How can Big Data Analytics transform Healthcare with precision medicine?
Dr. Watson: “This is indeed a mystery. What do you imagine it means?”
Holmes: “I have no data yet. It is a capital mistake to theorize in advance of the facts. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
Sherlock Holmes’ art of rational deduction has new-found relevance amongst healthcare practitioners these days. However, present-day Watsons need not turn to Holmes, to draw ingenious deductions about their patient’s health. The onset of Big Data analytics enables healthcare professionals improve personalized treatment by leveraging the tremendous wealth of available patient data.
Staying well-informed is fundamental – especially in the Healthcare industry. Savvy usage of patient data can help optimize healthcare operations by adding clinical intelligence to the process. Assessing past patient records, progress reports, suitable methods of treatment, and other records is helpful in acquiring valuable information.
According to Gartner, Big Data is essentially, “high-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight, and decision-making.”
Let us now focus on the pressing aspects of Big Data analytics in the Healthcare industry.
Need For a Unified Information Database
One of the notable flaws hindering the analytical process in the Healthcare industry is poor documentation and segmentation of data. When dealing with huge numbers, easy accessibility makes processing faster and yields quicker results. Often data comes in unstructured sets and needs sorting before initiating the analysis for insights. Provided that the information is accurate, there needs to be a free-flow of information between different departments. In cases, where the system needs to gather data from various departments, a unified information database immensely helps in reducing redundancies.
Avoiding the Trap of Easy Data Input
Organizations often fall into the trap of producing results from easily available data. For example, an organization might already have basic patient data, collected to serve administrative purposes. They need to be conscious, that this data lacks precise attributes helpful in defining individual patient care. Utilizing such raw data for any sort of analysis is a futile attempt. Organizations should nullify such practices. Acquiring data relevant to the area of interest demands concentrated effort. The quality of data fed into the system has direct implications on the analysis delivered. Needless to say, the analysis is as accurate as input.
Complying with Regulations and Protecting Data
The use of Big Data in the Healthcare sector needs a vigilant eye. Each attribute recorded – right from the patient’s name, vital health details, past records etc. is sensitive information. Deciding the range of patient data to disclose, and the data which needs safeguarding is of paramount importance. Organizations need to strictly comply with the stipulations pointed out in the Health Insurance Portability and Accountability Act (HIPAA), issued by the United States Department of Health and Human Services. This governs the protection of patient data and highlights the principles of use and disclosure, individual rights, non-compliance penalties etc.
Though there are certain challenges to tackle, Big Data analytics is a promising advancement for the healthcare industry. Many healthcare organizations already have the infrastructure in place. However, there needs to be a paradigm shift at the grassroots level, commencing from a) documentation of data under a unified platform, b) avoiding the trap of easy data input to avoid misleading analysis, c) and aligning to governing (HIPAA) standards to safeguard patient data.
Overcoming these challenges, would help curious Watsons carry out quicker analysis – ushering in a culture of favorable personalized treatment. Given the technological muscle it brings, Big Data analytics heralds a new age of precision medicine, and quality patient care, in the healthcare industry.