Big data is making huge strides in the healthcare sector and is transforming medical treatment
Big data continues to revolutionize the way we analyze, manage, and use data across industries. It’s no surprise that one of the most notable sectors where data is making big changes in healthcare.
In fact, the onset of a global pandemic has accelerated innovation and adoption of digital technology, particularly in big data and big data analytics. This enabled healthcare providers to reduce treatment costs, avoid preventable diseases, predict outbreaks of epidemics, and improve the overall life quality. On the flip side, the same events have also exposed many weaknesses of the healthcare sector. Here we outline the impact of big data and data analytics in healthcare as well as give a few examples of key applications of big data in the healthcare sector.
Big Data in Healthcare: Promise and Potential
A report from IDC shows that big data is expected to grow faster in healthcare than in other industries like financial services, manufacturing, or media. It’s estimated that the healthcare data will see a compound annual growth rate of 36% by 2025.
The international big data market in the healthcare sector is estimated to reach $34.27B through 2022 at a CAGR of 22.07%. Globally, it’s estimated that the big data analytics sector will reach more than $68.03B by 2024, driven massively by ongoing North American investments in practice management technologies, health records, and workforce management solutions. Recent findings from McKinsey & Co hint that big data in healthcare can save us between $300B to $450B each year.
Big data in healthcare is present across multiple sources – starting from wearable devices to electronic health records and server logs of search engines. The next big thing is knowing how to put this information to good use. With advanced analytical tools and proper storage at hand, major services in the healthcare system, including healthcare, pharmaceutical manufacturers, medical staff, patients, etc., can reap a number of benefits. In simple terms, medical providers can significantly enhance medical outcomes. Patients become healthier, healthcare organisations can save costs and improve the efficiency of operations, and pharmaceutical manufacturers can make more educated decisions.
4 Key Applications of Big Data Analytics in Healthcare
Information obtained from big data analytics provides healthcare experts with valuable insights that were not possible before. A great amount of data is applied at every step of the healthcare cycle: from medical investigation to patient experience and outcome.
1. Big Data in Diagnostic Predictions
Usually, when a personal injury lawsuit is filed, the injured person attaches documents, including a medical report, a police report, and medical expenses. But to sue someone and win the case, legal professionals have to appoint an expert to evaluate all the records and ensure they’re valid, process the claim, and pay it out. However, this process isn’t just unnecessarily long but also very tedious since it’s reliant on human labour.
Predictive analytics reduces the amount of time needed to process the information, making it more time-efficient and saving on salaries. AI-powered systems use the generated data to predict the outcome of personal injury cases that are ordinary and simple to handle.
This process involves feeding AI systems with data on past cases that are similar in order to analyze and identify patterns in how the past claims were solved.
2. Big Data in Personal Injury Claims
Usually, when a personal injury lawsuit is filed, the injured person attaches documents, including a medical report, a police report, and medical expenses. But to sue someone and win the case, legal professionals have to appoint an expert to evaluate all the records and ensure they’re valid, process the claim, and pay it out. However, this process isn’t just unnecessarily long but also very tedious since it’s reliant on human labour.
Predictive analytics reduces the amount of time needed to process the information, making it more time-efficient and saving on salaries. AI-powered systems use the generated data to predict the outcome of personal injury cases that are ordinary and simple to handle.
This process involves feeding AI systems with data on past cases that are similar in order to analyze and identify patterns in how the past claims were solved.
3. Big Data Improves Patient Engagement
Increasingly more consumers– and hence, potential patients – are interested in wearables that record every step they take, sleeping quality, their rates, etc., on a daily basis. All this critical data can be coupled with other trackable data to uncover potential health risks lurking. Tachycardia and chronic insomnia can signal the risk of heart diseases, for instance.
Today, a number of patients are directly involved in monitoring their own health, and incentives from health insurers can encourage them to lead a healthier lifestyle (such as giving money back to people using wearables).
The application of IoT devices and smart wearables, which healthcare providers now recommend, is among key healthcare technology trends. These technologies automatically collect health metrics and offer valuable indications, removing the need for patients to travel to the nearest medical facility or for patients to collect it themselves. It’s clear that the latest tech helped generate tons of valuable data that can help doctors better diagnose and treat common and complex health problems.
4. Big Data in Telemedicine
We can’t talk about telemedicine without mentioning big data and its role. With the application of high-speed real-time data, medical providers can perform operations while physically being miles away from the patient. While this might sound strange, it’s as real and possible as it could be. Big data has made possible not only robot-assisted surgeries but also accurate diagnosis, virtual nursing assistance, and remote patient monitoring.
Big data and telemedicine have made it possible for patients and doctors to :
- Avoid waiting for lines
- Reduce unnecessary consultations and paperwork
- For patients to be consulted and monitored anywhere and anytime
- Prevent hospitalization
- Improve the quality of service and reduce costs
The future of the healthcare sector looks bright enough thanks to the appearance of big data analytics and machine learning that are constantly being used to gain real-time patient insights, necessary in a fast-paced world. So far, as technologies advance, these invaluable functions will only get stronger – the future of healthcare is here, and it lies in data.
