Early technology assessment of new medical devices

Objectives: In the United States, medical devices represent an eighty-billion dollar a year market. The U.S. Food and Drug Administration rejects a significant number of applications of devices that reach the investigational stage. The prospects of improving patient condition, as well as firms' profits, are thus substantial, but fraught with uncertainties at the time when investments and design decisions are made. This study presents a quantitative model focused on the risk aspects of early technology assessment, designed to support the decisions of medical device firms in the investment and development stages. Methods: The model is based on the engineering risk analysis method involving systems analysis and probability. It assumes use of all evidence available (both direct and indirect) and integrates the information through a linear formula of aggregation of probability distributions. The model is illustrated by a schematic version of the case of the AtrialShaper, a device for the reduction of stroke risk that is currently in the preprototype stage. Results: The results of the modeling provide a more complete description of the evidence base available to support early-stage decisions, thus allowing comparison of alternative designs and management alternatives. Conclusions: The model presented here provides early-stage decision-support to industry, but also benefits regulators and payers in their later assessment of new devices and associated procedures.

[1]  M. Elisabeth Paté-Cornell,et al.  A Framework for Probabilistic Assessment of New Medical Technologies , 2004 .

[2]  D M Murphy,et al.  The SAM framework: modeling the effects of management factors on human behavior in risk analysis. , 1996, Risk analysis : an official publication of the Society for Risk Analysis.

[3]  Lawrence L. Kupper,et al.  Probability, statistics, and decision for civil engineers , 1970 .

[4]  J. Kankaanpää,et al.  Assessment of health care technologies : case studies, key concepts, and strategic issues , 1996 .

[5]  M. Eliasziw,et al.  Drugs and surgery in the prevention of ischemic stroke. , 1995, The New England journal of medicine.

[6]  C Guilleminault,et al.  Radiofrequency volumetric reduction of the tongue. A porcine pilot study for the treatment of obstructive sleep apnea syndrome. , 1997, Chest.

[7]  Hiromitsu Kumamoto,et al.  Probabilistic Risk Assessment , 1996 .

[8]  Clifford Goodman,et al.  The 5th Annual Meeting of the International Society of Technology Assessment in Health Care , 1988, International Journal of Technology Assessment in Health Care.

[9]  Markel,et al.  The effect of radiofrequency energy on the length and temperature properties of the glenohumeral joint capsule. , 1998, Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association.

[10]  C. Guilleminault,et al.  Radiofrequency volumetric tissue reduction of the palate in subjects with sleep-disordered breathing. , 1998, Chest.

[11]  D. Levy,et al.  Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. , 1998, Circulation.

[12]  J. Neumann,et al.  Theory of games and economic behavior , 1945, 100 Years of Math Milestones.

[13]  R. Clemen Combining forecasts: A review and annotated bibliography , 1989 .

[14]  Kaplan,et al.  ‘Combining Probability Distributions from Experts in Risk Analysis’ , 2000, Risk analysis : an official publication of the Society for Risk Analysis.

[15]  P. Taylor Clinical Decision Making: From Theory to Practice , 1996 .

[16]  E. Rowland Theory of Games and Economic Behavior , 1946, Nature.

[17]  Ronald A. Howard,et al.  Readings on the Principles and Applications of Decision Analysis , 1989 .

[18]  Ronald A. Howard,et al.  Influence Diagrams , 2005, Decis. Anal..