Control Systems for Excellence: Data & Processing Systems (specific reference to bionic eyes)
IGF Dynamic Coalition on Data Driven Health Technologies
Session 156
Frameworks for achieving excellent operational systems for best outcomes for health data and general applications
As we integrate systems globally, it is critical that we have excellence for data quality that sources other systems (including AI and Quantum) so as to minimize disruption from poor interoperability. Hence monitoring of the foundational systems for data quality including reliability, accuracy, authenticity, validity, relevance and so forth is important. We must be mindful of structured and unstructured data and how user that input and output data may be impacted by data quality such as hallucinations or basic accessibility for the disabled. Is the data meaningful for its intended purpose? Are the formats useful? Is the data up to date and free of errors? All these questions must be answered before the data is sent into another system.
The health Eco-System will integrate legal, financial, cultural and other relevant systems with the specific health system from say a pharmacy or hospital to provide the end user with an integrated service opportunity. Each integrating system must be it own stand alone "truth" for its data with ensuing meta tags so that there is excellence for interoperability.
To build data quality excellence we need to implement monitoring systems guided by internationally recognized frameworks and policies for all data gathering, storing, processing, feeding and reporting mechanisms. There are a number of manners of implementing these control and monitoring systems. This session we look at sensors and the bionic eye as an emerging technology that can support our work.
Bionic eyes — formally classified as visual prostheses or retinal/cortical prosthetic systems — represent one of the most complex intersections of embedded electronics, real-time data processing, neural interfacing, and clinical governance in the history of health technology. As these devices evolve from proof-of-concept implants into AI-augmented, wirelessly connected neural interfaces, the governance, risk management, and data control disciplines required to oversee them have grown correspondingly complex. This session examines the architecture of control excellence for bionic eye technologies through three converging lenses: (1) the COSO Internal Control and Enterprise Risk Management (ERM) frameworks as the foundational governance model for data and systems controls; (2) relevant ISO/IEC standards and technical reports governing medical device quality, risk, software lifecycle, network integration, and health informatics security; and (3) the some of the most recent research, clinical trials, and white papers addressing systems control, AI integration, cybersecurity vulnerabilities, and neurodata privacy in visual prostheses and so forth.
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C1. The role of governments and all stakeholders in the promotion of ICTs for development
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C2. Information and communication infrastructure
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C3. Access to information and knowledge
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C4. Capacity building
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C5. Building confidence and security in use of ICTs
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C6. Enabling environment
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C7. ICT applications: benefits in all aspects of life — E-government
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C7. ICT applications: benefits in all aspects of life — E-business
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C7. ICT applications: benefits in all aspects of life — E-learning
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C7. ICT applications: benefits in all aspects of life — E-health
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C7. ICT applications: benefits in all aspects of life — E-employment
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C7. ICT applications: benefits in all aspects of life — E-environment
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C7. ICT applications: benefits in all aspects of life — E-agriculture
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C7. ICT applications: benefits in all aspects of life — E-science
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C8. Cultural diversity and identity, linguistic diversity and local content
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C9. Media
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C10. Ethical dimensions of the Information Society
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C11. International and regional cooperation
Our main action line is C6 and C7 Health
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Goal 1: End poverty in all its forms everywhere
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Goal 2: End hunger, achieve food security and improved nutrition and promote sustainable agriculture
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Goal 3: Ensure healthy lives and promote well-being for all
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Goal 4: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
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Goal 5: Achieve gender equality and empower all women and girls
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Goal 6: Ensure access to water and sanitation for all
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Goal 7: Ensure access to affordable, reliable, sustainable and modern energy for all
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Goal 8: Promote inclusive and sustainable economic growth, employment and decent work for all
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Goal 9: Build resilient infrastructure, promote sustainable industrialization and foster innovation
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Goal 10: Reduce inequality within and among countries
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Goal 11: Make cities inclusive, safe, resilient and sustainable
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Goal 12: Ensure sustainable consumption and production patterns
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Goal 13: Take urgent action to combat climate change and its impacts
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Goal 14: Conserve and sustainably use the oceans, seas and marine resources
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Goal 15: Sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss
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Goal 16: Promote just, peaceful and inclusive societies
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Goal 17: Revitalize the global partnership for sustainable development
Main SDG is #3
However, this work will be an enabler and educator for all SDGs
- Objective 1: Close all digital divides and accelerate progress across the Sustainable Development Goals
- Objective 2: Expand inclusion in and benefits from the digital economy for all
- Objective 3: Foster an inclusive, open, safe and secure digital space that respects, protects and promotes human rights
- Objective 4: Advance responsible, equitable and interoperable data governance approaches
- Objective 5: Enhance international governance of artificial intelligence for the benefit of humanity
a. COSO
COSO Internal Control – Integrated Framework (ICIF): https://www.coso.org/internal-control — the foundational 1992/2013 framework for data and systems controls, applicable to health technology governance
COSO Enterprise Risk Management (ERM): https://www.coso.org/guidance-erm — the 2017 ERM update integrating strategy, performance, and risk
COSO Compliance Risk (Healthcare): https://www.corporatecompliance.org/coso — authored with SCCE & HCCA specifically for health compliance programs
COSO + AI Governance (Deloitte 2025): Deloitte's guide on applying COSO ERM to AI risks — directly relevant to AI-driven stimulation algorithms in bionic eyes
b. ISO Standards Stack
Standard
Relevance
ISO 42001
Responsible use of AI
ISO 13485:2016
Medical device QMS — full lifecycle quality
ISO 14971:2019
Risk management — hazard analysis for bioelectronics, software, wireless
IEC 62304
Medical device software lifecycle — Class C for AI stimulation algorithms
IEC 80001-1
IT networks with medical devices — wireless connectivity risk
ISO 27799:2016
Health informatics security — neurodata protection
ISO/IEC 25010
Software quality — reliability, security, maintainability