The BIG Decision- AI in Healthcare
Blog: NASSCOM Official Blog
The COVID-19 health crisis plagued the world taking it by sudden surprise. We weren’t prepared. The number of individuals hit by the pandemic far outnumbered those who would help treat it- viz health workers and the healthcare systems for the world.
Let’s hypothesize.
What if one had virtual healthcare workers for consultations or to address FAQ’s?
What if AI empowered healthcare sectors to take care of basic health needs of patients while the pandemic-related cases could be left for human nurses or doctors?
Could we have approached the crisis differently?
In 2016, AI healthcare projects attracted more investments than AI projects within any other sector in the global economy.2 There has been a significant rise in data w.r.t the healthcare systems and therefore it is highly likely that AI will increasingly be applied in the field.
Research (based on the NASSCOM report on AI)1 suggests that successful implementation of AI in healthcare will likely first emerge for applications that have reached a certain level of mindless repetition. AI tends to take over the easiest and most repeatable tasks from humans first. The key categories of application may be administrative, treatment recommendations and patient engagement et al. A few areas and touchpoints for AI in healthcare are as follows:
1.Automation– A recent HBR report suggests that AI is being used to monitor COVID-19 symptoms, providing decision support for CT scans, and automating hospital operations. Meanwhile, Zhongnan Hospital in China uses an AI-driven CT scan interpreterthat identifies Covid-19 when radiologists aren’t available.3
2.Real-time monitoring– AI platforms for real time monitoring of something as simple as surgical blood loss for example.
3.Measuring Progress– Prediction and measurement of progress in patients is an essential aspect that AI could target. Precision medicine for example is a means for predicting what treatment protocols may succeed on someone based on their attributes.4
4.Virtual Consultancy– This is particularly applicable in case of the current pandemic. Imagine the hypothetical scenario above and you being consulted from the comfort of your home.
An interesting example is AI startup Buoy’s, virtual agent trying to guess symptom analysis of patients by analysing existing clinical data, identifying the patient’s health issue and formulating the plan for the next steps of care.
Image: Hush Naidoo
However, healthcare is fundamentally different from others. This is mainly due to incomplete awareness of medical conditions, which makes it difficult to create trustworthy algorithms. Some of the key challenges to adopt AI in this sector could be:
1.Trust- Both for the patient and for the doctor. How likely are we to trust the authenticity of AI vis-a-vis an experienced practitioner? Similarly, how likely is an experienced doctor ready to bet his experience for a tech-empowered analysis measure which may go wrong thereby dissolving their reputation.
2. Algorithm Adaptability– Algorithms are outperforming radiologists at spotting malignant tumours, and guiding researchers for costly clinical trials. The question is how far are the algorithms dynamic to factor in the constant changes in the data thus provided?
3. Privacy– Medical records are classified as Sensitive Personal Data or Information under Data Protection Rules of IT Act 2000. The use of smart machines to make or assist in healthcare constantly raises issues of accountability, transparency, permission and privacy.
4. Lack of standardization of data and clear design guidelines.
The Correct Balance
Google is collaborating with health delivery networks to build prediction models from big data to warn clinicians of high-risk conditions, such as sepsis and heart failure.
Yet in many cases clinical reasoning and decision making may not be replaced by AI. AI must then become an enabler and augment human efficiency by finding the right balance. Human skills like empathy or persuasion could must blend with AI empowered data.
One can only be hopeful to be better warriors as future pandemics post the COVID world pose the next challenge.
Read the full report on Uncovering the True Value of AI to understand how AI is impacting key industrial sectors.
References:
- Uncovering the true value of AI – Executive AI playbook for enterprises. (2019, December 27). NASSCOM. https://www.nasscom.in/knowledge-center/publications/uncovering-true-value-ai-executive-ai-playbook-enterprises
- CB Insights Research Healthcare remains the hottest AI category for deals. 2017. https://www.cbinsights.com/research/artificial-intelligence-healthcare-startups-investors/(accessed 15 Jan 2018)
- How hospitals are using AI to battle COVID-19. (2020, April 3). Harvard Business Review. https://hbr.org/2020/04/how-hospitals-are-using-ai-to-battle-covid-19
- The potential for artificial intelligence in healthcare. (n.d.). PubMed Central (PMC). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181/
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