Contact us anytime to know more — Abhishek P., Founder & CFO CISIN
The Covid-19 pandemic is pushing the healthcare industry even more to adopt this new technology. A.I. can be extremely useful to healthcare providers and patients alike when it is used in areas such as chronic disease management and early risk identification.
This article will give you a detailed look at artificial Intelligence solutions and its use in healthcare, as well as how it will impact the industry in the future.
Let's Begin in wide range.
What is Digital Transformation in Healthcare?
The digital transformation process is how healthcare and life science organizations overhaul their enterprise. It integrates disparate data and connects decision-makers with real-time insights while automating administrative tasks.
This is a major undertaking to move a company away from its manual, siloed, on-premises past and towards a cloud-based, automated future. Digital transformation is a way to reduce costs and increase efficiency in healthcare as it begins to navigate through a challenging year.
The recent challenges of high costs and a more distributed workforce are being exacerbated by the macroeconomic turmoil.
Imagine this: Healthcare professionals access real-time, unified clinical data using innovative software. They then extract insights through artificial Intelligence (A.I.), machine learning, and other technologies.
This gives healthcare teams an overall picture of the patient, which allows them to make informed decisions both in a clinic and via virtual care. Automating the exchange of information between payers, providers, and other stakeholders streamlines this process. All of this is possible now.
According to research, healthcare and life science professionals believe that A.I.'s most important result is personalizing the consumer personalized experience. This is followed by the use of real-time data.
The healthcare industry has more digital opportunities to evolve with generative AI. Although generative A.I. is a relatively new technology, 15% of healthcare workers have already used it at work.
Trends For Digital Transformation In Healthcare
The life sciences industry may have given a hint of what is to come by stating that they intend to keep 99% of digital tools originally adopted during the Covid-19 Pandemic.
The ways that healthcare is leveraging technology to overcome new challenges have already evolved.
In 2023, there will be major changes in the digital transformation of healthcare and life science.
Exploring Artificial Intelligence And Increasing Digital Differentiation
Most healthcare and life science leaders (79%) agree that A.I. (69%) and automation (79%) are important for the future of their company.
Since 2020, healthcare and life science leaders have nearly doubled the number of those who believe digital offerings are a key way to gain a competitive edge. In response to rising consumer expectations, 93% of healthcare executives are innovating urgently.
Healthcare is still one of the industries that are least digitally mature. About half of the chief executives in the life sciences admit that their prior investments to personalize the consumer experience have not delivered the growth benefits they expected.
These leaders have shifted their focus to providing value to consumers.
Digital transformation has many benefits. In one study, technology enthusiasts in the healthcare sector spend half as much time on administrative tasks as their counterparts.
Over half of healthcare professionals (55%) say that inefficient processes and manual entry of data stymie their productivity. Tech pioneers are using tools like A.I. and speech recognition powered by machine learning to allow providers to record data at the point of care and reduce documentation time by up to 45%.
Using generative A.I. correctly could transform the healthcare industry, but many employees are cautious. Only 23% of employees in healthcare believe that generative A.I.
can be used safely at work.
Data Democratization Is Secure
The U.S. Department of Health and Human Services will release the Cures Act Final Rule in early 2020. This rule calls for the use of open APIs certified to promote secure access, exchange, and use of electronic medical information.
CMS (Centers for Medicare & Medicaid Services) has selected a standard foundation, HL7-FHIR, for data exchange through secure APIs. Interoperability and integration of data will allow healthcare organizations to better engage and treat patients by leveraging their data.
Recent research has shown that pharmaceutical and biotech companies use, on average, 78 different systems.
But data security cannot be compromised by a lack of ease of access. In a survey conducted in 2023 on data stewardship, nearly a quarter of respondents (22%) said that security protocols were not strictly enforced within their organization.
More than half of healthcare workers (39%) use multi-factor verification every time. One in four has accidentally clicked on suspicious links at work. During the pandemic period, approximately one-third of healthcare organizations suffered ransomware attacks.
Each attack costs an average of $ 1.27 million to fix. In an AI-driven environment, data security and stewardship are going to become more important. This is especially true in the healthcare industry, where privacy is of paramount importance.
A.I. is only as secure and trusted as the data that it is built on.
Data management is essential to the healthcare industry, given its constant flux. What is the key to healthcare and life science? Consolidate and combine all data and data solutions to produce secure, interoperable data that can be used for actionable insights.
Fewer than half (38%) of healthcare and life science organizations have implemented or achieved full integration.
Khanna stated that "data is great, but data overload can be crippling." "Healthcare and Life Sciences need intelligent insights to nurture their success."
You Can Get Care Anywhere
Telemedicine is a hit with the public. While patients are pushing for virtual care, 80 percent of consumers want remote monitoring.
It is particularly beneficial for 47% of consumers with lower incomes who have difficulty getting to their doctor's appointments.
Healthcare organizations must have the digital infrastructure necessary to meet diverse patient demands. To achieve this mission, it is essential that healthcare organizations have solutions that allow remote patient monitoring, intelligent appointment management, medication management, and regulatory compliance.
Hybrid Healthcare Workforce
It is true that the hybrid model, which combines remote and in-person work, has become more popular as a result of necessity since 2020.
However, its impact will continue to be felt. Since Covid-19, 78% of employees have said that their employer is either planning or has already introduced new ways of working.
This is up from 9% of employees in 2019. Almost 90% of healthcare executives believe that remote work increases competition for talent. Research shows that 75% of pharma companies and 68% of medical device companies have already adopted hybrid working.
In the next two-five years, more organizations are expected to adopt hybrid work arrangements.
Over half of healthcare organizations have invested in digital tools to support remote working. According to research, only 35% of applications and systems in the industry are distributed both on-premises and on a cloud.
Eighty percent (80%) of healthcare and life science organizations who have migrated to the cloud their customer relationship platform say that it has helped drive revenue, reduce costs, and achieve goals.
Healthcare and Life Sciences organizations that invest in digital collaboration and automated workflows can reduce costs and the time needed to complete tasks.
an expert stated that "more productivity with fewer resources is a pipedream." "But this is totally possible if you use the technology that allows your team to work at their best, wherever they May Be."
A.I. In Healthcare: 5 Ways It Is Changing The Industry
A.I. is a boon to the healthcare industry. From maximizing hospital efficiency to making accurate diagnoses, A.I.
has been a great help. Here are some ways A.I. is revolutionizing healthcare and driving the industry towards digital transformation in order to better engage users and generate revenue.
Offer Robot-Assisted Surgical Procedures
A.I. is used in many different ways to improve healthcare. The use of A.I. and collaborative robotics has revolutionized surgery in terms of speed and accuracy.
These systems are capable of performing complex surgical procedures without the risk of pain, side effects, or blood loss. Recovery after surgery is also faster and easier.
A.I. is a powerful tool that allows doctors and surgeons to gain real-time insights and information about a patient's health.
AI-backed data allows healthcare providers to make quick, intelligent decisions during and after procedures.
Fraud Detection
According to the US Justice Department, 3% of all healthcare claims are fraudulent. This is equivalent to a loss of 100 billion dollars per year.
A.I. can help the healthcare industry detect invalid claims and pay them before they're paid. It also helps speed up the processing, approval, and payment of valid claims.
A.I. can detect insurance fraud, but it also helps prevent patient data theft.
Leading healthcare providers, such as Harvard Pilgrim Health, are using A.I. to combat healthcare fraud. AI-based fraud detection is used to detect suspicious behavior and identify fraudulent claims.
Supporting Clinical Decisions
Artificial Intelligence is changing how clinical providers make decisions. A.I. provides data to healthcare providers to help with diagnosis, treatment planning, and population health management.
This technology can also be used to help support decision-making in specialties that require a lot of data, such as ophthalmology and radiology. In the near future, A.I. may be able to automate certain tasks.
A.I. can translate clinical notes into EHRs using natural language processing.
The clinician will only need to enter the data once. development team
Assisting with Repetitive Tasks
The healthcare industry is moving to a world of Cognitive assistants who have reasoning, advanced analytic capabilities, and complete medical knowledge.
Medical Sieve is a newly launched algorithm that has been qualified to assist in decisions related to cardiology and radiology.
The cognitive assistant analyzes radiology images in order to detect problems faster and more reliably.
Medical Sieve is just one example of how artificial Intelligence can be used in healthcare. Other technologies, such as Enlitic, aim to combine deep learning and medical data in order to aid advanced diagnosis and improve patient outcomes.
Changes In Online And In-Person Consultations
Babylon App shows how A.I. can transform doctor consultations. The app provides online medical consultations and healthcare services.
The app offers medical A.I. advice based on a patient's history of illness and available medical knowledge.
The AI-based apps work in such a way that users need only report their symptoms, and then the app will check the symptoms with the database of diseases by using speech recognition.
After noting the history of the patient and the circumstances in which they live, the app offers a course of action that the patient can take.
Over 54% of mHealth users are willing and able to use A.I. and Robotics in their medical and AI consultations.
When developed correctly with the assistance of a software development company/software development services for healthcare apps like these not only help patients manage their health but also reduce the crowds and waiting times in the waiting rooms.
Read More: What Is The AI Software Development Life Cycle In 2023?
Manage Your Medication And Get Health Assistance
Sense.ly is a medical start-up that developed Molly, the first digital nurse in the world. The virtual nurse is friendly and has a pleasant voice.
Her only purpose is to monitor and treat patients. Machine learning is used to support patients with chronic conditions in between doctor's visits.
This app offers a customized, tested monitoring system and follow-up treatment focusing on chronic illnesses.
A.I. has become a vital technology in the field of Health Assistance and Management of Medication by being able to tell patients when they should take their medications and monitor if they do.
Drug Production
Clinical trials are expensive and can take years to create pharmaceuticals. A.I. can make drug development faster and more cost-effective.
Atomwise, a network of supercomputers that root out therapies from databases of molecular structures is one of these networks.
Atomwise's A.I. technology was used in 2015 to identify existing drugs on the market that could be redesigned to treat the Ebola virus.
They found two drugs that they believed could help end the epidemic. Atomwise, AI technology accelerated the analysis, which would have normally taken years.
Precision Medicine
A.I. has a major impact on genetics and genomics. A.I. can identify patterns within massive data sets that contain medical records and genetic data, which helps to look for links between diseases and mutations.
A.I., in the future, will be able to tell doctors what happens to a cell when DNA is altered, either therapeutically or by natural genetic variation.
Analyzing a Healthcare System
As more healthcare bills become digital, it is now possible to retrieve all the data about the doctor, treatment, and medical establishment.
Hospitals can use data mining to generate reports about the errors they make in treating certain types of conditions and help them improve or even prevent unnecessary hospitalizations.
Zorgprisma Publiek in the Netherlands has analyzed the hospital invoices and used Watson technology to mine collected data.
Automating Image Diagnosis
A.I.'s computer vision capabilities are a great asset to the healthcare industry. A.I. is used by hospitals and clinics to detect abnormalities in medical images such as C.T.
scans or radiology. Image recognition helps doctors diagnose tumors, kidney infections, improve cancer prognosis, and more.
The tool used by the UVA University Hospital is the best example of A.I.-powered visual perception. The tool uses ML algorithms to analyze children's biopsy pictures and distinguish between celiac, environmental, and other diseases.
It does this as accurately as doctors do.
Let's explore the various types of A.I. technology relevant to the industry.
A.I. Types In Healthcare
Artificial Intelligence is a group of technologies that are used in healthcare. The majority of these technologies are relevant to healthcare, but their tasks and processes may be different.
Below are some of the most important A.I. technologies:
Machine Learning- This is one of the most common forms of artificial Intelligence in hospitals and healthcare.
Machine learning is a technique that uses data and algorithms to mimic the way humans learn. It gradually improves its accuracy. Precision medicine is the most common use of ML in healthcare. It can predict which treatment procedures will be most successful for patients based on their attributes and treatments.
Precision medicine and machine learning applications require a dataset of training data for which the final result is known. This is called supervised learning.
Deep Learning- Or neural network models, is the most complex machine learning. They have many features or variables to predict outcomes.
Deep learning is often used to detect potentially cancerous lesions on radiology images.
Natural Language Processing
NLP is used for a variety of purposes, including text analysis, speech recognition, and other language-related goals.
In healthcare, NLP is often used to create and classify published research and clinical documentation.
NLP systems are able to analyze unstructured clinical notes, giving them incredible insights into how to improve methods, understand quality and get better results for the patient.
Robotic Process Automation
RPA is a technology that automates business processes based on rules. It can mimic and learn from these processes.
They are transparent, inexpensive, and easy to program compared to other A.I. forms. In healthcare, these systems are used to automate repetitive tasks such as updating patient records and billing.
Expert System Based On Rules
Rule-based expert systems are the simplest artificial Intelligence. They use knowledge-based rules and prescribed knowledge to solve problems.
The business goal of an expert system is for it to convert the knowledge of a human expert into a set of hardcoded, predetermined rules that can be applied to input data.
They are used widely in healthcare for "clinical decision-support" purposes. They are simple to understand and work well until a certain point.
When the number of rules increases, they start to conflict and fail. In healthcare, however, they are now being replaced by more approaches that are based on machine learning algorithms and data.
A.I. Challenges In Healthcare
Using innovative technologies such as A.I., to a large extent, comes with a number of challenges. A.I. technology in the healthcare sector faces a variety of challenges, from a lack of data quality to security concerns.
Let's have a closer look.
Data availability- Training A.I. systems require a large amount of data, which can be obtained from a variety of sources, including electronic health records and pharmacy records.
The data becomes more complex and difficult to understand because the data are fragmented. Patients often visit different healthcare providers. The result is errors and increased costs.
Privacy concerns- A.I. in healthcare faces a number of challenges, including the volume of sensitive data that is collected.
This requires the implementation of additional security measures. It's crucial to find a partner in AI software development who offers a range of security features to ensure that your customer data will be handled appropriately.
Errors or injuries- It is possible that A.I. systems can make mistakes in detecting risks and treatments.
If an AI-based computer suggests the wrong drug to a client or fails to locate a tumor on a radiology scan, it can have serious health consequences.
Future of A.I. in Healthcare
A.I. has already begun to change the healthcare industry. It is changing how patients are treated, how doctors practice medicine, and how the pharmaceutical sector operates.
The journey is just beginning.
A.I. will, in the future, enable a new generation of radio instruments that are accurate and detailed enough to eliminate the need for tissue samples in certain cases.
This could help service providers better define cancers' aggressiveness and target treatment more effectively. A.I. also allows for "virtual biopsy" and advances the innovative field of radiomics.
Further, electronic health records can be used to identify patients at high risk of infection and help detect patterns before symptoms appear.
Machine learning and A.I. can be used to create more accurate alerts. This will help healthcare providers. A.I. can provide early warnings for conditions such as seizures or sepsis that require complex data analysis.
This revolutionary approach is based on leveraging A.I. for risk assessment, clinical decision support, and early warnings.
A.I. will bring about a new era in clinical quality and lead to exciting breakthroughs in patient care.
Conclusion
We can see that artificial Intelligence and healthcare are closely related because of all the benefits this technology provides.
A.I. in healthcare can lead to more accurate diagnosis and treatment plans and better outcomes for patients. All healthcare institutions should invest in A.I.
to provide customers with novel experiences and exceptional services.
We work with healthcare organizations to develop custom AI-based business models. These models help improve revenue, reduce costs, and offer enhanced customer experiences.
