Healthcare, like Banking and Financial Services has been one of the earliest adopters of Automation and Technology. Through the decades, advancements in antibiotics, radiology and anesthesia have been complemented by the use of softwares such as ERP, CRM and Hospital Management Systems (HMS).

Being a tech-savvy sector, it was an expected outcome that Healthcare would take to Artificial Intelligence in a big way. AI, which is bringing far-reaching business impact in one industry vertical after another, is changing the way Healthcare sector manages patient-care and business operations. AI harnesses new-age wireless communication protocols such as Bluetooth, RFID, ZigBee, technologies such as Mobility, Internet of Things (IoT), Big Data & Analytics, and Cloud computing, to capture, interpret and present data better.

This has brought technology companies like IBM, Microsoft, Google, Intel and hundreds of startups all around the world, into interesting AI initiatives that is transforming the Healthcare sector. Organizations like the WHO are advocating the creation of local data dictionaries, for this sector. This has forced governments of countries as well as Healthcare institutions to work on an ‘AI strategy’. With new strains of virus and bacteria, as well as new ailments being diagnosed all the time, AI offers hope in all the 3 areas of patient-care: Prevention, Intervention and Rehabilitation.

AI is not without its own share of challenges. That is why; an AI strategy is inevitable for Healthcare Institutions. An AI strategy will help these institutions leverage the benefits of AI and also create mechanisms to cope with its challenges.

Use-cases and Benefits of AI

Low hanging fruits for AI adoption would include:

  • Electronic Health Records: After Speech to Text, Text to Speech and Optical Character Recognition, AI is what can simplify Clinical Documentation, and quicker interpretations.
  • Medical Imaging Diagnostics: Applying AI techniques to diagnostic images can help detect minute anomalies and eliminate the chances of human error or inability in doing so.
  • Virtual Health Assistance: Intelligent Virtual Assistants (IVA) and Medical Virtual Assistants (MVA) are desktop or mobile applications (softwares) that can interact with patients to suggest or remind medical advice.
  • Robotic Interventions: Minimally Invasive Surgery was hailed as a breakthrough procedure for several conditions. In the coming years, robotic tools and devices will assist surgeons in procedures to either overcome tremor and fatigue issues or to access hard-to-reach areas of the body and perform an intervention.
  • Proactive patient-care: Analysis of heaps of patient data can help predict patients who are more likely to suffer from falls, fractures, tumors, alopecia, diabetes, eye disorders and several ailments.

Challenges in adopting AI

  • Risk of wrong analysis: There is a slim chance that the AI algorithms created can turn out a wrong prediction. So is there a backup plan, and who takes liability for damage claims?
  • Mindsets and comfort level: Some doctors and lab technicians may see AI as competition and develop hostility. Similarly, some patients may insist on human involvement.
  • Training required: Like any technology paradigm, all medical staff and the patient to some extent must be trained on the new approach.
  • Data Security: In a situation where there are no governmental regulations on protecting and flushing data, Healthcare institutions could sit on mounds of data and become vulnerable to hacking or malware attacks.

Conclusion

In the coming years, adopting AI will become inevitable for Healthcare institutions, in order to achieve competitive advantage and sustain operations. A clear AI strategy, drafted with careful consideration and advice from experts, will put a context to AI, and help manage both its benefits and drawbacks, better.