The Coronavirus Pandemic has spurred interest in big data to track the spread of the fast-moving pathogen and to plan disease prevention efforts. But the urgent need to contain the outbreak shouldn’t cloud thinking about big data’s potential to do more harm than good. Here is how big data analytics address COVID-19 concern in the healthcare industry.
They could also lead to draconian restrictions that disproportionately impact the rights of those under- or misrepresented by the data. In Israel, the government’s cell phone location-tracking program has caused complaints that the authorities are erroneously confining people to their homes based on inaccurate location data.
While the capacity of big data to help curb the coronavirus outbreak is, at best, uncertain, its risks to privacy are immense. Governments and companies have cited the anonymization of personal data as a key privacy safeguard, but multiple studies show that this may only delay rather than prevent the person’s re-identification.
Location data is particularly vulnerable since it can be combined with public and private records to create an intricate and revealing map of a person’s movements, associations, and activities.
COVID-19 has arrived with consequences that are grave and unsettling. Big Data lies at the heart of efforts to comprehend and forecast the impact that Coronavirus will have on all of us.
The near real-time COVID-19 trackers that continuously pull data from sources around the world are helping healthcare workers, scientists, epidemiologists and policymakers aggregate and synthesize incident data on a global basis.
There has been some interesting data resulting from GPS analyses of population movement by region, city, etc., which ultimately helps provide a view of the population’s compliance — or lack of compliance — with social-distancing mandates.
There are many opportunities to make the use of Big Data more impactful in situations like these as a society and as an industry, though no one yet been able to effectively leverage the power of Big Data in search of a cure.
Ideas such as creating large scale COVID-19 Real World Evidence (RWE) studies that pull data from a variety of real-world sources — including patients now be treated in the hospital setting — could help accelerate the development of treatments in a more patient-centric and patient-friendly way.
According to Goldstein Market Intelligence research, the market size of big data analytics in the healthcare industry was valued at USD 16.90 billion in 2017 and is projected to reach USD 68.20 billion by 2025 and is expected to expand at a CAGR of 18.6% over the forecast period.
Based on types of analytics type, the descriptive analytics segment is anticipated to account for the largest share of the big data healthcare analytics market and continue to dominate the big data analytics in the healthcare industry during the forecast period.
Based on geography, North America is expected to dominate the market followed by Europe during the forecast period, due to a rise in advancements in IoT and an increase in the demand for analytical models on patient information for better service delivery, government policies.
Every day, people working with various organizations around the world are generating a massive amount of data. The term “digital universe” quantitatively defines such massive amounts of data created, replicated, and consumed in a single year.
The digital universe in 2017 expanded to about 16,000 EB or 16 zettabytes (ZB) and would expand to 40,000 EB by the year 2020.
National Institutes of Health (NIH) recently announced the “All of Us” initiative that aims to collect one million or more patient’s data such as EHR, including medical imaging, socio-behavioral, and environmental data over the next few years. EHRs have introduced many advantages in handling modern healthcare related data.
The advantage of EHRs is that healthcare professionals have an improved access to the entire medical history of a patient. The information includes medical diagnoses, prescriptions, data related to known allergies, demographics, clinical narratives, and the results obtained from various laboratory tests.
Major factors driving the growth of big data analytics in the healthcare sector include substantial upsurge in demand for financial analytics. There is an increased demand for discovering structured and unstructured data existing in the healthcare industry, declining costs, and accessibility of big data software and services. There is also augmented adoption of novel technologies for data analytics in healthcare industry transformations, worldwide.
Big Data Analytics have already made a significant impact on grounds related to healthcare: medical diagnosis from imaging data in medicine, quantifying lifestyle data in the fitness industry, to mention a few.