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Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) – dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients’ quality of life. Integrating PK/PD–EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

A modular interdisciplinary platform was developed to investigate the economic impact of oseltamivir treatment by dosage regimen under simulated influenza pandemic scenarios.The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration-time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (ROseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios.This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework.

Background: The clinical outcomes and quality of care in acute ischemic stroke (AIS) are time-dependent and influenced by the effectiveness and efficiency of the care delivery system. Much attention has been given to improving process and procedure; however, the structure and inter[[Unable to Display Character: ‐]]dependencies of the stroke care teams must be integrated into any acute stroke care quality improvement process. Objective: The objective of this study was to apply an innovative multi[[Unable to Display Character: ‐]]modal analytic approach that combines formal epidemiologic analysis, process evaluation and social network modeling of stroke care teams to describe and improve the critical system characteristics of high[[Unable to Display Character: ‐]]performing units in real[[Unable to Display Character: ‐]]world hospital systems. Methods: Characteristics of individual hospital units, as well as variation of treatment delivery, were analyzed and compared. A critical path analysis was created based on a widely adopted acute stroke care process model. Stroke care team structures and inter[[Unable to Display Character: ‐]] dependencies were mapped based on the responses to a survey and the responses were analyzed using open[[Unable to Display Character: ‐]]source network graphing software. Results: The care team networks were overlaid on to the corresponding process pathways to create a final synthesis of the process and team structure (example below). Critical path analysis combined with mapping of the individual stroke team network interactions demonstrated additional associations between the team structures and process/clinical outcomes. Opportunities for improvement in both process and personnel organization were identified and integrated into existing CQI efforts. Conclusion: Multi[[Unable to Display Character: ‐]]modal systems analysis incorporating both care process and stroke care team inter[[Unable to Display Character: ‐]]dependencies offers an enhanced approach to integrated quality improvement for acute stroke care.

Clinical trial eligibility criteria define the target patient population for research studies. We assessed the eligibility criteria from 40 different protocols for Type II Diabetes Mellitus and depression (20 protocols each), to determine the extent to which protocol eligibility criteria were similar at three levels (test, test-value, and test-value-time clause). This was done to determine criteria that could be standardized to aid in identification of eligible patients from electronic health records. It was found that Type II Diabetes Mellitus had 36.9% similar and depression protocols had 53.1% similar at the test-value-clause level. This study demonstrates the need for more standardization of study protocol criteria as well as the associated query definitions to be run against the electronic healthcare data. Standardizing criteria based on the similar eligibility criteria between protocols will aid in patient recruitment by being able to reuse criteria and minimizing the time and money it takes to recruit patients.

Wu DBC1, Chaiyakunapruk N1,2,3,4, Pratoomsoot C5, Lee KKC1, Chong HY1, Nelson RE6, Smith PF7, Kirkpatrick C8, Kamal MA9, Nieforth K7, Dall G7, Toovey S10, Kong DCM8, Kamauu A11, Rayner CR7 1School of Pharmacy, Monash University, Sunway, Malaysia ,2 Center of Pharmaceutical Outcomes Research (CPOR), Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Thailand, 3 School of Pharmacy, University of Wisconsin, Madison, USA, 4 School of Population Health, University of Queensland, Brisbane, Australia, 5Faculty of Public Health, Naresuan University, Thailand, 6University of Utah, Salt Lake City, UT, 7 d3 Medicine LLC, 8Monash University, Melbourne, Australia, 9Hoffman-La Roche, Inc., Nutley, NJ, 10Royal Free and University College Medical School, London, UK, 11Anolinx LLC, Salt Lake City