Industry
Healthcare
Patient-centered Care: Health and Wellness Redefined
Highlights
- Healthcare and medical devices sectors have a lot to gain through artificial intelligence (AI) systems, which translates to enormous potential for significantly improving patients’ lives.
- AI can help industry players successfully deliver healthcare objectives such as improved accessibility, affordability, patient experience, and provider productivity while minimizing employee burnout and ensuring health equity for society at large.
- Organizations need to create an AI-first approach to integrate AI in healthcare based on these objectives, ensuring that true value is achieved.
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New opportunities to improve healthcare
The launch of ChatGPT has not only put GenAI in the spotlight but also sharpened the focus on traditional AI.
According to the TCS AI for Business Study, most senior executives in the healthcare industry believe AI’s impact (including established AI and GenAI) on their business model will be greater or equal to earlier disruptive technologies. And more than half (56%) of healthcare respondents are optimistic or excited about its potential impact on their business.
Artificial Intelligence (AI) in health and wellness is becoming ubiquitous as smartwatches and mHealth apps are being widely used. Some of these are getting FDA approvals for software as a medical device (SAMD). mHealth apps are becoming digital companions offering personalized guidance, transforming clinical pathways with (1) on-premise, in-person, (2) virtual, and (3) digital access to care.
Many of these devices use AI-ML algorithms to triangulate data from built-in or attached sensors.
There has been a steady supply of digital health technologies (DHTs) leading to the digitalization of healthcare and an uptick in their usage. Recently, the consumerization of healthcare has received a big push, especially during the pandemic when virtual care became the norm. As a result, comparison shopping and better control of health and wellness options are now a reality.
The potential of DHTs and composite AI
AI has been an integral part of DHTs, and this momentum will continue with generative AI.
Composite AI (traditional AI + generative AI) presents an excellent opportunity to channel tacit knowledge from across the enterprise, unlocking tremendous value and fueling innovation. This is especially true for a knowledge-intensive industry like healthcare, where knowledge is applied and retrieved on a daily basis.
86% of top financially performing pacesetter healthcare executives say they are primarily focused on using AI for innovation
Unstructured data like clinical notes and multi-modal imaging are inherent aspects of health records. AI’s cognitive and natural language processing (NLP) capability to recognize patterns and understand nuances of case history to drive deeper insights and new interventions is especially relevant to healthcare.
DHTs enabled with composite AI can be a force multiplier for augmenting healthcare teams, transforming the patient experience, and reducing costs by improving operational efficiencies and streamlining workflows.
How an AI-first architecture impacts healthcare
AI in healthcare has tremendous opportunities to make healthcare more accessible.
An AI-led business architecture (see Figure 1) can deliver on five key objectives of healthcare: increasing accessibility, improving affordability, enhancing patient experience, augmenting provider productivity and minimizing burnout, and ensuring health equity. These objectives guide the TCS approach to integrating AI in healthcare, ensuring we deliver the true potential of AI innovation.
Increasing accessibility
AI aids in delivering seamless care across settings by enabling remote patient monitoring and telehealth services, ensuring that care is not interrupted, regardless of location. Patients are empowered to participate in their health journey through AI-powered apps and devices. AI-enabled digitalization and the digital-first approach have also led to healthcare consumerization. Members shop online for their healthcare needs at their point of location and expect more personalized healthcare services. AI-predicted and -driven personalization of care pathways further enhances convenience and experience as individuals seek care from the comfort of their homes.
Improving affordability
The healthcare industry has its unique challenges, such as medical inflation, a shortage of medical staff, higher expectations from patients as they shop to compare prices of healthcare services or drugs, infrastructure challenges due to technical debt by way of legacy systems, and profit margins.
Given these inflationary and margin pressures, cost take-out is a pressing concern for healthcare companies. Some processes are still dependent on archaic technology, like fax machines, a technology dating back to the 1940s. It is still used to transmit scanned images over phone lines and is an important channel of document intake across healthcare entities.
AI offers opportunities to streamline fax, mail, and email inputs to process myriad correspondence layouts, hand-written forms, multiplicity of file formats, as well as various types of data formats (date, phone, zip code) and missing information, all with a high degree of confidence and minimal manual intervention. Information can be extracted as structured data, classified, split, and processed as per requirements, reducing handling time and costs.
Contact center transformation is another lever to bring down operational costs. Calls can be diverted to digital channels for better cost efficiency and the use of call center teams. Call containment is possible through better member self-service options with GenAI chatbots and virtual assistants. Using AI’s NLP capabilities, better root-cause analysis of calls can be performed to address systemic issues and proactively eliminate calls.
Alternate sites of care, including home health and hospital at home, promise to reduce healthcare costs by avoiding overheads involved in hospital stays while empowering patients to seek care from the place they feel most comfortable. As a result, home is becoming the new frontier in the health transformation journey.
Connected hybrid care promises to make cost-effective and convenient care available. Such cost take-outs across the healthcare spectrum have the potential to bring down healthcare costs and premiums and ultimately make healthcare more affordable for the society as a whole.
Enhancing patient experience
Patient experience is at the heart of any healthcare system. AI is transforming healthcare into a preventive, affordable, and participatory experience. Better engagement, better education of patients, personalized and affordable services, higher convenience, and thus enhanced patient experience are the top goals of most healthcare organizations today.
GenAI chatbots and virtual assistants can be great natural language, conversational, or multi-lingual tools to help members evaluate their plan options, seek appointments, get clarity on their plan benefits, understand their out-of-pocket expenses, evaluate low-cost alternatives, better control their health conditions, get needed support to adhere to treatment regimens and drug therapies, seek answers to medical questions, remain physically active and pursue their wellness journey.
On the other hand, by utilizing predictive algorithms, AI can detect diseases early and offer personalized treatment plans based on individual data, thereby elevating patient experience where it matters.
According to TCS’ AI for Business study, healthcare companies say chatbots for sales and product support remain essential, but they are also moving beyond commonplace chatbots for even more hyper-personalized customer interactions and augmenting them with other AI-driven approaches to accomplish these goals.
- 43% want to use AI for more personalized interactions for post-sales support
- 39% want to use AI for more personalized interactions with their marketing initiatives
- 31% want to embed AI for more personalized interactions within the products or services themselves
Augmenting provider productivity and minimizing workforce burnout
While knowledge augmentation is a repeating pattern in healthcare, the shortage of specific healthcare workforce makes its application more pertinent to certain roles than others. The healthcare staff performs activities like patient triaging, data entry of patient records, reviewing prior authorization, claims, grievances, appeals, and fetching relevant knowledge articles based on the context. AI augmentation will help automate these activities and enable the staff to predict outcomes based on historical information without them having to look through multiple systems or screens for decision-making, reducing the processing time and effort involved. This approach can drive clinical decisions faster as healthcare workers won’t need to refer to lengthy documentation such as clinical policies, guidelines, SOPs, and standards of care, each of which runs into several pages. AI can retrieve relevant sections with citations in an explainable way for a given patient's case or context.
The augmentation can be in real time, for example, based on the transcript of a live call, where AI agents can supportively nudge a human agent to request more information to resolve the problem.
For certain roles, this can also be a mixed-reality-enabled heads-up or hands-free experience that drives higher productivity gains and enables a futuristic way of working for employees. All this combined can improve overall efficiency while greatly reducing healthcare workforce burnout.
Figure 1: AI-enabled knowledge augmentation
Figure 1: AI-enabled knowledge augmentation
Productivity is a given when we talk about AI. Nearly half of the healthcare organizations in the AI for Business Study focus on productivity.
- 46% of healthcare organizations that took part in the AI for Business Study were solely or mostly focused on using AI just to enhance productivity.
- However, 22% prioritized productivity along with quality improvement.
- And another 25% focused more on quality but intended to improve productivity.
These findings demonstrate the need for a balanced approach to integrating AI and its benefits – through optimization, productivity, innovation, and quality. The more balanced the approach, the better the outcomes and overall boost to organizational excellence.
Ensuring health equity
AI presents opportunities to make healthcare more accessible and manageable for members navigating complex health systems. For example, a user doesn’t need to know the type and specialty of the provider to book an appointment, but natural language and conversational virtual assistants allow for booking based on simple language and description of symptoms. Even language barriers can be overcome with the multi-lingual capabilities of AI.
AI chatbots can also be sensitized to understand the social determinants of health (SDOH) and mobilize community support just like an empathetic contact center agent would. This sensitization of AI-enabled systems will help achieve health equity wherein everyone can reach their full health potential. A combinatorial approach by using traditional BI analytics to measure health equity measures coupled with AI-driven targeted interventions can also help address causal factors relating to inequities. This holistic approach to responsible AI, in addition to enforcing ethics, and avoiding bias and toxicity will foster better public health.
The road ahead
AI is not a plug-and-play technology with a one-size-fits-all strategy, and the findings from healthcare executives reflect their varied approaches to AI.
Over a quarter of the respondents in our study favor establishing an enterprise-wide AI strategy – but nearly as many are willing to wait and see how other healthcare companies use AI and follow their lead.
We see the adoption of AI and GenAI evolving in three stages:
- Assist with human-first approach; composite AI plays an assistive role to humans
- Augment, where GenAI agents augment human capability by performing specific tasks and then handing off the baton to humans in a well-orchestrated, seamless transition leading to deeper productivity gains
- Transform, where in an increasingly AI-first ecosystem, patient experience is personalized at scale to influence healthy behaviors, help members better manage their health conditions, or transform the way work gets done
Composite AI holds the key to driving better returns on health (ROH) outcomes through:
- Patient education, influencing healthy behaviors, helping patients better self-manage chronic conditions, and assisted living for senior citizens with the support of omnipresent chatbots or virtual assistants and sensors.
- Improve healthcare quality, reduce clinician burnout, and reduce turnaround time through knowledge augmentation.
- Lower healthcare costs by reducing systemic inefficiencies and ushering in higher automation, making care more affordable.
- Reduce health inequities and make care more accessible due to natural language, conversational interactions, and more virtualization of care and expanded access.
Striking a delicate balance between personalizing and digitalizing using AI is critical. While the personal touch is going to be an essential humane aspect of healthcare, personalizing too much will lead to higher costs and not necessarily a desirable member experience, as the wait time and turnaround time could increase, affecting access. Getting it just right will be a game-changer.
