Intelligent and analytical technologies have the potential to rebuild many areas of care provision with computing and empathy. The rate of change will differ tremendously upon the job to be done. While far-future is profoundly different, but pontificating on the short-term is fraught.
Impact Areas:
AI/ML/DL can make the biggest impact in clinical operations and better-utilizing staff and resources i.e. scheduling, billing, rev cycle management. AI/ML/DL-based systems are changing how health can be managed since it can flag things like which patients need treatments when, and who needs more at-home visits. The concept of the ‘AI doctor’ is over-hyped. HC is not replacing physicians anytime soon. Instead, AI will be assisting and improving the efficiency of providers. Replacing a holistic diagnosis, treatment, and management care pathway with machines is far out over the next decade or so.
To offer an exhaustive list, the following are areas of HC where AI/ML/DL can add value,
Patient care:
Diagnosis:
Research and development
Management
Considerations and Issues to address:
As the AI market continues to evolve and new best practices are established, there are challenges and unique considerations for the successful technology adoption. Providers must consider how patient privacy and security will be protected and how to:
i) Effectively process and take advantage of unstructured data
ii) Deal with limited access to high-quality and unbiased data sets
iii) Utilize high-performing and reliable network capabilities
iv) Implement data governance strategies
v) Tackle a lack of talent and develop and adopt new staffing and training strategies
vi) Find a balance between costs and potential benefits
