Esther W de Bekker-Grob1, Jorien Veldwijk2, Marcel Jonker3, Bas Donkers4, Jan Huisman5, Sylvia Buis6, Joffre Swait7, Emily Lancsar8, Cilia L M Witteman9, Gouke Bonsel10, Patrick Bindels11. 1. Section of Health Technology Assessment & Erasmus Choice Modelling Centre, Institute of Health Policy & Management, Erasmus University, Rotterdam, The Netherlands; Section of Medical Decision Making & Erasmus Choice Modelling Centre, Department of Public Health, Erasmus MC - University Medical Centre, Rotterdam, The Netherlands. Electronic address: debekker-grob@eshpm.eur.nl. 2. Section of Health Technology Assessment & Erasmus Choice Modelling Centre, Institute of Health Policy & Management, Erasmus University, Rotterdam, The Netherlands; Centre for Research Ethics & Bioethics, Uppsala University, Uppsala, Sweden. 3. Section of Health Technology Assessment & Erasmus Choice Modelling Centre, Institute of Health Policy & Management, Erasmus University, Rotterdam, The Netherlands. 4. Department of Business Economics & Erasmus Choice Modelling Centre, Erasmus School of Economics, Erasmus University, Rotterdam, The Netherlands. 5. General Practice, Het Doktershuis, Ridderkerk, The Netherlands. 6. General Practice, Gezondheidscentrum Ommoord, Rotterdam, The Netherlands. 7. Institute for Choice, University of South Australia, Sydney, Australia. 8. Centre for Health Economics, Monash University, Melbourne, Australia. 9. Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands. 10. EuroQoL Foundation, Rotterdam, The Netherlands. 11. Department of General Practice, Erasmus MC - University Medical Centre, Rotterdam, The Netherlands.
Abstract
OBJECTIVES: To improve information for patients and to facilitate a vaccination coverage that is in line with the EU and World Health Organization goals, we aimed to quantify how vaccination and patient characteristics impact on influenza vaccination uptake of elderly people. METHODS: An online discrete choice experiment (DCE) was conducted among 1261 representatives of the Dutch general population aged 60 years or older. In the DCE, we used influenza vaccination scenarios based on five vaccination characteristics: effectiveness, risk of severe side effects, risk of mild side effects, protection duration, and absorption time. A heteroscedastic multinomial logit model was used, taking scale and preference heterogeneity (based on 19 patient characteristics) into account. RESULTS: Vaccination and patient characteristics both contributed to explain influenza vaccination uptake. Assuming a base case respondent and a realistic vaccination scenario, the predicted uptake was 58%. One-way changes in vaccination characteristics and patient characteristics changed this uptake from 46% up to 61% and from 37% up to 95%, respectively. The strongest impact on vaccination uptake was whether the patient had been vaccinated last year, whether s/he had experienced vaccination side effects, and the patient's general attitude towards vaccination. CONCLUSIONS: Although vaccination characteristics proved to influence influenza vaccination uptake, certain patient characteristics had an even higher impact on influenza vaccination uptake. Policy makers and general practitioners can use these insights to improve their communication plans and information regarding influenza vaccination for individuals aged 60 years or older. For instance, physicians should focus more on patients who had experienced side effects due to vaccination in the past, and policy makers should tailor the standard information folder to patients who had been vaccinated last year and to patient who had not.
OBJECTIVES: To improve information for patients and to facilitate a vaccination coverage that is in line with the EU and World Health Organization goals, we aimed to quantify how vaccination and patient characteristics impact on influenza vaccination uptake of elderly people. METHODS: An online discrete choice experiment (DCE) was conducted among 1261 representatives of the Dutch general population aged 60 years or older. In the DCE, we used influenza vaccination scenarios based on five vaccination characteristics: effectiveness, risk of severe side effects, risk of mild side effects, protection duration, and absorption time. A heteroscedastic multinomial logit model was used, taking scale and preference heterogeneity (based on 19 patient characteristics) into account. RESULTS: Vaccination and patient characteristics both contributed to explain influenza vaccination uptake. Assuming a base case respondent and a realistic vaccination scenario, the predicted uptake was 58%. One-way changes in vaccination characteristics and patient characteristics changed this uptake from 46% up to 61% and from 37% up to 95%, respectively. The strongest impact on vaccination uptake was whether the patient had been vaccinated last year, whether s/he had experienced vaccination side effects, and the patient's general attitude towards vaccination. CONCLUSIONS: Although vaccination characteristics proved to influence influenza vaccination uptake, certain patient characteristics had an even higher impact on influenza vaccination uptake. Policy makers and general practitioners can use these insights to improve their communication plans and information regarding influenza vaccination for individuals aged 60 years or older. For instance, physicians should focus more on patients who had experienced side effects due to vaccination in the past, and policy makers should tailor the standard information folder to patients who had been vaccinated last year and to patient who had not.