Transforming Healthcare With AI
Artificial intelligence is poised to become a transformational force in the future Of Healthcare, enabling healthcare practitioners to work more quickly, be more accurate, and provide care more cost-effectively. How will AI-driven tools improve the way healthcare is delivered in 2021?
The healthcare industry is ripe for some major changes. From patient triage and risk assessment to preventative care and treating chronic disease, technology—and in particular Artificial Intelligence (AI)–offers endless opportunities to deploy more precise, efficient, and impactful interventions at exactly the right moment in a patient’s care.
AI offers a number of advantages over traditional analytics and clinical decision-making techniques. Algorithms become more precise as they interact with data, giving healthcare workers unprecedented accurate insight into diagnostics, care processes, treatment variability, and patient outcomes. Here are the top 10 ways AI and Healthcare together can change the future:
- Unifying mind and machine through brain-computer interfaces
Using computers to communicate is not a new idea by any means, but creating direct interfaces between technology and the human mind without the need for keyboards, mice, and monitors is a new area of research that has significant applications for some patients.Brain-computer interfaces could drastically improve quality of life for patients with ALS, strokes, or locked-in syndrome, as well as the 500,000 people worldwide who experience spinal cord injuries every year. Brain-computer interfaces (BCIs) backed by artificial intelligence could restore fundamental experiences to those who feared them lost forever. - Developing next-gen radiology tools
Radiological images obtained by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the body, but many diagnostic processes still rely on physical tissue samples obtained through biopsies, which carry risks including the potential for infection. Artificial intelligence will enable the next generation of radiology tools that are accurate and detailed enough to replace the need for tissue samples in some cases, experts predict.Succeeding in this quest may allow clinicians to develop a more accurate understanding of how tumors behave as a whole instead of basing treatment decisions on the properties of a small segment of the malignancy. Using AI, providers may also be able to better identify the aggressive cancers and target treatments more effectively. - Expanding healthcare access in underserved areas
Shortages of trained healthcare providers like ultrasound technicians and radiologists can significantly limit access to life-saving care in developing nations around the world. Artificial intelligence can help mitigate the impacts of this deficit by taking over many of the diagnostic duties typically allocated to humans.For example, AI imaging tools can screen chest x-rays for signs of tuberculosis, often achieving a level of accuracy comparable to humans. This capability could be deployed through an app available to providers in low-resource areas, reducing the need for a trained diagnostic radiologist on site. - Containing the risks of antibiotic-resistant superbugs
Antibiotic resistance is a growing threat to populations around the world. Overuse of antibiotics can foster the evolution of superbugs that no longer respond to available treatment. Multi-drug resistant organisms wreak havoc in hospital settings, claiming thousands of lives every year.Using AI and Machine Learning (ML), electronic health record data can identify infection patterns and highlight patients at risk before they begin to show symptoms. Leveraging technology to drive analytics enhances their accuracy, enabling systems to create faster, more accurate alerts for healthcare providers. - Creating more precise analytics for pathology images
Analytics that can drill down to the pixel level on extremely large digital images can improve a healthcare professional’s ability to deliver the most accurate diagnoses. By enabling providers to zero in on imaging details, AI provides unprecedented insight into critical nuances that may escape the human eye.Artificial intelligence can also improve productivity around imaging evaluation. By identifying and areas of interest upfront, AI streamlines the review process for human clinicians reviewing data. - Bringing intelligence to devices and machines
Smart devices are taking over the consumer environment, offering everything from real-time video from the inside of a refrigerator to cars that can detect when the driver is distracted. In the medical environment, smart devices are critical for monitoring patients in the ICU and elsewhere.Using artificial intelligence to enhance the ability to identify deterioration, suggest that sepsis is taking hold, or sense the development of complications can significantly improve outcomes, and may reduce costs related to hospital-acquired condition penalties. Inserting intelligent algorithms into these devices reduces cognitive burdens for physicians, while ensuring that patients receive care in as timely a manner as possible. - Advancing immunotherapy for cancer treatment
Immunotherapy is one of the most promising avenues for treating cancer. By using the body’s own immune system to attack malignancies, patients can have significantly better outcomes.Only a small number of patients respond to current immunotherapy options however, and oncologists don’t have a precise and reliable method for identifying the patients most likely to benefit from immunotherapy. Using AI and ML however, algorithms can synthesize highly complex datasets and can illuminate new options for targeting therapies based on an individual’s unique genetic makeup. - Transforming electronic health records into risk assessment tools
Electronic health records (EHRs) are a goldmine of patient data, but extracting and analyzing that wealth of information in an accurate, timely, and reliable manner has been a continual challenge. Data quality and integrity issues, multiple data formats, and other issues have made it very difficult to engage in meaningful risk stratification, predictive analytics, and clinical decision support.Using AI and ML to analyze EHR data enables more successful risk scoring and stratification, especially when researchers use deep learning to identify novel connections between seemingly unrelated datasets. - Monitoring patient health with wearables and personal devices
A majority of consumers today have access to devices with sensors that can collect valuable data about their health. Collecting and analyzing this data–and supplementing it with patient-provided information–can offer a unique perspective into individual and population health. Artificial intelligence will play a significant role in extracting actionable insights from this large and varied treasure trove of data.Experts also believe that images taken from smartphones and other consumer devices will be an important supplement to clinical quality imaging–especially in underserved or remote areas. Using smartphones to collect images of eyes, skin lesions, wounds, infections, medications, etc., may help underserved areas cope with a shortage of specialists while reducing the time-to-diagnosis for certain conditions. - Transforming clinical decision making with bedside AI
As the healthcare industry shifts away from fee-for-service, it’s also moving further from reactive care. Artificial intelligence will provide much of the bedrock for that evolution by powering predictive analytics and clinical decision support tools that alert providers to problems long before they might otherwise recognize the need to act.AI can provide earlier warnings for conditions like seizures or sepsis, which often require intensive analysis of complex datasets. Leveraging AI for clinical decision support, risk scoring, and early alerting is one of the most promising areas of development for this revolutionary approach to data analysis.
By powering a new generation of tools and systems that make clinicians more aware of nuances, more efficient when delivering care, and more likely to get ahead of developing problems, AI will usher in a new era of clinical quality and exciting breakthroughs in patient care. For more information about Pegasus One’s AI healthcare solutions, contact us for a free consultation.
