Abstract
The AMCP Abstracts program provides a forum through which authors can share their insights and outcomes of advanced managed care practice through publication in AMCP's Journal of Managed Care & Specialty Pharmacy (JMCP). Most of the reviewed and unreviewed abstracts are presented as posters so that interested AMCP meeting attendees can review findings and query authors. The Student/Resident/ Fellow poster presentation (unreviewed) is Wednesday, April 20, 2016, and the Professional poster presentation (reviewed) is Thursday, April 21. The Professional posters will also be displayed on Friday, April 22. The reviewed abstracts are published in the JMCP Meeting Abstracts supplement. The AMCP Managed Care & Specialty Pharmacy Annual Meeting 2016 in San Francisco, California, is expected to attract more than 3,500 managed care pharmacists and other health care professionals who manage and evaluate drug therapies, develop and manage networks, and work with medical managers and information specialists to improve the care of all individuals enrolled in managed care programs. Abstracts were submitted in the following categories: Research Report: describe completed original research on managed care pharmacy services or health care interventions. Examples include (but are not limited to) observational studies using administrative claims, reports of the impact of unique benefit design strategies, and analyses of the effects of innovative administrative or clinical programs. Economic Model: describe models that predict the effect of various benefit design or clinical decisions on a population. For example, an economic model could be used to predict the budget impact of a new pharmaceutical product on a health care system. Solving Problems in Managed Care: describe the specific steps taken to introduce a needed change, develop and implement a new system or program, plan and organize an administrative function, or solve other types of problems in managed care settings. These abstracts describe a course of events; they do not test a hypothesis, but they may include data.
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