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Private health insurance makes a small contribution to spending on health in most countries around the world, but its effect on health system performance can be surprisingly large owing to market failures and weaknesses in public policy. Because private health insurance can have a disproportionate impact, leading to risk segmentation, inequality and inefficiency, it should be considered and monitored with care.
Can private health insurance fill gaps in publicly financed coverage? Does it enhance access to health care or improve efficiency in health service delivery? Will it provide fiscal relief for governments struggling to raise public revenue for health? This book examines the successes, failures and challenges of private health insurance globally through country case studies written by leading national experts. Each case study considers the role of history and politics in shaping private health insurance and determining its impact on health system performance. Despite great diversity in the size and functioning of markets for private health insurance, the book identifies clear patterns across countries, drawing out valuable lessons for policymakers while showing how history and politics have proved a persistent barrier to effective public policy. This title is also available as Open Access on Cambridge Core.
Economic models play a central role in the decision-making process of the National Institute for Health and Care Excellence (NICE). Inadequate validation methods allow for errors to be included in economic models. These errors may alter the final recommendations and have a significant impact on outcomes for stakeholders.
Objective
To describe the patterns of technical errors found in NICE submissions and to provide an insight into the validation exercises carried out by the companies prior to submission.
Methods
All forty-one single technology appraisals (STAs) completed in 2017 by NICE were reviewed and all were on medicines. The frequency of errors and information on their type, magnitude, and impact was extracted from publicly available NICE documentation along with the details of model validation methods used.
Results
Two STAs (5 percent) had no reported errors, nineteen (46 percent) had between one and four errors, sixteen (39 percent) had between five and nine errors, and four (10 percent) had more than ten errors. The most common errors were transcription errors (29 percent), logic errors (29 percent), and computational errors (25 percent). All STAs went through at least one type of validation. Moreover, errors that were notable enough were reported in the final appraisal document (FAD) in eight (20 percent) of the STAs assessed but each of these eight STAs received positive recommendations.
Conclusions
Technical errors are common in the economic models submitted to NICE. Some errors were considered important enough to be reported in the FAD. Improvements are needed in the model development process to ensure technical errors are kept to a minimum.
To investigate the impact of the uncertainty stemming from products with European conditional marketing authorization (CMA) or authorization in exceptional circumstances (AEC) on the National Institute for Health and Care Excellence's (NICE) recommendations.
Methods
Products which received CMA/AEC by European Medicines Agency (EMA) up to 1 December 2016 were identified and matched with corresponding NICE decisions issued by August 2017, the status of which was then traced to August 2019. We assessed whether the conversion of CMA to full marketing authorization triggered a review of a NICE decision. The odds of a recommendation carrying a commercial arrangement for products with and without CMA/AEC were calculated.
Results
Fifty-four products were granted CMA/AEC by EMA. NICE conducted thirty evaluations of products with CMA/AEC. Twelve products were recommended by NICE by August 2017 and fourteen by August 2019. All recommendations had an associated commercial arrangement. The odds of carrying a commercial arrangement were higher for products with CMA/AEC compared to those with full authorization. Conversions from conditional to full authorization among products not recommended by NICE did not trigger an appraisal review.
Conclusions
Uncertainty, stemming from the lack of robust clinical data of products authorized with CMA/AEC, has a substantial impact on HTA recommendations, frequently requiring risk mitigation mechanisms such as commercial and data collection arrangements. Further analyses should be conducted to assess whether the benefits of early access strategies outweigh the risks for patients and the healthcare system.
This introduction outlines the scope of the book titled “Challenges in Tackling Antimicrobial Resistance: Economic and Policy Responses”, and then summarises the main messages of each chapter which focus on the following big questions around AMR policy. What is the evidence on the rise of AMR and its health and economic impact? How can it be most effectively addressed in the community and in hospitals? What role is played by antimicrobial use in the food and livestock sector and what can be done about it? How can the discovery of new antibiotics be reinvigorated to replace those rendered ineffective by resistance? What needs to be done to develop new diagnostic tests so that infections can be speedily identified or ruled out and unnecessary antibiotic use avoided? Can more use be made of vaccines to tackle AMR? How have civil society movements contributed to policy development in the fight against AMR? What does the international community need to do in terms of global collective action to tackle AMR?