The Role of Big-Data in Healthcare sector
Big data is a broad term that refers to an extensive collection of complicated data, whether unstructured or organized. The collected data could be efficiently.
Updated
On this page
Key takeaways
- The collected data could be efficiently utilized to reveal additional insight and to address business issues that were previously unsolvable using traditional analytic or software.
- It can identify methods and processes that provide inferior results or are too expensive in comparison to the results.
- On a broad level, healthcare stakeholders may depend on big data and predictive analytic to address critical problems like as readmission rates, high-risk patient care, staffing difficulties, and medication mistakes.
What is Big Data?
Big data is a broad term that refers to an extensive collection of complicated data, whether unstructured or organized. The collected data could be efficiently utilized to reveal additional insight and to address business issues that were previously unsolvable using traditional analytic or software. Typically, data scientists use artificial intelligence-powered analytic to examine these massive databases constructively to find relationships and correlations that might give valuable business insights.
Big Data in Healthcare Sector #
In healthcare, big data refers to the application of prescriptive, predictive, and descriptive analytic services to derive actionable insights from healthcare data. Three objectives underpin big date’s use in healthcare:
- Improve clinical results through the use of patient data;
- Boost employee productivity by using operational data;
- Utilize financial data from healthcare to help hospitals or healthcare institutions enhance their income stream.
The “Three Vs” are the pillars of big data technology - volume, velocity, and variety. These three characteristics or aspects define effective big data analytic in healthcare.
- Volume refers to the massive quantity of data generated by healthcare organizations via their applications, portals, websites, and EHRs (electronic health records)
- The term “velocity” relates to the rate at which datasets are created and processed.
- Variety refers to the numerous sorts of data that we may currently produce, collect, and evaluate.
Apart from these three, big data has two new Vs: veracity and value.
The term “value” refers to the monetary value of the data being created, gathered, or evaluated.
Finally, but certainly not least, veracity refers to the reliability, integrity, or quality of healthcare organizations’ data generation, collection, and analysis.
Big data is projected to enter the healthcare industry more quickly and deeply than it did in other sectors such as media, financial services, and manufacturing. This is unsurprising given that healthcare is the largest private sector employer in the United States and accounts for 20% of GDP.
Indeed, it is anticipated that the worldwide healthcare big data market would expand gradually at a compound annual growth rate (CAGR) of 22.07 percent to reach around $34 billion by 2022.
Another comprehensive analysis predicts that big data in healthcare will grow at an astounding 36 percent compound annual growth rate through 2025.
The term “big data in healthcare” refers to the massive amounts of health data gathered from a variety of sources, including electronic health records (EHRs), medical imaging, genetic sequencing, mayor records, pharmaceutical research, wearable, and medical devices. It differs from typical computerized medical and human health data used for decision-making in three ways: It is available in unprecedented volumes; data travels at a rapid rate and encompasses the vast digital universe of the health business; and, because it originates from a variety of sources, it is extremely varied in structure and character.
Applications of Big data #
The major application of big data in the field of health care sector are discussed below:
Maintaining patient health and preventing illness and disease should always be a top concern:
- Consumer gadgets such as the Titbit activity tracker and smart watches, monitors an individual’s physical activity and can also report on particular health trends. The resultant data is already being uploaded to cloud servers, where it is being used to tell clinicians about their patients’ general health and wellness.
- Titbit has already collaborated with United Healthcare, which pays its insured members with up to $1500 per year for frequent exercise. The One Drop app from Informed Data Systems for Android and Apple is causing substantial improvements in A1c levels in persons with diabetes. Meanwhile, Apple’s HealthKit, CareKit, and ResearchKit applications utilize the technology built into Apple’s mobile devices to assist patients in managing their diseases and to enable researchers to collect data from hundreds of millions of users globally.
Expanding diagnostic services enables patients to receive expert treatment more easily: Apes for mobile devices, such as Etna’s Triage, advise people about their medical conditions based on aggregated data and even recommend them to seek medical treatment depending on their input.
- Apple has teamed up with Stanford researchers to examine if the Apple Watch’s heart sensor can be used to detect atrial fibrillation, a disease that claims roughly 130,000 lives each year in the United States. If the gadget is successful in identifying the illness, Apple can alert wearers to the need for medical treatment.
- Propeller Health utilizes a Bluetooth-enabled sensor that connects to inhalers and spirometer used by individuals with asthma or COPD. The business monitors ambient conditions at sensor locations and delivers information directly to patients’ phones, enabling them to gain a better understanding of the reasons of their symptoms and take preventative steps. Additionally, the business sends reminders when prescriptions should be taken. Propeller says that patients are reporting 79% fewer asthma episodes and 50% more symptom-free days as a result of its 34 peer-reviewed papers.
Cost savings: Medical data provides clinicians with more insight, which translates into improved patient care, shorter hospital stays, and fewer admissions and readmission.
- Additionally, analysis of healthcare big data helps to a better understanding of patient cohorts at highest risk for sickness, allowing for a proactive approach to prevention. In brief, study of healthcare big data enables the identification of outlier individuals who spend much more health services than the average. It can identify methods and processes that provide inferior results or are too expensive in comparison to the results.
- The knowledge gained through big data analysis provides healthcare practitioners with clinical insights that would not be available otherwise. It enables them to prescribe therapies and make clinical decisions more precisely, removing much of the guesswork associated with therapy and resulting in cheaper costs and improved patient care.
Importance of big data in health care sector #
Yes, there is growing enthusiasm for the potential of big data in healthcare, and investment in analytic is expanding. However, according to a recent Dimensional Insight research, 56% of hospitals and healthcare institutions lack adequate big data governance or a long-term analytic strategy. Here are some of the reasons why big data is critical for healthcare:
- Inadequate data governance results in record duplication, unclaimed reimbursements, financial benchmarking issues, and other operational inefficiencies. That is something that big data can correct!
- Patient care is also becoming more complicated, and without adequate analytic, it becomes increasingly impossible to offer high-quality, safe, and effective patient care. Numerous healthcare companies have had inconsistencies between their clinical and accounting departments as a result of data errors and incompatibilities.
- In healthcare, big data is widely utilized to assist in identifying and managing patients who are both high-risk and expensive.
- Indeed, 71 percent of respondents to the aforementioned research reported seeing discrepancies between data from several sources inside their company, most notably financial, clinical, and administrative information. Additionally, 51% of executives discovered discrepancies between data from several clinical departments.
- Additionally, big data is utilized to identify high-risk regions where patients may get more efficient treatment, thus lowering costs and increasing patient satisfaction.
- By assisting payers and healthcare providers in identifying high-risk and costly patients, big data and analytic technologies enable these people to get appropriate intervention and save money on preventative treatment well in advance.
Challenges to big data: #
- The Difficulties of Data Aggregation To begin, patient and financial information is often dispersed among many payers, hospitals, administrative offices, government organizations, servers, and file cabinets. Bringing it all together and preparing for future collaboration amongst all data providers when new data is generated takes considerable preparation. Additionally, each participating business must comprehend and agree on the kinds and formats of big data to be analyzed.
- Management Obstacles Finally, achieving the promise of big data analytic in healthcare would require companies to change their business models. Data scientists will very certainly be required, as will IT personnel with the necessary expertise to operate the analyses.
- The scalability of data is also a problem in this sector, that needs to be taken care of.
Road ahead #
Big data is just now starting to transform healthcare and propel the sector ahead on a number of fronts. The advances in medicine, technology, and finance that big data in healthcare offers will enable healthcare companies to enhance patient care and generate value. However, it will need stakeholders — providers, payers, pharmaceutical manufacturers, government and politicians, as well as scientific and research communities — to cooperate and innovate in order to reinvent their systems’ design and performance. They must develop the technical infrastructure necessary to store and consolidate the enormous amount of healthcare data expected to reach 2,314 exabytes by 2020, according to industry experts. Additionally, they must invest in human capital—information technology professionals, data scientists, data architects, and big data engineers—to lead us into this new and exciting frontier of human health and well-being.
Final verdict #
Big data has the ability to completely transform healthcare. Healthcare companies should make significant investments in big data in order to improve patient outcomes, reduce costs, and increase efficiency across all departments. More importantly, big data will enable doctors and hospitals to provide more focused treatment with improved outcomes. For pharmaceutical firms, big data is a catalyst that will aid in the creation and development of more creative medicines and products.
On a broad level, healthcare stakeholders may depend on big data and predictive analytic to address critical problems like as readmission rates, high-risk patient care, staffing difficulties, and medication mistakes.
Related reading