Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
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A substantial gap exists between medical evidence that is known and medical evidence that is put into practice. Although the Agency for Healthcare Research and Quality (AHRQ) has a long history of developing the content of evidence, the agency now pivots to close that gap by focusing on evidence dissemination and implementation. Achieving better health outcomes requires both the generation of new patient-centered outcomes research (PCOR) knowledge and the appropriate and timely implementation of that knowledge into practice. ⋯ Toward this goal, AHRQ is actively engaging partners, such as professional societies and insurers, to make evidence central to decision making. In addition, AHRQ recently launched two programs that seek to both understand and encourage the use of evidence in clinical practice. Throughout these efforts, AHRQ will continually assess needs and adapt initiatives to ensure that PCOR translates into improved patient-centered health outcomes.
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Multicenter Study Comparative Study
Modeling Health State Utility Values in Ankylosing Spondylitis: Comparisons of Direct and Indirect Methods.
Cost-effectiveness analyses of technologies for patients with ankylosing spondylitis frequently require estimates of health utilities as a function of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Bath Ankylosing Spondylitis Functional Index (BASFI). ⋯ These results add to a body of evidence that the statistical model used to estimate health utilities matters. Linear models are not appropriate. The four-class bespoke mixture model approach provides the best performing method to estimate the EuroQol five-dimensional questionnaire values from BASDAI and BASFI.
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Comparative Study
Analysis of Medicine Prices in New Zealand and 16 European Countries.
To compare prices of medicines, both originators and generics, in New Zealand and 16 European countries. ⋯ Medicine prices varied considerably between European countries and New Zealand as well as among the European countries. These differences are likely to result from national pricing and reimbursement policies.
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In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling can be used more effectively than other modeling methods. The hierarchical relationship between the health care delivery system, providers, patients, and other stakeholders exhibits a level of complexity that ought to be captured using dynamic simulation modeling methods. As a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of an intervention on a health care system, we presented the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist consisting of eight elements. This report builds on the previous work, systematically comparing each of the three most commonly used dynamic simulation modeling methods-system dynamics, discrete-event simulation, and agent-based modeling. ⋯ Upon reviewing this report in addition to using the SIMULATE checklist, the readers should be able to identify whether dynamic simulation modeling methods are appropriate to address the problem at hand and to recognize the differences of these methods from those of other, more traditional modeling approaches such as Markov models and decision trees. This report provides an overview of these modeling methods and examples of health care system problems in which such methods have been useful. The primary aim of the report was to aid decisions as to whether these simulation methods are appropriate to address specific health systems problems. The report directs readers to other resources for further education on these individual modeling methods for system interventions in the emerging field of health care delivery science and implementation.
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Clinical trials evaluating medicines, medical devices, and procedures now commonly assess the economic value of these interventions. The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. As decision makers increasingly demand evidence of economic value for health care interventions, conducting high-quality economic analyses alongside clinical studies is desirable because they broaden the scope of information available on a particular intervention, and can efficiently provide timely information with high internal and, when designed and analyzed properly, reasonable external validity. ⋯ Uncertainty should be characterized. Articles should adhere to established standards for reporting results of cost-effectiveness analyses. Economic studies alongside trials are complementary to other evaluations (e.g., modeling studies) as information for decision makers who consider evidence of economic value along with clinical efficacy when making resource allocation decisions.