6 Areas Where Digital Health, AI are Transforming Healthcare

Nancy Mitchell, RN, is a contributing writer for symplr and AssistedLivingCenter.com. She has over 37 years experience in geriatric nursing care, both as a senior care nurse and director of nursing care.

When most people think about artificial intelligence (AI)-driven digital transformations in healthcare, they imagine robots replacing everyone and everything—from doctors, nurses, and devices, to traditional hospitals and healthcare centers. Turns out it’s not quite so.

Technology, and AI in particular, is proliferating in medicine. But it doesn’t sweep away the need for human connection in patient-provider relationships; it only enhances it. While some fear AI, others see advantages of the latest developments in this space and make the best use of them.

AI’s impact on healthcare systems is already visible, and it has further potential to greatly transform processes. AI-enabled medical tools, telemedicine, and assistive robots are only a few examples of digitally driven solutions changing care delivery. Because AI is reshaping standard methods and approaches, healthcare administrators and providers must adapt for a digital future.

AI is becoming a standard in digital health solutions

According to an Optum survey, the pandemic caused 56% of healthcare companies and executives to immediately unfold their AI deployment “roadmap” and expand or accelerate the timelines for it. Some 83% of the survey participants said they already have an AI strategy, and 15% of the surveyed said they’re planning to create one in the near term.

Gartner emphasizes that new demand patterns in healthcare are prompting provider organizations to look for faster, smarter, and optimized digital health business practices that incorporate AI. In nursing, for example, AI is already being used in clinical decision making and to improve care planning and delivery.

AI adoption drives revenue, reduces costs at the functional level, and makes healthcare more efficient. McKinsey & Company outlines six main areas of impact for AI in healthcare:

  •     Chronic care management
  •     Self-care/prevention/wellness
  •     Triage and diagnostics
  •     Clinical decision support
  •     Care delivery
  •     Diagnostics

AI-driven changes underway

We focus on the following six areas in which AI is changing healthcare for the better.

1. Digital and physical safety of patients and systems

Increased AI use in digital health first and foremost concerns data privacy. Patients’ personal data, hospital financial records, and other proprietary and confidential information is a frequent target of cybercriminals. AI-powered programs help bolster cybersecurity efforts in particular by helping detect fraud and predict cybercrime. 

Robot-assisted surgery is improving safety and the ushering in the possibility of error-free surgeries. For example, an experiment showed the potential for implementing a neural network in robot-human handover tasks. 

Robotic collaborators are changing long-standing care procedures and processes, but it isn’t about stealing humans’ jobs. Rather, it’s rather about complementing and adding value to the tasks people perform. AI is also used to minimize the risk of harm associated with other healthcare processes. By reducing health risks of patients, AI creates the potential for improvements in quality of care and patient safety outcomes.

2. Healthcare management

According to KPMG, 82% of healthcare and life science executives would like their organizations to more aggressively adopt AI-driven technologies. And it’s no wonder, as computer-assisted solutions are among the healthcare compliance tools that help organizations navigate all possible challenges. In general, AI-based software and applications transform the way organizations approach healthcare management. Specifically, they are beneficial for:

  •     Data management
  •     Workforce management
  •     Healthcare governance
  •     Workflow coordination
  •     Risk management
  •     Financial control, etc.

Through predictive analysis, which becomes possible with AI, health systems can optimize processes and expenses, handle shortages, and better predict and control costs. And robotics are a productivity booster in revenue cycle management.

AI’s potential to cut costs is also attention worthy. It saves healthcare systems and services around $269.4 billion yearly, while administrative savings account for $18 billion out of that number. By improving workplace technology and automating certain workflows with AI-based decisions, healthcare leaders can increase workforce morale, on top of that.

3. Predictive patient care

The global health crisis brought about by COVID-19 placed the predictive capabilities of AI front and center. For example, AI used questionnaires and voice cues to preliminarily diagnose the disease. 

In the future, nurses, physicians, and other healthcare providers will see more AI-driven transformations in the ability to:

  •     Detect diseases faster and more efficiently
  •     Forecast the likelihood of disorders
  •     Verify how successful treatment protocols may be
  •     Provide the most effective dosage (by helping to eliminate human errors)
  • Lower total healthcare spend
4. Distant healthcare delivery

The effectiveness of digital nursing technologies is a highly controversial topic. Nevertheless, virtual nursing assistants and other AI-based caregiving services enable productive remote communication capabilities between patients, payers, and healthcare providers. For example, NurseWise, an AI app created by the American Nurses Association, aims to improve telehealth patient care by providing nursing advice and guiding patients in real time.

Virtual nursing assistants, chatbots, and Internet of Things (IoT) interfaces can minimize the number of hospital visits, decrease the workload on medical professionals, and potentially save the healthcare industry $20 billion on a yearly basis.

5. Patient engagement

Increasingly, healthcare providers opt to use telehealth to boost patient satisfaction with their services, and artificial intelligence helps them to do that via socially assistive robots or conversational interfaces, for instance. IoT technologies make it possible to achieve effective patient-doctor communications with the help of virtual visits and remote monitoring.

In addition, some AI applications use natural language processing (NLP) and can improve patient engagement. NLP makes it possible to use human language when interacting with patients, so that the latter feel more comfortable hearing a human voice rather than an artificial one.

How else can AI and deep learning technologies help to engage patients? Here’s a short list of relevant advantages:

  •     They provide endless resources to boost patient health literacy.
  •     They predict patient care needs.
  •     They support holistic patient care.
  •     They drive care coordination.

CommonSpirit Health, for example, is effectively using an AI-powered tool to take patient care to the next level.

6. Healthcare research and analytics

Healthcare interoperability makes it possible to use AI in data processing. As a result, AI and big data analytics are giving rise to “smart healthcare.” In the era of precision (i.e., personalized) medicine, statistically based machine learning models enable even more rapid advances in image analysis. In particular, they enhance accuracy and sensitivity of diagnostic medical imaging.

AI will also guide researchers on how to construct cohorts for clinical trials. It could help simplify and accelerate recruitment for clinical trials by assisting with entry criteria and patient identification—although of course there will be challenges along the way as outlined in one recent article. Multiple clinical trial start-ups (e.g., Unlearn.AI, Owkin, VeriSIM Life, AiCure, and Deep Lens) are already harnessing AI technology for research and analytics.

Ready for the future of digital health with AI transformations?

Artificial intelligence is transforming healthcare and nursing, and we can expect a rapid acceleration in its use going forward. AI creates opportunities for predictive care and higher patient engagement, speeds up healthcare process improvement, and guarantees better results in planning and decision-making, especially for long-term perspectives. It also opens new horizons for clinical research and advanced data analytics.

It’s worthwhile for provider organizations of all types and sizes to develop a plan that will help prepare for AI transformations, actualize health service cost efficiencies, and achieve desired patient outcomes.

When it comes to a digital health transformation strategy, symplr offers a wide range of options: from provider data management and access management, to clinical communications and spend analytics. We enable more automated approaches in healthcare operations and unify aspects in healthcare operations business coordination.

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