Approaches to Mobile Health Evaluation: A Comparative Study

Digital Health Applications (DiGAs) on a Fast Track: Insights From a Data-Driven Analysis of Prescribable Digital Therapeutics in Germany From 2020 to Mid-2024

BACKGROUND

This study aimed to analyze the rapidly evolving ecosystem of digital health applications (Digitale Gesundheitsanwendung; DiGAs) in Germany, spurred by the 2019 Digital Healthcare Act. With over 73 million people in Germany now having access to DiGAs, these prescribable digital health apps and web-based applications represent a substantial stride in health care modernization, supporting both patients and health care providers with digital solutions for disease management and care improvement.

OBJECTIVE

Through a data-driven approach, this research aimed to unpack the complexities of DiGA market dynamics, economic factors, and clinical evidence, offering insights into their impact over the past years.

METHODS

The analysis draws from a range of public data sources, including the DiGA directory, statutory health insurance reports, app store feedback, and clinical study results.

RESULTS

As of July 1, 2024, there are 56 DiGAs listed by the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte), divided into 35 permanently and 21 preliminarily listed applications. Our findings reveal that a majority of DiGAs extend beyond the intended 1-year period to achieve permanent listing, reflecting the extensive effort required to demonstrate clinical efficacy. Economic analysis uncovered a dynamic pricing landscape, with initial prices ranging from approximately €200 to €700 (€1=US $1.07), averaging at a median of €514 for a 3-month DiGA prescription. Following negotiations or arbitration board decisions, prices typically see a 50% reduction, settling at a median of €221. Prescription data offer valuable insights into DiGA acceptance, with total prescriptions jumping from around 41,000 in the first period to 209,000 in the latest reporting period. The analysis of the top 15 DiGAs, representing 82% of the total prescriptions, shows that these best-performing apps receive from a minimum of 8 to a maximum of 77 daily prescriptions, with native apps and early market entrants achieving higher rates. Clinical evidence from all 35 permanently listed DiGAs indicates a uniform preference for randomized controlled trials to validate primary end points, with no noteworthy use of alternative study designs encouraged in the Digital Healthcare Act and related regulations. Moreover, all evaluated DiGAs focused on medical benefits, with health status improvement as a key end point, suggesting an underuse of patient-relevant structural and procedural improvement in demonstrating health care impact.

CONCLUSIONS

This study highlights the growth and challenges within the DiGA sector, suggesting areas for future research, such as the exploration of new study designs and the potential impact of patient-relevant structural and procedural improvements. For DiGA manufacturers, the strategic advantage of early market entry is emphasized. Overall, this paper underscores the evolving landscape of digital health, advocating for a nuanced understanding of digital health technology integration in Germany and beyond.

Benefit Assessment and Reimbursement of Digital Health Applications: Concepts for Setting Up a New System for Public Coverage

In Germany, some digital health applications (DiHA) became reimbursable through the statutory health insurance system with the adoption of the Digital Healthcare Act in 2019. Approaches and concepts for the German care context were developed in an iterative process, based on existing concepts from international experience. A DiHA categorization was developed that could be used as a basis to enable the creation of a reimbursed DiHA repository, and to derive evidence requirements for coverage and reimbursement for each DiHA. The results provide an overview of a possible classification of DiHA as well as approaches to assessment and evaluation. The structure of remuneration and pricing in connection with the formation of groups is demonstrated.

[Evidence-based primary prevention and health promotion: methods and procedures in 5 research consortia]

Von 2014 bis 2022 erforschen die 5 deutschen Forschungsverbünde AEQUIPA, CAPITAL4HEALTH, HLCA, PartKommPlus und SMARTACT Themen der Primärprävention und Gesundheitsförderung mit dem Ziel, die Evidenzgrundlagen in diesen Bereichen weiterzuentwickeln. In diesem Beitrag wird die Arbeit der 5 Forschungsverbünde für Primärprävention und Gesundheitsförderung unter dem Aspekt der Evidenzbasierung aus der internen Perspektive vorgestellt, analysiert und diskutiert. Als orientierender Rahmen dient ein Modell der evidenzbasierten Public Health.

Die 5 Forschungsverbünde nutzen für die Evidenzgenerierung vielfältige Zugangswege bzgl. der Beteiligung nichtakademischer, zivilgesellschaftlicher Akteur*innen und Nutzer*innen. Es finden sich vielfältige Studiendesigns, die von randomisiert kontrollierten Studien und systematischen Reviews zu diversen qualitativen Designs reichen. Die Nutzung von Modellen und Theorien unterstützt die Evidenzbasierung. Über die Evidenzentwicklung hinaus legen alle Verbünde einen Schwerpunkt auf die zumindest exemplarische Implementierung des neuen Wissens.

Durch die Methodenvielfalt kann eine breit gefächerte Evidenzbasierung unter Berücksichtigung verbundspezifischer Aspekte realisiert werden. Grenzen für eine weitere systematische Stärkung der Evidenzbasierung liegen in strukturellen Rahmenbedingungen. Insbesondere die Einbindung von nichtakademischen, zivilgesellschaftlichen Akteur*innen und Nutzer*innen für die Arbeit mit schwer erreichbaren Zielgruppen kann oft nicht ausfinanziert bzw. zeitlich berücksichtigt werden. Die COVID-19-Pandemie verdeutlicht die Wichtigkeit eines flexiblen Methodenspektrums, in dem ein sinnvolles Zusammenspiel von digitalen und analogen Methoden anzustreben ist.

["Alternative study designs" for the evaluation of digital health applications - a real alternative?]

INTRODUCTION

After the Digital Healthcare Act (Digitale-Versorgung-Gesetz, DVG) reformed digital health applications' (Digitale Gesundheitsanwendungen, DiGAs) access to German Statutory Health Insurance (SHI) reimbursement, the discussion concerning necessary evidence requirements has intensified. In the past, different "alternative study designs" have been proposed to replace randomized controlled trials (RCTs) in the DiGA efficacy and benefit assessments. The present paper examines the suitability of these alternative designs for informing SHI reimbursement decisions.

METHODS

The four alternative study designs primarily discussed in the context of DiGA - "Continuous Evaluation of Evolving Behavioral Intervention Technologies" (CEEBIT), "Multiphase Optimization Strategy" (MOST), "Sequential Multiple Assignment Randomized Trial" (SMART) and "Micro-Randomized Trial" (MRT) - are characterized and compared on the basis of relevant primary and secondary sources. Subsequently, their suitability for effectiveness and benefit evaluation in the context of SHI reimbursement decisions is discussed.

RESULTS

None of the study designs examined aims primarily at conclusively demonstrating efficacy and benefit. Three of the four designs (MOST, SMART, MRT) focus on the development and optimization of interventions. In order to reduce resource requirements, the approaches presented sometimes deviate considerably from the methodological approach in traditional RCTs. This is especially true for their applied statistical error tolerance and their underlying randomization logic. Three of the four concepts (MOST, SMART, MRT) therefore still require RCTs after the development phase in order to demonstrate the effectiveness and benefit of the optimized intervention.

DISCUSSION

The methodological differences of the alternative study designs compared to classical RCTs are accompanied by serious potentials for bias and uncertainties with regard to the identified intervention effects. These may be acceptable in the context of intervention development, but do not appear to be appropriate for use in collective SHI reimbursement decisions.

CONCLUSION

The alternative study designs presented cannot be regarded as a suitable RCT alternative for efficacy and benefit assessments. A pragmatic study design, which continues to meet high methodological standards, and better utilization of real-world data could, in the future, contribute to a compromise between the justified claims to sufficient certainty of results on the one hand and appropriate procedural effort on the other.