Despite the challenges faced by healthcare in 2020, there were also some silver linings. One of the most significant was the accelerated adoption of AI in healthcare. Hospitals and clinics have long been struggling to keep up with the sheer volume of data generated by their patients. This data includes everything from medical records and lab tests to X-rays and MRIs. AI provides a way to quickly and effectively analyze this data, identify patterns, and make predictions. One thing is for sure – Benefits of AI in Healthcare are innumerable.
As a result, AI is being used to help diagnose diseases, predict patient outcomes, and develop new treatments. In addition, AI is being used to improve workflow efficiency and optimize resource allocation.
In other words, AI has the potential to make healthcare more efficient, effective, and accessible than ever before. So far, the benefits of AI in healthcare have been largely theoretical. But as AI technology continues to evolve, it’s only a matter of time before these benefits become a reality for both caregivers and patients alike.
What is AI in Healthcare?
Machine learning has the ability to provide doctors and hospital workers with data-driven clinical decision support (CDS), opening the door for greater income potential. Deep learning, a branch of AI that seeks out patterns, employs algorithms and data to provide healthcare professionals with automated insights.
There is no doubt that AI in healthcare industry is having a great impact. One of the most promising applications of AI is in the area of clinical decision support (CDS).
CDS systems use data-driven insights to help physicians and other healthcare providers make better decisions about patient care. Deep learning, a subset of AI, is particularly well-suited to this task.
Deep learning algorithms are able to identify patterns in data that would be difficult for humans to discern. As a result, deep learning-based CDS systems have the potential to greatly improve the quality of patient care.
In addition, CDS systems have the potential to generate significant revenue for hospitals and other healthcare organizations. By providing data-driven insights that help clinicians improve the quality of patient care, CDS systems can help hospitals optimize their revenue streams.
Application Of AI In Healthcare
MarketsandMarkets estimates that healthcare AI investment would reach $36.1 billion by 2025. The healthcare industry is ripe for automation and efficiency gains across a wide range of end users, including healthcare providers, hospitals, payers, pharmaceuticals, and biotechnology firms.
It’s possible to achieve more ambitious AI solutions with improved models and algorithms, access to data, lower hardware prices, and better connection such as the 5G network. Only the introduction of the 5G network has made it possible for machines to process large volumes of data in real time without the previous barrier of network reliability.
AI’s future depends on its capacity to operate at high speeds and with high levels of consistency in a field as life-critical as healthcare. Healthcare providers are struggling to meet the rising demand for their services as a result of the COVID-19 outbreak. AI has made it easier of healthcare workers to leverage the benefits of artificial intelligence, all while meeting the demand through the following:
A lot of people fear that a robot-assisted surgery may lead to AI taking over the role of doctors and making decisions on surgical motions. In actuality, the surgeon is in charge, but AI-powered robotic equipment allow surgeons to perform their tasks with greater precision and delicacy.
An AI-powered robot is used at the Maastricht University Medical Center to stitch blood arteries as thin as 0.03 millimeters.
Administrative Workflow Assistants
Just completing electronic health record (EHR) forms takes doctors about 16 minutes per patient. However, thanks to AI-powered workflow efficiency, caregivers may focus on their patients instead of their administrative duties.
Medical records can be navigated with voice commands and transcribed clinical data captured during patient visits with the use of AI technologies such as machine learning, robotic process automation, and natural language processing. Workflow assistants enabled by artificial intelligence (AI) make scheduling appointments easier while also helping to prioritize and discharge patients more quickly.
Ascend Analytics provides healthcare quality management to assist the healthcare industry in managing data quality, safety, and ensuring results that are driven by quality. We help organizations by helping them find new opportunities in their data, automating processes, and ensuring that you put the needs of your patients first.
Prescription Error Recognition
Every year, 5,000 to 7,000 persons in the US alone pass away as a result of medication errors. These errors frequently result from poor EHR interfaces, wherein clinicians select the incorrect medications from a drop-down option or become perplexed by dosing units. The benefits of AI in healthcare combats this problem.
The Brigham and Women’s Hospital employs artificial intelligence (AI) to identify medication problems. The technology identified 10,668 potential errors over the course of a year, and 79 percent of them were clinically significant, allowing the hospital to avoid paying $1.3 million in healthcare-related expenses.
In the US, about 3% of all healthcare claims are false. It amounts to an annual loss of $100 billion, which is not a huge sum. Assessment of claims is automated using artificial intelligence. Machine learning models assist in expediting the processing, validation, and payment of legitimate claims by identifying bogus ones before they are paid for.
But AI can also detect other types of fraud outside insurance fraud. AI also helps in preventing patient data theft, upcoding—charging for a basic operation as for something more complex—and invoicing for services a patient never had.
Cyberattacks are nothing new for the healthcare industry. The notorious WannaCry ransomware in 2017 rendered parts of the UK’s National Health Service inoperable for days. A rogue agent exposed the personal information of thousands of HIV-positive Singaporeans in 2019. The necessity of cybersecurity has increased during the pandemic. Healthcare firms are utilizing AI-powered cybersecurity to prevent system outages and data breaches.
Data flows within a technological system are analyzed by AI-based security solutions to determine what user behavior is typical and anomalous. Using this information as a foundation, AI tracks down and stops cyberattacks so that attackers are stopped before they can cause any systemic harm.
Benefits of AI in Healthcare & Medicine
Diagnostic Procedure Efficiency
AI in healthcare has the potential to improve diagnostic accuracy. Human errors can be exacerbated by a lack of medical history and huge caseloads in healthcare settings. In comparison to clinicians, AI systems can identify and predict diseases more quickly and with less inaccuracy (assuming robust data quality, which we will talk about later).
Deep learning AI models, for example, have been shown to diagnose breast cancer at a higher rate than 11 pathologists in a 2017 study!
PathA artificial intelligence in medical diagnosis enhances patient outcomes with AI-Powered technology and partner collaboration to give the most accurate artificial intelligence in medical diagnosis and the most effective therapy.
Reduced Business Costs
AI can frequently be used to improve procedures like diagnosis at a fraction of the initial cost. Consider the case when artificial intelligence in medical imaging can go through millions of images for medical symptoms. It eliminates the expensive manual labor required. Patients receive quicker and more efficient care, which lowers the need for beds, wait periods, and admissions.
Healthcare IT News forecasts that AI automation will result in significant cost savings across a variety of industries. The top five cost benefits of artificial intelligence are listed as follows:
- Surgery with robot assistance: $40 billion
- Virtual nursing aides: $20 billion
- Assistance with administrative workflow: $18 billion
- Verification of fraud: $17 billion
- Reduced dosage errors – $16 billion
In the field of medical robotics, artificial intelligence (AI) is making a name for itself by giving surgeons with useful and original help during surgery. Surgeons can operate in tight spaces without resorting to open surgery because they have improved dexterity.
Reduced blood loss, infection risk, and post-surgery pain can all be attributed to the use of robots in surgical procedures. Robotic surgery patients also claim less scars and shorter recovery times due to the smaller incisions required by the technology.
For instance, while waiting for surgery, patients are exposed to antibacterial nanorobots to get rid of any infections in their bloodstream. The AI-backed information on the patient’s current condition that is readily available to surgeons in real-time is arguably the greatest component. Patients’ concerns, particularly those related to surgery under general anesthesia, have been allayed because to this.
Artificial Intelligence (AI) currently relies on people’s data to analyze the health of patients in the past and present. Doctors are better able to make an accurate artificial intelligence in medical diagnosis when they compare the symptoms amongst patients. Millions of symptoms and diagnoses have been entered into the database of many healthcare mobile apps. Moreover, it can forecast future health problems that an individual may face.
For example, Google’s Verily app can predict hereditary and non-contagious genetic disorders, such as Alzheimer’s. Using these techniques, health care professionals may accurately identify and plan for potential hazards in the future. Predictive analysis has also made healthcare facilities more known for their operational management.
Better Prevention Care
Artificial intelligence (AI) and machine learning can help with the prevention and management of infectious diseases. AI can be extremely useful in averting epidemics like COVID-19 because of its ability to handle massive amounts of data, including medical records, behavioral patterns, and the physical environment.
COVID-19 was predicted to travel from Wuhan to Bangkok, Seoul, and Taipei by the outbreak intelligence platform, Blue Dot, based on an analysis of airline tickets and flight itineraries. For successful isolation and quarantine processes, similar AI-enabled solutions can help doctors detect the spread of disease when patients arrive at an establishment with the help an immediate artificial intelligence in medical diagnosis.
Benefits Of AI In Healthcare – Summary
Artificial intelligence (AI) has the potential to transform the global healthcare system, but they are not without risk or challenge. Internet of Medical Things (IoMT) and AI-driven tools have shown great success, especially in human lives. We are now better aligned with mindful health management and a healthy lifestyle thanks to benefits of AI in healthcare.
By automating tasks and analyzing large data sets, AI can help to improve patient care and deliver better healthcare faster, and at a lower cost.
One of the benefits of AI in healthcare is that it can help to identify trends and patterns in patient data. This information can be used to develop new treatments and therapies, as well as to improve disease prevention and management.
AI can also be used to automate tasks such as billing and coding, which can free up staff time to focus on more important tasks.
In addition, AI-enabled chatbots can provide 24/7 access to medical information and advice, making it easier for patients to get the care they need.
By integrating AI into the healthcare ecosystem, we can realize a multitude of benefits that will improve patient care and deliver better healthcare faster, and at a lower cost.
At Ascend Analytics, we use descriptive, diagnostic, prescriptive, and advanced analytics to maximize an organization’s potential. With our data science providers, we can improve operational efficiency and increase profitability.