Descriptive analytics are the tools used for the collection and analysis of historical data and use that to find meaningful patterns and results. In case of the healthcare industry, the insights can be in terms of the number of disease cases, medicines used to treat certain ailments, average stay in hospital, etc. Descriptive analytics can prove useful when personalized healthcare has to be provided to patients. Past data metrics can be formed to provide a better visualization of the results and draw the diagnosis or trends to analyze current condition and predict further steps required.
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The market for healthcare analytics is in the growth stage due to government initiatives to make the industry low cost, better quality- that can be achieved through the use of analytics. This is made possible since the diagnosis can be made more clearly and accurately, avoiding the costs of having undergone unnecessary treatment.
Analytics is of three types- predictive, descriptive, and prescriptive. Out of these, descriptive analytics lies on the bottom-most level of the big data value chain. It provides the ability to analyze data quantitatively and present the results in a form easy to understand. It largely deals with events that have already happened in an attempt to diagnose the issues of new and existing patients.
Data mining methods like decision tree making, neural network formation, clustering, and time series analysis are used to draw insights from the data available- but the approaches are still somewhat restricted to academia and still has apprehensions faced from the industry. One way to appeal to the healthcare providers is to present an aggregate system in the form of an enterprise data warehouse containing clinical, financial, and patient related data.
The healthcare industry is in the transition stage from volume-based medicines to value-based medicines. The factors pushing this growth forward is intervention of government through policy implementation like EHR, technological advancement, growth in the sector due to emerging need for personalized treatment, etc.
However, the initial investment amount is large- due to which the entry barrier in the industry is set pretty high. Moreover, there is a need gap for trained IT professionals in healthcare due to which the backward support required is not there. Also, there is still apprehension in terms of sharing information with vendors and analytics companies.
The Global Healthcare Descriptive Analytics Market can be segmented based on the following attributes:
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