DO UTILITY VALUES USED IN HEALTH TECHNOLOGY ASSESSMENT MAINLY COME FROM WIDELY CITED REFERENCES?
Author(s)
Smela-Lipińska B1, Szawara P1, Taieb V2, François C3
1Creativ-Ceutical, Krakow, Poland, 2Creativ-Ceutical, London, UK, 3Creativ-Ceutical, Paris, France
OBJECTIVES: The objective of this study was to assess whether utility source references used in economic modelling for health technology assessment come from widely cited publications. METHODS: We reviewed The National Institute for Health and Care Excellence (NICE) technology appraisal documents and Evidence Review Group (ERG) comments for diseases across four therapeutic areas: oncology, cardiology, ophthalmology and mental health. Utility values used in manufacturer’s submissions and ERG models were identified and corresponding references were extracted. The application of Publish or Perish was used to identify most commonly cited citations from Google Scholar. Different combinations of keywords were tested. Most commonly cited citations and utility references were compared. RESULTS: References from 8 documents were reviewed. In general, 65% (18/28) of the utility source references were among the mostly cited references (with minimum 20 citations): 91% (10/11) in the ophthalmology, 57% (4/7) in oncology, 50% (3/6) in mental health, and 25% (1/4) in cardiology. Our results have shown that most of utility source references used in economic modelling for health technology assessment in ophthalmology example came from widely cited publications, however many relevant references in oncology, mental health and cardiology would have been missed focusing only on widely cited citations. CONCLUSIONS: These results suggest that looking for widely cited citations in Google Scholar can be a good starting point when searching for utilities but should be complemented by a formal literature review when searching for utilities values to inform models as part of health technology assessment.
Conference/Value in Health Info
2018-11, ISPOR Europe 2018, Barcelona, Spain
Value in Health, Vol. 21, S3 (October 2018)
Code
PRM214
Topic
Methodological & Statistical Research
Topic Subcategory
PRO & Related Methods
Disease
Multiple Diseases