The Internet has become an everyday reality. In the network, we draw information, work, have fun, learn. We talk about ourselves, leaving a daily mark, like thousands of other people. We are drowning in the flow of information and constant call to action.
The constant desire to keep abreast of news, discoveries, events no longer leaves us for a minute. We process large flows of information and risk drowning in it.
But many have already heard the expression Big Data – big data. And, perhaps, this is our lifeline in the modern information world.
In this article, we will look at how to make an app HIPAA compliant and what does BigData has to do with it.
So what is Big Data?
If we pay attention to today’s reform of the US health care, we see the possibility of more delicate work with the usage and learning of Big Data. Its authors adhere to the concept of “accountable assistance”, in the framework of which, first of all, the effectiveness of the treatment will be evaluated.
Thus, thanks to the processing and analysis technologies of big data, they will pay not so much for the treatment process as for the ability to quickly heal and maintain the health of patients.
Another critical area was cost forecasting. It is based on a multivariate analysis of statistics such as the number of repeated visits, the percentage of complaints about specific doctors and departments, the prevalence of various pathologies, the number of patients with chronic diseases, as well as epidemiological indicators.
Medical analytical tasks that can be solved using the analysis of “big data” can be of various types depending on the level of maturity (ascending):
- descriptive analytics (answering the question “What happened?”);
- diagnostic analytics (“Why did this happen?”);
- predictive analytics (“What will happen in the future?”);
- prescriptive analytics (“What needs to be done to prevent this from happening?”).
With the increasing complexity of tasks, the complexity of the analytical system and algorithms increases, as well as the number of necessary data sources – from simple information from medical histories and biometric monitoring data to genomic and family data and even information from social networks.
Modern technologies come to healthcare that supports all standard methods of working with data. This is the design and filling of multidimensional OLAP cubes, the ability to synchronize OLTP and OLAP repositories in real-time, the rapid development of dashboards using a library of visual components, the ability to analyze unstructured text data and conduct predictive analytics.
The analysis made by McKinsey’s report shows how “big data” can not only create an additional source of cost compensation but also improve the quality of medical care. At the core of Big Data can be combined information stored in four primary data sources, which today are not interconnected. They are:
- data obtained during research and testing;
- data from clinics for medical histories and diagnostics;
- data on patient behavior, their purchases, reviews, data from home medical devices and even from clothes and shoes, such as sneakers with sensors;
- data from medical institutions on the provision of services, pharmacies on the release of drugs, information on prices in the healthcare market.
Based on the analysis of all these data, it is supposed to develop the following areas of Big Data use:
1. The operational activities of medical institutions. There is an opportunity to study the effectiveness of treatment by processing all available information about treatment practice. Based on the analysis of all known medical histories and diagnostics, the method of doctors will include the widespread use of decision support systems that will provide the clinician with unprecedented access to the experience of thousands of colleagues across the country. Methods of personal and preventive medicine based on remote monitoring of patients will lead to a significant reduction in costs and an increase in the quality of life. The proliferation of various sensors of the human body’s activities connected to wearable gadgets reduces the need for laboratory tests, prevents unexpected complications, and an automatic reminder of the need for independent treatment and prophylactic manipulations will increase the quality of the prescribed medication;
2. Pricing and payment system. Analysis of accounts and receipts using automatic procedures based on machine learning and neural networks will reduce the number of errors and thefts when paying. The formation of price plans that take into account the real capabilities of the population and the need for services also increases the total income from patients. Only systems working with “big data” allow us to switch to a payment based on the quality of assistance provided and jointly regulate the costs of medicines and medical staff;
3. Research and development. The most significant effect here should be expected from the new predictive modeling capabilities in drug development. Statistical algorithms and big data tools have no less influence on the planning of clinical trials and the involvement of patients in such experiments. Processing the results of such tests is another crucial big data application. Innovations in personalized medicine now occupy a special place in research and development in healthcare. Based on the processing of gigantic amounts of genetic information that are becoming more accessible to humans, doctors will be able to prescribe unique drugs and treatment methods. Finally, the development of patterns of diseases will provide reasonable prognostic estimates of the growth of various types of viruses, identify risk profiles and not only carry out preventive measures but also predict the need for the development of treatment methods that are effective for future types of diseases;
4. New business models. Based on digital data in healthcare, these models can complement existing or even compete with some of them. These are data aggregators that supply analyzed and assembled data blocks that satisfy specified conditions to third parties. For example, all medical histories of patients who have used a particular pharmacological preparation are essential for pharmaceutical enterprises, and they are ready to buy such data. Other potential new business models are online platforms for patients and doctors, medical researchers and pharmacologists;
5. Mass screening and prevention and detection of epidemics. This direction is based on Big Data. The development of technology allows you to build both geographical and social models of public health and predictive models of the development of epidemic outbreaks.
Although medicine (domestic in particular) is one of the industries in which the “big data” management technologists give the most vivid effect, many still treat them with skepticism, perhaps due to the not always understood business benefits and lack of specialists.