Artificial Intelligence (AI) in healthcare is a reality. However, the industry is facing a lot of challenges and the dismal state of the industry globally has been more apparent of late. The World Health Organization (WHO) estimates a shortage of 4.3 million doctors, nurses, and other health professionals worldwide, which doesn’t augur well for the welfare of patients. Reports as recent as April 2019 show that the US is expected to face a shortage of 46,900 to 121,900 physicians by 2032. The UK, on the other hand, is forecasted to experience a deficit of 190,000 clinical posts by 2027, which is roughly twice the size of the British Army. India isn’t immune to the existential crisis either. As per estimates, the country is running short of 600,000 doctors and 2 million nurses.
All these figures forewarn of a world that may be mourning on the quality of care in the future. While one might think that the existing doctors and nurses can fill some gaps, their overworked condition at all levels is clear. A 2018 study has revealed that burned out physicians are more likely to suffer from anxiety and depression, making them predisposed to committing errors and negligence. The revolution in medicine is further expected to increase the workload for medical practitioners and make them dangerously stressed out.
In the wake of today’s crippling physician shortage, several reforms have been set in motion worldwide to handle the situation. This includes easing the physician licensing process, making it easier for international medical graduates to practice, and building reforms that propose improved and affordable access to medical care for all. While these initiatives are praiseworthy, one shouldn’t neglect the role of emerging technologies in bringing the healthcare industry back on rails. Conversational Artificial Intelligence (AI) in healthcare is geared up to redefine the industry’s core bottom lines. Accenture predicts that the US healthcare industry can save $150 billion a year by 2026 if it adopts AI applications. Given so, how global savings would look like is something we leave to the imagination.
The article to follow takes a deeper view into the potential of conversational AI and ways in which it can save the beleaguered healthcare economy. It also covers the aspects adopters must look into while implementing conversational interfaces.
Pivoting to the Clinic of Tomorrow with Conversational AI
Conversational AI has begun to make a rallying case for the stress-ridden healthcare industry. It offers an interactive, intuitive, and patient-centric approach to remediate the sector, which is currently battling a chronic undersupply of health professionals and low-quality care. Apparently, the experience offered by traditional voice recognition systems is static and disconnected. However, with healthcare conversational AI solutions, ‘empathy’ is the operative word. The customer asks questions, healthcare conversational chatbots comprehend it, and direct them to the right answer—all while leveraging their ability to emulate human thought and compassion. Below are the key areas where conversational AI is believed to bring much-needed stability for the healthcare sector.
- Transforming Patient Experience
Today’s healthcare sector has a skewed doctor-patient ratio. Exhausted doctors have to squeeze maximum number of people in their schedules, which undercut the quality of experience. Conversational AI, on the other hand, can significantly raise the bar of service quality by automating the routine processes. The technology can help healthcare providers diagnose symptoms on the go, identify patients requiring attention from the less urgent ones, and schedule appointments accordingly. In addition to this, they can collect basic information at the time of patient check-ins, eliminating the chances of human errors.
By leveraging cognitive behavioral therapy, conversational AI can play a vital role in scaling down the number of unnecessary doctor visits and helping patients save a lot of time and money. AI applications for healthcare can help patients feed the details of their conditions and in return, get an accurate analysis of what they are suffering from—all without any frustration or delay.
Conversational AI can remind patients of the medications they need to take and ensure that they follow the doctor’s instructions. It can also double up as a healthcare assistant to answer queries related to drugs and diet. They can also provide personalized answers based on the patients’ medical history to further facilitate the end-user experience.
- Revolutionizing Care and Reducing Physicians’ Burden
Conversational AI in healthcare works wonders when working with patients in remote locations. When the patient’s health is critical, personalized assessment is urgently needed. In such a case, conversational AI can help. Conversational AI has introduced the concept of Telemedicine chatbots, which can be used by healthcare providers to diagnose, treat patients, and provide clinical services remotely. These chatbots can effectively convey the instructions and procedures to follow by patient’s relatives until help arrives.
NLP-enabled healthcare chatbots can help doctors to retrieve critical information quickly without having to meddle with complex CRM tools. It helps increase the doctors’ effectiveness in administering the medications. Another important aspect of AI chatbots is that they can save every patient’s medical history in the database. This information can help doctors prescribe the right treatment at the right time and foresee problems before they occur.
Some people are allergic to certain types of drugs, which when administered lead to far serious repercussions than the disease itself. But that won’t happen now. The conversational AI chatbots can follow up and track how the patients feel after they are discharged from the hospitals. They can eliminate the need for physical checkups after patients have fully recovered, thus freeing doctors’ time for more patients.
Of all the things, conversational AI can assist the healthcare industry in reducing human-induced errors as it affects the trust people have on the industry.
Things to Remember When Getting Started with Conversational AI Implementation
Implementing conversational AI is no walkover. Make no mistake; it’s a paradoxical technology. While it promises breakthrough benefits, its wrongful implementation can strike many sour notes. So to avoid the sticking wicket, it’s important that leaders must carefully consider the following aspects:
- Integration: Conversational AI is tied to backend systems for funneling dialogues and capturing the contextual information that might help. Given so, enterprises must define an articulated integration model that streamlines data access and powers the contextual capabilities of a virtual assistant.
- Change Management: This emphasizes increased transparency by communicating to customers that might be interacting with a virtual assistant. Further, it involves helping employees adapt swiftly to technological change and encouraging their engagement during the transition phase.
- Security: Security takes precedence over any other matter. When it’s about implementing conversational AI, enterprises must stop and check whether or not they are complying with various data regulations across the world.
Prepare for Conversational AI
Amid the deepening crisis in the healthcare sector, conversational AI has emerged as a new avenue for change. From delivering timely care to easing the workload for medical professionals, the technology has been teasing out a number of possibilities to transform the essence of the industry. But, every rose has its thorn. The road to conversational AI has its own obstacles as most of the healthcare providers refuse to let go of legacy systems and resist to adapt. Lack of accountability and job loss are one of the most pressing AI drawbacks already. But, having said that, we fail to imagine a future where conversational AI will not disrupt healthcare in the coming years. The technology is on its way to raise an army of intelligent bots and assistants that will greatly enhance the delivery of advanced care. So, change isn’t a matter of if, but a matter of when.