OBJECTIVES: The aim of this study was to review 5 years of activity from a new system devised by the National Institute for Health and Care Excellence (NICE), for assessing medical devices and diagnostics aimed at identifying and speeding adoption of technologies with clinical and cost advantages, compared with current practice in the United Kingdom healthcare system. METHODS: All eligible notified technologies were classified using the Food and Drug Administration and Global Medical Device Nomenclature nomenclatures. Decisions about selecting technologies for full assessment to produce NICE recommendations were reviewed, along with the reasons given to companies for not selecting products. RESULTS: Between 2009 and 2014, 186 technologies were notified (46 percent therapeutic and 54 percent diagnostic). Thirty-nine were judged ineligible (no regulatory approval), and 147 were considered by an independent committee. Of these, eighty (54 percent) were not selected for full assessment, most commonly because of insufficient evidence (86 percent): there were uncertainties specifically about benefits to the health service (54 percent), to patients (39 percent), and about cost (24 percent). The remaining 67 were selected and assessed for Medical Technology guidance (52 percent) (noninferior and/or lower cost consequences than current practice), for Diagnostics guidance (43 percent) or other NICE recommendations about adoption and use. Classifying technologies by two different systems showed no selection bias for any technology type or disease area. CONCLUSIONS: Identifying new or under-used devices and diagnostics with potential benefits and promoting their adoption is important to health services in the United Kingdom and worldwide. This new system offers a means of fostering both uptake and further research. Lack of research data on new products is a major obstacle to evaluation.
OBJECTIVES: The aim of this study was to review 5 years of activity from a new system devised by the National Institute for Health and Care Excellence (NICE), for assessing medical devices and diagnostics aimed at identifying and speeding adoption of technologies with clinical and cost advantages, compared with current practice in the United Kingdom healthcare system. METHODS: All eligible notified technologies were classified using the Food and Drug Administration and Global Medical Device Nomenclature nomenclatures. Decisions about selecting technologies for full assessment to produce NICE recommendations were reviewed, along with the reasons given to companies for not selecting products. RESULTS: Between 2009 and 2014, 186 technologies were notified (46 percent therapeutic and 54 percent diagnostic). Thirty-nine were judged ineligible (no regulatory approval), and 147 were considered by an independent committee. Of these, eighty (54 percent) were not selected for full assessment, most commonly because of insufficient evidence (86 percent): there were uncertainties specifically about benefits to the health service (54 percent), to patients (39 percent), and about cost (24 percent). The remaining 67 were selected and assessed for Medical Technology guidance (52 percent) (noninferior and/or lower cost consequences than current practice), for Diagnostics guidance (43 percent) or other NICE recommendations about adoption and use. Classifying technologies by two different systems showed no selection bias for any technology type or disease area. CONCLUSIONS: Identifying new or under-used devices and diagnostics with potential benefits and promoting their adoption is important to health services in the United Kingdom and worldwide. This new system offers a means of fostering both uptake and further research. Lack of research data on new products is a major obstacle to evaluation.
Authors: Bruce Campbell; Mark Campbell; Lee Dobson; Joanne Higgins; Bernice Dillon; Mirella Marlow; Chris J D Pomfrett Journal: Int J Technol Assess Health Care Date: 2018-07-20 Impact factor: 2.188
Authors: Steven M Bradley; Sophia Emmons-Bell; R Kannan Mutharasan; Fatima Rodriguez; Divya Gupta; Gregory Roth; Ty J Gluckman; Rashmee U Shah; Tracy Y Wang; Rohan Khera; Pamela N Peterson; Sandeep Das Journal: Sci Rep Date: 2021-07-23 Impact factor: 4.379