There’s no wonder that the technological advancements have a significant impact on our lives. From navigation of apps, to guide you home safely, everywhere technology is playing a significant role.
However, technology in healthcare industry is transforming convenience, patient communication, improving diagnosis levels and prove to be life-saving.
The key technologies are providing the foundation for many booming healthcare innovations that are disrupting the industry. To keep pace with this continuous transformation, healthcare organization will need to embrace new technologies that will improve health outcomes, make it cost-effective, and provide value-based care.
As healthcare shifts to a model of any-time, any-place, continuous and personalized care, it is essential to analyze the prime technologies that will redefine the future of healthcare segment in 2019.
“ We believe consumer health technologies — apps, wearables, self-diagnosis tools — have the potential to strengthen the patient-physician connection and improve health outcomes.”
The emerging new technologies combined with the variety of new drivers that include technology-centric transformation not only leads to cost reduction but also ensures value-based care in the healthcare industry.
Healthcare industry has been impacted in a substantial positive way in case of automation, machine learning, and artificial intelligence.
According to a study from the University of Michigan, the transformation of information from the conventional paper to electronic health records through digitization reduces the cost of outpatient care by 3%. These researchers estimated this as $5.14 in savings per patient each month.
Healthcare industry is facing revolutionary changes, looking out for the innovative ways to deliver the best patient outcomes while eliminating the dramatic healthcare expenses. What does the future of healthcare hold in 2019? Let’s look at six promising technology ready to transform the healthcare environment.
Artificial Intelligence plays an integral role in reshaping healthcare. The adoption of artificial intelligence in the healthcare industry is gaining momentum and solving a variety of problems of patients, hospitals, and healthcare industry faces.
It will provide much of the bedrock by powering predictive analytics and clinical decision support tools that help the providers into problems long before they might otherwise recognize the need to act.
Nowadays every patient is digitally empowered and prefer personalized care that has more accountability and is also more affordable. Artificial Intelligence does have numerous implications on various fields of the healthcare industry that includes disease management, clinical trials, diagnosis and treatment, patient engagement, monitoring of the patient, and wellness management.
AI is dominating healthcare treatments, such as making better treatment plans, assessing data to provide customized medication, and monitor procedures.
AI has the potentiality to track the chronic diseases through MRI, CT scans, ultrasound and x-rays, and thus saving the time of the patients to wait for a diagnosis from weeks to a few hours.
According to a 2016 report from CB Insights, about 86% of healthcare provider organizations, life science companies, and technology vendors are adopting artificial intelligence technology in healthcare. By 2020, these organizations will spend an average of $54 million on artificial intelligence projects.
Let’s look at some of the ways how AI is redefining the healthcare industry:
The demand to bring dramatical changes has always been an underlying ripple in every facet of business, and when it comes to healthcare, this is done with a sense of inimitable urgency. Creating high valuable virtual records associated with a patient is one of the most significant challenges of healthcare IT.
The blockchain is a distributed system that records peer to peer transactions, tracks the changes across networks, and stores and exchanges data for cryptographies. Blockchain technology has the potential to revolutionize healthcare, placing the patient at the core of the healthcare ecosystem and enhancing the security, privacy, and interoperability of health data. This technology will offer a new model for health information exchanges (HIE) by making electronic medical records more effective, and secure.
This statistic depicts the projected distribution of healthcare blockchain adoption across healthcare applications worldwide, in 2017, 2020, and 2025. It is projected that 55 percent of healthcare applications will have adopted blockchain for commercial deployment by 2025.
“Adoption of blockchain technologies will be driven organizations basing their development on providing better quality care much the same way the regional health information exchange concept kicked off digital health data-sharing. In some jurisdictions data exchange worked pretty well.”
The health data volume is multiplying, and it is expected to breed dramatically in the years ahead. With more than 1.2 billion clinical documents are produced in the U.S. yearly, doctors and life scientists have an ocean of big data for their core research. Moreover, massive amount of health-related information is produced and shared with adoption of wearable tech. The wave of such data flow opens new opportunities for more informed healthcare.
Data science stands an effective healthcare trend to optimize the way hospital operations are managed. With data science, the industry can find well organized, cost-effective ways to harness vast amounts of existing healthcare data, enhance its potential to revolutionize healthcare with a precise diagnosis.
With the capability to collect, structure, and process a high volume of data and analyze a pattern, to gain in-depth knowledge of the human body is the essential requirement for data scientists and machine learning experts across the world.
Despite having a vast amount of health data at disposal, the diagnostic failure rates are still high. According to the recent research by the National Academics of Sciences, Engineering, and Medicine, around 5% of adult patients are misdiagnosed every year in the United States making it a total of 12 million people. Additionally, the postmortem examination results research reveals that diagnostic errors cause almost 10% of patient deaths.
Whether it’s predicting a patient with a tumor, the risk of re-admission, or the misclassified diagnoses in electronic medical records, data science plays a significant role. Data science will transform the future of the healthcare by managing and organizing enormous volume of data that will prevent healthcare problems and saving lives of millions.
It is one of the critical technology in healthcare that can dramatically improve clinical decision making, administrative functions, patient monitoring, and pharmaceutical research is Machine Learning. By implementing machine learning technology in healthcare, we can– detect patient’s health real time, understand the disease patterns, find possible treatment, and analyze result with a clinical trial that is underway.
With the aid of machine learning, mobile-enabled care management platforms can be made available to offer all stakeholders customized plans, automatically adjusting based on experiences.
Uncompensated care is one of the rapidly growing problems for most healthcare systems. With machine learning, health systems can determine who needs reminder alerts, who need financial assistance, and how the patterns of payment change over time.
Physicians are smart, well-skilled and they like to stay abreast with the advanced research. It’s not possible for them to memorize and gather all the knowledge they require for every situation, and they probably don’t have it easily available at their fingertips. Though they have the access of the massive data in hand required to compare treatment outcomes for all various types of diseases they come across, but they still lack time and expertise to assess that information and integrate it with the patient’s own medical profile. But this kind of comprehensive research and statistical analysis is beyond the reach of a physician’s work.
That’s why myriads of the physicians – as well as insurance companies – are adopting predictive analytics.
Predictive analytics (PA) utilizes technology and statistical methods to gather huge amounts of information, that stands necessary to detect the patient’s outcome. That information can imbibe data from past treatment results as well as the advanced medical research published in peer-reviewed journals and databases.
Not only can PA help to solve difficult issues and predict but it can also display amazing associations in data that our human brains fail to suspect.
In medicine, predictions may vary from medication responses to hospital readmission rates. Examples are diagnosis of infectious diseases from methods of suturing, assessing the likelihood of disease, helping a physician in examination procedure, and even detecting the future wellness.
Technology has a lot of room for growth in healthcare, and in 2019 will see how companies are applying these intelligent tools to their organizations. Whether you are looking for an AI-driven solution or applying machine learning to your current healthcare software, you need a right team to create a smooth journey for you. If technology is one of your challenges, OSP Labs’ experts are ready to help!
Riken Shah is the CEO of OSP. He is a tech enthusiast, healthcare innovation specialist, and avid reader. With over a decade of experience, Riken has helped healthcare companies to be more productive and successful.
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