Key questions for responsible AI innovation in healthcare

Are you asking the right questions for responsible AI innovation?

Here are some of key questions to consider for business and use case development in healthcare to responsibly innovate.

Understanding stakeholders

What do you think about ‘Chatbots’?
What are your biggest challenges?
How do you think we can address the challenges?
Are there any barriers?
What are the regulations & legal requirements?
What are their expectations & intention of use?
Any conflict of interest?

Clinical Discovery & Process

What patient problem you are trying to address?
Current decision making process? Who is involved in the treatment?
What difference would AI achieve?
Are there any adverse consequences?
What the the different systems used?

Data Source & ICT Systems

Do you have access to the required data sources?
Is there a standardised approach for data collection?
How is the quality of data?
What is the current infrastructure?
What systems would you need access to?
Are there any restrictions?

Problem & Value Determination

What is the problem?
Is there a need to solve the problem?
What is the scope, boundaries & context?
Analysis of socio-technical scenarios
Would patient outcome be effective using AI? 
Cost-benefit and risk-benefit analysis?

Regulation, Bias. Privacy, Ethics & Safety

How would you safeguard privacy & comply with law? 
Would misuse of data/ algorithm contribute to social/ ethical problems?
Map to trustworthy AI
Risks, ethical tensions & mitigations
What patient groups can be denied opportunities/ face negative consequences?

Capability, High-level Architecture & Data Pipeline

Do you have a multidisciplinary team?
Do you have access to AI experts for the project?
Do you have support from the executives, clinicians, patients, regulators & others?
Do you have a systems view of the architecture and data pipeline?

Data Source Integration & infrastructure

Do you have access to data?
How will your existing systems integrate?
What computing & data storage power do you need?
How will you monitor KPIs?
What is the infrastructure?
Any dependencies/ issues?
What would be the harm in providing the solution?
Data maintenance process

AI Strategy, Commercial Strategy & Costs

What is your value proposition?
Is your AI strategy aligned with the business strategy?
What are the future prospects & commercial viability?
Do you have the required finance for the project?
Does the financial forecast cover ongoing maintenance? 

Share:

More Posts

Modernising Applications

Overcoming Obstacles: Why Application Modernisation Matters

In today’s fast-paced digital landscape, legacy systems can often hinder #business growth and impede essential processes. Recognising this tipping point, leaders are turning to application modernisation to overcome these obstacles and propel their organisations forward.

Send Us A Message