Analyzing the concept of spillover effects for expanded inclusion in health economics research

On spillovers in economic evaluations: definition, mapping review and research agenda

An important issue in economic evaluations is determining whether all relevant impacts are considered, given the perspective chosen for the analysis. Acknowledging that patients are not isolated individuals has important implications in this context. Increasingly, the term "spillovers" is used to label consequences of health interventions on others. However, a clear definition of spillovers is lacking, and as a result, the scope of the concept remains unclear. In this study, we aim to clarify the concept of spillovers by proposing a definition applicable in health economic evaluations. To illustrate the implications of this definition, we highlight the diversity of potential spillovers through an expanded impact inventory and conduct a mapping review that outlines the evidence base for the different types of spillovers. In the context of economic evaluations of health interventions, we define spillovers as all impacts from an intervention on all parties or entities other than the users of the intervention under evaluation. This definition encompasses a broader range of potential costs and effects, beyond informal caregivers and family members. The expanded impact inventory enables a systematic approach to identifying broader impacts of health interventions. The mapping review shows that the relevance of different types of spillovers is context-specific. Some spillovers are regularly included in economic evaluations, although not always recognised as such, while others are not. A consistent use of the term "spillovers", improved measurement of these costs and effects, and increased transparency in reporting them are still necessary. To that end, we propose a research agenda.

Management of Digital Dermatitis in Dairy Herds: Optimization and Time Allocation

The objective of this study is to determine the most effective time allocation for digital dermatitis management and to quantify the marginal economic gain from extra time devoted to digital dermatitis management. The model simulating foot disease occurrence and the associated management was Dairy Health Simulator©. Then, an econometric model was applied to identify the relationship between the dairy workshop's gross margin and time for lameness management as well as the hourly marginal gain curve associated with lameness management. The gross margin was optimized under two constraints, i.e., the overall time spent for lameness management and the mean lameness duration (mimicking cow welfare). The results show that allocating less time to lameness detection and more to footbath application can contribute as follows: (i) reduces time spent for lameness management, (ii) maintains the best welfare level, and (iii) obtains the highest gross margin. The optimal time to devote to footbath application ranged from 17.8 to 22.3 h/month. A hiring strategy was investigated, and the break-even point ranged from 16.1 to 19.8 h/month. The recommended time to spend on footbath application is relatively important; therefore, stakeholders should consider the importance of lameness to the dairy industry and should devote enough time for footbath applications.

Incorporating Cascade Effects of Genetic Testing in Economic Evaluation: A Scoping Review of Methodological Challenges

Cascade genetic testing is indicated for family members of individuals testing positive on a genetic test, and is particularly relevant for child health because of their vulnerability and the long-term health and economic implications. Cascade testing has patient- and health system-level implications; however cascade costs and health effects are not routinely considered in economic evaluation. The methodological challenges associated with incorporating cascade effects in economic evaluation require examination. The purpose of this scoping review was to identify published economic evaluations that considered cascade genetic testing. Citation databases were searched for English-language economic evaluations reporting on cascade genetic testing. Nineteen publications were included. In four, genetic testing was used to identify new index patients—cascade effects were also considered; thirteen assessed cascade genetic testing strategies for the identification of at-risk relatives; and two calculated the costs of cascade genetic testing as a secondary objective. Methodological challenges associated with incorporating cascade effects in economic evaluation are related to study design, costing, measurement and valuation of health outcomes, and modeling. As health economic studies may currently be underestimating both the cost and health benefits attributable to genetic technologies through omission of cascade effects, development of methods to address these difficulties is required.