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Healthcare industry data analytics

In health domain and in any other field, data are of paramount importance. They are found on health care books and laboratory analysis sheets. Unfortunately, they sometimes seem cumbersome and their understanding is not always obvious. However, their analysis could permit to easily analyze a medical situation, to facilitate decision-making and, above all, to predict future scenarios. In the following lines of this article, let’s discover more about the subject.

What is healthcare data analytics?

In general, analyzing data consists of giving a graphic and literary interpretation of numbers for a better understanding. This practice is also valid in the healthcare sector. It consists of the analysis of informations derived from to the physical or mental health which is related to the physical state of a person. There are two important categories of analyzable data :

Health data by nature.

The health data by nature will take into account the types of diseases, medical history, prescriptions and results of examinations carried in real time.

Secondary data.

In addition to this first category of data, we also have the secondary data. In fact, those data have an indirect influence on our health. This is for example the number of steps taken per day. Even if this data has no direct indication on our health, it still contributes to the proper functioning of the Heart and to the good circulation of the blood.

Unfortunately, all of those categories of data are not identical and are extremely difficult or impossible to analyze by current data analytics software. Thus, health data analytics platforms such as LOAMICS are essential tools that store all this valuable information in one place. This is an opportunity for physicians and healthcare data analystics to work in better working conditions. This opportunity would also enable researchers and the health system to improve the quality of care they provide to patients.

What Is the Role of Data Analytics in Healthcare?

The main role of data analytics in Healthcare is to digitally map a medical care pathway. They will provide an overview of important medical elements to prevent adverse events.

Data analytics for doctors

The data analytics will help physician, practitioners and analyst better understand and organize the full range of therapeutic areas. This will give them access to data that indicates the risk for a patient to be readmitted or hospitalized. Preventive measures may then be taken to avoid this situation. This will, for example, enable data analyst to generate models that will guide physicians along the clinical pathway that best suited a patient.

Data analytics for hospitals

By optimizing medical pathways, hospitals can make economic gains of their business by reducing the time it takes to provide care to a patient. As a result, they will be able to receive a significant number of patients and reduce expenditures on social services. And all this while delivering qualitative services to patients. Analysing data healthcare can help hospitals predict the resurgence or the fall in patient flow to emergencies. They will then be able to establish rigorous health system for a better health management system.

How to use Healthcare Analytics?

Healthcare Analytics is a way of introducing big data recording in Healthcare domain. It Can be used to upgrade the heed of patients and allows the treatment of each patient to be special to him and personalized. It also allows getting rapid diagnoses with reduced margin of error and insurance measures. Aside from these multiple uses, healthcare analytics can also lower the cost of treatments, predict the onset of epidemics, and better preventable diseases.

Let’s highlight a few other usefulnesses of data analytics in healthcare such as the preventive analytics. In fact, anticipate risks during the processes of data analytics help doctors to quickly recognize common manifestation, cause and effect of a disease. This also enable also them to have a quick diagnostic and solution as well, when a patient could have some risk of having a health problem.

Improving patient satisfaction by analyzing healthcare data is also possible. The information obtained can enable doctors to know how to treat and care for their patients in a personalized way.

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The use of the electronic record storages sheets allows economy and increases productivity.
It also allows to reduce the waste of time which occurs when one finds oneself to search heaps of file.
Health professionals can access the same files at any time without having to move documents from one establishment to another.

Artificial intelligence (AI) and natural language processing represent serious future paths for a better healthcare system. Indeed, AI intervention in healthcare will introduce robots capable of thinking and acting for the well-being of patients. They can then make a diagnosis, perform surgical operations or administer vaccines. They may also use existing data to identify pathologies or propose appropriate medical pathways for a patient.

Apart from AI, the treatment of language is also a boon for the medical field because it will make it possible to analyze manuscripts made by man. This new technology will thus be able to detect and enhance the relevant information that is present on patient’s medical books. And most important, the analysis of these qualitative data science and machine learning will play a crucial role in advancing health conditions.

The health care system is a sensible field that generates a huge quantity of data. Most of the time, those data are not exploited and are not easily understandable. Fortunately, healtcare data analysis helps to understand them and interpret those qualitative and quantitative data. In fact, understanding those data present positive impact on hospitals, patients and physicians. Most important, it helps to give a better healthcare to patient by using technology and thus to improve the caregivers work conditions.