Search

Background: Vaccination is generally considered the most direct way to restoring normal life after the outbreak of COVID-19, but the available COVID-19 vaccines are simultaneously embraced and dismissed. Mapping factors for vaccine hesitancy may help the roll-out of COVID-19 vaccines and provide valuable insights for future pandemics., Objectives: We investigate how characteristics of a COVID-19 vaccine affect the preferences of adult citizens in the Netherlands to take the vaccine directly, to refuse it outright, or to wait a few months and first look at the experiences of others., Methods: An online sample of 895 respondents participated between November 4th and November 10th, 2020 in a discrete choice experiment including the attributes: percentage of vaccinated individuals protected against COVID-19, month in which the vaccine would become available and the number of cases of mild and severe side effects. The data was analysed by means of panel mixed logit models., Results: Respondents found it important that a safe and effective COVID-19 vaccine becomes available as soon as possible. However, the majority did not want to be the first in line and would rather wait for the experiences of others. The predicted uptake of a vaccine with the optimal combination of attributes was 87%, of whom 55% preferred to take the vaccine after a waiting period. This latter group tends to be lower-educated. Older respondents gave more weight to vaccine effectiveness than younger respondents., Conclusions: The willingness to take a COVID-19 vaccine is high among adults in the Netherlands, but a considerable proportion prefers to delay their decision to vaccinate until experiences of others are known. Offering this wait-and-see group the opportunity to accept the invitation at a later moment may stimulate vaccination uptake. Our results further suggest that vaccination campaigns targeted at older citizens should focus on the effectiveness of the vaccine., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: The objective of this study was to assess the predictive value of a discrete choice experiment (DCE) in public health by comparing stated preferences to actual behavior., Methods: 780 Type 2 diabetes mellitus (T2DM) patients received a questionnaire, containing a DCE with five attributes related to T2DM patients' willingness to participate in a combined lifestyle intervention. Panel mixed-multinomial-logit models were used to estimate the stated preferences based on 206 completed DCE questionnaires. Actual participation status was retrieved for 54 respondents based on patients' medical records and a second questionnaire. Predicted and actual behavior data were compared at population level and at individual level., Results: Based on the estimated utility function, 81.8% of all answers that individual respondents provided on the choice tasks were predicted correctly. The actual participation rate at the aggregated population level was minimally underestimated (70.1 vs. 75.9%). Of all individual choices, 74.1% were predicted correctly with a positive predictive value of 0.80 and a negative predictive value of 0.44., Conclusion: Stated preferences derived from a DCE can adequately predict actual behavior in a public health setting.

Objectives: To evaluate the cost-effectiveness of a tight-control treatment strategy using the handscan (TCHS) compared to using only clinical assessments (TC) and compared to a general non-tight-control treatment strategy (usual care; UC) in early rheumatoid arthritis (RA)., Methods: Data from 299 early RA patients from the CAMERA trial were used. Clinical outcomes were extrapolated to Quality Adjusted Life Years (QALYs) and costs using a Markov model. Costs and QALYs were compared between the TC and UC treatment strategy arm of the CAMERA trial and a simulated tight-control treatment strategy using the handscan (TCHS). Incremental Cost-Effectiveness Ratios (ICERs) were calculated and several scenario analyses performed. All analyses were performed probabilistically to obtain confidence intervals and costs-effectiveness planes and acceptability curves., Results: In TCHS, €4,660 (95% CI -€11,516 to €2,045) was saved and 0.06 (95% CI 0.01 to 0.11) QALYs were gained when compared to UC, with an ICER of €77,670 saved per QALY gained. Ninety-one percent (91%) of simulations resulted in less costs and more QALYs. TCHS resulted in comparable costs or even limited savings €642 (95% CI -€6,903 to €5,601)) and comparable QALYs to TC. In all scenario analyses, TCHS and TC were found to be cost effective as compared to UC., Conclusions: A tight-control treatment strategy is highly cost-effective compared to a non-tight-control approach in early RA. Using the handscan as a monitoring device might facilitate implementation of tight-control treatment strategy at comparable costs and with comparable effects. This approach should be investigated further.

Background: Scientific evidence for the frequency of monitoring of type 2 diabetes patients is lacking. If three-monthly control in general practice could be reduced to six-monthly control in some patients, this would on the one hand reduce the use of medical services including involvement of practice nurses, and thus reduce costs, and on the other hand alleviate the burden of people with type 2 diabetes. The goal of this study is to make primary diabetes care as efficient as possible for patients and health care providers. Therefore, we want to determine whether six-monthly monitoring of well-controlled type 2 diabetes patients in primary care leads to equivalent cardiometabolic control compared to the generally recommended three-monthly monitoring., Methods and Design: The study is a randomised controlled patient-preference equivalence trial. Participants are asked if they prefer three-monthly (usual care) or six-monthly diabetes monitoring. If they do not have a preference, they are randomised to a three-monthly or six-monthly monitoring group. Patients are eligible for the study if they are between 40 and 80 years old, diagnosed with type 2 diabetes more than one year ago, treated by a general practitioner, not on insulin treatment, and with HbA1c < or = 7.5%, systolic blood pressure < or = 145 mmHg and total cholesterol < or = 5.2 mmol/l. The intervention group (six-monthly monitoring) will receive the same treatment with the same treatment targets as the control group (three-monthly monitoring). The intervention period will last one and a half year. After the intervention, the three-monthly and six-monthly monitoring groups are compared on equivalence of cardiometabolic control. Secondary outcome measures are HbA1c, blood pressure, cholesterol level, Body Mass Index, smoking behaviour, physical activity, loss of work due to illness, health status, diabetes-specific distress, satisfaction with treatment and adherence to medications. We will use intention-to-treat analysis with repeated measures. For outcomes that have only baseline and final measurements, we will use ANCOVA. Depending on the results, a cost-minimisation analysis or an incremental cost-effectiveness analysis will be done., Discussion: This study will provide valuable information on the most efficient control frequency of well-controlled type 2 diabetes patients in primary care.

Among all public health provisions national immunization programs (NIPs) are beyond doubt one of the most effective in reducing mortality, morbidity, and costs associated with major infectious diseases. To maintain their success, NIPs have to modernize in response to many new and old demands regarding efficacy, safety, availability of new vaccines, emerging and evolving pathogens, waning immunity, altered epidemiological situations, and the public's trust in the program. In this paper we present an evaluation model in the form of a checklist that may help in collecting relevant scientific information that is necessary for evaluation and decision making when considering changes in a NIP. Such a checklist points to relevant information on the vaccine-preventable disease, the pathogen causing it, the vaccine, and the cost-effectiveness ratio of the vaccine. However, the final judgment on a potential change in the NIP cannot be based on a simple algorithm, as the relevant information reflects factors of a very different kind and magnitude, to which different value judgements may be added, and which may have certain degrees of uncertainty. Because any change in the NIP may be accompanied by more or less unforeseen changes in the vaccine's efficacy, evolutionary consequences, including the antigenic composition of the pathogen, and the vaccine's safety profile, an intensive surveillance program should accompany any NIP. Elements thereof include clinical-epidemiological surveillance, surveillance of vaccination coverage, immune surveillance, surveillance of microbial population dynamics, and surveillance of adverse events and safety issues. We emphasize that the decision to introduce a vaccine in the NIP should be taken as seriously, both scientifically and ethically, as the decision to withhold a vaccine from the NIP. In the latter case one might be responsible for vaccine-preventable disease and mortality.