Advances in health economic models and outcomes: a necessary condition to make advances in healthcare policy

Health economic evaluations of health technologies such as medicines, medical devices, diagnostics, etc. still receive increasing attention throughout the world.

Indeed, “value for money” assessments are being made on an increasing scale in many countries, not only with regard to medicines, but also for investments relating to medical and diagnostic devices, prevention and screening programs, programs for integrated care, etc.

That makes a lot of sense. Indeed, if we want to aim for healthcare systems that offer good quality of care, that are based on solidarity (meaning that two persons with the same health problem or health need should receive the same quality of care), and that are moreover sustainable (meaning that the healthcare money is spent wisely), we need to better understand and interpret the value for money of public health investments. By doing so the chance for wise investments in health and healthcare increases.

Compared to the early years, whereby rather simple approaches related to costs, cost-offsets, and health benefits of health technologies were applied, we see an evolution towards more sophisticated and complete analysis.

One domain of progress is the perspective of our evaluations. More and more studies look into the full societal impact of health technologies. We have seen in the past that bringing in the full societal perspective may lead to rather different conclusions as compared to a limited healthcare payer perspective. In the current special section in the Journal of Medical Economics, Grosse et al.¹ calculate the economic value of productivity in the US not only for paid activities, but also for non-market time spent in household, caring, and volunteer services. The latter appear to represent 36% of total mean annual productivity, showing that ignoring it in economic evaluations could lead to biased interpretations of value for money of health investments.

Another important field is the measurement of the actual health benefits to patients. It is now generally accepted that the way we calculate QALYs is often not sufficiently representing the true benefits that matter to patients, and there is an increased attention to patient reported outcomes that are related to the specific situation and condition of patients. However, for these condition-specific patient reported outcomes measures (PROMs) to be useful, they need to be of good quality. McKenna et al.^2,3 offer a wake-up call with their original insights and contributions about PROMs and argue that much more need to be done and more sophistication is needed to make these really objective.

Dealing with uncertainty is crucial in health economic evaluations. Most think spontaneously then about data uncertainty. However, structural uncertainty related to the model methodology and its structure might be even more impacting on the final assessment. Again, advances are made with the trend towards more patient level modeling as compared to cohort-based models. Although in several situations and conditions the patient level approach might not contribute much to the final result and assessment as compared to cohort based models, in the case of immune-oncology, Gibson et al.⁴ show that the patient level approach does much better reflect heterogeneity in treatment response, leading to a more valid and reliable estimate of future QALYs.

Regarding data input in health economic evaluations, the increasing importance of Real World Data (RWD) cannot be ignored. However, this does not go without issues, to say the least. The overview by Bowrin et al.⁵ in this section summarizes nicely the role of RWD in the evidence generation of innovative technologies, as well as the key issues related to data quality and availability. It is clear that, for RWD to play a prominent role in the evidence generation of (claimed) innovative technologies, truly data governance is needed on a National and International level.

One particular application is the incorporation of adherence into health economic evaluations. It is generally accepted that adherence in routine practice situations is lower than in clinical trials, not only because of the less controlled setting but also because participants in clinical trials are likely to be more motivated patients.⁶ Chongmelaxme et al.⁷ correctly point to the impact of non-adherence on the results of health economic evaluations, and yet observe– in the field of asthma – that only few economic evaluations account for it correctly.

Finally, technologies not only need to be assessed, they also need to be appraised. Cheung et al.⁸ contribute to both assessment, and appraisal with their comparative analysis of different methods for object case Best Worse Scaling that was policy oriented. Their case selection (barriers to HTA use) moreover lead to practical insights into current views on decision-making by policy-makers and HTA experts.

It is fantastic to see how the creativity of health economic researchers helps to make progress in this field and, by doing so, to make progress in health policy overall, bringing us closer to the ideal of quality, solidarity, and sustainability.

Transparency

Declaration of funding

There is no funding to disclose.

Declaration of financial/other relationships

The author and JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgements

None reported.