BIG DATA HEALTH INFORMATICS HOW TO

Research throughout all levels of accessible data, using various data mining and analytical techniques, can be used to help the healthcare system make decisions faster, more accurately, and more efficiently, all in a more cost-effective manner than without using such methods. The main level of questions that TBI ultimately tries to answer are on the clinical level, as such answers can help improve HCO for patients. TBI and the idea of combining data from all levels of human existence is a popular new direction in Health Informatics. In particular, TBI is specifically focused on integrating data from the Bioinformatics level with the higher levels, because traditionally this level has been isolated in the laboratory and separated from the more patient-facing levels (Neuroinformatics, Clinical Informatics, and Population Informatics). The scope of data used by the subfield TBI, on the other hand, exploits data from each of these levels, from the molecular level to entire populations

The tissue level is of analogous scope to the human-scale biology questions, the scope of patient data is related to clinical questions and the scope of the population data is comparable to the epidemic-level questions. In addition, within a given data level we will break down studies based on the type (i.e., level) of question a study attempts to answer, where each question level is of a relatively comparable scope to one of the data levels. These subfields do sometimes overlap (for example, a single study might consider data from two adjacent levels), but in the interest of minimizing confusion we in this work will classify a study based on the highest data level used (as this paper will be structured according to data usage). : Bioinformatics uses molecular level data, Neuroinformatics employs tissue level data, Clinical Informatics applies patient level data, and Public Health Informatics utilizes population data (either from the population or on the population). However, the scope of this study will be research that uses data mining in order to answer questions throughout the various levels of health.Įach of the studies done in a particular subfield of Health Informatics utilizes data from a particular level of human existence Research done in Health Informatics (as in all its subfields) can range from data acquisition, retrieval, storage, analytics employing data mining techniques, and so on. Neuroinformatics), Clinical Informatics, Public Health Informatics, and also Translational BioInformatics (TBI). There are numerous current areas of research within the field of Health Informatics, including Bioinformatics, Image Informatics (e.g. Health Informatics is a combination of information science and computer science within the realm of healthcare.

Data mining and Big Data analytics are helping to realize the goals of diagnosing, treating, helping, and healing all patients in need of healthcare, with the end goal of this domain being improved Health Care Output (HCO), or the quality of care that healthcare can provide to end users (i.e. The field of Health Informatics is on the cusp of its most exciting period to date, entering a new era where technology is starting to handle Big Data, bringing about unlimited potential for information growth. We will also analyze and examine possible future work for each of these areas, as well as how combining data from each level may provide the most promising approach to gain the most knowledge in Health Informatics. In addition to gathering data at multiple levels, multiple levels of questions are addressed: human-scale biology, clinical-scale, and epidemic-scale. This paper will present recent research using Big Data tools and approaches for the analysis of Health Informatics data gathered at multiple levels, including the molecular, tissue, patient, and population levels. The basic goal of Health Informatics is to take in real world medical data from all levels of human existence to help advance our understanding of medicine and medical practice.

BIG DATA HEALTH INFORMATICS HOW TO

However, there are a number of issues that arise when dealing with these vast quantities of data, especially how to analyze this data in a reliable manner. In addition, this information can improve the quality of healthcare offered to patients. The amount of data produced within Health Informatics has grown to be quite vast, and analysis of this Big Data grants potentially limitless possibilities for knowledge to be gained.

Big data health informatics