Business Analytics

Business Analytics

Understanding healthcare, hospitals can benefit most from the existing patient, treatment and related information if it is used in an effective way to do the analysis and then focus on improving the RoI of marketing, operations and administration departments of hospitals.
While healthcare has taken longer than other industries to incorporate the use of analytics, such adoption is radically transforming the delivery of healthcare for the better. Now that the necessary data pieces are being put into place, analytics can, and must, play a pivotal role in the transformation of indian healthcare into an efficient, value-driven system.
By investing in the implementation of healthcare information technology, and by shifting the focus from quantity of treatment to overall value in healthcare, the stage is set for the application of advanced analytics.
Data Generation:
In healthcare industry, data is generated through various systems already deployed in hospitals, diagnostics, clinics viz. are Electronic Health Records(EHR), laboratory Information System(LIMS), systems in Diagnostics Labs, Pharmacy etc. Most clinical information systems were not designed with analytics in mind and as such, do not necessarily make it easy to “get the data out.
Data Extraction:
Most clinical information systems were not designed with analytics in mind and as such, do not necessarily make it easy to “get the data out. While there is no shortage of data standards in the healthcare industry, there is a distinct lack of uptake of those standards by the health IT community. Within a given clinical information system, vendors are free to define their own data structures, and often do. The same element may be stored and coded in myriad ways by vendors, and sometimes even within different systems from the same vendor.
Business Analysis to help revenue generation
Business analytics in healthcare industry can be helpfull to generate revenue. The application of analytics in healthcare requires the transformation of data into usable information that can be relayed back to end-users. The adoption of EHRs and other electronic data mechanisms makes the application of analytical tools more tractable by providing the basic electronic data upon which to act. This coincides with the rise of the “data scientist,” a term sometimes applied to those who use analytics and can serve as a one-stop shop for data management, analysis, and interpretation of electronic data. In healthcare, this is particularly important for translating electronic bits into meaningful data which can help a hospital generate more business and profitability to justify the RoI.
Understanding the healthcare sector and its know how, we have experienced the challenges w.r.t implementation of analytics in hospitals and have avoided the pitfalls of this critical activity.
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