Technology is revolutionizing the healthcare industry. The digitization and the information revolution has shifted the understanding and the way of treating a disease. However, one of the main limitations of medicine today is the understanding of the biology of disease.
The increasing digitization of the healthcare sector means that organizations often add terabytes of patient data to data centers annually. The healthcare industry produces the most amount of complex and voluminous data that can provide precious insights to improve the quality of human lives. There is no denying that big data has emerged as a big game changer for the healthcare industry to help it evolve to a new level.
With the rise of Big Data technologies, the healthcare industry is on the brink of a huge transformation through the utilization of advanced analytics and sophisticated big data technologies. It can be a paradigm shift from the way medicine is practiced now. Big Data can help patients get tailor-made treatments. Besides, with the popularity of remote consultation services and wearable diagnostics, Big Data along with IoT can play a critical role in the evolution of the new-era healthcare practices.
Role of Big Data Analytics In The Healthcare Industry
80% of all healthcare information is unstructured data which is so vast and complex that it needs specialized methods and tools to make meaningful use of the data. The new and emerging technologies like artificial intelligence (AI), machine learning, and predictive analytics are bringing in powerful new tools for healthcare technologists and thought leaders to capture these data and process it effectively for the complete transformation of the healthcare industry.
Let’s take a look at the ways how Big Data can help the healthcare industry to evolve and make it more consumer friendly.
Improving Overall Population Health
Big data analytics can play a vital role in the medicine and the pharmaceutical industry by building better health profiles and better predictive models around individual patients helping better diagnosis and treatment of diseases.
Big data can help in aggregating more and more information about a disease, ranging from the DNA, metabolites, and proteins to cells, tissues, organs, organisms, and ecosystems. The aggregated insights can help to drive demonstrated clinical improvements while rendering the ability to understand comparative effectiveness thereby improving the overall health conditions of a population.
Reducing Healthcare Costs
Big Data is enabling the healthcare industry to reduce the per-capita cost of healthcare by reducing avoidable overuse of resources. Health Insurance enterprises are moving away from fee-for-service compensation model to value based data-driven incentives that reward high-quality, cost-effective patient care and exhibit sensible use of electronic health records.
Big Data can help reduce the cost of fraud, waste, and abuse in the healthcare industry by analyzing large unstructured datasets of historical claims and identifying the fraud much before disbursing the resources.
Providing Patient-Centric Care or Value-Based Care
The goal of value-based care is to provide personalized treatment to the patient that is cost effective and measured based on patient satisfaction. The Big Data technologies can facilitate the healthcare industry to collaborate with doctors, hospitals, and health insurance to focus their processes on patient outcomes, need for providing an efficient and value-based care that is price conscious and transparent in its delivery and billing.
Big Data is also playing a significant role in assisting the health insurers and public health systems to shift from fee-for-service compensation to value-based data-driven incentives that reward high-quality, cost-effective patient care and encourage meaningful utilization of electronic health records.
Creating Electronic Health Records (EHRs)
Creating and maintaining EHRs is, perhaps, the most widespread application of big data in healthcare. The main motive behind creating EHRs is to maintain a database of patients’ health history. EHRs comprise a unique digital record for every patient that includes demographics, medical history, laboratory test results, allergies, etc.
The records are shared using secure information systems and are made available to healthcare providers from both public and private sector. Each record contains one modifiable file that can be changed by doctors over time, depending on the change of patient’s health condition, with no paperwork needed.
Predictive Analytics to Improve Patient Outcomes
Predictive analysis of health is facilitated by EHRs that enables healthcare professionals to combine and analyze a variety of structured and unstructured data across multiple data sources aiding accurate diagnosis of patient conditions and improving treatment outcomes.
Predictive analytics is particularly helpful for patients with complex medical histories, suffering from multiple conditions. It helps clinicians and doctors to take big data-informed decisions and improve patients’ treatment.
Reducing Fraud, Waste, and Abuse
Big Data analytics enables healthcare organizations to store data and go back in history, whenever required, to analyze historical claims and detect anomalies and patterns using machine learning algorithms. This can help the healthcare providers to reduce the cost of fraud significantly.
The Centers for Medicare and Medicaid Services prevented healthcare fraud worth more than $210.7 million in just one year using predictive analytics. Predictive models analyze specific claims and providers, to identify claim aberrancies and billing patterns. Then the charges are compared against a fraud profile before raising suspicion.
Real-time Monitoring of Patients
The practice of medicine is shifting towards providing proactive care to the patients by constantly monitoring patient vital signs and this is powered by the Big Data technologies. Wearable devices with sensors present the opportunity of interaction with patients making the doctors instantly aware about the changes in a patient’s condition.
The data from various monitors can be processed in real-time using machine learning algorithms, enabling physicians to make effective interventions and take lifesaving decisions.
Engaging patients as consumers
As information becomes increasingly available, patients are taking an active interest in their healthcare choices. For beginners, patients have become keener to evaluate services using information from the Web and other online channels. This highlights the importance of using analytics for risk-adjustment to provide the consumer with the accurate information to make informed decisions.
With increased information, patients are more engaged in their own treatments. They tend to play a role in collecting and sharing their own healthcare data with providers, which enables doctors to get access to the current state of the patient’s health. This also allows for proactive analysis, based on which doctors can adjust the treatment and prevent potential problems.
The healthcare industry is moving towards evidence-based medicine by using all clinical data available and factoring that into clinical and advanced analytics to achieve the triple aim of improving the patient experience, improving overall population health and reducing the per-capita cost of healthcare.
The ability to capture, store, and share all of the information about a patient together, provides a more comprehensive idea of a patient’s health condition. This, in turn, engenders better care coordination, improved population health management, and enhanced patient engagement and outreach.
The 360-degree view of the patient, made available by the Big Data technologies, is transforming the healthcare scenario by reducing errors in administering and prescribing drugs, by eliminating redundant and expensive testing, and even avoiding preventable deaths.
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