GenAI in Healthcare: Deciphering key challenges
From our conversations with Healthcare and Life Sciences organizations, we discovered that over 80% of GenAI PoCs and initiatives are delayed due to compliance and regulatory concerns, and lack of trust in GenAI solutions.
Some of the major challenges are:
Retrieval
Finding the right document, selecting the right section and ordering them correctly needs to be addressed
Data Privacy
Since GenAI tools rely on vast data sets, some concerns on the privacy of the information used will arise
Accuracy
GenAI tools can make factually wrong or biased decisions based on the training data
Hallucinations
GenAI models are fundamentally probabilistic and non-deterministic and can generate outputs that are not grounded in the input data
Healthcare Awareness
GenAI tools may not have healthcare context in representing the output to the user or understanding the questions
Generalizability
Solution built for one area (say therapeutic area or plan) may not generalize to another area, resulting in significant costs
Retrieval
Finding the right document, selecting the right section and ordering them correctly needs to be addressed
Data Privacy
Since GenAI tools rely on vast data sets, some concerns on the privacy of the information used will arise
Accuracy
GenAI tools can make factually wrong or biased decisions based on the training data
Hallucinations
GenAI models are fundamentally probabilistic and non-deterministic and can generate outputs that are not grounded in the input data
Healthcare Awareness
GenAI tools may not have healthcare context in representing the output to the user or understanding the questions
Generalizability
Solution built for one area (say therapeutic area or plan) may not generalize to another area, resulting in significant costs
R.A.G.
Design Pattern
R.A.G. design pattern gives fine grain control over search and retrieval of your internal information. And limits the LLM to be the interface layer
Trust and Quality Framework
Track quality and trust across layers – source data, search/retrieval, response and application layer. Integrate into ML Ops pipeline
Private or On-Prem GenAI Stack
LLM services are now available as a private version with no data sharing back with CSPs. On-prem solution with open source LLM is an option
Healthcare and Business Ontology as Embeddings
Adding embeddings from healthcare ontologies, as well as any internal dictionaries
Right LLM for Right Use Case
Determine the LLM to be used based on the use case, cost per transaction constraints and context needed
R.A.G.
Design Pattern
R.A.G. design pattern gives fine grain control over search and retrieval of your internal information. And limits the LLM to be the interface layer
Trust and Quality Framework
Track quality and trust across layers – source data, search/retrieval, response and application layer. Integrate into ML Ops pipeline
Private or On-Prem GenAI Stack
LLM services are now available as a private version with no data sharing back with CSPs. On-prem solution with open source LLM is an option
Healthcare and Business Ontology as Embeddings
Adding embeddings from healthcare ontologies, as well as any internal dictionaries
Right LLM for Right Use Case
Determine the LLM to be used based on the use case, cost per transaction constraints and context needed
Adopt & scale at speed with 70+ metrics and 25+ methods
Evaluate enterprise readiness from quality & trust perspective with speed and accuracy
Intuitive dashboards for Q&T Analytics and reporting for monitoring & governance
Gain trust with Gap analysis and maturity assessment
Work with any tech stack & cloud service provider
Improve performance with embedded engineering productivity-augmenting GenAI tools
Adopt & scale at speed with 70+ metrics and 25+ methods
Evaluate enterprise readiness from quality & trust perspective with speed and accuracy
Intuitive dashboards for Q&T Analytics and reporting for monitoring & governance
Gain trust with Gap analysis and maturity assessment
Work with any tech stack & cloud service provider
Improve performance with embedded engineering productivity-augmenting GenAI tools
Talk to our GenAI Expert
Explore our GenAI solutions
