TIBCO Software Case Studies Business Process Optimization for Healthcare Services

	Business Process Optimization for Healthcare Services TIBCO Software

Business Process Optimization for Healthcare Services

TIBCO Software

Technology Category	Analytics & Modeling - Predictive Analytics
Applicable Industries	Healthcare & Hospitals
Applicable Functions	Business Operation
Use Cases	Predictive Maintenance
Services	Data Science Services
Challenge	The Company, a leading provider of Specialty Benefits Management solutions, was struggling with managing the extraordinary amount of data associated with benefits management in healthcare. As the number of insured members increased, it became crucial for them to leverage the constant influx of data to achieve operational efficiency. Their previous approach involved multi-month cycles with IT normalizing the data, and inconsistent ways of implementing their models into production. In order to scale their data efforts and achieve a more streamlined process, the company needed an end-to-end advanced analytics solution, from data blending to modeling. Read More
About Customer	The customer is a leading provider of Specialty Benefits Management solutions with a net worth of $1.5B. They provide services to payers and other risk-bearing entities, such as Accountable Care Organizations (ACOs). The company serves over 70 million insured members and processes over 2.5 million patient transactions every month. As a benefits organization, they deal with an extraordinary amount of data from medical procedures, insurance claims, to patient data. Read More
Solution	The Company adopted the Alpine Chorus platform, an end-to-end advanced analytics solution. This platform allowed the company to deploy advanced analytics solutions across business units easily and efficiently. The process of preparing and modeling the data for a particular unit is centralized within the Alpine Chorus platform, and allows business users to maintain governance over the entire process without putting stress on their data science team. Business analysts at The Company are able to access the power of predictive analytics through the Alpine platform, and can make determinations for authorizing medical procedures based on the new data. For the first time, The Company’s analysts can receive the input and approvals of various stakeholders in the analytics process from one collaborative platform, allowing them to deploy predictive models into production without wasted cycles. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Healthcare & Hospitals

Applicable Functions

Business Operation

Use Cases

Predictive Maintenance

Services

Data Science Services

Challenge

The Company, a leading provider of Specialty Benefits Management solutions, was struggling with managing the extraordinary amount of data associated with benefits management in healthcare. As the number of insured members increased, it became crucial for them to leverage the constant influx of data to achieve operational efficiency. Their previous approach involved multi-month cycles with IT normalizing the data, and inconsistent ways of implementing their models into production. In order to scale their data efforts and achieve a more streamlined process, the company needed an end-to-end advanced analytics solution, from data blending to modeling.

About Customer

The customer is a leading provider of Specialty Benefits Management solutions with a net worth of $1.5B. They provide services to payers and other risk-bearing entities, such as Accountable Care Organizations (ACOs). The company serves over 70 million insured members and processes over 2.5 million patient transactions every month. As a benefits organization, they deal with an extraordinary amount of data from medical procedures, insurance claims, to patient data.

Solution

The Company adopted the Alpine Chorus platform, an end-to-end advanced analytics solution. This platform allowed the company to deploy advanced analytics solutions across business units easily and efficiently. The process of preparing and modeling the data for a particular unit is centralized within the Alpine Chorus platform, and allows business users to maintain governance over the entire process without putting stress on their data science team. Business analysts at The Company are able to access the power of predictive analytics through the Alpine platform, and can make determinations for authorizing medical procedures based on the new data. For the first time, The Company’s analysts can receive the input and approvals of various stakeholders in the analytics process from one collaborative platform, allowing them to deploy predictive models into production without wasted cycles.

Impact #1	The Company is now able to deploy advanced analytics solutions across business units easily and efficiently.
Impact #2	The process of preparing and modeling the data for a particular unit is centralized within the Alpine Chorus platform.
Impact #3	Business analysts at The Company are able to access the power of predictive analytics through the Alpine platform.

Impact #1

The Company is now able to deploy advanced analytics solutions across business units easily and efficiently.

Impact #2

The process of preparing and modeling the data for a particular unit is centralized within the Alpine Chorus platform.

Impact #3

Business analysts at The Company are able to access the power of predictive analytics through the Alpine platform.

Benefit #1	Analyst teams can easily understand a business unit’s problem, process their data, construct a model, and deploy that model into production in a matter of weeks. Previously, the data processing step alone would take several months, and required both data science and IT resources to complete.

Benefit #1

Analyst teams can easily understand a business unit’s problem, process their data, construct a model, and deploy that model into production in a matter of weeks. Previously, the data processing step alone would take several months, and required both data science and IT resources to complete.

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Overview

Business Process Optimization for Healthcare Services

Operational Impact

Quantitative Benefit