Community Pharmacy Professional Service Availability: An International Comparison

Abstracts / Research in Social and Administrative Pharmacy 10 (2014) e1–e64 continued with one task for a long period of time, regularly task-switching to manage changing demands, often without completing their initial task. Distractions involved pharmacists splitting their attention between two tasks. As with interruptions, pharmacists would often handle these on demand. Furthermore, the combination of interruptions and distractions meant workload was fragmented. Sources of interruptions and distractions included staff, customers and telephone calls. Many involved issues which may have been resolved by other support staff. Questions from staff or customers were especially problematic, demonstrating a range in awareness of pharmacists’ apparent busyness; some waited for pharmacists to end their task, whilst others would interrupt or distract without regard. Conclusions: Use of observational narrative was successful in capturing snapshots of pharmacists’ working practices. Interruptions and distractions drive task-switching and fragmentation of workload, with potential to affect productivity and task accuracy. Not only is this an important consideration for patient safety, but increasing busyness of community pharmacists make these factors key in the management of workload. A shift in culture is required to change the dynamics of working practices for a safer and more sustainable outcome. Community Pharmacy Professional Service Availability: An International Comparison J.P. Perepelkin1, E.E. Ulrich2, 1College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada, 2College of Pharmacy and Health Sciences, Drake University, Des Moines, Iowa, United States The objective of this study is to determine what services are currently being offered in the community pharmacies, cost of service to the patient, how often the pharmacy offers each service, and the types of pharmacy settings are offering services in Iowa, United States and Saskatchewan, Canada. These two regions were chosen primarily for their similarities in geography and population demographics. Methods: A list of all pharmacies and contact information in the state of Iowa was provided by Iowa Pharmacy Association and in the province of Saskatchewan, the Saskatchewan College of Pharmacists. Furthermore, information was compiled on the scopeof-practice in Iowa and Saskatchewan, as well as which services were remunerated through a health plan and/or insurance provider (i.e. not out-of-pocket or free). Each pharmacy was surveyed (spring 2014) via phone on what services they offer, how much, if at all, each service costs to patients and/or how the services are remunerated, how often they provide the service (walkin, specific times/days, etc.), number of pharmacists and pharmacy technicians on duty at a time, and the type of pharmacy setting. Overall descriptive statistics will be conducted on all variables. Spearman and Pearson correlations will be

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also performed between variables. To determine differences between different community pharmacy settings, Chi-square and t-tests will be conducted on all variables. A logistic regression will be conducted to determine if controlling for state/province, pharmacy setting, staffing, and perceived cultural attitude are related to offering services. A linear regression analysis will be conducted to determine if pharmacy setting, staffing, and perceived cultural attitude of providing services are related to frequency of providing professional services. Expected Outcomes: We expect to see that variation exists between on the availability and provision of services, based on pharmacy staffing, and type of community pharmacy. Comparison of self-reported medicine use with the pharmaceutical claims database in patients with osteoarthritis R. Braund, N. Allison, University of Otago, Dunedin, New Zealand To investigate the correlation between self-reported medicine use and dispensing data obtained from the pharmaceutical claims database and determine whether the correlation changes over time or if it is affected by an individual participants pill burden. Additionally to determine whether self-report is an appropriate way to measure medicine usage. A secondary objective was to examine the profile of therapeutic agents used in this group of people with osteoarthritis. Method: This report is a secondary analysis of results from a randomised controlled trial – the Management of Osteoarthritis (MOA) trial. Self-reported medicine use obtained during the MOA trial was compared to data contained in the pharmaceutical claims database. Medicine use as reported in the MOA trial was also investigated to see how this compared with current guideline advice. Results: 70% of participants reported the same medicine information that was recorded in the pharmaceutical claims database. When excluding those who had no medicines to report, 59% reported the same medicines as recorded in the database. Participants with a drug burden of 0 to 4 medicines were most accurate at recalling the medicines they had been dispensed. Paracetamol was the most commonly used medicine followed by glucosamine. Of those using opioids, codeine was most common followed by oxycodone. Less than half of those using NSAIDs were also using a proton pump inhibitor (PPI). Conclusion: This comparison of self-reported medicine usage versus medicine use information obtained by a pharmaceutical claims database found that neither method of obtaining this information is perfect. It is possible that the most accurate way to gather information about a patient’s medicine use would be to use a combination of both methods. Many patients with osteoarthritis are using treatments recommended by