Health Technology Assessment

Einleitung / Introduction

Rising health care cost due to ageing populations and medical innovations increasingly put a strain on (national) health care budgets. Health technology assessment and especially cost-effectiveness analysis can be helpful tools for allocating these scarce resources and are applied in many jurisdictions. One of the challenges of cost-effectiveness analysis, which compares costs and health benefits (in QALYs), of a medical intervention, is that it requires a threshold value to be fully informative. This threshold indicates the still acceptable amount of resources spent for gaining one QALY. Obtaining such a monetary estimate of health is difficult, one reason why some jurisdictions are hesitant to implement cost-effectiveness analysis and has predominantly been based on the consumption value of health. More recently, researchers attempted to base this value on opportunity costs, i.e. the marginal returns to health care spending. The objective of this study is to obtain a cost-effectiveness threshold value for Germany based on such an approach. Due to limitations in data availability, we focus on the marginal returns of hospital spending. The approach consists of two steps: First, the impact of hospital spending on mortality is estimated using dynamic first-difference models on region, age, and gender level for the years 2007 to 2017. Mortality data was obtained from the official mortality statistics and hospital cost data from the DRG-statistics. Besides using the relationship between total mortality and costs, we also conduct the analysis for cardiovascular diseases, respiratory diseases, and cancer, separately. In a second step, quality of life data and life tables are used to transform the estimates into the average marginal return of hospital spending in euros per QALY. While the analysis is still ongoing, the study will provide insights into the efficiency of hospital care in Germany and may initiate a discussion on the acceptable level of resources spent per health gain for medical interventions in general.

AutorInnen

Sebastian Himmler, Erasmus School of Health Policy & Management

Einleitung / Introduction

In times of scarce health resources, economic evidence plays an important role when making decisions about the reimbursement of health technologies. Health Technology Assessment (HTA) organisations use either primary economic evaluations (P-HE) or Systematic Reviews of health economic evaluations (SR-HE) to inform decision-making. The last is a rather new approach that poses an important question: Are the results from existing economic evaluations generalisable to specific decision contexts (e.g. jurisdictions)? This can principally be queried - especially due to the high variability of cost and resource needs across countries. Therefore, someone might doubt the usefulness of SR-HE in general. However, in contrast to a P-HE, a SR-HE can save effort and time. Our objective was to review the methods documents of HTA organisations to determine how generalisability is recommended to be considered when performing a SR-HE.

Methode / Method

We systematically hand searched the webpages of 158 HTA organisations for potentially relevant methods documents from January to March 2019. We identified the HTA organisations through publicly available member lists of international HTA umbrella organisations. Two independent reviewers performed hand searches and selected documents according to pre-defined eligibility criteria. One reviewer extracted data in standardised and piloted tables and a second reviewer checked them for accuracy. We extracted and aggregated data according to the following issues: the types of considered health technologies, the underlying terminology (e.g. generalisability or transferability), the assessment approach concepts (e.g. assessment standardisation) and the recommended assessment criteria. We describe our findings in a structured narrative manner and visually present extracted data using tabulations. Additionally, we analyse similarities and differences between the recommendations.

Ergebnisse / Results

We identified 155 potentially relevant documents on the webpages of 63 HTA organisations. Of these, 7 fulfilled our eligibility criteria and were included in the synthesis. The methodological recommendations vary regarding the underlying terminology, the assessment approach concepts (e.g. assessment standardisation) and the content of assessments (e.g. assessment criteria). The organisations consider the generalisability of health economic evaluations identified in Systematic Reviews when determining the need for developing an own P-HE.

Zusammenfassung / Conclusion

Despite its importance, only few HTA organisations address the assessment of generalisability in their methodological recommendations for SR-HE. The assessment concepts and content of those that consider generalisability are heterogeneous. Developing standards to consider generalisability in SR-HE is desirable

AutorInnen

Roland Büchter, Institut für Forschung in der Operativen Medizin (IFOM), Fakultät für Gesundheit, Department für Humanmedizin, Universität Witten/Herdecke

Dawid Pieper, Institut für Forschung in der Operativen Medizin (IFOM), Fakultät für Gesundheit, Department für Humanmedizin, Universität Witten/Herdecke

Tim Mathes, Institut für Forschung in der Operativen Medizin (IFOM), Fakultät für Gesundheit, Department für Humanmedizin, Universität Witten/Herdecke

Einleitung / Introduction

Germany’s 2019 Digital Healthcare Act (Digitale-Versorgung-Gesetz, or DVG) created a number of opportunities for the digital transformation of the health care delivery system. Key among these was the creation of a reimbursement pathway for patient-centered digital health care applications (digitale Gesundheitsanwendungen, or DiGA). Worldwide, this is the first structured pathway for “prescribable” apps at scale. As of November, 2020, five DiGA were already listed in the official registry of the Federal Institute for Drugs and Medical Devices (BfArM); these are prescribable and thus reimbursed by the German statutory health insurance system for its 73 million patients. Initial prices for these early DiGA vary from €240 to €500 (mean: €430) per course of treatment. Additionally, at least 50 DiGA are under review and hundreds are expected to enter the German market over the coming years.

Methode / Method

A major challenge facing DiGA manufacturers will be the generation of evidence required for ongoing market access and reimbursement. Current health technology assessment (HTA) methods will need to be adapted for DiGA. We describe the two core issues that distinguish HTA in this setting: (1) the nature of initial evidence generation, which can be delivered up to one year after introduction to the market (the so called “DiGA-Fast-Track”) and gives producers a large degree of flexibility in choosing research design and (2) the dynamic nature of both product development and product evaluation, where a DiGA is continuously updated and evaluated using real world data (RWD) and real world evidence (RWE). We present case studies and highlight the role of RWD and RWE in the successful evaluation of DiGA on an ongoing basis.

Ergebnisse / Results

We describe why successful management of these DiGA-specific issues will require moving beyond traditional, 20th century HTAs. We present our solution as a “Dynamic HTA” and the DVG provides regulatory tools for its development. These include lower initial evidence levels to facilitate market entry, followed by evidence-dependent reimbursement decisions. Further, the DVG allows for reimbursement for DiGA that show medical or structural benefits for patients.

Zusammenfassung / Conclusion

DiGA and the accompanying demand for dynamic HTAs present both a significant challenge and a great opportunity for contemporary health care delivery. We describe how DVG-facilitated solutions fit current HTA approaches and the additional needs of DiGA, in particular continuous evaluation. This new, dynamic HTA is important both to facilitate continuous improvement and market entry of innovative health care solutions and their efficient reimbursement. Furthermore, we discuss implications for the development of HTA for both digital and non-digital products.

AutorInnen

Ariel Dora Stern, Harvard Business School & Health Innovation Hub

Jan Broenneke, Health Innovation Hub

Annika Herr, Leibnitz Universität Hannover

Simon Reif, ZEW – Leibniz Centre for European Economic Research

Einleitung / Introduction

Outcomes in economic evaluations, such as health utilities and costs, are products of multiple variables, often requiring complete item responses to questionnaires. Therefore, missing data are very common in cost-effectiveness analyses. Multiple imputations (MI) are predominately recommended and could be made either for individual items or at the aggregate level. We, therefore, aimed to assess the precision of both MI approaches (the item imputation vs. aggregate imputation) on the cost-effectiveness results.

Methode / Method

The original data set came from a cluster-randomized, controlled trial and was used to describe the missing data pattern and compare the differences in the cost-effectiveness results between the two imputation approaches. A simulation study with different missing data scenarios generated based on a complete data set was used to assess the precision of both imputation approaches.

Ergebnisse / Results

For health utility and cost, patients more often had a partial (9% vs. 23%, respectively) rather than complete missing (4% vs. 0%). The imputation approaches differed in the cost-effectiveness results (the item imputation: - 61,079€/QALY vs. the aggregate imputation: 15,399€/QALY). Within the simulation study mean relative bias (< 5% vs. < 10%) and range of bias (< 38% vs. < 83%) to the true incremental cost and incremental QALYs were lower for the item imputation compared to the aggregate imputation. Even when 40% of data were missing, relative bias to true cost-effectiveness curves was less than 16% using the item imputation, but up to 39% for the aggregate imputation.

Zusammenfassung / Conclusion

The imputation strategies could have a significant impact on the cost-effectiveness conclusions when more than 20% of data are missing. The item imputation approach has better precision than the imputation at the aggregate level.

AutorInnen

Wolfgang Hoffmann, Deutsches Zentrum für Neurodegeneratie Erkrankungen (DZNE) e.V., Standort Rostock/ Greifswald

Fenx Xie, McMaster University, Hamilton, Kanada