While the healthcare

sector varies widely in

the structure and

processes for care

delivery across geographies, healthcare providers globally

face similar business challenges. These include spiralling

costs, regulatory compliance and low technology adoption

leading to a poor patient and hospital experience. There are

also issues related to inefcient processes, poor care

execution, expensive treatments and staff productivity. Added

to this, a labour-intensive workplace and expensive

workforce necessitates improved work coordination for an

already stretched staff. This is further fuelled by an increasing

out-of-the-pocket expense for the patients. A recent

NASSCOM report “HealthTech in India” pegs India’s Out of

Pocket expenses for healthcare at a whopping 62.4%.

However, AI requirements and priorities of developed

economies like the US & UK and developing economies like

India are different. While the West looks at AI robots and

diagnosis, majority of the hospitals in developing countries

like India look for ease of access, awareness and

affordability. Developing nations have to leverage existing

foundational technologies like EHR, HIS and others to drive

AI adoption. While interpretive and futuristic initiatives are

underway, the current entry point for AI in Healthcare could

be via transforming non-interpretive areas of operations and

patient

experience.

These include

automating

routine, time-

consuming

administrative tasks

and provider operations.

C-suite executives across the board in the healthcare sector

are struggling with these issues that are quickly turning

business-critical. They are working on initiatives to drive

convenience, quality, personalization and lower costs, and

deliver a superior patient experience. Technology is being

considered as a crucial enabler to drive these initiatives. And

AI, now poised to deliver the biggest technological disruption

in healthcare, is setting a vigorous pace.

2018 has been an inection points for AI in healthcare. On

one hand, radiology took a giant stride with US FDA

approving an AI-based algorithm to detect wrist fractures.

FDA also approved marketing of the rst AI-based device to

detect diabetic retinopathy that does not require a clinician’s

intervention. On the other hand, futuristic robotic-assisted

surgeries are now moving from a support to a frontal and

mainstream role. In step with these global trends, Microsoft

India and Apollo Hospitals joined hands to develop an AI-

powered heart risk score to drive preventive cardiac care in

India. Bengaluru-based Manipal Hospitals is using IBM

Watson to support physicians in discovering personalized

cancer care strategies.

In less than half a decade, Articial Intelligence (AI) in

healthcare has moved from the realm of conceptual

boardroom discussions to exponential market growth.

Currently valued at USD 2.1 billion market by

MarketsandMarkets, it is slated to grow

to USD 36.1 billion by 2025 at a

CAGR of 50.2%. In this period,

software is expected to hold the

largest market, while Machine

Learning (ML) is expected to

show the maximum CAGR.

Coupled with this, easy information availability, rising

urbanization & disposable incomes, and privatization is

propelling patients’ demands for convenience, affordability

and accessibility of care.

Mohanakrishnan

Head, CoE – Data Science & Articial Intelligence

Emerging

5Non-Interpretive and

Non-Clinical Areas of AI

Transformation in Healthcare

to Drive Patient Experience.

mkrishnan@nasscom.in | Twitter @mkrishnanp | linkedin.com/in/mohanakrishnanp

$ 2.1 billion

$ 36.1 billion

20252019

50.

2% C

AGR

Environment: Healthcare providers are exploring

delivering superior in-patient

experiences by providing a restful

and quiet environment. Hospitals

are toying with noiseless device

alarms, minimizing ambient noises,

delivering soundscapes and digital

picture walls with personalized

music and movie playlists. These are

expected to reduce patient stress

and promote quicker healing,

reducing hospitalization time.

AI solutions are helping provide information to patients, simplify stafng models, improve operational workows, manage

nance, improve care quality, and handle unplanned events better. In India alone, NASSCOM estimates that 54% of all AI start-

ups have a healthcare component to their solutions. Well planned AI deployments can help healthcare providers focus on care

delivery and become patient centric, enabling better business outcomes. Five key AI areas showing rapid market growth and

transforming provider experience include:

There are multiple opportunities

for AI in the healthcare value

chain, including screening

patients at risk of condition or

disease, better and faster clinical

trials, better disease

management, clinical decision

making through Internet of

Medical Things etc. The AI

juggernaut is moving inexorably

to challenge and change the face

of healthcare for both patients

and providers. Hospitals and

healthcare providers have no

option but to embrace this

change or be left behind. The

question is no longer about

whether AI will make a difference

in the healthcare sector, but more

about where, when and how.

Patient Communication: Bots are pushing boundaries of

communication between patients and

providers. Providers are deploying NLP-

based AI chatbots to answer patient

queries, schedule appointments and even

provide directions within their premises.

French hospitals have demonstrated better

engagement with patients, driven down

costs and freed up staff using AI-driven

bots. Bots are managing hospital

discharges more efciently and reducing

unnecessary lengthening of hospital stays.

Combined with RPA tools they can initiate

and coordinate concurrent activities

including instruction adherence, discharge

summary, prescriptions, transportation,

referrals for support services, and

appointment scheduling for specialists.

Nursing: Automating routine tasks like medication

management are already a market reality.

Onscreen computer-generated virtual

nurses like Sensely are supporting patients

with information, medication and social

support. This could result in increased

home-based care and a drastic reduction

in the number of hospital visits. Providers

are now exploring large scale integration

b<ms, Communications, Workows and

Monitoring Stafng to transform nursing

as a function.

Wearables: This is another area where AI is

making a big splash in delivering

patient centricity. They are

increasingly used to improve care

and monitor health vitals – both

within and outside hospitals.

Brigham and Women’s Hospital’s

initial trial on wearables showed

better monitoring of patients at

home using wearables resulting in

better care. There are wearables

undergoing clinical trials, including

those to detect fever & seizures and

monitor bedridden patients.

Wearables will support nurses in

making complex decisions and

prioritizing care… an area that

cannot be handled by AI.

Supply Chain: AI in supply chain is already seeing

a huge potential. IBM, UPMC and

Pensiamo have tied up in 2016 to

drive AI into healthcare supply

chain transformation. AI will

optimize all areas of supply chain

and streamline inventories. AI will

decrease search time of supplies

and automate orders and delivery.

Combined with RPA, AI can quickly

handle areas from routine queries

on supplies and inventory. It can

minimize inventory and decrease

the search time for locating

supplies. AI can also play a role in

maintaining equipment and

coordinating maintenance schedule

and lower equipment down times.