Harnessing Big Data to Improve Healthcare
The application of Big Data across different industries has seen rapid growth in recent times and the Healthcare industry is no different. Many countries now use Big Data as an important database that provides tools to manage, analyze, and accumulate large volumes of structured and unstructured data. The objective is to generate information that could be used for the treatment and exploration of diseases and improve healthcare overall.
Big Data differs from traditional electronic data for medical and healthcare decision making in the following three ways:
- The extraordinary volume of data available
- The high Variability in nature and structure
- The high velocity at which the data moves within the healthcare universe
These are the 3 Vs that define the incredibility of Big Data and its potential for the healthcare industry.
The implementation of Big Data analytics in the Healthcare vertical can bring about manifold structural development in sharing patient’s medical record data, general epidemics reports among public or other healthcare institutions which will definitely help in improved personal care for the one in need at the right time.
Like two sides of a coin, there are some positive and negative aspects in implementing the technology of Big Data in Healthcare. While the positives outweigh the negatives, the latter’s presence cannot be put aside.
- Improved identification of diseases
- Proactive prevention of disease
- Enhanced clinical trials
- Improved care
- Heightened efficiency
- Reduction of cost
- Reduction of waste
- Prediction of disease
- Optimal utilization of resources
- Enhanced medical research
- Adaptation and implementation of the technology by public and healthcare service providers.
- Classification and accommodation of data.
- Data integration
It is imperative that the challenges be overcome to utilize the offering of the technology in the healthcare foreground to its maximum potential. The concept of Big Data in Healthcare has always had an ever-dynamic implementation.
A plethora of data from various sources including EHR, Pharmacy, Medical devices, Wearables, Insurance companies, Hospitals, IoTs, and more, provide the medical record transparency to use those data for predictive analysis and research.
The understanding and prediction of diseases requires a study of myriad structured or unstructured data from clinical or non clinical modality. Here, the study of the characteristic of data and analytics performed on it in relation to medical science is the approach that aims for a revolutionary change in the Healthcare industry and the treatment of the available data resources.
The Capabilities of Big Data in Healthcare
Improved treatment and quality of life can be one of the major advantages of using health informatics to prevent death, disease development, and epidemics. Big Data can be beneficial in the diagnosis and detection of a patient’s overall medical record for faster development of treatments and health decision making with updated health information.
Also without proper data controlling channel there is always a threat of loss or misinterpretation of data, thereby compromising the accuracy and efficiency of the data. Big Data comes in the picture here. It saves the extra time and cost of repeated medical tests on the patient.
For instance, let’s assume a patient is diagnosed with diabetes and referred to a specialist in a different healthcare facility. The person need not run the same test again as the result from the previous test is already available, saving both time and money. The healthcare service providers, too, can run the initial round of treatment without further delay.
However, nowadays, patients want an active participation in their healthcare decisions so the transparency this advanced technology could bring to the healthcare sector is incredible. There will be a reduction in the amount of fraudulent cases especially in Insurance claims as the data management will be secured.
In a 2015 report by the Malaysian National Health and Morbidity Survey, they revealed that 17.5% of those who are 18 years of age and above have diabetes in 1996 as compared to 11.7% in 2006.
These kinds of raw information are available on the web. However, to perform meaningful analytics and to draw comprehensive outcomes for better Healthcare facility is what the need of the hour is.
Another very important usefulness of Big Data is easy access to real time result. Yes, errors can be identified immediately and troubleshooting is made a little less complex. In consideration of a patient’s medical records the caregiver tends to look for the ‘recentness’ of data – the recent Xray or the recent blood report which may sometimes turn out to be crucial in providing with the actual required information.
Whereas, implementation of Big Data will cater to this need as access to ‘medical history’ will be handy. The information pattern distributed across the network facilitates quick intervention for effective healthcare delivery.
Addressing the Challenges of Big Data in Healthcare
The major challenges in the implementation of Big Data in Healthcare lie in the collection, protection, sharing, and usage of data. There will be an enormous amount of data available and the organizations will have to deal with all the critical information with the utmost protection.
This database could easily pose a threat to privacy, falling in the hands of hackers and leading to cyber phishing and data theft. This is why the accessibility of the data should be constantly reviewed.
Under no circumstances should the security of the database be compromised while sharing data. This could turn into a major concern unless there is a properly developed security software that can be implemented by the healthcare operators.
In 2014 medical records accounted for 43% of stolen data and the Healthcare sector has seen the biggest increase in data theft since 2010, reported by Berkeley University of California.
The storage of the data is another major loophole. The cloud storage must be spacious enough to store a huge bulk of data. And, this storage needs to be in word document format as well as graphics, X-Rays and MRI’s. The objective is to facilitate effective decision making without having to rummage through piles of unorganized data or searching for the right format and not finding any.
Most data are fragmented and dispersed among various stakeholders. In this case, stakeholders are pharma vendors, patients, doctors, clinics, etc. Data needs to be uploaded to a ‘warehouse’ to generate and disseminate information via Big Data. There is also a need to apply technology 2.0. It is still an arduous task to find a data scientist with the capabilities required to transform the healthcare data scenario effectively.
The Healthcare outlook can be revolutionized with the adoption of Big Data in so many ways! This includes personalized care, improved clinical treatment, heightened drug discovery, safety management. Access to better data minimizes risk and paints a clearer picture for the caregiver. Big Data is definitely here to stay despite the few challenges it faces. This technological advancement has immense potentialities and holds the key to the future of the healthcare field.