Artificial intelligence (AI) in healthcare is defined as the use of algorithms and software to approximate human cognition in the analysis of complex medical data. Precisely, AI is the capability for computer reducing algorithms to approximate conclusions without direct human input to support increased healthcare facility and healthcare professional productivity and profitability, along with the potential for significantly lowering patient costs and improving the quality of patient care and outcomes.

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AI in healthcare represents an assembly of multiple smart digital solutions enabling equipment to sense, comprehend, act and learn so they can augment human activity and help complete administrative and clinical healthcare activities. Nowadays, it is a reality that AI cognitive technologies can successfully emulate and supplement the power of the human brain and provide real and advanced life-saving and quality-of-life solutions.

“AI offers the opportunity to free physicians and other clinicians from tedious work analyzing data, giving them time to apply their knowledge in a more focused, informed way. We think AI allows clinicians to work at the highest level of their ability by making them far more informed and effective patient advocates.”
Lisa Suennen, Managing Director at GE Ventures

The primary AI Healthcare goal is to analyze relationships between prevention or treatment techniques and patient outcomes with massive amount of data. AI solutions, in recent years, have been developed to support smart practices including, diagnosis processes, treatment protocol development, drug development, personalized medication, and patient monitoring and care.

Medical and technological innovation activities occurring since the 1960s that have enabled the progress of AI Healthcare solutions include:

  • Faster data collection and data processing.
  • Genomic sequencing databases.
  • Increased volume and availability of health-related data from personal and healthcare-related devices.
  • Natural language processing and computer vision, enabling machines to replicate human perceptual processes.
  • Robot-assisted surgery precision.
  • Widespread implementation of electronic health record systems.

AI-Healthcare research reports:

Frost & Sullivan’s AI research in healthcare reveals that the AI healthcare market is projected to exhibit an explosive growth, from $600 million in 2014 to an estimated $6.6 billion in 2021 with a CAGR of 40%.
According to a 2017 PwC Survey, a majority of consumers are willing to consider non-traditional options for managing their healthcare and substitute the care of human clinicians with the use of AI technologies.

AI and Preventable Healthcare Professional Mistakes

At a minimum, healthcare should not harm patients, particularly through medical errors. However, human mistakes by healthcare professionals is a continual challenge for successful patient care and a well-recognized key performance indicator (KPI) of medical and healthcare facilities. Market research reports that hospitals experience a level of fatalities, resulting from preventable errors, comparable with heart disease and cancer.

Over the years, many research studies have struggled to quantify direct and indirect costs of measurable medical human errors. The most recent research, from National Center for Biotechnology Information, in 2008, reported measurable human error cost in the US at about US$17.1 billion, with 2,500 additional deaths and over 10 million excess days missed from work due to short-term disability.

Many fatal errors are associated with healthcare technology design flaws as found in system algorithms and calculations and interpretation and use of the healthcare systems by healthcare professionals supporting patient care and research activities.

AI is technically positioned to significantly reduce the current level of human error and improve healthcare services. Many of these errors can be prevented by applying current artificial intelligence techniques on existing medical data in order to predict high-risk error situations. Since most of the conditions leading to human-induced errors are known and well-studied, predicting and preventing them is more attainable in the design and deployment of AI-based solutions.

Healthcare AI Value-Add Solutions 

Improving healthcare requires total alignment of patient data with appropriate and timely decisions, and predictive analytics that can support clinical decision-making and actions as well as prioritize physician and healthcare facility administrative tasks.

AI healthcare solutions that are changing patient treatment, directly and indirectly, are as follows:

Patient Medical Records

AI solutions collect, store, re-format, and trace, and analyze vast amounts of data to provide faster, more consistent patient and healthcare research and related decisions.

Patient Care Treatment Plans

AI solutions analyze meaning and context of patient’s structured and unstructured data in clinical notes and reports combined with clinical expertise, and external research to identify potential patient treatment pathways and plans.

Healthcare Professional Productivity

AI solutions analyze lab tests and other mundane patient care, and clinical tasks that can be accomplished faster, more accurately, and consistent to appropriate standards. AI effectively and efficiently covers a broad variety of body diseases and imaging modalities, including, X-rays, CT scans, etc.

Medical Research

AI solutions detect abnormalities in X-rays and MRIs, genomics to perform complex processing and, in precision medicine to aid in creating highly customized treatments for individual patients.

Patient Digital Consultations

AI solutions, via mobile, provide patient feedback on healthcare data elements captured on their cell phone or wearable devices for medication adherence or a motivational voice that encourages fitness activities and healthy wellness habits.

Healthcare Bots

AI Healthcare bots interact through a chat window on websites or via telephone to help patients with healthcare care requests. Bots offer 24/7 assistance for scheduling, billing and other clinical requests.

Drug Discovery

AI solutions speed up drug discovery, cut R&D costs, decrease failure rates in drug trials and  create better medicines.

Robotic Surgery

AI solutions helps licensed surgeons, perform fine precision surgeries and in tight spaces and with less tremors than would be possible by the human hand alone.

End-of-Life Care 

AI solutions support healthcare facilities improve palliative health care delivery for cancer patients and patients with terminal illnesses.

Personal Healthcare Management 

Patients are proactively getting involved in managing their own personal health. AI-supported Wearables and connected digital devices are assisting individuals make healthy lifestyle choices addressing conditions such as asthma, COPD, heart arrhythmia, pain management etc.

Gartner reported in 2017 AI Research:

“What makes the best AI projects stand out is that they allow for solutions that previously would have been impossible to conceive, because they include what seems like human insights but at a volume humans could never achieve.”

AI and 3rd Platform Technologies Model

3rd Platform Technologies is a term created by International Data Corporation (IDC) as a computing platform model that supports organizations in there quest to accelerate successful digital transformation. The model supports the inter-dependencies among mobile computing, social media, cloud computing, and information / analytics (big data), AI, and Internet of Things (ioT).

IDC – FutureScape: Worldwide IT Industry 2018 Predictions reports:

“IDC described the next generation of the 3rd platform as unleashing multiplied innovation through platforms, open innovation ecosystems, massive data sharing and modernization, hyper-agile application.”

The Way Forward 

The demand for continual precision medicine and healthcare cost reduction are the key drivers for AI in the healthcare industry. AI is positioned to transform all areas of healthcare,  from hospital processes and activities to diagnosing patient health conditions and thereby providing significant automation enrichment, improving productivity, and increasing diagnostic accuracy and positive outcomes. 

As AI becomes more widely adopted in healthcare services, physicians and healthcare professionals will see a substantially non-critical work load lifted off their shoulders, burnout rates reduced, and a significantly improvement in personal productivity. 

Market research suggests that AI agents will be deployed as integrated assistants suggesting diagnoses; tailoring order sets to a patient’s unique conditions and associated circumstances; projecting potential risks and interventions; and taking-over laborious patient monitoring and data interpretation tasks.

Instead of having to view and act on every bit of data and anticipate potential actions and reactions, they will be able to focus solely on those issues and opportunities that require their direct attention and spend the rest of their time dedicating themselves to increasing patient face time.

“By 2019, 40% OF Digital Transformation Initiatives and 100% of IoT initiatives will be supported by AI capabilities.”
IDC FutureScape