Digital Health Ecosystem Research Articles

Perception towards electronic health records & uptake of digital health IDs among the urban residents in northern India: A mixed methods study.

Background & objectives Ayushman Bharat Digital Mission (ABDM) envisages a unique digital health ID for all citizens of India, to create electronic health records (EHR) of individuals. The present study assessed the uptake of Digital Health IDs by the patient and general population, their attitude toward EHR, and explored the barriers to digital ID and utilizing electronic health records services. Methods A concurrent explanatory mixed methods study was undertaken in Chandigarh, India, with an analytical cross-sectional design as a quantitative part and a qualitative descriptive study. The study participants were 419 individuals aged ≥18 yr who attended the urban primary healthcare centre (n=399) and the community-based screening camps (n=20) between July 2021 and January 2022. Latent Class Analysis (LCA) was undertaken to identify hidden sub-population characteristics. In-depth interviews were done to identify the barriers to health ID uptake. Results The digital health ID uptake rate was 78 per cent (n=327). Among the study participants, those who were aware of EHR, those who wanted a national EHR system, those who were confident with the government on EHR security, and those who were willing to make national EHR accessible for research showed significantly higher digital health ID uptake than their counterparts. The themes identified under barriers of uptake from the qualitative interviews were lack of awareness, technology-related (including digital literacy) and utility-related. Interpretation & conclusions Increasing EHR awareness, digital health literacy, and enacting data protection laws may improve the acceptance of the digital health ecosystem in India.

Characteristics of a Successful Nurse Peer Champion in the Implementation of Innovative Digital Technologies in Hospitals: A Qualitative Study

ObjectivesUsing the Motivational Theory of Role Modelling as a framework, this study explores which attributes nurses deem essential for an effective peer champion, particularly in digital transformation processes within hospitals. MethodsA qualitative study was conducted with semi-structured interviews. Transcripts were coded using a hybrid approach of inductive and deductive coding and analysed using thematic analysis. ResultsTen nurses from Germany participated. The attributes most often mentioned were competence, taking on responsibility, a positive and passionate attitude, transferring knowledge and supporting aspirants in applying it, and leadership skills. Four types of champions were identified: a pragmatic and structured champion, a passionate innovator, a social and outgoing team leader, and a calm and empathetic team leader. ConclusionsThe findings largely align with the body of literature on peer champion characteristics in other populations and should therefore be used to guide peer champion application in hospitals to enhance effective implementation of innovations. InnovationThe identification of four unique champion types offers an innovative contribution to the field. Highlighting the unique requirements of nurses when implementing innovative technologies in healthcare, this study emphasises the importance of involving end-users in the design and implementation process of new technologies, a crucial step towards a more sustainable and user-centred digital health ecosystem.

Empowering Citizens Through Translated Patient Summary Access and Sharing in Digital Health Ecosystems.

This paper introduces a mobile framework designed to enhance citizen access to and sharing of health data, aiming to empower individuals with greater control over their personal health information. Accessing and sharing health-related data is essential in everyday scenarios, from routine doctor visits or viewing your health on your own to emergencies where swift access can save lives. It addresses the challenges posed by the fragmented nature of healthcare services and the barriers of language differences in patient records. The framework utilizes the EU eHealth Digital Service Infrastructure (eHDSI) OpenNCP for translating patient summaries and the FHIR Smart Health Links Protocol for secure sharing. A pilot study with 40 participants was conducted to assess the usability and effectiveness of the app, revealing a strong demand among citizens for such innovative health services.

Representing Nursing Practice in EMR/EHRs.

Review of the ISO 18104 technical standard for a Nursing Categorial structure to best represent nursing practice in EMR/EHRs and digital health ecosystems. Application of ISO standard review guidelines in consultation with ISO member stakeholders. Comprehensive views of the nursing practice knowledge domain are presented as mindmaps. Groups of patients can now be identified using the 'type of subject of care' category. The collaborative role of nurses is now recognized. This high level structured information model recognises nursing diagnosis, nursing actions and nurse sensitive outcomes relative to other categories and sub-categories known to influence nursing actions and nurse sensitive outcomes. This nursing practice framework reflects the nursing process. It supports conceptual and logical analysis of patient journey related nursing practice. This updated categorial structure is a good fit with today's information technologies. Its adoption enables the value of nursing services provided to be demonstrated.

Optimizing electronic health records to support artificial intelligence

Electronic health records (EHRs) provide the most important data sources for artificial intelligence (AI). Gaining access to quality data suitable for advanced analytics continues to be challenging. This rapid review documents the current state of available data; identifies foundational AI data/information needs; and explores the benefits of adopting new and emerging technologies to design and implement next-generation EHRs. Opportunities to optimize EHRs for AI purposes are identified. This review was informed by expert knowledge and shared experiences supported by the literature, including technical standards. Main findings include poor ecosystem-wide infrastructures due to the lack of adopting the right set of standards, and current data and knowledge governance no longer fit for purpose. While many jurisdictions are continuing the use of legacy systems, some forward-looking national health systems and health-care facilities are adopting transformational strategies by adopting a strong data and digital focus to transition to new-generation systems. New foundational-level national infrastructures with strong leadership and governance are essential to enhance the governance and quality of available data, from collection at source throughout the entire data supply chain. Secure and ubiquitous access to high-quality EHR data at scale will foster the evolution of more intelligent and trustworthy AI. Key characteristics of next-generation EHRs supported by currently available technologies and standards that are able to meet digital era demands are provided in this paper. We conclude that the use of generative AI in clinical settings can only be reliably achieved when EHRs are optimized throughout the entire global digital health ecosystem.

Healthcare professionals' perspectives towards the digitalisation of paediatric growth hormone therapies: expert panels in Italy and Korea.

To analyse the perspectives of healthcare professionals (HCPs) regarding the acceptance of digital health solutions for growth hormone (GH) deficiency care. This study identified factors impacting HCPs' intent to use and recommend digital solutions supporting recombinant-human growth hormone (r-hGH) therapy in Italy and Korea with a use case of connected drug delivery system (Aluetta® with Smartdot™) integrated in a platform for GH treatment support (the Growzen™ digital health ecosystem). Participatory workshops were conducted in Rome, Italy, and Seoul, Korea, to collect the perspectives of 22 HCPs on various predefined topics. HCPs were divided into two teams, each moderated by a facilitator. The workshops progressed in five phases: introduction of the project and experts, capturing views on the current context of digitalisation, perceived usefulness and ease of use of Aluetta® with Smartdot™, exploration of the perception of health technology evolution, and combined team recommendations. Data shared by HCPs on technology acceptance were independently analysed using thematic analysis, and relevant findings were shared and validated with experts. HCPs from both Italy and Korea perceived Aluetta® with Smartdot™ and the Growzen™ based digital health ecosystem as user-friendly, intuitive, and easy-to-use solutions. These solutions can result in increased adherence, a cost-effective healthcare system, and medication self-management. Although technology adoption and readiness may vary across countries, it was agreed that using digital solutions tailored to the needs of users may help in data-driven clinical decisions and strengthen HCP-patient relationships. HCPs' perspectives on the digitalisation in paediatric GH therapies suggested that digital solutions enable automatic, real-time injection data transmission to support adherence monitoring and evidence-based therapy, strengthen HCP-patient relationships, and empower patients throughout the GH treatment process.

The growzen™ buddy smartphone app to improve adherence in patients receiving recombinant human growth hormone therapy: a retrospective observational study in Argentina.

This study in Argentina evaluated the impact of the growzen™ buddy smartphone app on adherence to recombinant human growth hormone (r-hGH) treatment. The adherence data, invitation dates with a link to the app, app activation dates, and height measurements entered were extracted from the growzen™ digital health ecosystem. Patients with 12 months of adherence data, aged ≥2 years at treatment start, and aged <19 years were selected both before and after app implementation. Mean adherence was classified as optimal (≥85%) versus suboptimal (<85%). Adherence before and after implementation and the pre-post effect on adherence were assessed. Data for 830 patients were available. Prior to app implementation, the proportion of patients with optimal adherence was 68% (n = 348/515). Following the app implementation, out of 315 patients, 302 (96%) received an invitation with a link to the app, 225 (71%) activated their account, and 127 (40%) entered height data in the first year. There was a significant early increase in the proportion of patients with optimal adherence following implementation: 82% (n = 258/315), p < 0.001. After implementation, the proportion of patients with optimal adherence included 80% (n = 78/98) of those with an active account who did not enter height measurements and 89% (n = 113/127) of those who did. There was a significant and positive pre-post app effect on adherence (p < 0.01) in patients with an active account. Our results show that using the growzen™ buddy app has a rapid and positive impact on adherence to r-hGH treatment, and patients who were more engaged with the app demonstrated better adherence.

Incidental findings in development and use of digital health ecosystems for older people

Healthcare sectors are globally facing challenges delivering services for older people,. Although the implementation of digital technology has brought positive effects on caring older people in their homes, it has also resulted in arising ethical challenges including incidental findings (IF). The purpose of this systematic review is to reveal ethical challenges in the development and use of digital health ecosystems for older people. The objectives are 1) to reveal incidental findings, 2) ethical vulnerabilities and treats for integrity associated with the use of Artificial Intelligence (AI); 3) to analyse ethical management of IF, and 4) to create recommendations for the use and development of digital health ecosystems. Systematic data search was completed in ProQuest, EBSCOhost, and Ovid databases. Peer-reviewed full text research articles on ethical guidelines for developing and implementing digital health ecosystems for care of older people published in English between 2012 and 2022 were included. Previously published articles focusing on younger population or other than digital services were excluded. The included thirteen articles were appraised by design specific tools (PRISMA 2009, SANRA, STROBE, CAGSCS). The article texts were analysed and reported thematically. The IF revealed were violation of user autonomy, independence, and privacy during the development and use of the ecosystems; social isolation of the end-user; user unfriendly devices; additional workload to the care providers; technology induced anxiety; and biases and errors in use of the ecosystems. The ethical vulnerabilities and threats to integrity associated with use of AI. Observation and implementation of ethical values were found important in co-creation of ethically conscious ecosystems for older people. Empowering the designers, developers, and healthcare professionals on ethical competencies, and inclusion of the end-users’ preferences in designing of digital health ecosystems were included in the constructed recommendations. This article disseminated within the SHAPES Horizon 2020 project.

Balancing stakeholder interests and paradoxes in health data sharing within health ecosystems

Personal health data sharing can facilitate value co-creation between multiple stakeholders, including individuals, public organisations, private companies, research institutes, and policymakers. Yet, when companies are involved in sharing health data to develop health-related solutions, it can lead to conflicts and contradictions between stakeholders. We apply a qualitative research approach over two cases in the Finnish healthcare sector to explore the tensions and contradictions in sharing personal health data that companies can utilise in the development of new products/or services in the healthcare sector. We identify the tensions and paradoxes from multiple stakeholders’ perspectives and provide management approaches on three levels: (I) The micro-level focusing on individuals as users, (II) The meso-level concerns businesses operating within the digital health ecosystem. (III) The macro-level addresses broader societal impact and policies governing the secondary use of health data.

A perspective on digital health platform design and its implementation at national level.

Accessible and affordable health services and products including medicines, vaccines, and public health are an important health agenda of all countries. It is well understood that without digital health technologies, countries will face difficulties in tackling the needs and demands of their population. Global agencies including the World Health Organization (WHO), United Nations (UN), International Telecommunication Union (ITU), etc. have been instrumental in providing various tools, and guidance through digital health strategies in improving health and digital health maturity of the countries. The Digital Health Platform Handbook (DHPH) is a toolkit published by WHO and ITU to help countries create and implement a digital health platform (DHP) to serve as the underlying infrastructure for an interoperable and integrated national digital health system. We apply the foundational principles of DHPH and provide a perspective of DHP components in a layered, enterprise architecture of a digital health infrastructure. India has rolled out the blueprint of its National Digital Health Mission (NDHM) to address the emerging needs for digitization of healthcare in the country. In this paper, we also illustrate the design and implementation of WHO-ITU DHP components at the national level by exploring India's digital health mission implementation utilizing various digital public goods to build a digital health ecosystem in the country.

A Sustainable W-RLG Model for Attack Detection in Healthcare IoT Systems

The increasingly widespread use of IoT devices in healthcare systems has heightened the need for sustainable and efficient cybersecurity measures. In this paper, we introduce the W-RLG Model, a novel deep learning approach that combines Whale Optimization with Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) for attack detection in healthcare IoT systems. Leveraging the strengths of these algorithms, the W-RLG Model identifies potential cyber threats with remarkable accuracy, protecting the integrity and privacy of sensitive health data. This model’s precision, recall, and F1-score are unparalleled, being significantly better than those achieved using traditional machine learning methods, and its sustainable design addresses the growing concerns regarding computational resource efficiency, making it a pioneering solution for shielding digital health ecosystems from evolving cyber threats.

IJCM_214A: Digital interventions for childhood malnutrition in a tribal area of Andhra Pradesh: Understanding the problem through a health system perspective

Background: Childhood malnutrition is a major public health concern in the tribal areas of Andhra Pradesh, India, particularly in the region of ITDA Rampachodavaram. The integration and effectiveness of digital health interventions in these underserved regions are vital for addressing this endemic issue. However, the unique challenges posed by the remote and resource- limited settings of tribal areas make the implementation of such interventions particularly complex. Moreover, the varying complexity of the digital health ecosystem in these areas adds another layer of concern to deploying digital health solutions. Objectives: 1. To explore digital health interventions related to childhood malnutrition in the Integrated Tribal Development Agency (ITDA) of Rampachodavaram. 2. To understand the dynamics of the local health system and the digital health ecosystem in the implementation of these interventions. 3. To examine the role of street-level bureaucrats in implementing digital interventions and identify the barriers and facilitators affecting this process Methodology: The research was conducted in ITDA Rampachodavaram, involving interviews with health system officials and Focus Group Discussions (FGDs) with frontline health workers. The Health System Dynamics (HSD) framework and Lipsky’s theory on street-level bureaucrats were utilized, and enriched with insights into the digital health ecosystem. Results: The study reveals significant systemic, contextual, and human factors influencing the implementation of digital health interventions. Challenges include the complex role of street-level bureaucrats and systemic barriers like inadequate training, technological limitations, and disparities in digital access and literacy. Conclusion: This study highlights the potential of digital health interventions in improving childhood malnutrition outcomes in tribal areas. It stresses the importance of adaptive, inclusive strategies and advocates for digital health equity. Empowering frontline health workers and tailoring interventions to the specific health system dynamics and digital ecosystem of tribal regions are key for effective implementation.

Support for Chronic Pain Management for Breast Cancer Survivors Through Novel Digital Health Ecosystems: Pilot Usability Study of the PainRELife Mobile App.

Chronic pain is one of the most common and critical long-term effects of breast cancer. Digital health technologies enhance the management of chronic pain by monitoring physical and psychological health status and supporting pain self-management and patient treatment decisions throughout the clinical pathway. This pilot study aims to evaluate patients' experiences, including usability, with a novel digital integrated health ecosystem for chronic pain named PainRELife. The sample included patients with breast cancer during survivorship. The PainRELife ecosystem comprises a cloud technology platform interconnected with electronic health records and patients' devices to gather integrated health care data. We enrolled 25 patients with breast cancer (mean age 47.12 years) experiencing pain. They were instructed to use the PainRELife mobile app for 3 months consecutively. The Mobile Application Rating Scale (MARS) was used to evaluate usability. Furthermore, pain self-efficacy and participation in treatment decisions were evaluated. The study received ethical approval (R1597/21-IEO 1701) from the Ethical Committee of the European Institute of Oncology. The MARS subscale scores were medium to high (range: 3.31-4.18), and the total app quality score was 3.90. Patients with breast cancer reported reduced pain intensity at 3 months, from a mean of 5 at T0 to a mean of 3.72 at T2 (P=.04). The total number of times the app was accessed was positively correlated with pain intensity at 3 months (P=.03). The engagement (P=.03), information (P=.04), and subjective quality (P=.007) subscales were positively correlated with shared decision-making. Furthermore, participants with a lower pain self-efficacy at T2 (mean 40.83) used the mobile app more than participants with a higher pain self-efficacy (mean 48.46; P=.057). The data collected in this study highlight that digital health technologies, when developed using a patient-driven approach, might be valuable tools for increasing participation in clinical care by patients with breast cancer, permitting them to achieve a series of key clinical outcomes and improving quality of life. Digital integrated health ecosystems might be important tools for improving ongoing monitoring of physical status, psychological burden, and socioeconomic issues during the cancer survivorship trajectory. RR2-10.2196/41216.

How to establish digital health ecosystems from the perspective of health service-organizations: A taxonomy developed based on expert interviews conducted as modified Delphi approach.

Digital health ecosystems may be the next revolution in improving citizens' well-being, health delivery, data management, and health system processes, but solutions have not yet been broadly established. Reasons could be that health service-organizations have misaligned interests or lack capabilities. This study investigates reasons from a multi-health-service-organization perspective, differentiating between payers, insurers, healthcare providers, and innovators, detailing the expected value-adds, preferred participation roles, and required capabilities including a rating assessment. Findings are based on a taxonomy development methodology, which combines a literature review with semi-structured qualitative expert interviews, conducted using a modified Delphi approach. Interviews were thematically analysed. In total, 21 experts across the four health service-organization groups were interviewed. The capability taxonomy includes a total of 16 capabilities, categorized in three themes: 'Health market', 'organizational', and 'technology and informatic'. Providers expect a value-add from strengthening their health process economics through efficiency gains but reveal the largest capability gaps, especially in 'interoperability' and 'platform'. Innovators' 'technology and informatic' capabilities complement well with those of payers for the 'health market'. We present a health service-organization-specific three-stage approach for establishing digital health ecosystems. Payers and insurers should address their 'technology and informatic' capability gaps, using technical enablers or forming new entities to reduce dependencies from legacy information technology systems. Innovators should clarify their monetization models and create positive awareness for their services, possibly entering the market directly. Providers must address interoperability issues and may require incentives to encourage their participation. Findings suggest governmental policymakers to prioritize three health policy initiatives.

The Ayushman Bharat Health Account: A New Frontier for Smart Healthcare Delivery in India

The ever-changing healthcare landscape in India, focusing particularly on the ABHA and the broader Ayushman Bharat Digital Health Mission. Despite significant progress made in the last decade to mitigate disparities in healthcare access between rural and urban regions, challenges persist in providing healthcare services to underprivileged groups. Telehealth, combining video conferencing and mobile health apps, is essential for distant healthcare and overcomes geography. Telehealth services like consultations and education have grown in prominence, notably during the COVID-19 epidemic. It has helped to modernise healthcare delivery and lead to better results. Statistical assessments of the establishment of ABHA, categorised by state, gender, and age group, uncover distribution patterns and geographical inequalities. The report highlights the increasing influence of digitization in healthcare, specifically emphasising the Ayushman Bharat Digital Health Mission’s objective of establishing a complete digital health ecosystem to enhance the accessibility, efficacy, efficiency, and transparency of healthcare delivery. Ultimately, India’s healthcare industry is poised to enter a period of significant change, propelled by breakthroughs in technology, regulatory changes, and comprehensive efforts. In order to achieve sustainable and equitable healthcare results, it is imperative to address obstacles and allocate resources towards new solutions as the country advances. The integration of artificial intelligence (AI) with health data shows potential for transforming healthcare delivery, providing customised treatments, and enhancing overall health outcomes for India’s varied population.

Integrating a Categorial Structure for Clinical Practice into EHRs.

A continuing global desire to be using clinical systems within a digital health ecosystem, able to facilitate data flows and information exchange as required to support person-centred, predictive, preventative, participatory and precision (5p) health and medical care can best be supported through the use of the standard categorial structure able to represent not only the clinical nursing practice domain but also other clinical disciplines by the generic labelling of some high-level categories. It is hypothesised that adoption of this generic clinical categorial structure within any electronic health/medical record within a well connected digital health ecosystem, supported by a cloud based openEHR platform, will enable the 5p support to be realized. This presentation provides the results of the latest update of this technical standard based on the 20+ year nursing practice categorial structure development process adopted to achieve this aim and a summary about linking this categorial structure to standard terminologies and to standard EHR/EMR system architectures.

Understanding citizens' attitudes within user-centered digital health ecosystems: A sequential mixed method methodology including a web-survey.

Transitioning from digital health applications to digital health ecosystems, leveraging the advances in technologies and informatics, could be the next revolution in digital health. This includes offering centralized access to various health services and improving citizens' well-being, delivery, clinical processes, and data management. However, a limited understanding of citizens may impede adaptation. Therefore, this study investigates citizens' attitudes within digital health ecosystems, differentiated by their characteristics, to support health service-providers and governmental policymakers in establishing user-centered solutions. This study follows a three-step sequential mixed method methodology: (1) a literature review. (2) Qualitative thematic analyses based on semi-structured qualitative interviews. (3) Quantitative analyses based on a web-survey (descriptive statistics, one-way analysis of variances, Tukey-honestly, and Cohen's d tests). N = 15 citizens were interviewed and n = 1289 responded to the web-survey, to our knowledge the largest survey on this topic. Citizens desire a more convenient management of health services and data (M = 5.2, SD = 1.59). Services with peer-to-peer interactions (M = 3.7, SD = 1.81) and lower involvement of health professionals (M = 3.8, SD = 1.75) are less demanded. Data protection is critical (M = 6.2, SD = 1.23). Public payers are mandated as orchestrators (M = 4.3, SD = 1.99), while private companies receive lower acceptance (M = 3.0, SD = 1.42). Health service-providers could follow a three-staged approach to establish digital health ecosystems: (1) Increasing the convenience for citizens by enabling online management of health services and data. (2) Extending the citizen-healthcare provider partnership through online interactions. (3) Fostering preventative behaviors and quicker recovery by personalizing health services and interactions. Governmental policymakers should integrate an electronic health record.

Identification of required capabilities of digital health ecosystems when preventing and managing non-communicable diseases.

Non-communicable diseases cause annual mortality for 41 million people worldwide. These diseases include coronary heart disease, cancer, stroke, diabetes, and musculoskeletal as well as mental disorders. Innovation ecosystems in healthcare are multifactor networks in which different stakeholders interact together to create socio-economic (patient and cost) value via research, co-creation, and traditional market activities. Although there is much evidence about the impact of digital health interventions and the capabilities needed to support individual actors and specific diseases in non-communicable disease prevention and management, the current understanding of the concept of innovation ecosystems associated with theories is not well understood. There is also a lack of research about innovation ecosystems in the healthcare context. Or understanding of the holistic perspective of the capabilities needed in innovation ecosystems to support future digital health. The objective of this study was to answer this research gap by identifying what capabilities are needed in future digital health ecosystems related to people with non-communicable diseases or at risk of non-communicable diseases. By doing this, the study will help different organisations and policies address this very challenging situation. To answer this objective, a qualitative interview-based study including 34 semi-structured interviews was conducted in Finland. Complex adaptive systems theory was used as a theoretical lens to analyse empirical data. Several new capabilities were identified for digital health innovation ecosystems to make organisation managers and policymakers aware of how to deal with future health system demands. From the organisational perspective, capabilities are needed to use non-medical and heterogeneous data to support better treatments and clinical decision-making and provide better and safer data access. From the management perspective, hospitals need capabilities to allow critical experts to participate in innovation work, and overall, all ecosystem actors need capabilities to orchestrate research and innovation actions in the area of digital health.

Digital Health Nursing and ecosystem proposal: technological prospection protocol

Digital Health Nursing and ecosystem proposal: technological prospection protocol

Datafication, Power, and Publics in India's National Digital Health Ecosystem

While evident for a long time, the COVID-19 pandemic starkly illustrated the need to strengthen India’s public healthcare system. But since 2017, the solution to India’s public health woes takes the shape of the National Digital Health Ecosystem (NDHE) – a digital system for the generation, use, and ‘frictionless’ circulation of health data across healthcare actors through the use of artefacts such as health IDs, electronic health records, data standards, and federated computing architectures. These artefacts are not neutral technological systems. Rather, together with social practices, they constitute a “data infrastructure”. Seeing the NDHE as a data infrastructure allows us to visibilise the regulatory effects of the NDHE, i.e., the ways in which the NDHE creates “communities of the affected” whose access to public health is now mediated by affordances granted by the NDHE. This, in turn, shapes law and regulation of the NDHE, where legal frameworks for (health) data protection are not weakened by accident, but weakened by design. At the same time, the regulatory effects of the NDHE can and should be regulated by law, by channelling law’s commitment to the creation of healthy public spheres to ensure the vitality of a democracy. Accordingly, this paper makes three contributions – one, it provides a brief overview of the political economy and the regulatory effects of the NDHE; two, it analyses the ways in which the regulatory effects of the NDHE shape legal frameworks for health data to disempower individuals and communities who are the generators of this data; and three, it outlines research and policy suggestions for how the law can intervene in limiting the exclusionary data-politics of the NDHE.