Axel C Mühlbacher1, Susanne Bethge. 1. IGM Institut Gesundheitsökonomie und Medizinmanagement, Hochschule Neubrandenburg, Brodaer Straße 2, 17033, Neubrandenburg, Germany, muehlbacher@hs-nb.de.
Abstract
BACKGROUND AND OBJECTIVE: Cardiovascular disease is the main cause of death in Germany and other industrialized countries. However, until now, little has been known about how people with acute coronary syndrome (ACS) value aspects of their medical treatment. The objective of this study was to evaluate patients' preferences regarding different antiplatelet medication options following an ACS. METHOD: After identification of patient-relevant treatment attributes (a literature review and qualitative interviews), a discrete-choice experiment (DCE) including five patient-relevant attributes was conducted. The DCE used a forced-choice approach in which no "opt out" was present, as no treatment is not an option after ACS. The attribute and level combinations were created using a fractional-factorial NGene design with priors. Data analysis was performed using a random-effects logit model. An additional generalized linear latent and mixed models (GLLAMM) analysis was performed to evaluate subgroup differences. RESULTS: ACS patients (N = 683) participated in computer-assisted personal interviews. Preference analysis showed a clear dominance of the attribute "mortality risk" (coefficient: 0.803). Ranked second was "side effect: dyspnea" (coefficient: 0.550) followed by "risk of a new myocardial infarction" (coefficient: 0.464) and "side effect: bleeding" (coefficient: 0.400). "Frequency of intake" was less important (coefficient: 0.025). Within the 3-class GLLAMM, the variables "marital status" (p = 0.008), "highest level of education" (p = 0.003), and "body-mass index" (according to World Health Organization cluster; p = 0.014) showed a significant impact on the estimated class probabilities. CONCLUSION: Our study found "mortality risk" to be of the highest value for patients. Patient-centered care and decision making requires consideration of patient preferences; moreover, the information on preferences can be used to develop effective therapies after an ACS. The data generated will enable healthcare decision makers and stakeholders to understand patient preferences to promote patients' benefit.
BACKGROUND AND OBJECTIVE:Cardiovascular disease is the main cause of death in Germany and other industrialized countries. However, until now, little has been known about how people with acute coronary syndrome (ACS) value aspects of their medical treatment. The objective of this study was to evaluate patients' preferences regarding different antiplatelet medication options following an ACS. METHOD: After identification of patient-relevant treatment attributes (a literature review and qualitative interviews), a discrete-choice experiment (DCE) including five patient-relevant attributes was conducted. The DCE used a forced-choice approach in which no "opt out" was present, as no treatment is not an option after ACS. The attribute and level combinations were created using a fractional-factorial NGene design with priors. Data analysis was performed using a random-effects logit model. An additional generalized linear latent and mixed models (GLLAMM) analysis was performed to evaluate subgroup differences. RESULTS: ACS patients (N = 683) participated in computer-assisted personal interviews. Preference analysis showed a clear dominance of the attribute "mortality risk" (coefficient: 0.803). Ranked second was "side effect: dyspnea" (coefficient: 0.550) followed by "risk of a new myocardial infarction" (coefficient: 0.464) and "side effect: bleeding" (coefficient: 0.400). "Frequency of intake" was less important (coefficient: 0.025). Within the 3-class GLLAMM, the variables "marital status" (p = 0.008), "highest level of education" (p = 0.003), and "body-mass index" (according to World Health Organization cluster; p = 0.014) showed a significant impact on the estimated class probabilities. CONCLUSION: Our study found "mortality risk" to be of the highest value for patients. Patient-centered care and decision making requires consideration of patient preferences; moreover, the information on preferences can be used to develop effective therapies after an ACS. The data generated will enable healthcare decision makers and stakeholders to understand patient preferences to promote patients' benefit.
Authors: John F P Bridges; A Brett Hauber; Deborah Marshall; Andrew Lloyd; Lisa A Prosser; Dean A Regier; F Reed Johnson; Josephine Mauskopf Journal: Value Health Date: 2011-04-22 Impact factor: 5.725
Authors: Robert F Storey; Richard C Becker; Robert A Harrington; Steen Husted; Stefan K James; Frank Cools; Philippe Gabriel Steg; Nardev S Khurmi; Håkan Emanuelsson; Anna Cooper; Richard Cairns; Christopher P Cannon; Lars Wallentin Journal: Eur Heart J Date: 2011-07-30 Impact factor: 29.983
Authors: Robert F Storey; Richard C Becker; Robert A Harrington; Steen Husted; Stefan K James; Frank Cools; Philippe Gabriel Steg; Nardev S Khurmi; Hakan Emanuelsson; Soo Teik Lim; Christopher P Cannon; Hugo A Katus; Lars Wallentin Journal: Am J Cardiol Date: 2011-09-03 Impact factor: 2.778
Authors: Lars Wallentin; Richard C Becker; Andrzej Budaj; Christopher P Cannon; Håkan Emanuelsson; Claes Held; Jay Horrow; Steen Husted; Stefan James; Hugo Katus; Kenneth W Mahaffey; Benjamin M Scirica; Allan Skene; Philippe Gabriel Steg; Robert F Storey; Robert A Harrington; Anneli Freij; Mona Thorsén Journal: N Engl J Med Date: 2009-08-30 Impact factor: 91.245