Policymaking based on CERs: changes in costs are not the same as changes in benefits

BACKGROUND: Earlier cost-effectiveness studies showed the cost-effectiveness ratios for pneumococcal vaccination in preventing cases of Bacteremic Pneumococcal Disease (BPD) alone to vary between € 11,000 and € 33,000 per quality-adjusted life year. If vaccination is also assumed to be effective in preventing cases of Non Bacteremic Pneumococcal Disease (NBPD) (at the same level of effectiveness), vaccinating all elderly persons becomes highly cost-effective or even cost saving. METHODS: The present article examines the effect of partial preventive power of the vaccine against cases of NBPD additional to its preventive power against cases of BPD, and the consequences this has in terms of cost-effectiveness. RESULTS: The analysis shows that even a fairly small additional preventive power against cases of NBPD leads to a dramatic and unexpected decrease in the cost-effectiveness ratio. CONCLUSION: Because a Cost-Effectiveness Ratio (CER) is a ratio, changes in costs and changes in effects have rather different influences on its value. There is a linear relation between a change in costs and a change in CER if the effects are kept constant. This linear relation is not found on the effect side. Assuming that costs are constant, a change in effect will be different for low levels of effect than for high levels

Out-of-hours primary care. Implications of organisation on costs

BACKGROUND: To perform out-of-hours primary care, Dutch general practitioners (GPs) have organised themselves in large-scale GP cooperatives. Roughly, two models of out-of-hours care can be distinguished; GP cooperatives working separate from the hospital emergency department (ED) and GP cooperatives integrated with the hospital ED. Research has shown differences in care utilisation between these two models; a significant shift in the integrated model from utilisation of ED care to primary care. These differences may have implications on costs, however, until now this has not been investigated. This study was performed to provide insight in costs of these two different models of out-of-hours care. METHODS: Annual reports of two GP cooperatives (one separate from and one integrated with a hospital emergency department) in 2003 were analysed on costs and use of out-of-hours care. Costs were calculated per capita. Comparisons were made between the two cooperatives. In addition, a comparison was made between the costs of the hospital ED of the integrated model before and after the set up of the GP cooperative were analysed. RESULTS: Costs per capita of the GP cooperative in the integrated model were slightly higher than in the separate model (ε 11.47 and ε 10.54 respectively). Differences were mainly caused by personnel and other costs, including transportation, interest, cleaning, computers and overhead. Despite a significant reduction in patients utilising ED care as a result of the introduction of the GP cooperative integrated within the ED, the costs of the ED remained the same. CONCLUSION: The study results show that the costs of primary care appear to be more dependent on the size of the population the cooperative covers than on the way the GP cooperative is organised, i.e. separated versus integrated. In addition, despite the substantial reduction of patients, locating the GP cooperative at the same site as the ED was found to have little effect on costs of the ED. Sharing more facilities and personnel between the ED and the GP cooperative may improve cost-efficiency

Follow-up care by patient's own general practitioner after contact with out-of-hours care. A descriptive study

BACKGROUND: Little is known about the care process after patients have contacted a GP cooperative for out-of-hours care. The objective of this study was to determine the proportion of patients who seek follow-up care after contact with a GP cooperative for out-of-hours care, and to gain insight into factors that are related to this follow-up care. METHODS: A total of 2805 patients who contacted a GP cooperative for out-of-hours care were sent a questionnaire. They were asked whether they had attended their own GP within a week after their contact with the cooperative, and for what reason. To investigate whether other variables are related to follow-up care, a logistic regression analysis was applied. Variables that entered in this analysis were patient characteristics (age, gender, etc.) and patient opinion on correctness of diagnosis, urgency and severity of the medical complaint. RESULTS: The response rate was 42%. In total, 48% of the patients received follow-up care from their own GP. Only 20% were referred or advised to attend their own GP. Others attended because their medical condition worsened or because they were concerned about their complaint. Variables that predicted follow-up care were the patient's opinion on the correctness of the diagnosis, patient's health insurance, and severity of the medical problem. CONCLUSION: Almost half of all patients in this study who contacted the GP cooperative for out-of-hours care attended their own GP during office hours within a week, for the same medical complaint. The most important factor that predicted follow-up care from the patient's own GP after an out-of-hours contact was the patient's degree of confidence in the diagnosis established at the GP cooperative. Despite the limited generalisability, this study is a first step in providing insight into the dimension of follow-up care after a patient has contacted the GP cooperative for out-of-hours primary care

Value for money in changing clinical practice: should decisions about guidelines and implementation strategies be made sequentially or simultaneously?

Decisions about clinical practice change, that is, which guidelines to adopt and how to implement them, can be made sequentially or simultaneously. Decision makers adopting a sequential approach first compare the costs and effects of alternative guidelines to select the best set of guideline recommendations for patient management and subsequently examine the implementation costs and effects to choose the best strategy to implement the selected guideline. In an integral approach, decision makers simultaneously decide about the guideline and the implementation strategy on the basis of the overall value for money in changing clinical practice. This article demonstrates that the decision to use a sequential v. an integral approach affects the need for detailed information and the complexity of the decision analytic process. More importantly, it may lead to different choices of guidelines and implementation strategies for clinical practice change. The differences in decision making and decision analysis between the alternative approaches are comprehensively illustrated using 2 hypothetical examples. We argue that, in most cases, an integral approach to deciding about change in clinical practice is preferred, as this provides more efficient use of scarce health-care resources

Modeling the value for money of changing clinical practice change: a stochastic application in diabetes care.

BACKGROUND: Decision making about resource allocation for guideline implementation to change clinical practice is inevitably undertaken in a context of uncertainty surrounding the cost-effectiveness of both clinical guidelines and implementation strategies. Adopting a total net benefit approach, a model was recently developed to overcome problems with the use of combined ratio statistics when analyzing decision uncertainty. OBJECTIVE: To demonstrate the stochastic application of the model for informing decision making about the adoption of an audit and feedback strategy for implementing a guideline recommending intensive blood glucose control in type 2 diabetes in primary care in the Netherlands. METHODS: An integrated Bayesian approach to decision modeling and evidence synthesis is adopted, using Markov Chain Monte Carlo simulation in WinBUGs. Data on model parameters is gathered from various sources, with effectiveness of implementation being estimated using pooled, random-effects meta-analysis. Decision uncertainty is illustrated using cost-effectiveness acceptability curves and frontier. RESULTS: Decisions about whether to adopt intensified glycemic control and whether to adopt audit and feedback alter for the maximum values that decision makers are willing to pay for health gain. Through simultaneously incorporating uncertain economic evidence on both guidance and implementation strategy, the cost-effectiveness acceptability curves and cost-effectiveness acceptability frontier show an increase in decision uncertainty concerning guideline implementation. CONCLUSIONS: The stochastic application in diabetes care demonstrates that the model provides a simple and useful tool for quantifying and exploring the (combined) uncertainty associated with decision making about adopting guidelines and implementation strategies and, therefore, for informing decisions about efficient resource allocation to change clinical practice

Follow-up care by patient's own general practitioner after contact with out-of-hours care. A descriptive study

Abstract Background Little is known about the care process after patients have contacted a GP cooperative for out-of-hours care. The objective of this study was to determine the proportion of patients who seek follow-up care after contact with a GP cooperative for out-of-hours care, and to gain insight into factors that are related to this follow-up care. Methods A total of 2805 patients who contacted a GP cooperative for out-of-hours care were sent a questionnaire. They were asked whether they had attended their own GP within a week after their contact with the cooperative, and for what reason. To investigate whether other variables are related to follow-up care, a logistic regression analysis was applied. Variables that entered in this analysis were patient characteristics (age, gender, etc.) and patient opinion on correctness of diagnosis, urgency and severity of the medical complaint. Results The response rate was 42%. In total, 48% of the patients received follow-up care from their own GP. Only 20% were referred or advised to attend their own GP. Others attended because their medical condition worsened or because they were concerned about their complaint. Variables that predicted follow-up care were the patient's opinion on the correctness of the diagnosis, patient's health insurance, and severity of the medical problem. Conclusion Almost half of all patients in this study who contacted the GP cooperative for out-of-hours care attended their own GP during office hours within a week, for the same medical complaint. The most important factor that predicted follow-up care from the patient's own GP after an out-of-hours contact was the patient's degree of confidence in the diagnosis established at the GP cooperative. Despite the limited generalisability, this study is a first step in providing insight into the dimension of follow-up care after a patient has contacted the GP cooperative for out-of-hours primary care.</p