conversational AI

The Secret to Happy Patients? 7 Healthcare Challenges Solved with AI

Medical science has improved life quality, yet the demand for AI-fueled systems that help satisfy patients' and medical staff's expectations is growing.

Medical science has transformed healthcare into one of the major success stories of our lifetimes. But while medical science has improved healthcare and life expectancy, there is still an ever-growing demand for healthcare service providers to make available to patients and the medical staff the AI-empowered systems they expect and deserve.

Although medical science has improved healthcare and lifespan, the need to build AI-empowered healthcare systems so much expected by the medical staff and patients is still there. This has resulted in healthcare providers struggling to meet the needs of their medical professionals, patients and their families. Artificial Intelligence (AI) and Machine Learning (ML) solutions offer a real opportunity to transform how healthcare is organized, experienced and delivered. Healthcare providers already use AI for claims processing, cancer diagnosis, reduction of dosage errors, automating image analysis, early diagnosis of fatal blood diseases, and medical records management. Each is an important step in the evolution of affordable, smart healthcare provision.

Conversational AI in Healthcare

Conversational AI (CAI) and conversational business applications (CBA) use technologies like NLP (Natural Language Processing) to enable patients and healthcare staff to accomplish a wide range of healthcare-related tasks. Through a simple conversation with a virtual AI assistant:

  • Patients can schedule appointments with doctors, raise queries regarding their medical appointments or bill payments, and triage their medical symptoms before meeting a healthcare professional.
  • Healthcare professionals can communicate with patients regarding their illness, symptoms, dosage and medical treatments, manage patients’ medical information, or send follow-ups and clinical appointment reminders to patients.

These healthcare tasks can be completed using intelligent multi-modal interfaces such as voice, online chat services or smart webforms and are enabled by applying a conversational layer over any automated back-end system to consolidate existing applications and offer a seamless resolution of any business task. A conversational AI assistant will help reduce the medical staff's workload while conversing with patients to provide the best experience with the health service provider.


Solving Healthcare Challenges with the Help of AI

Service Efficiency and Cost Control

With 30% of healthcare costs associated with routine, repetitive and largely administrative tasks, there is a tremendous opportunity for healthcare organizations to save money on back-office admin and reinvest that money into improving patient care. Smart healthcare providers use AI to capture and process information and build automated solutions around the data.

For example, AI can be used to automate tasks such as pre-authorizing insurance, optimizing scheduling or bed management, chasing unpaid medical bills, maintaining records, improving fraud detection, improving billing efficiency, faster onboarding of patients, improving claims handling, migrating and maintaining patient data between and across medical applications and health care providers, and lots more.

The more AI is used to automate, the more it will ease the workload of healthcare professionals and promote better medical care as freed administrative time can be reinvested in patient care. Ultimately this will save healthcare companies money as well.

Reduce Healthcare Staff Burnout

Healthcare organizations can use AI solutions to automate problem-solving by doctors, nurses and other medical professionals. This can help improve the experience of healthcare practitioners, enabling them to spend more time in direct patient care and reducing the likelihood of healthcare burnout.

For example, AI can perform mundane and relatively routine imaging tasks, such as reading and categorizing radiology, pathology, and ophthalmology images. This can reduce staff burnout and staff attrition and may result in more people being attracted to the healthcare profession at precisely the time when the World Health Organisation predicts there to be a global shortage of healthcare staff of some 9.9 million physicians, nurses and midwives globally by 2030.


Healthcare Facility Management

Medical facilities need to be available 24/7. And whilst there are already examples of AI being used to optimize bed management and surgery scheduling, there are many other facilities management use cases available. For example, AI can now be programmed to help determine if patients have an elevated temperature, provide real-time computer vision for social distancing surveillance, assist with contactless patient monitoring, provide patient fall detection alerts and use thermal detection to aid infection control. To such an extent that now, intelligent systems can limit the spread of infectious diseases and deliver insights such as operating room analytics and workflow automation, which can help keep facilities open longer and improve the flow of patients in and out of healthcare facilities.

If patients can access better, faster and readily available healthcare, then AI-infused systems can potentially improve the overall health of the wider population.

Optimize Patient Pathways

AI can increase productivity and the efficiency of care delivery. This enables healthcare systems to provide more effective and efficient care to a wider number of people at a more affordable cost per patient.

For example, Flagler Hospital in St. Augustine, Florida, USA, used AI to optimize care pathways for pneumonia. As a result, the hospital was able to save $1,350 per pneumonia patient and reduce the length of stay by two days. Moreover, the collaboration between the University of California, Stanford University and the University of Chicago generated an AI system that predicts the outcomes of hospital visits. This acts to prevent readmissions and shorten the amount of time patients are kept in hospitals.

Foster Preventative Medicine, Self-Care and Wellness

Managing patients is expensive and requires systems to shift from an episodic care-based philosophy to one that is much more proactive and focused on long-term care management. AI can be used to foster preventative medicine. For example, wearable healthcare technology that uses AI is nowadays used to monitor patients. Smartwatches use AI to analyze data to proactively alert users and their healthcare professionals on potential health issues and risks. The sooner healthcare professionals detect and intervene, the higher the likelihood that patients will benefit from better, faster medical care. In addition, being able to assess one’s own health using technology eases the workload of healthcare professionals and prevents unnecessary hospital visits or remissions.

Improved Clinical Decision Making

AI applications enhance and improve healthcare delivery by driving improvements in clinical decision-making. Even the most experienced doctor will not have seen all types of cancer or heart MRIs (magnetic resonance imaging). Machine learning algorithms can pool the data from hundreds of thousands of rare cancer or heart MRIs and act as a second observer and support clinicians in the detection and diagnosis of cancer or heart defects. For example, AI used by cloud providers now takes data from users’ electronic health records through machine learning – creating insights for healthcare providers to make better clinical decisions.

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There's No Reason to Fear AI

AI is impacting the work of many people in the healthcare industry, enhancing the quality of the services provided and not replacing healthcare providers. AI made fame from recognizing patterns, which is great when one has to sift through massive amounts of data to find the cause of a disease, saving valuable time. "On the other hand, humans are great at wisdom, common sense, empathy, and creativity, all of which are vitally important when you think about the care process.

To adapt to future trends and the integration of AI into the healthcare system, clinicians need to become aware of the power of this new technology and understand that the world is changing. Today, not only do we need to attract, train and retain more healthcare professionals, but we also need to ensure their time is used where it adds the most value - caring for patients. Yet our modern healthcare system faces huge challenges exacerbated by the pandemic, a rise in lifestyle-related diseases, and an exploding world population. The good news is that by using AI, healthcare providers can deliver better patient outcomes and make care delivery more efficient, personalized and productive.

To Conclude

While we are still in the very early days of understanding AI and its full capabilities in healthcare, AI has already demonstrated the potential to provide data-driven clinical decision support to patients, physicians and hospital staff. And by allowing healthcare professionals to spend more time with patients, AI can lead to higher morale, reduced staff turnover and better patient care.

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