Dec 05, 2021

Basics of the Healthcare Big Data Warehouse

  • By RICKY M.,
  • 419 Views
Basics of the Healthcare Big Data Warehouse

There is only one ultimate goal of most of the health IT infrastructure to provide more sophisticated insights, answers, and suggestions to the decision-makers at the care point. This goal has resulted in the evolution of the basic electronic health records to the new modern technologies such as the health information exchange (HIE), clinical decision support (CDS), business intelligence ecosystem and big data analytics dashboard.

The healthcare industry has faced many challenges in developing an integrated, interoperable data pipeline from patchworks of legacy tools, best of breed offerings, and multi-vendor products. Some of these challenges of the industry are much greater than the one involved in the healthcare data warehouse.

The healthcare data warehouse is a centralized platform for the data repository that enables organizations to store, integrate, recall, and analyze information. The organizations of the healthcare industry may wish to use their warehouses to perform clinical analytics by using the patient’s data stored in their EHRs (Electronic Health Records). This will also enable these organizations to improve their financial instability through forecasting by diving into the business intelligence and revenue cycle analytics using claims and billing codes.

Healthcare industry analytics is almost a limitless field to explore, however, it can be broken into three major areas, which are:

  1. Descriptive Analytics: It is the story of what has been already happened. This analytics can help to record the growing number of patients who visited the emergency department last year or it can also track how much money was spent on the overtime for nurses within a given period of time. It shows real-time data rarely, it can also delay the data for several weeks or months but apart from these things this analytics still provides an incredible amount of insight into the operations of a hospital or the clinics.
  2. Predictive Analytics: The EHR (Electronic Health Record) has been enabled to provide basic descriptive reporting that can be used for analytics. But for entering predictive analytics the organizations may require a data warehouse that demands real-time data manipulation capabilities and a high degree of integration and interoperability between the disparate systems.
  3. Prescriptive Analytics: It is the ultimate goal of every data warehouse owner or provider, but it is currently beyond the scope of the majority of healthcare organizations. Rather than just describing what has happened or predicting what might happen, this type of analytics delivers actionable suggestions about how to avoid a problem altogether.

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