Page 41 - GHES-3-2

Global Health Economics and
Sustainability
Random price generators in health policy

it to the car industry. Research is ongoing on the BLP Tai-Seale, 2012; Chen et al., 2023), and may lead to different
model, for possible computation on analytical datasets public policies, especially with science and technology.
for medical markets. This type of business research helps Introducing more demand-side parameters in
quantify changes in cross-price elasticities between market healthcare is a scientific challenge, even if predictive
segments and may also be useful for other policy-aiding econometrics in some diseases improves quickly. The
tools, especially in the case of mergers, for instance, in gene advances in genomic medicine raise expectations toward
sequencing.
precision medicine and personalization of clinical
Different extensions of multilevel demand systems may pathways. Scientific discoveries (especially genome-wide
also be useful, including dynamic random coefficient logit association studies) are promising. For instance, modeling
applications in the health sector in longitudinal medical monogenic diseases leads to beneficial causal inference
claims databases. Other contributions include research relationships with genetic predictors, but monogenic
on comparative estimators, e.g., on simulated maximum diseases do not represent many diseases.
likelihood (Park & Gupta, 2012), generalized methods
of moments estimators (Berry et al., 1995), and recent Moreover, the growth of complexity may limit the
interfaces to adjust to the latest forms of such models, advance of models using genetics as predictors, especially
e.g., in Python see, Colon & Gortmaker (2020) or STATA for disease econometrics. Asthma genetics is a good
technical notes. example, where the discovery process in asthma genetics
has expanded quickly and led to reliable associations with
Incorporating choice modeling with microdata into genetic biomarkers and beneficial asthma drug therapies.
macroeconomic models may be helpful for healthcare However, the complexity of the interactions, especially
budget forecasting (Soekhai et al., 2019; Vass et al., ISPOR gene-gene interactions and epigenetic modifiers according
Interest Group report, 2022), aiding in considering the to geographical sites, has slowed the predictability of
heterogeneity of preferences. Random price generators models, including genetic predictors in this disease.
in such a demand model may fit the US medical Controversies remain between geneticists and biologists
markets with strong oligopolies or monopsonies and (Huttin, 2015) with such evolving scientific advances.
large demand heterogeneity. Globally, many countries Only system biologists may be able to capture the role of
do not use a demand approach and prefer to set the gene-gene interactions and epigenetic modifiers’ influence
rules with governmental agencies (such as health on outcomes of chronic diseases such as asthma and
technology assessment agencies, using techniques like its complications (e.g., chronic obstructive pulmonary
quality-adjusted life year and threshold adjustments). disease) in the future (see also Appendix A2).
Therefore, this approach to strengthening the demand
system does not automatically apply to regulated health Despite current scientific limitations and new uncertainties,
systems with health technology assessment agencies, it is relevant to strengthen the demand function with a better
such as Nice in the UK or other European systems, using understanding of individual choices and not only market
conventional pharmacoeconomics or economic evaluation products and services. Moreover, as longevity challenges
methodologies. welfare economic theory, it also shows the interest in using
Controversies among economists also exist on micro-macro modeling in evolving value frameworks.
contingent valuation methods or stated-preference studies 6. Conclusion
for health service research; however, they are increasingly
used in health care studies, especially for revisions of In health policies, the cost-benefit analysis framework,
welfare contracts (e.g., review of contingent valuation including for evidence in development, is very used,
methods, ISPOR task force report) (Hauber et al., 2016). especially in countries with strong health technology
Discrete choice experiments can very well operationalize assessments. This paper proposes approaches to strengthen
the responses of various actors to financial changes or the demand system in medical markets using choice
variations of access to care according to types of barriers. modeling techniques and random price generators.
They help target the different needs of subpopulations of Reliable metrics are needed for advanced value
patients and limit the overuse of medical services. frameworks and evolving multi-stakeholders impact
Additional supply and demand parameters in structural assessments to complement existing thresholds used
models help address broader consumption behavior in cost-benefit analysis, for example, incremental cost-
changes. Strengthening the demand system may shift the effectiveness ratios (Solow & Pezalla, ISPOR Value
priority setting from technology-driven medical systems, assessment framework, 2018). Decision tools using cost
usually more induced by supply (Evans, 1974; Sina Shih & and price information rely on cognitive architecture and

Volume 3 Issue 2 (2025) 33 https://doi.org/10.36922/ghes.3579