Concordance, compliance and adherence in health care: closing gaps and improving outcomes
Concordance, Compliance and Adherence in Health Care: Closing Gaps and Improving Outcomes
Chris Wahl1, BSc, Jean-Pierre Gregoire2,3, MPH, PhD, Koon Teo4, MD, PhD,
Michelle Beaulieu2, MEd, Serge Labelle2, PEng, MBA, Brigitte Leduc2, BSc,
Bonnie Cochrane2, MSc, Liette Lapointe1, PhD, Terrence Montague2, MD
1Faculties of Management and Medicine, McGill University, Montreal, QC,
2Department of Patient Health, Merck Frosst Canada Ltd., Kirkland QC,
3Population Health Research Unit and Faculty of Pharmacy,
4Faculty of Medicine, McMaster University, Hamilton, ON
Correspondence: Dr. Terrence Montague Merck Frosst Canada Ltd. 16711 Trans Canada Hwy. Kirkland, Quebec H9H 3L1 Telephone: 514-428-3891 Fax: 514-428-2850 e-mail: firstname.lastname@example.org Running head: The challenge and opportunity to improve patient adherence Abstract
The gap between best care and usual care is large for many important diseases. In
particular, poor adherence remains a significant, inadequately addressed, cause of the
care gap. About half of all patients with chronic diseases stop refilling prescriptions by
one year. Several effective interventions are available and adaptations of clinical trials
practices offer promise for further improvement. Poor adherence is a remedial problem
in health care quality and its improvement and accountability offer shared opportunities
There is a large gap between best care, defined as the optimal use of proven
efficacious therapies in whole populations at risk from any disease, and usual care, the
actual level of efficacious care being provided (Montague et al 1997). This gap in
patient care has four main causes: diseases may not be diagnosed, efficacious
therapies may not be prescribed, access to therapy may be restricted or patients may
Irrespective of causation, the ultimate result of care gaps is the same – less than
optimal clinical outcomes and associated lost opportunities for improved quality of life
and productivity. Systematic approaches to improving prescribing practices are
increasing and there is much debate around improving patients’ access to care. Poor
diagnosis is judged to be relatively uncommon, leaving decayed adherence as the
major under-addressed cause of care gaps and a major opportunity for improvement.
This paper reviews the scope and causation of sub-optimal adherence, evaluates
improvement strategies and explores a best-practice benchmark.
The Importance of Adherence to the Health System
Adherence is an umbrella term used to embrace various components involved in the
process of patients taking medication as prescribed (Urquhart 2001). Acceptance is
defined as the initial decision of the patient to agree to the treatment, fill the first
prescription and obtain the first refill; persistence refers to continued prescription
renewal; and, compliance refers to taking treatment in accord with facets such as proper
The degree of adherence varies across diseases, but for many chronic diseases, 40%
to 50% of patients do not persist with initial treatments beyond 12 months (Andreade et
al 1995; Bloom 1998; Sidel et al 1998). In hypertension and cardiovascular risk
management adherence rates at one year average about 60% (Figure 2), undoubtedly
contributing to the less than optimal blood pressure control (Joffres 1997) and less than
optimal clinical outcomes (Sullivan 1990) of these patients. In dollar terms, the cost of
poor adherence for Canada, because of avoidable negative outcomes not being
prevented, has been estimated to be $7 to $9 billion per year (Coambs 1995).
Improving adherence provides, therefore, an enormous national opportunity for both
Causes of Non-adherence
The causes of non-adherence are complex. Demographic characteristics, ethnicity,
sex, age and socioeconomic status are not very predictive (Haynes 1979). More
important are complexity of treatment (Meichenbaum and Turk 1987), patient self-
efficacy, social support, disease knowledge, treatment alternatives, costs and side
effects (Gregoire et al 2002); Sackett and Haynes 1976) and disruption of patients’ life
style (Baum et al 2000). These latter factors are important in the health belief model of
patient decision making, which states: “In order for an individual to take action to avoid
a disease he would need to believe (i) that he was personally susceptible to it, (ii) that
the occurrence of the disease would have at least moderate severity on some
component of his life and, (iii) that taking a particular action would in fact be beneficial
by reducing his susceptibility to the condition or, if the disease occurred, by reducing its
severity, and that it would not entail overcoming important psychological barriers such
as cost, convenience, pain, embarrassment” (Rosenstock 1974).
Overlaying these factors is the human relationship between provider and patient.
Patients want a more active role in their medical care (Vertinsky 1974), supported by
information from their physicians (Cassileth et al 1980). More conversation by patients,
relative to physicians, is positively correlated to health status (Kaplan et al 1989). But
Leclere et al (1990)rate the doctor - patient relation as the most common difficulty in
medical practice. Key problems are differing perceptions of the health problem and
One way to improve this relationship is enhancement of communication skills of
providers, an important determinant of patient satisfaction with care (Williams and
Calnan 1991). Patient satisfaction, in turn, is a major determinant of commitment to
adherence (Newcomer et al 1996). Communication behaviors that reinforce patients’
self-confidence, motivation and positive view of their health improve patient satisfaction
and health practices (Donovan 1995), including adherence improvement (DiMatteo et al
1993); dissatisfaction fosters non-adherence (Roter 1977).
Traditionally, adherence is viewed in a relational context where the provider weighs the
diagnosis and therapies in terms of risk and benefit, makes a decision, informs the
patient and assumes the patient understands and will adhere. In this model, patient
beliefs may even be viewed as an obstacle to treatment.
The concordance model of the patient - physician relation is characterized as: "two sets
of contrasted but equally cogent health beliefs - that of the patient and that of the doctor.
The task of the patient is to convey his or her health beliefs to the doctor; and of the
doctor, to enable this to happen. The task of the doctor or other provider is to convey
his or her health beliefs to the patient; and of the patient, to entertain these. The
intention is to assist the patient to make as informed a choice as possible about the
diagnosis and treatment, about benefit and risk and to take full part in a therapeutic
alliance. Although reciprocal, this is an alliance in which the most important
determinations are agreed to be those made by the patient” (Royal Pharmaceutical
Improved provider - patient communication is intuitively attractive to improve adherence
and health outcomes. However, one very practical challenge is the enormous degree of
non-concordance of patients and providers in how they rate the importance of
adherence as a cause of care gaps and sub-optimal outcomes (Figure 3). Briefly,
providers rate poor adherence as the greatest contributing cause; patients, on the other
Interventions for Improvement
Programs to increase adherence fall under the category of disease management, the
focused application of resources to drive improved care and outcomes (Montague et al
2003). Weingarten et al (2002) recently evaluated the efficacy of interventions used to
improve the management, including adherence, in chronic diseases like asthma,
coronary disease, depression, diabetes, hypertension and pain. Patient education was
the most common intervention (78%), followed by provider education (40%) and
feedback (27%); with most (59%) programs using a combination of interventions.
At the provider level, all interventions were associated with significant improvements in
adherence to guidelines (44% to 61%) and disease control (17% to 35%). Among
patients, interventions were also associated with significant increments in disease
control, including education (24%), reminders (27%) and financial incentives (40%).
A traditional focus for providers has been continuing medical education, including newer
online decision support systems to help doctors with diagnosis and treatment decisions
(Montgomery et al 2000). Programs focusing on improvement in patient-centered
interviews are also gaining popularity. They encourage concordance by facilitating
patients to intervene and express their expectations, ideas and feelings (Levenstein
1986). Measurement and feedback of actual practices to providers is a proven tool for
generating improved prescription patterns (Montague et al 2003). Provider reminders,
independent of measurement-feedback programs, are less common but they also
improve medication management (Bennett and Glasziou 2003).
Patient education is the most widely used disease management intervention and
includes one-on-one sessions, mailings and telephone calls (Piette et al 2001). These
programs incorporate various providers of the education including physicians,
pharmacists, nurses and trained educators. Topics normally include information on the
disease, possible treatments and lifestyle changes. For example, a rheumatoid arthritis
program might involve sessions with a nurse practitioner focusing on drugs, physical
exercise and joint protection, pain control and general coping strategies (Hill et al 2001).
Pharmacist-based patient education is growing, in part because pharmacists are
appreciated to be “in a privileged position, with their expertise in pharmacological
treatment, to provide education, identify medication adherence issues and counsel the
patient ” (Rosenstock 1974). In addition, many pharmacists utilize shared databases
and information system capabilities that facilitate the flow of information and generate
improved clinical outcomes and cost benefits in the management of diseases like
hypertension (Chabot et al 2003; Cote et al 2003), diabetes and cardiovascular disease
(Galt 1998; Munroe et al 1997), asthma (Munroe et al 1997) and HIV (Bozek et al
In one recent Canadian trial to improve treatment persistence among patients with
hypertension, hypercholesterolemia and heart failure, 824 patients were enrolled by
their pharmacist in two Ontario communities (Poston et al 1999). In the control setting
(n=28 pharmacies), all usual practices were followed; in the intervention setting (n=26
pharmacies), patients were given serial educational videos, printed materials and
newsletters, in addition to all usual pharmaceutical care and counseling. Patients were
followed at 3 month intervals, for an average duration of 269 days. For lipid lowering
therapy, among new patients, the intervention was associated with an increase of 13%
in patient adherence (p<0.005). For patients prescribed angiotensin converting enzyme
inhibitor medication, the impact was an additional 8% adherence in the intervention arm
for new patients. Interestingly, in both control and intervention sites, patients had higher
than usually reported adherence rates, suggesting the presence of an important trial
Patient reminders are also becoming more prevalent as an adherence strategy, usually
as telephone calls and/or mailings before a prescription must be refilled or after the refill
date if the prescription has gone unfilled. Lastly, a small number of interventions
incorporate patient financial incentives. Although they have had their sustainability and
cost-effectiveness questioned, they can be efficacious in improving adherence ((Bock et
Establishing a benchmark
The overriding goal of patient adherence programs is to increase acceptance of, and
persistence with, prescribed treatment regimens. However, it is unclear as to what
constitutes the best case benchmark that can be reasonably achieved. What is the gold
Some HIV medication treatment programs set their target benchmark at > 90%
adherence because patients must take their antiretrovirals 95% of the time to get
complete viral suppression (Paterson et al 2000). In coronary heart disease an
equivalent target might be 80%, since studies have found progressively decreased risk
reduction, or increased risk of clinical events, with adherence levels below that figure
(Psaty et al 1990; Blackburn et al 2004).
The highest reported adherence rates occur in randomized controlled trials, as high as
95% for multiple medications over several years (Figure 4; Teo et al 2000). If the
clinical trials results are assumed to be optimal adherence, and the levels from
database analyses are considered the real-world average, then the average gap
between best and usual adherence, after three months of treatment, is about 20%,
However, rates in trials are likely inflated by run-in periods, during which continued
eligibility usually demands >80% adherence with medications for 2-6 weeks before
randomization. This results in a pre-randomization exclusion of non-compliant patients
that is not a realistic management option in usual practice. Not withstanding, it is
important to realize that it is the repeated measurement and feedback of adherence
levels to patients that is the vital discriminating process between trials and usual
medical practice. This continuous measure-feedback loop almost certainly drives the
superior and persistent adherence levels that characterize clinical trials.
The variation in how adherence is measured adds some complexity to this issue.
Patient self-reports, biochemical measures, pill counts, electronic monitoring, pharmacy
renewal rates and provider assessment have all been used. No single measurement
may be appropriate for all situations. The over-riding, take-home lesson is formal
measurement of some kind is valuable, particularly if it is fed back to patients.
In summary, irrespective of situational, drug-specific and measurement-specific
adjustments, the weight of data suggests that persistence expectation can be
realistically set at >80%, and perhaps as high as 95%, over long periods.
Poor adherence is a complex and significant cause of the gap between usual and best
care and a driver of sub-optimal health outcomes. Interventions improve adherence,
although achieving optimal levels remains elusive. A communicative and concordant
patient-provider relationship offers promise of further improving adherence, as does
measurement and feedback of actual adherence patterns as a regular aspect of patient
care and communication. If these promising changes were made in usual care
practices the adherence gap would almost certainly close.
Despite its important contributory role in less than optimal care and outcomes, and its
demonstrated improvability, adherence is somewhat of an orphan in terms of
stakeholder attention, ownership and commitment to make things better. There seems
to be an inertial gap between what we know and what we can do. There is lots of
opportunity and accountability to share, especially for patients and providers. The
arena needs champions. Things can be better.
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Figure 1. The adherence processes depicted as serial decision points in a patient’s therapeutic journey. Figure 2. Two-year persistence patterns of 26,000 patients prescribed cardiac risk- reduction therapy, either angiotensin converting enzyme inhibitor (ACEi) or lipid- lowering (HMG) medications, all of whom were beneficiaries of third party insurance coverage for the medication costs. Reproduced, with permission, from Hospital Quarterly (Sidel et al 1998). Poor Diagnosis Poor prescription Poor adherence Poor access Providers’ Poor Diagnosis Poor prescription Poor adherence Poor access Figure 3. A concordance gap: providers’ (top graph) and patient-consumers’ (bottom graph) opinions of the relative importance of the major causes of care gaps, the difference between best and usual care. Providers feel that adherence is the single most important cause of care gaps; consumers of care, on the other hand, seem to feel that restriction in access is the only cause of care gaps. Provider results were determined from an audience survey at the 1999 Atlantic Canada Cardiovascular Conference; the respondents, a mix of physicians, nurses and pharmacists. Patient consumer results were determined from an audience survey of a 2000 meeting of the Kiwanis Club of Montreal. Figure 4. Five-year persistence patterns of several hundred patients prescribed lipid- lowering (HMG) or placebo control (Placebo) medications during the Simvastatin/enalapril Coronary Atherosclerosis Trial (SCAT). Adapted, with permission, from data provided by the SCAT investigators(Teo et al 2000).
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Chapter 22 Solutions 22.1. (a) Diagram below. (b) The null hypothesis is “all groups have the same mean rest period,” and the alternative is “at least one group has a different mean rest period.” The P -value shows significant evidence against H 0, and the graph leads us to conclude that caffeine has the effect of reducing the length of the rest period. Note: Students mig