessment may be patient self-report—and, in clinical practice, the most likely adherence assessment method will be self-report (Jerant et al., 2008). The accuracy of assessment is essential for promoting adherence, and a trusting, collaborative relationship is not only key to honest self-reporting of adherence behaviors but also encourages the effective communication and conversation about adherence that can strengthen the therapeutic relationship (Turner & Hecht, 2001; Simoni et al., 2006).
The Adherence Conversation
Asking patients about their adherence using open communication and a nonjudgmental attitude is (p. 375) essential in the context of provider–patient communication. Helping patients feel comfortable admitting their adherence difficulties and offering them opportunities to ask for assistance and to contribute to clinical decision making are central to achieving patient adherence.
Awareness of and sensitivity to patients’ communications (both spoken and unspoken) are essential elements of clinical care. When patients are attended to and understood as individuals, they are more likely to offer evidence of their intentions to adhere (or not), as well as their understanding of their treatment, commitment to follow it, difficulties they may be having, and needs for help (Hall, 2011). Talking about adherence improves clinician–patient communication by opening up opportunities to negotiate the best treatment, one that the patient can incorporate into his or her life; conversations about adherence offer the patient and provider a chance to work together as partners in informed collaborative choice (Teutsch, 2003).
Despite their importance, conversations about adherence can be difficult for a number of reasons. Bringing up the issue at all can be a challenge. Clinicians might ask their patients regularly about how they are doing in their self-management, and they must do so with a nonjudgmental and helpful attitude. When clinicians suspect nonadherence, they might be hesitant to ask direct questions because they fear that they will insult the patient. Or perhaps they believe that, although monitoring is part of their task, the final responsibility lies with the patient (e.g., Tarn, Mattimore, Bell, Kravitz, & Wenger, 2012). Clincians may feel that they are limited in what they can accomplish through such questioning.
Taking a nonjudgmental approach makes things easier. For example, “So, we can see here that your blood pressure is higher than we had hoped. How are things going for you with taking the medication we decided on together at our last visit?” or “Can we talk for a bit about how things have been going for you with the new medication? I’m noticing that the blood pressure levels we were concerned about are still high.” The relationship and manner of communication between the healthcare professional and the patient have been found to significantly affect adherence (Farmer, 2009).
There is more to be concerned about, though, than just the interpersonal aspects of questioning about adherence. When providers are not precise about their adherence queries and when they fail to listen for relevant details about patients’ adherence, important clues can be missed. The wording of questions about adherence can also affect how patients will respond; negative questions that seem to blame the patient for not complying will bias the answers that many patients give (Farmer, 2009).
Precision in what patients are asked is vital so that they are encouraged to provide the most accurate information possible and so that the clinician can assess the patient’s precise understanding of and belief in the regimen. For example, if a patient is asked only “how they are doing with their medication,” without specifics about their actual behavior, opportunities to examine adherence in detail are likely to be lost. A patient might say she is doing well and taking her medication “regularly,” but she may think that one pill a day is enough, when the prescribed dose is actually two pills per day. Or, a patient may be taking her two doses of medication within the space of just a few hours instead of roughly every 12 hours. Or, she may be taking her medication with meals when it is supposed to be taken on an empty stomach. Asking precisely how the medication is being taken is essential (Hays & DiMatteo, 1987).
In asking patients about the precise details of their adherence, clinicians can also unearth evidence for patients’ motivation (or lack of motivation) to adhere. Patients’ motivation also extends to their desire to accurately recall their behavior and be truthful about it. Patients need skills for self-monitoring and self-assessment, as well as the time and attention to report accurately (for example, to keep a written diary of their behavior or use technologies to track their activities). The essential skills that patients need to accurately monitor and report their own adherence are often the same as those needed for adherence itself—and are not easy to achieve.
Barriers to Effective Assessment
Low health literacy is one major impediment, not only to adherence but also to the accurate assessment of adherence. As Keller, Sarkar, and Schillinger have detailed in “Health Literacy and Information Exchange in Medical Settings,” low health literacy may affect at least a third of the adult US population and an even larger proportion of some populations. As Keller et al. (in press) have noted, effective communication with all patients, particularly those with low health literacy, requires interactive dialogue about their understanding of the disease and treatment; their beliefs about treatment and motivation (p. 376) to follow it; and their concerns, barriers, and treatment side effects, among other elements of care. To assess patients’ adherence accurately, the clinician must build on the knowledge, barriers, and deficits that are identified through elicitation-type communication. For example, a clinician can help the patient to recognize the connection between behavior and health outcomes (e.g., the link between not taking blood pressure medications and increased blood pressure) and to organize behavior to increase adherence.
Another possible barrier to adherence assessment is age. A patient’s advanced age might contribute to difficulties remembering what actions have been taken and the degree to which adherence has been effective. As Greene and Adelman, in “Beyond the Dyad: Communication in Triadic (and more) Medical Encounters” have noted, a third person in the medical visit, such as an adult child, might help the patient with accurate reporting. A third person might offer a somewhat more truthful or even more nuanced response than the patient, but there is also the potential for trouble or even interpersonal chaos. The patient might feel discounted or disbelieved by the physician and the adult child. Greene and Adelman point out that the patient may also have less time to talk and to share concerns, and might feel incompetent or unreliable. In “Issues in Aging, Adherence, and Health Behavior Change” Bradley and Hughes highlight the limitations in how adherence is measured in aged populations, the lack of commonality in terms, and the complexities associated with trying to synthesize the wide range of diseases and ages in the literature. As with all patients, nonadherence in the elderly involves the failure of the health professional and patient to fully agree on the prescribed behavior so that the clinician can provide adequate follow-up support (Nunes et al., 2009)—support that takes into account the competing demands of a patient’s life and the barriers he or she may be expected to encounter. As Morris and Schulz (1992) put it, nonadherence follows from “collisions between the clinical world and other competing worlds of work, play, friendship and family life.”
Variability in patients’ views of the world can also affect the assessment of adherence. Cultural background (as discussed by Flynn, Cooper, and Gary-Webb in “The Role of Culture in Promoting Effective Clinical Communication, Behavior Change, and Treatment Adherence”), mental health status (Haskard-Zolnierek and Williams in “Adherence and Health Behavior Change in the Context of Mental Health Challenges”) can meaningfully influence how questions are understood, the comfort level that patients have when responding to queries, the specific needs of patients for help with understanding and remembering, motivations for truthfulness (or deceit), and incentives for monitoring behavior.
Points Worth Remembering when Measuring Patient Adherence
Whether adherence is measured in clinical practice or in research, several issues are important to keep in mind. First, as previously outlined, there is a difference between assessing adherence for research and assessing it for clinical practice. Clinical practice assessment allows for greater flexibility and tailoring of methods to accommodate individual patients’ needs and strengths. Adherence in clinical practice requires communication and discussion between provider and patient, of course, and so approaches are likely to be primarily, or even exclusively, self-report. The standardization required by research, conversely, often depends on additional approaches, such as electronic monitoring of medication containers and pharmacy claims data. Self-report on the part of the patient (or research participant) is very often central to both types of assessment. Development and refinement of measures depends on effective communication about the patient’s behavior.
Second, several core elements have shown, over more than five decades of research, to be critically important to adherence (DiMatteo et al., 2012); clinician–patient conversations about adherence should always assess the patient’s understanding of the treatment regimen, his or her beliefs about the disease and the treatment, the patient’s commitment to the treatment, the social context in which the patient is trying to manage his or her disease, and the patient’s emotional and practical resources available to support the regimen (Manias, 2010). One major challenge to the assessment of adherence, however, is making sure that adherence measurements focus on adherence behavior (Morisky & DiMatteo, 2011). As Tim Wysocki has noted in “Managing Complex Regimens: The Psychological Context of Family Management of Pediatric Diabetes” assessment of these elements enables screening and risk assessment of youth and their families, thus facilitating opportunities for prevention and early intervention rather than attempts to remedy complex and difficult clinical problems once they have already occurred. (p. 377) We would extend this to all age groups—not just children, youth, and their families. Thus, although it is important to understand adherence predictors (e.g., patient beliefs) and consequences (e.g., health outcomes), assessing adherence should not involve assessing the antecedents and consequences, but rather what the patient is actually doing. Relatedly, researchers sometimes assess the intent to adhere; although an intent might well predict adherence (if the necessary skills and resources are present), intent to adhere is not adherence behavior.
Third, and flowing naturally from this, is the point that adherence is not a health outcome. Although adherence is a means to accomplishing a treatment goal, and there is a significant relationship between adherence and disease outcomes, the relationship is not perfect (DiMatteo, Giordani, Lepper, & Croghan, 2002). Although the average correlation between adherence and health outcome is 0.26, this effect size varies by disease condition. There is not always a clear path from adherence to outcome; an adherent patient might have unchanged or worsening disease parameters because the prescribed treatment is not effective or is not the right treatment for him or her. Thus, although a poor health outcome might be a warning sign of nonadherence, accusing the patient of being nonadherent can undermine trust and the therapeutic relationship. Similarly, when a nonadherent patient nonetheless demonstrates good outcome indicators, the provider may assume that the patient has been adherent, thus encouraging the patient’s future failure to be truthful and discouraging efforts at improving adherence behavior. In research, such outcome measures as HbA1c and blood pressure readings might have some use as proxy measures for adherence, but this conceptual approach and operational definition should be kept in mind when interpreting the data.
Fourth, adherence is often measured in research as a dichotomous variable; participants are divided into categories of “adherent” or “nonadherent,” sometimes even by collapsing a continuous variable. This approach is sometimes chosen when the split is based on the degree of adherence considered clinically necessary to achieve the desired outcome (e.g., at least 80% of the medication must be taken). Needless to say, the loss of information about the degree of adherence is problematic; with an 80% cut-off, a patient who consumes 75% of his or her medication would be categorized as nonadherent, along with someone who takes no medication at all. The dynamics surrounding the former patient, who may be trying to adhere but struggling because of competing life demands, would be very different from those of someone who has rejected the treatment altogether because of serious doubts about the treatment’s efficacy and/or safety or concerns about the provider.
Relatedly, adherence itself is not unidimensional. As Wysocki has noted in “Managing Complex Regimens: The Psychological Context of Family Management of Pediatric Diabetes” with many diseases (diabetes is an excellent example), simple assessment of treatment adherence as the percentage of instances in which a specific treatment action is completed as prescribed may not be nuanced enough. Care may involve a number of fundamental, yet varying, activities such as insulin administration, daily self-monitoring of blood glucose, consistent carbohydrate intake, and physical activity. These may be inherently quite varying behaviors. For example, with medication taking, primary nonadherence (nonfulfillment) involves never filling a prescription (e.g., because of memory failure, distrust of the health professional, or copayment costs that are unaffordable). Secondary nonadherence (also called nonpersistence), which involves beginning a regimen correctly but not continuing, could occur because of side effects, regimen fatigue, development of bad habits, or a host of other factors that make continuing any activity difficult. Another type of nonadherence, treatment error, could also occur for many reasons, such as failure to have understood the regimen correctly in the first place, a decision to alter the regimen, or simply becoming lax about some of the details while maintaining other aspects of the regimen. These are all very different types of nonadherence, and dichotomizing a patient into one or another category sacrifices an enormous amount of information.
Fifth, some measurements of adherence can actually serve as interventions to change adherence. For example, take-home paper diaries for pill taking, food intake, or exercise can encourage the individual to self-monitor, self-assess, and ultimately make adjustments to personal behavior. Such measures serve a dual purpose: they help people to become aware of their behavior and note where they are falling short, and they then encourage behavior that is closer to the ideal. Self-monitoring alone has been found to affect behavior change (Brownell, 1995; Dunlap, Clarke, Jackson, & Wright, 1995). Diary-type approaches, for example, might have a component in which the person analyzes the circumstances that may have attended the (p. 378) behavior (or the behavioral failure) and tracks the environmental factors (e.g., feeling stressed) that might trigger the behavior (e.g., overeating). This self-assessment can help the person prepare for such situations in the future or may assist him in scheduling desired behaviors (e.g., focused relaxation, exercise). These approaches might be very useful in clinical practice, although their usefulness as “pure” measures of adherence behavior of the sort needed for research may be limited.
Finally, related to the often complex and interactive nature of health behaviors, summary scores of treatment adherence do not differentiate among the many points in time that adherence or nonadherence can occur. In the case of chronic illness, many patients make decisions to act or not act (or respond habitually) in accordance with prescribed treatment several times a day. Adherence “patterns” might provide useful data for better understanding a patient’s particular challenges, although the statistical methods for dealing with these patterns may be complex (e.g., see Drotar & Rohan’s discussion in “Pediatric Adherence and Health Behavior Change”). Patterns of treatment adherence demonstrated by individuals, as well as patterns across samples as a whole, can be examined in the context of clinically relevant health outcomes over time (Singer & Willett, 2003; Borckardt et al., 2008).
Essential Elements of Adherence Assessment
When assessing patient adherence, several elements are essential. The primary focus is to determine what the patient is actually doing—how many pills are actually ingested at what times, how often exercises are done and how they are done, and so on. In addition, there needs to be an accurate assessment, not a conjecture, of why the individual does or does not enact the prescribed behavior, offering clues about what could be changed to help the patient achieve an acceptable level of disease management.
Patient comprehension might be considered the primary element in adherence assessment. When patients are asked whether and to what degree they are adhering, they need, first and foremost, to have comprehended what they were originally asked to do and why. It is only then that they will be able to render an accurate statement of how well they are doing it. Patients must also understand accurately the question they are being asked, and their level of health literacy is likely to affect this understanding. As an example, consider the patient who is asked: “So, are you taking your medication three times a day, as directed?” An affirmative response would be appropriate, even if the patient were taking his or her medication at 9 a.m., noon, and 3 p.m., instead of every 8 hours. The prescription instructions assume, but do not explicitly state, that the doses should be spread out over the 24-hour day; a patient who does not have a high level of health literacy might know nothing of the necessity of equal temporal spacing of doses and may receive no information from the prescription directions. As Keller and her colleagues (in “Health Literacy and Information Exchange in Medical Settings”) have noted, misunderstanding related to medications is quite common, and many of the 1.5 million preventable adverse drug events every year are the results of medication errors made by patients (Institute of Medicine, 2007). The chances of such errors are highest among those with low health literacy, which strongly affects understanding of medication-related instructions and the ability to adhere to medication schedules (Sarkar et al., 2010; Lindquist et al., 2012).
Adherence assessment in clinical practice should make the distinction among different types of adherence (nonfulfillment, nonpersistence, and treatment errors) in an effort to uncover the reasons for nonadherence. “How’s it going with your medication?” is far too general. More useful is a set of utterances (of course, not fired at a patient all in a row): “So, did you fill the prescription for ___ that we decided on last time? Yes, so how have you been taking it? Every day? How many times per day? On what schedule…?” Or more simply “Walk me through your day—tell me how you have been taking your medication, the times you take it…Has this been a consistent pattern? Have you missed any doses? When and why do you think you missed them?”
Discussion is the key and should involve asking open-ended questions, following up with further questions, and inviting discussion and even disagreement (e.g., “Do you think we should reconsider this regimen? It seems not to be working for you…”). Asking patients their thoughts about the difficulties they are having with adherence can do a lot to reveal ways to help patients adhere and enhance their treatment outcomes. Keller and colleagues, in “Health Literacy and Information Exchange in Medical Settings” have offered a number of valuable “best practices” for communication with all patients, especially those with lower levels of health literacy. These practices include inquiring (p. 379) about patients’ baseline knowledge and barriers to adherence, using clear verbal communication, and perhaps using pictures with simply worded captions (Houts, Witmer, Egeth, Loscalzo, & Zabora, 2001; Houts, Doak, Doak, & Loscalzo, 2006; Yin et al., 2008).
The validity or accuracy of a report of adherence depends on several factors, in addition to the patient’s understanding of what he or she is supposed to be doing to adhere. Patients may vary in the degree to which they are motivated to make the effort to remember correctly what they have been doing. Remembering accurately might be done better by another person in conjunction with the patient (e.g., a parent for the diabetic adolescent, an adult child for the aging patient with some cognitive deficits, a spouse for the reluctant heart disease patient). Another interested party might better recall what the patient has been doing, after observing it, and the third party might be more forthright about disclosing the patient’s actions. Issues of self-determination, responsibility, and privacy are always of concern, of course (see Wysocki, in “Managing Complex Regimens: The Psychological Context of Family Management of Pediatric Diabetes”), and measures of adherence with the various components of multidimensional disease management protocols may have differential transparency to various parties. Furthermore, various elements of disease management protocols, such as for diabetes, often are not correlated with one another and may be differentially stable over time. (Johnson, Silverstein, Rosenbloom, Carter, & Cunningham, 1986; Glasgow, Schafer, & McCaul, 1987; Johnson et al., 1992). Thus, it should be clear that adherence is not single unitary construct, and it cannot be easily measured in a single way with the input of a single respondent.
Validity of responses from all concerned, patients and their proxies, depend on trust in the provider–patient (or provider–family) relationship. Without trust in the relationship, motivation to be honest and forthcoming about adherence challenges may be lacking. Trust is important for patients to feel comfortable reporting nonadherence, as well as for clinicians to be able to trust patients’ reports of good adherence. Harvey, in “Health Beliefs and Health Outcomes,” has pointed out that denial can be a problem in assessment. A patient’s emotional response to illness might include denial that he or she is even ill, and this can be an impediment to clear communication about adherence and to accurate assessment.
As Wysocki (“Managing Complex Regimens: The Psychological Context of Family Management of Pediatric Diabetes”) has noted, it is not advisable to conduct continuous direct measures of adherence, such as electronic measurements (electronic monitoring of medications, for example), which can have ethical as well as interpersonal concerns. Ideally, a measure of chronic disease self-management would involve a comprehensive sample of the adherence behaviors enacted by the individual available from a variety of sources, all with the patient’s knowledge and permission. Ideally, this approach would also involve the patient’s desire to have all the help possible to assist him or her in achieving adherence and effective health outcomes.
Wysocki (“Managing Complex Regimens: The Psychological Context of Family Management of Pediatric Diabetes”) and Drotar and Rohan (“Pediatric Adherence and Health Behavior Change”) have both noted that, in the long-term management of chronic illness, assessment may also need to be long-term, with continuous assessment of changes over time for each individual and of how adherence behavior affects treatment outcomes. Beni (in “Technology and Implications for Patient Adherence”) offers insights into the role of technologies in adherence assessment, such as text reminder systems with patient response options. Drotar and Rohan have also offered a very comprehensive table of the various methods for monitoring and assessing treatment adherence in pediatric and adult populations, including self-reported measures of adherence and objective approaches such as electronic monitoring and pharmacological assays. These authors examine the strengths and weaknesses associated with each measure, particularly in the context of longitudinal research and/or long-term clinical disease management. They note that longitudinal measurement of adherence must take into account variability of adherence measurement over time. Wysocki similarly reviews many approaches for measuring the many elements of type 1 diabetes mellitus, from individuals’ self-reports to clinician ratings to real-time assessments of diabetes self-management behavior.
In this essay, our goal has been to link our discussion with the treatment given to these issues, as well as to offer illustrative examples of adherence measurement approaches based on the principles outlined here. Some of these measures are summarized in Table 20.1 and offer examples of various approaches, illustrating the ideas presented throughout the essay. (p. 380)
The examples in Table 20.1 are arranged according to four conceptual (although sometimes overlapping) approaches to adherence measurement:
1. Questionnaires and scales that measure adherence directly focus on specific treatment behaviors, asking the patient to report on exactly what he or she did, vís a vís the regimen. Such measures ask the patient to identify behaviors that allow identification of the type of nonadherence (nonfulfillment, nonpersistence, treatment errors) and offer the opportunity to remedy observed problems.
2. Some measures of adherence are actually not focused on behaviors at all, but rather on factors that predict behavior. They are not measures of adherence behavior but instead they assess potential “red flags” that might alert the clinician to likely nonadherence. They might be useful to identify at-risk patients.
3. Likewise, measures that assess readiness or intention to adhere also assess likelihoods, not behavior. Although it may be reasonable to assess intentions—they are important—intentions are not enough. Because of difficulties changing or modifying their behaviors, individuals may not follow through on their intentions for various reasons.
4. Electronic and other means of real-time assessment can serve not only to measure adherence but also to intervene and change adherence. When individuals fill out take-home paper diaries of pill taking, food intake, or exercise, the process of recording behavior offers the chance to self-monitor, self-assess, and change behavior. Continuous attention to personal adherence behavior can help patients to become aware of where they are falling short, and the process of self-monitoring can, in itself, be useful in promoting change, as was previously noted.
Conclusion and Future Directions
Despite the many challenges and difficulties, it is vital to make the effort to measure adherence (p. 381) (p. 382) effectively and to correctly recognize nonadherence. Effective assessment can significantly influence a wide range of patient outcomes, and talking about adherence with patients can improve trusting communication, allowing patient and provider to work together as partners in informed collaborative choice.
Table 20.1 Assessments of Adherence Behavior
Assessments of Adherence Behavior
To test the Brief Medication Questionnaire (BMQ) ability to detect repeat and sporadic nonadherence.
Varied by type of nonadherence, with the regimen and belief screens having 80–100% sensitivity for “repeat” nonadherence and the recall screen having 90% sensitivity for “sporadic” nonadherence. The BMQ appears more sensitive than some other tools and may be useful in identifying and diagnosing adherence problems.
To find the reliability and validity of the adherence instrument, the Brief Adherence Rating Scale (BARS) using electronic monitoring (EM) as the reference standard.
Estimates of oral antipsychotic medication adherence using the BARS were similar to those produced by EM across the 6-month period, with the BARS slowly overestimating adherence as referenced to EM.
To test the validity of two self-report scales (created for this study) to assess the adherence of adults to asthma medication and inhaler use.
Correlation between medication and inhaler adherence was 0.43 at baseline, 0.41 at 12-month follow-up, and 0.46 at baseline in second study.
To test the Medical Event Monitoring System (MEMS) against self-reports, with the MOS General Adherence Scale being the primary tool.
MEMS and self-report were both reliable measures of adherence but both have their own flaws. The MEMS does not account for actual pill-taking behavior, and self-report does not account for forgetfulness. Combining methods should be most accurate.
Assessments of Predictors of Adherence
To evaluate the reliability and validity of the Beliefs about Medication Compliance Scale (BMCS) and the Beliefs about Dietary Compliance Scale (BDCS) in patients with heart failure.
Overall, both the BMCS and BDCS demonstrated acceptable reliability and validity.
To develop a questionnaire (Adherence Determinants Questionnaire) to assess seven factors expected to correlate with adherence to preventive and treatment measures in cancer control.
Intentions to adhere were most correlated with the perceived adherence. Adherence (self-reported and objectively measured) was related most strongly to the presence of support for the absence of barriers to adherence.
To develop a self-administered tool to predict adherence to antiretroviral therapy.
Tool was easy to use and well-accepted by study group; should be appropriate for large-scale community-based environments.
To develop and validate the ASK-20 survey, created to identify actionable risk factors for medication nonadherence and to improve communication about adherence.
The ASK-20 survey demonstrated satisfactory validity and internal consistency and may be used to identify actionable barriers to adherence across a spectrum of chronic diseases.
To test validity of the five measurements making up the Rating of Medication Influences (ROMI) scale to determine its utility for assessing attitudinal and behavioral factors that influence adherence to neuroleptic treatments.
After testing all five subcomponent measurements making up ROMI, it was concluded that it is a valid and useful tool.
Create a valid and reliable questionnaire for the assessment of adherence problems that hamper intake of medication in patients taking antihypertensive medications.
The created questionnaire (MUAH) demonstrated test-retest reliability and convergent validity with the BMQ.
Assessments of Readiness or Intention to Adhere
To develop a measure of HIV medication readiness (the HMRS) as a predictor of HIV treatment adherence among patients beginning HAART therapy.
The total HMRS demonstrated good internal consistency and appears to be a reliable measure of intention to adhere.
Assessments of Adherence-Improving Techniques Using Newer Technologies
To test the utility of text messages to promote adherence to sunscreen use.
After 6 weeks, reminder group had nearly twice the rate of sunscreen application adherence as control.
To test the utility of text messages with respond-back to improve ART adherence.
Over 6 weeks, adherence increased and remained significantly higher in the reminder group using multiple measures of adherence (self-report and pill counts).
To test the utility of short message services (SMS) for improving adherence to antiasthmatic medications.
The difference in mean adherence between the two groups after 12 weeks was nearly 18%.
To test the utility of text message reminders with respond-back to improve adherence to a prophylactic vitamin C regimen.
There was a significant (negative) association between the number of text messaging acknowledgments and the number of pills missed during the last week of the trial.
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