Off-pump coronary bypass surgery.
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Cardiopulmonary Bypass↗
Biomedical subjects
Bernie O'Brien
Publications and source records attributed to Bernie O'Brien.
Drug policy: making effective drugs available without bankrupting the healthcare system.
To the extent possible, drug policy should be based upon good quality evidence. This must extend beyond the traditional focus on efficacy and safety in carefully selected patients, to evidence about real-world effectiveness, cost-effectiveness and safety of drugs. This paper will consider methods of improving the quality of the evidence currently available, and the implications of requiring that evidence. Historically, there has been a direct link between research evidence and policy at the level of licensing - drugs are only made available after they have been shown to be safe and efficacious in well-designed and independently assessed research studies. We propose that this reliance on evidence be logically extended to cover the formulary inclusion and post-marketing surveillance aspects of modern prescription drug policy. More specifically we propose that the decision to initially list a drug on a benefit formulary be based on evidence from relevant head-to-head comparisons and well-designed cost-effectiveness analyses. This evidence would be produced by industry in cooperation with independent peer-reviewed funding agencies. Drugs could only be added to a formulary if they met specific predetermined criteria, and drugs could be removed as superior alternatives became available. The provincial governments are monopsony buyers of medicines, and they wield the power to determine public payer "market access'for medicines. This power (within and across provinces) could be used more effectively to negotiate price in the context of reimbursement. The effect of different methods of influencing prescribing (e.g., 'limited access?) upon drug utilization and patient outcomes should be rigorously assessed, including the randomization of groups of patients or communities to different strategies. We also propose that all drugs on the formulary would be subject to a well-designed post-marketing surveillance program. This program would build on the existing passive reporting of adverse events by adding a proactive system that would systematically describe the use and impact of drugs. The notion of drug safety would be extended to include not only adverse events, but also inappropriate use of drugs that results inpatients receiving drugs that do not benefit them. Inappropriate use wastes resources and can put patients and populations at risk.
Adverse Drug Reaction Reporting Systems↗
Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices--Modeling Studies.
OBJECTIVES: Mathematical modeling is used widely in economic evaluations of pharmaceuticals and other health-care technologies. Users of models in government and the private sector need to be able to evaluate the quality of models according to scientific criteria of good practice. This report describes the consensus of a task force convened to provide modelers with guidelines for conducting and reporting modeling studies. METHODS: The task force was appointed with the advice and consent of the Board of Directors of ISPOR. Members were experienced developers or users of models, worked in academia and industry, and came from several countries in North America and Europe. The task force met on three occasions, conducted frequent correspondence and exchanges of drafts by electronic mail, and solicited comments on three drafts from a core group of external reviewers and more broadly from the membership of ISPOR. RESULTS: Criteria for assessing the quality of models fell into three areas: model structure, data used as inputs to models, and model validation. Several major themes cut across these areas. Models and their results should be represented as aids to decision making, not as statements of scientific fact; therefore, it is inappropriate to demand that models be validated prospectively before use. However, model assumptions regarding causal structure and parameter estimates should be continually assessed against data, and models should be revised accordingly. Structural assumptions and parameter estimates should be reported clearly and explicitly, and opportunities for users to appreciate the conditional relationship between inputs and outputs should be provided through sensitivity analyses. CONCLUSIONS: Model-based evaluations are a valuable resource for health-care decision makers. It is the responsibility of model developers to conduct modeling studies according to the best practicable standards of quality and to communicate results with adequate disclosure of assumptions and with the caveat that conclusions are conditional upon the assumptions and data on which the model is built.
Benchmarking↗