The Use of Health State Utility Values In Decision Models
| Autor: | John Brazier, Roberta Ara, Ismail Azzabi Zouraq |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Time Factors Health Status Population Disease Decision Support Techniques Health administration 03 medical and health sciences 0302 clinical medicine medicine Humans 030212 general & internal medicine education Adverse effect Pharmacology education.field_of_study Actuarial science Health economics business.industry 030503 health policy & services Health Policy Public health Uncertainty Public Health Environmental and Occupational Health Patient Preference Models Theoretical Double counting (accounting) Quality of Life 0305 other medical science business Decision model |
| ISSN: | 1170-7690 |
| Popis: | Methodological issues of how to use health state utility values (HSUVs) in decision models arise frequently, including the most appropriate evidence to use as the baseline (e.g. the baseline HSUVs associated with avoiding a particular health condition or event), how to capture changes due to adverse events and how to appropriately capture uncertainty in progressive conditions where the expected change in quality of life is likely to be monotonically decreasing over time. As preference-based measures provide different values when collected from the same patient, it is important to ensure that all HSUVs used within a single model are obtained from the same instrument where ever possible. When people enter the model without the condition of interest (e.g. primary prevention of cardiovascular disease, screening or vaccination programmes), appropriate age- and gender-adjusted HSUVs from people without the particular condition should be used as the baseline. General population norms may be used as a proxy if the exact condition-specific evidence is not available. Individual discrete health states should be used for serious adverse reactions to treatment and the corresponding HSUVs sourced as normal. Care should be taken to avoid double counting when capturing the effects for both less severe adverse reactions (e.g. itchy skin rash or dry cough) and more severe adverse events (e.g. fatigue in oncology). Transparency in reporting standards for both the justification of the evidence used and any ‘adjustments’ is important to increase readers’ confidence that the evidence used is the most appropriate available.\ud \ud |
| Databáze: | OpenAIRE |
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