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      Unpacking Performance Factors of Innovation Systems and Studying Germany’s Attempt to Foster the Role of the Patient Through a Market Access Pathway for Digital Health Applications (DiGAs): Exploratory Mixed Methods Study

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          Abstract

          Background

          Health care innovation faces significant challenges, including system inertia and diverse stakeholders, making regulated market access pathways essential for facilitating the adoption of new technologies. The German Digital Healthcare Act, introduced in 2019, offers a model by enabling digital health applications (DiGAs) to be reimbursed by statutory health insurance, improving market access and patient empowerment. However, the factors influencing the success of these pathways in driving innovation remain unclear.

          Objective

          This study aims to identify the key performance factors of the innovation system shaped by the patient-relevant structural and procedural improvement (pSVV) pathway within the DiGA model. By examining how this pathway supports the entry of innovative digital health technologies, we seek to uncover the systemic dynamics that influence its effectiveness in fostering patient-centered digital health solutions.

          Methods

          This study, conducted from May 2023 to November 2024, used a mixed methods approach. A descriptive analysis assessed how DiGA manufacturers use positive health care effects, giving a market overview of the pSVV technology. A qualitative analysis using grounded theory and Gioia methodology provided insights into stakeholder perspectives, focusing on manufacturers and regulatory bodies. A functional-structural analysis examined how components of the innovation system, such as actors, institutions, interactions, and infrastructure, interact and impact the effectiveness of the pathway.

          Results

          The descriptive analysis showed that only 11 (20%) of the 56 DiGAs available in Germany used the pSVV pathway, with only 1 (2%) provisionally listed DiGA using pSVV as a primary end point; 6 of 9 (67%) pSVV key areas were used. The qualitative analysis revealed that manufacturers prioritize demonstrating medical benefits over pSVV due to evidence requirements and uncertainties around pSVV acceptance. Operational barriers hindered the adoption of pSVV, despite a positive reception among stakeholders. The systemic analysis identified key issues, including a lack of entrepreneurial focus on pSVV, limited regulatory experience, inadequate measurement methods, and entrenched practices prioritizing medical benefits, that hinder market formation and legitimacy.

          Conclusions

          This study identifies key factors for effectively implementing innovation systems through regulated market access pathways, including content and format security, clearer framework specification, active innovation process management, and market formation stimulation. Addressing these factors can reduce uncertainties and promote wider adoption of digital health technologies. The findings highlight the need for future research on patient empowerment and the development of methodologies beyond traditional therapeutic outcomes.

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          Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups.

          Qualitative research explores complex phenomena encountered by clinicians, health care providers, policy makers and consumers. Although partial checklists are available, no consolidated reporting framework exists for any type of qualitative design. To develop a checklist for explicit and comprehensive reporting of qualitative studies (in depth interviews and focus groups). We performed a comprehensive search in Cochrane and Campbell Protocols, Medline, CINAHL, systematic reviews of qualitative studies, author or reviewer guidelines of major medical journals and reference lists of relevant publications for existing checklists used to assess qualitative studies. Seventy-six items from 22 checklists were compiled into a comprehensive list. All items were grouped into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. Duplicate items and those that were ambiguous, too broadly defined and impractical to assess were removed. Items most frequently included in the checklists related to sampling method, setting for data collection, method of data collection, respondent validation of findings, method of recording data, description of the derivation of themes and inclusion of supporting quotations. We grouped all items into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. The criteria included in COREQ, a 32-item checklist, can help researchers to report important aspects of the research team, study methods, context of the study, findings, analysis and interpretations.
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            Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology

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              Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies

              Background Many promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level. Objective Our objective was to produce an evidence-based, theory-informed, and pragmatic framework to help predict and evaluate the success of a technology-supported health or social care program. Methods The study had 2 parallel components: (1) secondary research (hermeneutic systematic review) to identify key domains, and (2) empirical case studies of technology implementation to explore, test, and refine these domains. We studied 6 technology-supported programs—video outpatient consultations, global positioning system tracking for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organizing software, and integrated case management via data sharing—using longitudinal ethnography and action research for up to 3 years across more than 20 organizations. Data were collected at micro level (individual technology users), meso level (organizational processes and systems), and macro level (national policy and wider context). Analysis and synthesis was aided by sociotechnically informed theories of individual, organizational, and system change. The draft framework was shared with colleagues who were introducing or evaluating other technology-supported health or care programs and refined in response to feedback. Results The literature review identified 28 previous technology implementation frameworks, of which 14 had taken a dynamic systems approach (including 2 integrative reviews of previous work). Our empirical dataset consisted of over 400 hours of ethnographic observation, 165 semistructured interviews, and 200 documents. The final nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework included questions in 7 domains: the condition or illness, the technology, the value proposition, the adopter system (comprising professional staff, patient, and lay caregivers), the organization(s), the wider (institutional and societal) context, and the interaction and mutual adaptation between all these domains over time. Our empirical case studies raised a variety of challenges across all 7 domains, each classified as simple (straightforward, predictable, few components), complicated (multiple interacting components or issues), or complex (dynamic, unpredictable, not easily disaggregated into constituent components). Programs characterized by complicatedness proved difficult but not impossible to implement. Those characterized by complexity in multiple NASSS domains rarely, if ever, became mainstreamed. The framework showed promise when applied (both prospectively and retrospectively) to other programs. Conclusions Subject to further empirical testing, NASSS could be applied across a range of technological innovations in health and social care. It has several potential uses: (1) to inform the design of a new technology; (2) to identify technological solutions that (perhaps despite policy or industry enthusiasm) have a limited chance of achieving large-scale, sustained adoption; (3) to plan the implementation, scale-up, or rollout of a technology program; and (4) to explain and learn from program failures.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                2025
                6 January 2025
                : 27
                : e66356
                Affiliations
                [1 ] Working Group for Data-Driven Innovation Hamburg University of Technology Hamburg Germany
                Author notes
                Corresponding Author: Moritz Goeldner moritz.goeldner@ 123456tuhh.de
                Author information
                https://orcid.org/0009-0004-3193-3521
                https://orcid.org/0000-0002-8584-8080
                Article
                v27i1e66356
                10.2196/66356
                11747537
                39761562
                f42277db-e3a9-49da-afde-56e149059047
                ©Sara Gehder, Moritz Goeldner. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.01.2025.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 10 September 2024
                : 4 November 2024
                : 8 November 2024
                : 13 November 2024
                Categories
                Original Paper
                Original Paper

                Medicine
                regulatory market access pathways,digital health application,diga,patient-relevant structural and procedural improvement,psvv pathway analysis,qualitative and systemic analysis,policy and stakeholder insights,innovation system analysis

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