Being one of the most exciting fields in the world, Artificial intelligence is already changing the face of healthcare as we know it. However, automated surgeons are not coming into the picture anytime soon.
HIPAA compliance comes with a few challenges like many things around us, these challenges are nonetheless not difficult to deal with.
To identify any minor signs of illness and sickness, MRI scans are examined by an AI algorithm. These are so minor to detect that even a trained and experienced clinician can potentially miss it. Supercomputers are assisting research teams to help them develop new drugs. Doctors are being walked through the process of the devised treatment plan by an AI assistant.
About a decade ago, these circumstances were impossible to think—let far be practiced. Today they are part of our everyday life and they are a reality. This is just the beginning. The potential o research, treat, and care practiced by AI is downright incredible.
The course is set by imagining its possibilities and then making it happen. Imagine an AI algorithm proficient enough to track dangerous diseases by merely scanning the patient’s DNA. Imagine a smart machine analyzing the patient and within seconds and conveying an accurate diagnosis. Imagine robots performing complex surgeries without errors and in lesser times.
An exciting and promising future is lying ahead—and the future is AI. Alike every other path, this path also comes with its roadblocks. The most significant and prominent of which is HIPAA compliance. This is a complex issue that is evolving to incorporate various advancements happening in the trail of technology.
Data is collected and analyzed in bulk daily that is being received from the patients. With the adoption of new technology, one cannot neglect the importance and necessity of security measures that need to be practiced under HIPPA Compliance.
How to Implement AI under HIPAA Compliance
- Access to stored data: HIPAA Compliance law requires giving access to Protected Health Information to personnel that needs it as part of their job function.
- Data encryption: Data passes through servers after being received. If data is to be sent eternally, it must be encrypted.
- Deidentifying data: Any data when conducting research, can never be tied to any individual. It should be adequately de-identified.
- Updated policies and procedures: with the implementation of new policies or technologies, internal policies should always b revised.
- Business associate agreement (BAA): Before using any new technology, an organization should have a signed BAA.
Several platforms on the market use machine learning to assist help care providers to effectively categorize, store, and protect all the information. Many AI tools are present now that make HIPAA compliance easier than ever.
What Exactly Is The Problem, Then?
AI-driven systems own the significant potential of committing accidental HIPAA compliance violations. As AI in healthcare is growing more complex and decision making is getting opaquer, it will be difficult to segregate every little detail that whether it falls under the HIPAA compliance umbrella or not.
The Obvious Solution
The AI in healthcare must be designed and implemented in a manner that will enable humans to examine them conveniently to look back to their decision-making process. This, however, also comes with its challenges. The decisions made by AI are done without much explanation and making it understandable is exactly what we need in the healthcare space.
Outcomes and analysis determine the progress of a patient’s care. This process is guarded by morality and it cannot be practiced if physicians have no earthly idea of how their tools work.
Undoubtedly, artificial intelligence and machine learning are transforming technologies in the healthcare space. Nonetheless, at the same hour, we need to be well prepared and aware of the potential dangers and errors they possess. For the reason that getting things right and orderly in healthcare is a matter of life and death.