Class of 2015 Abstract / Objectives: Our specific aim is to assess the changes in patient adherence in response to medication synchronization. Our working hypothesis is that medication synchronization will have a positive impact on patient adherence. Methods: This retrospective pre-post cohort study assessed medication adherence 365 days before and 365 days after enrollment into a prescription synchronization program. There were 5,994 patients included in the study. Seven medication classes and three demographic groups were chosen to assess for adherence. Adherence was determined by calculating mean proportion of days covered. A paired t-test was used to determine statistical significance for each drug class and demographic group. Exploratory analyses were done at 90 days and 180 days before and after the sync date to determine differences in terms of time. An alpha a-priori was set at 0.05 before analysis was started. Results: Current Fry’s Pharmacy patients greater than 18 years old that met the Centers for Medicare and Medicaid Services (CMS) for STARs rating criteria were included in the study. Results at 365 days showed a statistically significant decrease in PDC (p<0.0001), and was not affected by demographics. Conclusions: One year after the implementation of medication synchronization program at Fry’s Pharmacy, a statistically significance decrease in PDC is seen across all categories of chronic medications: statins, ACE-I/ARBs, beta-blockers, CCBs, metformin, thiazides, loop-diuretics, and inhaled corticosteroids. As such, medication synchronization may decrease patient adherence to the maintenance medications evaluated.

Class of 2005 Abstract / Objective: The purpose of this study was to explore whether current meta-analyses on exercise interventions assess adherence and/or compliance of the studies included in the meta-analyses and to determine if subject adherence had any effect on outcomes of the analyses. Methods: Data was collected through a search of the MEDLINE database using the key words exercise, adherence, compliance, clinical trials, and meta-analysis. Data on study title, author, number of studies screened, number in meta-analysis, range of sample sizes, total number of subjects, primary intervention, primary outcome, how study quality was assessed, how adherence was assessed, whether adherence was used as a control variable, and did adherence affect the outcome was recorded on a paper and pencil data extraction form. Data was analyzed by constructing a table describing the meta-analyses and calculating the number and percent of analyses that included adherence. The table allowed for the evaluation of the strength and methodology of each piece of literature with respect to acknowledging adherence as a significant variable in the strength and legitimacy of each analysis. Results: Nineteen meta-analyses met our search criteria and were evaluated. Five of the nineteen meta-analyses (26 percent) described a method for assessing adherence. It was found that none of these used adherence as a control variable. Four of the nineteen meta-analyses did not assess the quality of the studies contained within the analysis. One of these meta-analyses suggested that adherence may have confounded outcomes, but did not provide any data to address their concerns. Conclusions: In meta-analyses, adherence is unlikely to be addressed. Current meta-analyses frequently lack methods for assessing adherence, and do not use adherence as a control variable. Whether adherence to exercise regimens affects outcomes cannot be determined from current meta-analyses.

ST-segment elevation myocardial infarction (STEMI) is a common presentation of acute myocardial infarction, constituting approximately 30% of all cases. Based on the highest level of evidence for improvement in both morbidity and mortality in these patients, clinical guidelines from around the world support the prolonged use of secondary preventative medications (e.g., acetylsalicylic acid, second antiplatelet [clopidogrel, prasugrel, and ticagrelor], statin, beta-blocker, and angiotensin blocker). While in-hospital and discharge prescription rates for these essential life-saving medications is excellent, adherence is known to decline within weeks of hospital discharge. This decline in evidence-based medication use was confirmed in a population of patients with coronary artery disease in Ontario (Chapter 3). Furthermore, it was demonstrated that this decline was consistent across all medication classes and subgroups of patients. We developed a protocol (Chapter 4) for a cluster-randomized controlled trial evaluating the impact of repeated reminders sent by mail to the family physician and the patient, starting one month after the STEMI. The fifth chapter highlights the results of the cluster-randomized controlled trial, which demonstrates suboptimal persistence to all 4 of 4 cardiac medication classes at 12-months. There was no significant difference compared to usual care in the use of guideline-recommended medications post-STEMI when participants (and their family physicians) receive repeated postal reminders.

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Objectives Three objectives were to compare: 1) treatment success; 2) healthcare resource uses; and 3) out-of-pocket (OOP) expenditures, indirect costs, and health-related quality of life (HRQoL) associated with pharmaceutical care, home visit, and modified DOT in three referral hospitals in Songkhla province, Thailand. Methods Project 1&2 were retrospective cohort study collecting data from 1,398 pulmonary TB patients who started treatment between October 2010 and September 2013. Project 3 was a prospective study collecting data from 104 pulmonary TB patients who started treatment between January and May 2014. The propensity score matching and generalized linear models (GLMs) were used to compare the outcomes associated with three supervision approaches by adjusting for baseline characteristics. Results Project1: The differences in treatment success rate were not statistically significant when comparing pharmaceutical care with either home visit (success rate: 92.76% versus 94.74%) or modified DOT (success rate 93.37% for both). Project2: The mean direct healthcare costs to public payer were $519.96 (95% confidence interval (CI): $437.31 to $625.58) for pharmaceutical care, $1,020.39 (CI:$911.13 to $1,154.11) for home visit, and $887.79 (CI:$824.28 to $955.91) for modified DOT. Project3: Mean OOP expenditures were $907.56 (CI:$603.80 to $1,269.41), $148.47 (CI:$109.49 to $194.89), and $95.35 (CI:$69.11 to $129.63), while the indirect costs were $1,925.68 (CI:$922.06 to $3,284.94), $2,393.66 (CI:$1,435.01 to $3,501.98), and $833.33 (CI:$453.87 to $1,263.45), for those receiving pharmaceutical care, home visit, and SAT, respectively. Mean health utility scores at the baseline and the end of treatment were 0.679 and 0.830, 0.713 and 0.905, and 0.708 and 0.913 for the patients receiving pharmaceutical care, home visit, and SAT, respectively. Conclusion Pharmaceutical care is clinically and economically effective compared with the other strategies studied. A large-scale prospective study is warranted to strengthen evidence to support policy making in TB management in Thailand. / Thesis / Doctor of Philosophy (PhD)

No / Objective The objective of this study was to evaluate adherence and causes for non-adherence to antihypertensive therapy in Austrian patients. A special focus was placed on social parameters and behavioural theories. Methods Patients were invited via advertisements in community pharmacies in Austria to complete an online survey. Inclusion criteria were an age of 18 years or older, a diagnosis of arterial hypertension and a current prescription of antihypertensive medication. Adherence was measured by the four-item Morisky scale. Non-adherence was defined by at least one point in the Morisky scale. Several demographic, social and behavioural parameters were analysed as potential co-variables associated with adherence. Results A total of 323 patients completed the online survey, of which 109 (33.7 %) met the criteria for nonadherence. In a multivariable model, self-efficacy and age were associated with adherence, whereas intention and barriers were linked to non-adherence; 56 patients (17.3 %) were classified as intentionally non-adherent. Conclusion This study demonstrates that non-adherence affects an important proportion of patients in the treatment of arterial hypertension. Young age was a particularly important risk factor for non-adherence, and this patient population is, therefore, in need of special attention. Modifiable risk factors were identified that could help improving the treatment of arterial hypertension and potentially other chronic conditions. / European Union’s Seventh Framework Programme FP7/2007–2013 ‘Ascertaining Barriers to Compliance (ABC) project’ under grant agreement number 223477.

Across the literature it is seen that when trying to enact change in a patient’s everyday life there is always some degree of adherence risk. In the field of voice therapy this risk is particularly high. Traditional comparisons of therapy techniques focus only on change achieved as opposed to the ways in which each therapy protocol was carried out. This type of focus minimizes the amounts of adherence risk present in each therapy technique. This risk can have a fundamental impact on the success of therapy. A comparison of the types of adherence risk that exists and the ways they can be minimized is useful for the treatment of voice disorders. This report serves to address issues of adherence risk in voice by examining relevant research outside the field of speech language pathology. It contains information regarding the most commonly seen adherence risks encountered, research on how those risks were addressed in the fields of medicine and physical therapy, and how those techniques can be adapted for clinical use. A comparative analysis of the types of risks present in the most common therapy protocols and how those risks can be minimized is also included. Tables are included in order to provide the speech language pathologist (SLP) with a user-friendly guide on the possible ways to determine adherence risks present in their client and possible ways to address this risk. Sample dialogue is also provided. Adherence risk is a key component in voice therapy that is often not being considered when choosing and implementing therapy protocols. There are many factors that make up adherence risk including personality characteristics, motivation, expectations for therapy, ease of use of the technique/instructions, client understanding of implementation, and the nature of the disorder itself. It is useful to look at how such factors are addressed. We’re asking our clients to do many things that will change their daily lives: behaviorally, diet-wise, it may even impact the way they feel about themselves. How do we ask them this and expect that it’ll actually get done? / text