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Patient centered care approach to adherence with cardiovascular medications: Self-determination theory integration

Dissertation
Author: David S. Li
Abstract:
Problem statement . Behavioral intervention is used to improve adherence with medication in patients with cardiovascular diseases (CVD), but the effect was not sustainable. Patient-centered care (PCC) as a consumer movement has gained acceptance, but it lacks a theoretical framework. Self-determination theory (SDT) may provide an alternative to improve patients' adherence to chronic cardiovascular medication, as well as a theoretical framework for PCC. Both approaches to CVD management have not been evaluated. Methods . The study was a quasi-experimental pretest posttest comparison design with consecutive sampling of a hospitalized cardiac patient population. Sixty patients each for the usual care (UC) group and the PCC group were recruited. The patient sample consisted of 83% Caucasian, 39% female, 93% insured, an average age of 68 years old, 43% had a NYHF classification of three and above, and an average of 9.7 prescriptions at discharge. A medication teaching intervention was supported by an interactive system designed for PCC. The intervention addressed patients' socioeconomic needs, health literacy adequacy, illness level, timing and amount of teaching, and psychological needs for competence, relatedness, and autonomous motivation. Patients were surveyed once before discharged from the hospital and once three months post discharge. Results . The SDT motivation variables (perceived competence, perceived autonomous support and autonomous motivation) were significantly correlated with the adherence index. Stepwise multivariate regression analyses identified autonomous motivation as an independent predictor of adherence index, along with age, insurance coverage, adverse drug reaction, adequate health literacy, illness level and number of prescription doses taken per day. Patients in the PCC group had significantly higher scores on all three SDT motivation variables, adherence index and higher portion of adherence status than patients in the UC group. Sequential logistic regression analyses reported that PCC intervention, perceived competence and autonomous motivation were independent predictors of adherence status, as well as adverse drug reaction, illness level and number of doses taken per day. Conclusion . Self-determination theory helped to explicate patients' adherence behavior. A patient-centered care environment designed with SDT improved patients autonomous motivation, which improved cardiac patients' adherence to CVD medications.

VI TABLE OF CONTENTS Page LIST OF TABLES viii LIST OF FIGURES ix Chapter I. INTRODUCTION PURPOSE 1 SIGNIFICANCE 1 BACKGROUND 3 PROBLEM STATEMENT 13 II. LITERATURE REVIEW INTRODUCTION 19 APPLICATION OF SELF-DETERMINATION THEORY 23 RELEVANT STUDIES 26 INTEGRATION OF SELF DETERMINATION THEORY IN PATIENT CENTERED CARE 39 HYPOTHESES 40 III. METHOD STUDY DESIGN 42 STUDY VARIABLES AND MEASUREMENTS 43 RESEARCH QUESTIONS AND HYPOTHESES 65 POPULATION AND SAMPLE 69 SETTING CHARACTERISTICS 72 PROTECTION OF HUMAN PARTICIPANTS 73 PROTOCOL 74 PROCEDURES 80 STATISTICS AND DATA ANALYSES 81 IV. RESULTS RESULTS OF DATA ANALYSES 89 V. CONCLUSIONS SUMMARY 109 SUPPORT OF FINDINGS AND OTHERFINDINGS 110 POLICY IMPLICATIONS 115 POLICY RECOMMENDATIONS 118 FUTURE RESEARCHES 121 STUDY LIMITATIONS 122 CONTRIBUTION TO BODY OF KNOWLEDGE 123

REFERENCES APPENDICES A. SCHEDULE OF EVENTS 153 B. SCRIPT FOR RECRUITING PARTICIPANTS 154 C. AN INVITATION TO PARTICIPATE IN A STUDY 155 D. CONSENT FORM 156 E. MEDICAL RECORD ABSTRACTION FORM 158 F. MEDICATION LOG 160 G. PRE-DISCHARGE SURVEY OR SURVEY 1 162 H. POST-HOSPITALIZATION SURVEY OR SURVEY 2 , 166 I. DATA DICTIONARY 2: VARIABLE NAMES, LABELS AND RESPONSES USED IN STATISTICAL SOFTWARE 171 J. IRB APPROVAL 177 K. DATA QUALITY EVALUATION 179 L. SUMMARY OF HYPOTHESES TESTS FOR ADHERENCE 180 FOOTNOTES GETWELLNETWORK IN PATIENT CENTERED CARE 183 VITA 185

via LIST OF TABLES Table Page 2-1. Psychological concepts and operational definition of SDT constructs .... 21 3-1. Data Dictionary 1: Sources of variables 44 3-2. Cardiovascular medications most likely to be prescribed for patients with cardiovascular diseases 52 3-3. New York Heart Association (NYHA) functional classification of heart failure and American College of Cardiology (ACC)/American Heart Association (AHA) classification update for Chronic Heart Failure 62 3-4. Research questions and hypotheses 66 3-5. Population Characteristics of Virginia Beach, Virginia (2008) 70 4-1. Pearson Correlations for interval variables 90 4-2. Characteristics of adherent patients vs. non-adherent patients 93 4-3. Correlations and regression coefficients for adherence index and SDT variables 95 4-4. Predicting adherence index (cadh) with multiple regression 98 4-5. Predicting adherence status with logistic regression 99 4-6. Value of pretest SDT variables vs. posttest SDT variables 101 4-7. ANCOVA tests of between-subjects effects 104

ix LIST OF FIGURES Figure Page 1 -1. Primary and Secondary Prevention of cardiovascular diseases 6 2-1. The Self-Determination Theory Adherence Model 20 2-2. The Self-determination continuum showing types of motivation with their regulatory styles, loci of causality, and corresponding processes.... 24 2-3. SDT guided patient centered care adherence model 40 3-1 / Visual analog scale for adherence to prescription 49 3-2. A 4 days schedule of the CHF interactive care pathway schedules 75 3-3. Flow diagram for CHF interactive care pathway day 1 part 1 76 3-4. Flow diagram for CHF interactive care pathway day 1 part 2 77 3-5. Flow diagram for CHF interactive care pathway day 2 part 1 78 3-6. Flow diagram for CHF interactive care pathway day 2 part 2. 78 3-7. Flow diagram for CHF interactive care pathway day 3 79 3-8. Flow diagram for CHF interactive care pathway day 4 part 1 79 3-9. Flow diagram for CHF interactive care pathway day 4 part 2 80 5-1. Concept mapping for Patient Centered Care and Self-Determination Theory 115 5-2. Factors affecting health. 117

1 CHAPTER I Introduction Purpose The purpose of this study is twofold: 1) to examine the extent to which self- determination theory (SDT) can be used to model adherence to cardiovascular prescriptions; and 2) to describe the effect of a hospital patient-centered care (PCC) program on adherence to cardiovascular prescriptions for the secondary prevention of cardiovascular diseases. Significance Cardiovascular diseases (CVD) comprise conditions such as stroke, hypertension, congestive heart failure (CHF), and coronary heart disease (CHD) (also known as coronary artery disease or CAD) (Lloyd-Jones et al., 2009). CVD is caused by atherosclerosis from the deposition of lipoproteins (plasma proteins that carry cholesterol and triglycerides) to arterial blood vessels. The hardening of the arteries is due to the formation of multiple atherosclerotic plaques within the arteries. Acute coronary syndrome (ACS), an acute manifestation of CHD, occurs when one or more of the coronary arteries become severely or totally blocked by blood clots due to the disruption of unstable atherosclerotic plaque in the coronary artery. The blockage deprives the heart muscle of oxygen-rich blood, leading to subsequent cell death. ACS consists of a constellation of ischemic-induced syndromes such as myocardial infarction (MI; also known as heart attack) and Angina Pectoris (AP; also known as chest pain) (Topol, 2002). The severity of a heart attack usually depends on how much of the heart muscle is injured or dies during the heart attack. If not stabilized by early intervention within the first one to two hours after the onset of symptoms (Sabatine et al., 2005; Antman et al., 2004) from ventricular fibrillation (VF), the odds of survival decrease by 7% to 10% for each minute that a patient remains in VF (Antman et al., 2004; Cummins, Ornato, Thies &Pepe, 1991). After hospitalization for ACS, patients are at high risk of future heart failure, CHD, and stroke (Berthonneche et al., 2007; Cheng et al., 2007; Hochman et al., 2006; American Heart Association, 2005). Newer and more selective cardiovascular (CV) medication is important in the primary prevention of acute myocardial infarction (AMI)

2 medication is important in the primary prevention of acute myocardial infarction (AMI) and may have contributed to the decline of initial AMI. The age-adjusted incidence rates of initial AMI dropped from 272 per 100,000 in 1981, to 184 per 100,000 in 1995. Improved cardiac interventional technologies with effective CV medications may have further contributed to the decline of crude and multivariable-adjusted in-hospital case- fatality rates (17.8% between 1975-1978, 17.0% between 1986-1988, and 11.7% between 1993-1995), as well as morbidity associated with CVD (Spencer, 2003; Goldberg, Yarzebski, Lessard & Gore, 1999). However, patients saved from initial ACS later develop heart failure because of existing risk factors that continue (Hurst, 2002). One of the risk factors is non-adherence to important CV medication (Ho et al., 2006: WHO, 2003). In general, non-adherence to medication, which occurs in 30% to 60% of cases, may lead to undesirable consequences both on an individual and a societal level (Osterberg & Blaschke, 2005; Gehi, Haas, Pipkin & Whooley, 2005; DiMatteo, 2004; Blue Cross & Blue Shield Association, 2003; WHO, 2003; Miller, Hill, Kottke & Ockene, 1997; Rogers & Bullman, 1995; National Pharmaceutical Council, 1992). Besides the simplification of medication regimens, approaches such as education or behavioral interventions alone have not always been effective in the improvement of adherence (Atreja, Bellam & Levy, 2005; DiMatteo, 2004; Blue Cross & Blue Shield Association, 2003; WHO, 2003; Peterson, Takiya & Finley, 2003; Rodgers, 2003; Wald & Law, 2003; Jackevicius, Mamdani & Tu, 2002; Wei et al., 2002; Frantz, Hammann, Pfautsch, Fleck & Herzzentrum, 2002). Psychologically, the concept of compliance is associated with blame, be it of providers or patients, and does not facilitate understanding of the underlying complex systemic issues (WHO, 2003). However, the concept of adherence captures the dynamic and complex changes required of patients and healthcare providers over long periods to maintain optimal health in people with chronic diseases (WHO, 2003). Because the concept of adherence reflects a more contemporary approach to medical treatments, and in the case of this study with secondary prevention of CVD in hospitalized cardiac patients, it is worthy of consideration and reexamination within the paradigm of patient- centered care (PCC) (Kravitz & Melnikow, 2004).

3 The paradigm of PCC provides a framework of thought processes that allows convergence of psychological motivational factors, as addressed by self-determination theory (SDT) (Williams et al., 2006; Williams, McGregor, Freedman & Deci, 2004; Williams, Frankel, Campbell & Deci, 2000; Quill & Brody, 1996; Quill & Cassel, 1995; Deci & Ryan, 1985; Deci & Ryan, 1980). PCC also allows the examination of interventions that are patient-centered. The SDT theoretical framework provides a method of explaining the level of a patient's autonomous motivation within the arena of secondary prevention of C VD of hospitalized cardiac patients with recurrent acute coronary syndromesor chronic heart failure. With chronic CV illnesses, as well as other chronic illnesses, active engagement by a patient because of autonomous motivation may prove to be more important and beneficial than passive behavioral interventions, especially for long-term success with treatment (Williams, Freedman & Deci, 1998; Williams, Grow, Freedman, Ryan & Deci, 1996). Based on numerous precepts of motivational factors relevant to health-related behaviors (Deci & Ryan, 1985; Deci & Ryan, 1980), this study proposes to demonstrate that an autonomous supportive healthcare environment will encourage more self-perceived competence and autonomous motivation. With more autonomous motivation, it is hopeful that patients would be able to better regulate health-related behaviors such as adherence to regimens associated with chronic CVD (Williams et al., 2006; Williams et al, 2004; Williams et al., 2002; Williams, Rodin, Ryan, Grolnick & Deci, 1998; Williams, Freedman & Deci, 1998). Background Intervention to improve adherence with chronic CV medical regimens requires an understanding of the impact of CVD progression, CVD treatments, healthcare environments, as well as the social and psychological functioning of both patients and healthcare providers. Impact of cardiovascular diseases. CVD mortality. Since 1900, CVD, including heart diseases and cerebrovascular diseases, has been the number one killer in the United States every year (CDC, 2009) with the exception of 1918 due to the Spanish flu epidemics (Laver, Bischofberger & WTebster, 1999). CVD claims more lives each year than cancer, chronic lower respiratory diseases, accidents, and diabetes mellitus combined (CDC National Vital Statistics

4 Reports, 2007; Minino, Heron & Smith, 2006). CVD mortality was nearly 60 percent of the total mortality (CDC National Vital Statistics Reports, 2007). This means that of about 2.4 million deaths from all causes, CVD was listed as a primary or contributing cause on about 1.4 million death certificates (Minino et al., 2006). The 2006 overall death rate from CVD was 262.5 per 100,000 population (based on the year 2000 standard U.S. population), accounting for 1 out of every 2.9 deaths (34.3% of all deaths) in the United States. The death rate has declined 25% from 1994 to 2004 overall. The Centers for Disease Control (CDC) estimates that each year 400,000 to 460,000 people die of heart disease in an emergency department or before reaching a hospital, which accounts for more than 60 % of all cardiac deaths, and approximately 60% of unexpected cardiac deaths are treated by emergency medical services (EMS) (Chugh et al., 2004). About 2/3 of unexpected cardiac deaths occur without prior recognition of cardiac disease. The National Center for Health Statistics estimates that life expectancy would rise by about 7 years if all forms of major CVD were eliminated (National Center for Health Statistics, 1999). CVD prevalence and incidence. Contributing to the total 79,400,000 cases of CVD in the United States were 15,800,000 cases of coronary heart disease (CHD), 5,200,000 cases of heart failure (HF), 5,600,000 cases of stroke, 650,000 to 1,300,000 cases of congenital cardiovascular defects, and 72,000,000 cases of high blood pressure (HBP) (Rosamond et al., 2007). CHD manifested as acute coronary syndrome (ACS) with 7,900,000 cases of myocardial infarction (MI), and 8,900,000 cases of angina pectoris (AP). Multiple kinds of CVD also affect people older than 65 years at a disproportionate rate. Of the American adults diagnosed with CVD, 47% were estimated to be age 65 or older (Rosamond et al., 2007). Since the progression of CVD is relatively silent, the devastating effects of CVD are not apparent until the manifestation of an acute coronary event such as angina or acute myocardial infarction (AMI). Admissions to hospital services and cost of cardiovascular disease. CVD as the first-listed diagnosis for short-stay hospitals increased 30% to 6,363,000 from 1979 to 2004, with cardiovascular operations and procedures performed on 3.2 million males, 3.1 million females (National Center for Health Statistics, 2006; Hurst, 2002), and ranked the highest among all disease categories in hospital discharges (DeFrances & Podgornik,

5 2006). In 2001, $29.3 billion in program payments, averaging $8,354 per discharge, were made to Medicare beneficiaries discharged from short-stay hospitals with a principal diagnosis of CVD (Centers for Medicare and Medicaid Services, 2003). In 2007, the total direct and indirect cost was $431.8 billion (Rosamond et al., 2007). Despite the improved outcomes of cardiac interventions in patients who suffered from an initial acute coronary event, continuous vigilance of disease progression combined with risk reduction measures are needed to prevent future heart failure, to prevent recurrent coronary events, and to improve the quality of life of patients. Heart failure (HF). Prevalence of heart failure is on the rise due to people living longer with better health and better medical care. It is also due to the higher survival rates from ACS (Hurst, 2002), since ACS survivors tend to contribute to HF deaths later in life. Heart failure, also known as congestive heart failure (CHF), is a complex clinical syndrome manifested by shortness of breath, fatigue, and abnormal heart function (Topol, 2002). As people age, progressive loss of cardiac function due to heart failure can cause another round of ACS, more heart failure, kidney failure, or stroke (Kannel & Belanger, 1991). Currently, 5.7 million patients in this country suffer from HF (Lloyd-Jones et al, 2009), and another 550,000 patients are being diagnosed with HF for the first time each year (Hunt et al., 2005). Hospital discharges for HF rose from about 0.88 million in 1996 to 1.1 million in 2006 (Lloyd-Jones et al., 2009). Subsequently, the number of HF deaths has increased steadily despite better hospital treatment of CVD in general. In 2005, HF was mentioned on about 292,000 U.S. death certificates, and was selected as the "underlying cause" in about 59,000 of those deaths (Lloyd-Jones et al., 2009; National Center for Health Statistics, 2009). In 2006, $33 billion in hospital charges were incurred by about 1.1 million HF patients (Andrews, 2008). The total estimated direct and indirect costs for HF in 2009 were approximately $37.2 billion (Lloyd-Jones et al., 2009). In the United States, approximately $2.9 billion annually is spent on drugs for the treatment of HF (American Heart Association, 2005). HF is a major and growing public health problem in the United States that warrants a reevaluation of the current approach to the secondary prevention of CVD.

6 Secondary prevention of CVD with medication. Prevention strategies. Prevention studies and policies are based on the concept of dual strategies articulated by Rose as the "mass strategy" and "high-risk strategy" (Rose, 1981). Mass strategy is also known as primary prevention, while high-risk strategy is known as secondary prevention. Each of these strategies may be seen as complementary, not as competing alternatives (Rose, 2001). Primary prevention. Primary prevention is a population-based approach to etiology that seeks to control the determinants of incidence in the population as a whole. Primary prevention of C V diseases involves the reduction of modifiable cardiovascular risks such as lack of physical activity to prevent the first episode of coronary disease, stroke, aortic aneurysm and peripheral arterial disease (Fiebach & Barker, 2006; Pearson et al., 2002). In cardiology, primary prevention is supportive of the traditional approach to health in the general population (i.e., healthy dietary pattern, weight control, appropriate exercise, avoidance of tobacco and secondhand smoke),as well as drug interventions to help patients achieve safe levels of blood pressure, blood sugar, blood cholesterol, and coagulation (Pearson et al., 2002).. Secondary CVD Prevention: Patients with ACS. HE stroke, etc. Primary CVD Prevention: 1 Persons with major CVD risk factors but no acute episodes yet 2 Entire population, including persons with no CVD risk factors. Figure 1-1. Primary and secondary prevention of CVD diseases

7 In Figure 1-1, primary CVD prevention to prevent the first episode of acute coronary syndrome (ACS) or stroke is represented in the lower portion of the pyramid, and the high-risk approach or secondary prevention of ACS is represented at the upper portion of the pyramid. Secondary prevention with CVD medications. Secondary prevention in non- cardiac clinical practice means the early detection of disease before it becomes clinically apparent (Fiebach & Barker, 2006). Secondary prevention in cardiology refers to treating and rehabilitating patients after the occurrence of an ACS (such as myocardial infarction) to prevent future ACS and HF (Fiebach & Barker, 2006). It involves exercise, smoking cessation, management of dyslipidemia, hypertension, diabetes, weight, depression, social isolation, return to work, and other psychosocial factors (American Heart Association, 2007). A major target of secondary CVD prevention is HF. Prevalence of HF has been increasing steadily because of better treatment and salvage of patients from ACS earlier in life (Hurst W, 2002). Since we cannot prevent eventual death in the high-risk CVD population, prevention strategies should not be viewed simply as ways to prevent heart diseases or death, but as a means to control CVD symptoms, slow down the progression of heart failure, and improve patients' quality of life. Most patients with HF do not typically show an uninterrupted worsening of symptoms. When CVD symptoms and risks are managed appropriately, secondary prevention can have marked favorable effects on patients' functional capacity and quality of life (Hunt et al., 2005). Medical management with medications is a major component in the secondary prevention of CVD (Braunwald et al., 2002; Antman et al., 2004; Eagle et al., 2004; Hunt et al., 2005). Depending on the signs and symptoms of CVD, physicians are recommended to customize a patient's medication regimen with one or more of the following: (a) control of hypertension (HBP), fluid, and electrolytes with diuretics, angiotensin converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB), and beta-blockers; (b) prevention of ischemic events with antiplatelet and/or anticoagulation therapy, beta-blockers, and ACEI/ARB; (c) management of diabetes with antidiabetic medications, as well as using ACEI/ARB even with normal blood pressure; (d) management of atherosclerotic disease with antihyperlipidemics and ACEI/ARB; (e) recommendations to change behaviors that increase the risk of HF, such as smoking,

8 excessive alcohol intake, use of illicit drugs, excessive salt intake, unhealthy diet, sedentary life style, and over-weight; (f) management of depression with cognitive- behavioral therapy and/or SSRI (selective serotonin reuptake inhibitor) medications; and (g) management of HF symptoms, arrhythmia, treatment of thyroid disorders and valvular disease, and immunization from respiratory infection as necessary. Successful secondary prevention of CVD requires continuous monitoring by the patient's healthcare team and adherence to CV medications by patients. Adherence to CV medications has the characteristic of being a "prevention paradox": "A preventive measure which brings much benefit to the population offers little to each participating individual" (Rose, 1985, p. 38). The benefit of preventing major CHD events due to "silent" causal factors such as atherosclerosis and high blood pressure is not obvious until it is too late (Labarthe, 1998; National Heart Lung and Blood Institute, 1995; WHO, 1994; Stamler, 1992; Silver, 1990; Keys, 1980; Brook et al., 1979; WHO, 1952). This is significant because patients are not likely to adhere to CV medications unless the factors affecting the behavior of adherence are understood and addressed. The importance of behavioral factors in'health has been recognized and promoted in both primary and secondary prevention (U.S. Department of Health and Human Services, Nov. 2000). Healthy People 2010 estimates that individual behaviors and environmental factors were responsible for about 70% of all premature deaths in the United States by the end of the 20th century (U.S. Department of Health and Human Services, 2000), up from 50% during the 1980s (Centers for Disease Control and Prevention, 1986). Adherence to efficacious medical treatments as a health behavior is necessary for optimal outcomes in the secondary prevention of CVD (Hunt et al., 2005; Atreja et al., 2005; WHO, 2003; Bellg, Rivkin & Rosenson, 2002; Jackevicius et al., 2002; Wei et al., 2002), and needs to be evaluated within the domain of CVD (Bellg, 2003; Sheretal., 2002). Adherence to cardiovascular medications. Definition of adherence. Adherence is defined as "the extent to which a person's behavior - taking medication, following a diet, and/or executing lifestyle changes, corresponds with agreed recommendations from a healthcare provider" (WHO, 2003 p. 3). Medical recommendations are multiple and range from taking a single pill to

9 following a complex drug regimen, seeking preventive care, returning for follow-up appointments, and modifying aspects of one's lifestyle (Roter et al., 1998). Motivational issues of adherence. Although "adherence" and "compliance" have been used interchangeably in healthcare, there are some fundamental differences between them. While adherence emphasizes the active participation of a patient in the patient's care, compliance implies the passive role a patient assumes in the patient and healthcare provider relationship. Compliance is defined as "the act of conforming, acquiescing, or yielding" (Random House Unabridged Dictionary, 2006, p. 419) and is operational in a paternalistic framework in which the physicians make all or most of the decisions, while the patients comply passively (Conrad, 1985). Superficially, complying with the use of prescription medication would seem to be a normal patient behavior. However, medication use involves an active and highly complex decision-making process with many trade-offs in the context of an individual's life choices (Conrad, 1985). Before adopting a medical recommendation from a physician, a patient may also consider drug information provided by other healthcare providers, on-line medical literature, news reports, second opinions, and experiences of family and friends who have taken similar prescriptions. A patient may also evaluate the expected therapeutic efficacy of drugs against the achievement of some specific outcomes in terms of expected time frames. A patient may also derive some idiosyncratic meaning from their decisions about medication use, such as using it as a means to assert control in the doctor-patient relationship (Hayes-Bartista, 1976) or to exert control over one's own life. A patient's decision in medication usage will also be influenced by restrictive managed care requirements and co-payments (Cunningham, 2005). Since a patient does make the ultimate healthcare decisions regarding prescriptions, the notion of adherence is a more appropriate term than compliance in trying to understand why patients decide to take or not take medication for their illnesses (Blue Cross & Blue Shield Association, 2003; WHO, 2003). Thinking in terms of non-compliance may lead to blaming the patient for being disobedient or ignorant. Thinking in terms of non-adherence may compel one to search for unresolved conflicts between an individual patient and recommendations from healthcare providers. Determinants of adherence. The key factors that contribute to poor patient

10 adherence to CVD medications are motivational reasons, along with the asymptomatic characteristic and lifelong nature of CVD (WHO, 2003). Other factors affecting medication adherence include depression, patient demographics, side effects of medication, convenience of drug dosing, cost and number of medications, patient's knowledge, beliefs and attitudes, involvement with care, and health system issues. The relationship between the determinants of adherence and the adherence rate of the cardiac patients at risk of HF discharged from Sentara Virginia Beach General Hospital is unknown. With the support of an interdisciplinary team of cardiac care providers, a patient-centered care model was developed to help address these factors. The model was further implemented and supported by an interactive information system. The proposed study was designed to explore the relationship between adherence to CV prescriptions and factors affecting adherence. Significance of non-adherence. Non-adherence is a hidden epidemic that has been shown to jeopardize patients' health and welUbeing, increase physician and patient frustration, and lead to incorrect diagnoses, unnecessary treatment, and wasted health resources (Osterberg & Blaschke, 2005; DiMatteo & DiNicola, 1982). Non-adherence is associated with the development of complications, disease progression, avoidable hospitalizations, premature disability, and death (Piadevall et al., 2004). In multivariate survival analysis, medication therapy discontinuation due to non-adherence was independently associated with higher mortality (hazards ratio, 3.81; 95% CI=1.88, 7.72) (Ho et al., 2006). The World Health Organization stated that, "...poor adherence increases with the duration and complexity of treatment regimens.. .duration and complex treatment are inherent to chronic illnesses. Across diseases, adherence is the single most important modifiable factor that compromises treatment outcome" (WHO, 2003, p. 135). The economic costs associated with poor medication adherence are estimated to approach $100 billion annually (Hughes, Bagust, Haycox & Walley, 2001; Berg, Dischler, Wagner, Raia & Palmer-Shevlin, 1993). Non-adherence to medication has been estimated to be responsible for as much as 22% of acute care admissions of primary care patients (Lynch & Grant, 2003), 2.5 million medical emergencies per year, 10% of

11 hospital admissions, 23% of nursing home admissions (National Pharmaceutical Council, 1992), and nearly 125,000 deaths per year. Prevalence of non-adherence with CVD medications. In general, the rates of non- adherence to medication vary from 30% to 60%. One'third of all prescriptions are never filled, and more than 50% of prescriptions that are filled are incorrectly administered (Blue Cross & Blue Shield Association, 2003; Peterson et al., 2003; Vermeire, Hearnshaw, Van Royen & Denekens, 2001; Rogers & Bullman, 1995). Almost one third of patients who receive prescriptions are using them in a manner that poses a serious threat to their health (Boyd, Covington, Stanaszek & Coussons, 1974). Yet, patients do not usually volunteer this information to their doctors, and doctors rarely ask (Roter et al., 1998). Studies have been conducted on individual clinical risk factors of CVD such as hypertension and hyperlipidemia. For hypertension, of the 50% of patients who persisted with anti-hypertensive treatment, one-third did not take sufficient medication doses to achieve optimal blood pressure control. In terms of drug class, adherence has been shown to be higher with angiotensin-converting enzyme inhibitors (ACEI) or calcium channel blockers, when compared to diuretics or beta-blockers (Mallion, Baguet, Siche, Tremel & de Gaudemaris, 1998). For hyperlipidemia, fewer than 50% of elderly patients prescribed statin medications for hyperlipidemia were adherent 12 months after initiating therapy (Benner et al., 2002). Adherence for statins has been shown to be higher than adherence with other classes of lipid-lowering agents such as resins or niacin (Avorn et al., 1998). For secondary prevention of CVD with multiple prescriptions after hospitalization for ACS or MI, patients often stop taking medication therapy early. In one month after discharge, of the patients in a multicenter prospective study (n=1521) taking at least three of the most prescribed class of CVD drugs (aspirin, statin, and beta-blocker), only 66% of the patients continued taking all three medications, 12%) discontinued use of all three medications, 4%> discontinued use of two medications, and 18%) discontinued use of one medication (Ho et al., 2006). In a long-term study, only 3-9% of patients continued to take all three for secondary prevention of CVD from 1995 to 2002 (Newby et al., 2006). In secondary prevention of CVD, statins have demonstrated a reduction of the risk of

Full document contains 197 pages
Abstract: Problem statement . Behavioral intervention is used to improve adherence with medication in patients with cardiovascular diseases (CVD), but the effect was not sustainable. Patient-centered care (PCC) as a consumer movement has gained acceptance, but it lacks a theoretical framework. Self-determination theory (SDT) may provide an alternative to improve patients' adherence to chronic cardiovascular medication, as well as a theoretical framework for PCC. Both approaches to CVD management have not been evaluated. Methods . The study was a quasi-experimental pretest posttest comparison design with consecutive sampling of a hospitalized cardiac patient population. Sixty patients each for the usual care (UC) group and the PCC group were recruited. The patient sample consisted of 83% Caucasian, 39% female, 93% insured, an average age of 68 years old, 43% had a NYHF classification of three and above, and an average of 9.7 prescriptions at discharge. A medication teaching intervention was supported by an interactive system designed for PCC. The intervention addressed patients' socioeconomic needs, health literacy adequacy, illness level, timing and amount of teaching, and psychological needs for competence, relatedness, and autonomous motivation. Patients were surveyed once before discharged from the hospital and once three months post discharge. Results . The SDT motivation variables (perceived competence, perceived autonomous support and autonomous motivation) were significantly correlated with the adherence index. Stepwise multivariate regression analyses identified autonomous motivation as an independent predictor of adherence index, along with age, insurance coverage, adverse drug reaction, adequate health literacy, illness level and number of prescription doses taken per day. Patients in the PCC group had significantly higher scores on all three SDT motivation variables, adherence index and higher portion of adherence status than patients in the UC group. Sequential logistic regression analyses reported that PCC intervention, perceived competence and autonomous motivation were independent predictors of adherence status, as well as adverse drug reaction, illness level and number of doses taken per day. Conclusion . Self-determination theory helped to explicate patients' adherence behavior. A patient-centered care environment designed with SDT improved patients autonomous motivation, which improved cardiac patients' adherence to CVD medications.