A systematic literature review of the key challenges for developing the structure of public health economic models

OBJECTIVES: To identify the key methodological challenges for public health economic modelling and set an agenda for future research. METHODS: An iterative literature search identified papers describing methodological challenges for developing the structure of public health economic models. Additional multidisciplinary literature searches helped expand upon important ideas raised within the review. RESULTS: Fifteen articles were identified within the formal literature search, highlighting three key challenges: inclusion of non-healthcare costs and outcomes; inclusion of equity; and modelling complex systems and multi-component interventions. Based upon these and multidisciplinary searches about dynamic complexity, the social determinants of health, and models of human behaviour, six areas for future research were specified. CONCLUSIONS: Future research should focus on: the use of systems approaches within health economic modelling; approaches to assist the systematic consideration of the social determinants of health; methods for incorporating models of behaviour and social interactions; consideration of equity; and methodology to help modellers develop valid, credible and transparent public health economic model structures.This work has been developed under the terms of a doctoral research training fellowship issued by the National Institute for Health Research (NIHR)

A Framework for Developing the Structure of Public Health Economic Models

Background: A conceptual modeling framework is a methodology that assists modelers through the process of developing a model structure. Public health interventions tend to operate in dynamically complex systems. Modeling public health interventions requires broader considerations than clinical ones. Inappropriately simple models may lead to poor validity and credibility, resulting in suboptimal allocation of resources. Objective: This article presents the first conceptual modeling framework for public health economic evaluation. Methods: The framework presented here was informed by literature reviews of the key challenges in public health economic modeling and existing conceptual modeling frameworks; qualitative research to understand the experiences of modelers when developing public health economic models; and piloting a draft version of the framework. Results: The conceptual modeling framework comprises four key principles of good practice and a proposed methodology. The key principles are that 1) a systems approach to modeling should be taken; 2) a documented understanding of the problem is imperative before and alongside developing and justifying the model structure; 3) strong communication with stakeholders and members of the team throughout model development is essential; and 4) a systematic consideration of the determinants of health is central to identifying the key impacts of public health interventions. The methodology consists of four phases: phase A, aligning the framework with the decision-making process; phase B, identifying relevant stakeholders; phase C, understanding the problem; and phase D, developing and justifying the model structure. Key areas for further research involve evaluation of the framework in diverse case studies and the development of methods for modeling individual and social behavior. Conclusions: This approach could improve the quality of Public Health economic models, supporting efficient allocation of scarce resources

Economic implications of the use of Basiliximab in addition to triple immunosuppressive therapy in renal allograft recipients: a UK perspective

Objective: To compare resource use and costs in renal transplant recipients treated with basiliximab or placebo plus triple immunosuppressive therapy. Design: International randomised, double-blind, placebo-controlled trial; economic evaluation undertaken alongside the efficacy trial. The economic evaluation was performed from a UK National Health Service hospital perspective. Setting: 31 centres in 12 countries. Participants: 345 renal transplant recipients were enrolled; 340 were randomised (basiliximab 168; placebo 172) and included in the intention-to-treat analysis. Intervention: Treatment with placebo or basiliximab (20mg intravenous bolus) on day 0 and day 4 after transplantation. Main outcome measures: Resource utilisation in multiple categories and treatment costs for basiliximab and placebo-treated patients during the 6-month post-transplantation period. Results: No statistically significant differences were found in any of the economically important categories of resource use or in the mean cost of treatment per person across the whole trial. The mean cost of treatment, including the cost of basiliximab, was £16 095 for basiliximab recipients and £15 864 (1997/1998 costs) for placebo recipients, a mean difference of £231 (95%; CI: -£1983 to £2446), which was not significant. Basiliximab treatment led to a significant reduction in acute rejection episodes (basiliximab 20.8%; placebo 34.9%; p = 0.005). Conclusions: Basiliximab therapy confers a significant clinical benefit to renal transplant recipients without increasing overall treatment costs

Economic Implications of the Use of Basiliximab in Addition to Triple Immunosuppressive Therapy in Renal Allograft Recipients: A UK Perspective

Objective: To compare resource use and costs in renal transplant recipients treated with basiliximab or placebo plus triple immunosuppressive therapy. Design: International randomised, double-blind, placebo-controlled trial; economic evaluation undertaken alongside the efficacy trial. The economic evaluation was performed from a UK National Health Service hospital perspective. Setting: 31 centres in 12 countries. Participants: 345 renal transplant recipients were enrolled; 340 were randomised (basiliximab 168; placebo 172) and included in the intention-to-treat analysis. Intervention: Treatment with placebo or basiliximab (20mg intravenous bolus) on day 0 and day 4 after transplantation. Main outcome measures: Resource utilisation in multiple categories and treatment costs for basiliximab and placebo-treated patients during the 6-month post-transplantation period. Results: No statistically significant differences were found in any of the economically important categories of resource use or in the mean cost of treatment per person across the whole trial. The mean cost of treatment, including the cost of basiliximab, was Lstg 16 095 for basiliximab recipients and Lstg 15 864 (1997/1998 costs) for placebo recipients, a mean difference of Lstg 231 (95% CI: -Lstg 1983 to Lstg 2446), which was not significant. Basiliximab treatment led to a significant reduction in acute rejection episodes (basiliximab 20.8%; placebo 34.9%; p = 0.005). Conclusions: Basiliximab therapy confers a significant clinical benefit to renal transplant recipients without increasing overall treatment costs.Basiliximab, Cost analysis, Immunosuppressants, Pharmacoeconomics, Renal transplant rejection, Resource use

What is driving HTA decision-making? Evidence from cancer drug reimbursement decisions from 6 European countries

Background Decisions on the reimbursement of the same cancer drugs are different across European countries, but empirical work on the reasons behind these differences has been scarce. The main objective of this paper is to make a methodological contribution to existing research, specifically by outlining the systematic process of analysis to address such questions and determining the factors that might lead to different drug reimbursement decisions, and to explore its application in the field of oncology. Methods Reimbursement decisions on cancer drugs in six European countries (Belgium, England, Poland, Portugal, Scotland, and Sweden) between 2006 and 2014 were included in the study. A taxonomy was developed, comprising two groups of variables (system-level and product-specific) and an econometric model was specified (multilevel mixed-effects ordered probit). Results Only one in six evaluations in the sample reach the same reimbursement recommendation. Most health system variables were not determinants of a higher or lower probability of a positive reimbursement recommendation. However, the probability of reimbursement was higher when a drug was considered cost-effective by NICE/SMC and when there was a financial Managed Entry Agreement. This work also demonstrated a possible econometric approach for analysing differences in reimbursement decisions and contributes a structured approach for collecting and preparing data for such analyses. Conclusions Drug reimbursement decisions can be analysed in detail along a set of factors that are related to each decision. This information is essential, not only for understanding why a particular drug is accepted in one country and not in another but also when trying to implement a new HTA system or reform an existing one. This analysis provides policy makers and stakeholders with a model that enables a better understanding of the factors that drive HTA decisions and is adaptable to answer similar questions. Moreover, the data collection limitations encountered and described in this work shed light on the need for greater accessibility and transparency in HTA systems and regarding HTA outcomes.This research was funded under the European 7th Framework Programme with Advance-HTA (no305,983). The results presented reflect the author’s views. The EC is not liable for any use of the information communicated