Visiba's Responsible AI Principles

As a healthtech company renowned for high quality solutions, working with Responsible AI Principles is part of our DNA. We believe that all providers should be held to the same high standards.

 

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Our commitment to high quality healthtech

We've been working with innovative healthcare providers to deliver high quality healthtech since 2014. When we launched our AI-enabled triage solution in 2018, we took the same quality-first approach. 

This approach was heavily guided by input from our medical team and clinicians using the system, alongside our fundamental belief in the importance of working with Responsible AI Principles.

These principles are embedded in every phase of our development process in the form of 'practices' and form an integral part of our daily work.

Smarter software. Better healthcare

Our Responsible AI Principles

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1. Clinically safe

Healthcare professionals, patients and commissioners should feel confident that our solution is clinically safe. 

2. Transparent

Our technology should be developed in a way that affords an appropriate level of transparency and explainability.

3. Secure

In addition to complying with relevant regulations, confidentiality, integrity and availability are cornerstones of our work.

4. Ethical 

The technology should work in a way that enhances and does not detract from the human element of healthcare.

 

 

 

Examples of our principles in practice

Clinically safe

  • We employ risk identification and assessment processes for every phase and individual development initiative.
  • We use a clinical feedback loop to continually develop and improve the clinical model to improve accuracy.
  • Throughout the development cycle we work cross-functionally to ensure technical and architectural components work together in a way that continually delivers on clinical performance and safety.
  • We implement in a phased and controlled way to ensure clinical safety.
  • Our clinicians undertake continuous evaluation of patient cases to enable rapid identification and response to anomolies.

Transparent

  • The model is designed to ensure appropriate transparency and so that the decisions it makes are traceable and easy to understand.
  • All changes to the model are traceable and managed by humans. The system is intentionally designed to not be self-learning to minimise the risk of bias.
  • The development of interfaces is data-driven and decisions about designs are traceable and explainable.
  • There is clear visibility of data used in the machine learning model.
  • The entire development process is evidenced in technical documentation.

Secure

  • Robustness and availability are ensured through the design of the architecture and infrastructure, along with well-defined processes for maintenance, testing, tracking and responding to issues.
  • The architecture is designed to support scalability, resilience and fault tolerance, ensuring the system can handle varying loads and recover quickly from any failures.
  • Protecting data and patient privacy are cornerstones of our work, with clear processes around data protection and handling.
  • We adhere to industry standards that enable us to ensure balance between benefits and risks in a structured and accountable way. This compliance provides a framework for making informed decisions, maximizing positive outcomes and mitigating risks.

Ethical

  • We employ a holistic approach to understanding and solving the problems that exist for users across the healthcare system.
  • Cross-functional teams are involved in the development of our human-centric designs, using concrete goals for fairness and inclusion and tested at all phases for usability.
  • We implement in a phased manner with  evidence collection that includes evaluations with users in the early phases before full roll-out.
  • We work to consciously address potential sources of bias.

Clinically led development

The medical team drive the development of Visiba Triage to ensure it is clinically safe. Leaning on extensive clinical experience they review hundreds of real-world patient cases weekly and use this information, along with feedback from practising clinicians, to develop a solution they want to use for their own patients.
Dr Annabelle Painter, CMO

Dr Annabelle Painter

Chief Medical Officer at Visiba

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Dr Christer Rosenberg

Senior Medical Specialist at Visiba

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Dr Katherine Leung

Medical Specialist at Visiba

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Dr Joel Ellbin

Medical Specialist at Visiba

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Dr Edwin Gidestrand

Medical Specialist at Visiba

Mats_Halldin

Dr Mats Halldin

Medical Specialist at Visiba

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Dr Marcus Olausson

Medical Specialist at Visiba

Related content

Learn more about the reality of AI in healthcare thorough evaluations, publications, perspectives and webinars.

Want to know more?

If you'd like to know more about our guiding principles and how we practise them then please get in touch.
Annabelle-Painter
Anastacia-Simonchik
Marcus_Olivecrona

Visiba Group AB
Adolf Edelsvärds Gata 11 Göteborg, 414 51
Phone: 0761993666