iese essay : industry ov
TRANSCRIPT
Naresh R Shah | Saathi Healthcare
Prepared by
H. What do you believe are the greatest challenges facing the sector or industry you would like to specialize in at IE? What role do you hope to be able to playing this sector or industry in the medium term?
A presentation for IE Business School’s
MSc. In Business Analytics and Big Data
Overview of the Healthcare Sector
Conclusion
Introducing a data-driven culture and its benefits to the Healthcare delivery industry, particularly the Indian Healthcare sector would be a great boon for the industry.
What is the problem? Healthcare Analytics
Focus currently is on the “volume” end of analytics, mainly data management and governance.
There is a lot of scope for companies to work with advanced analytics and predictive modeling. Hospitals are currently understaffed for even the most basic reporting and analytical needs.
Some of the problems with Data Analytics within the Indian Healthcare Industry are as follows:
Lack of adequate survey data or Key Performance Indicators data.
No administrative reporting system which provides basic hospital service statistics.
Lack of understanding of the overall benefits of Data Analytics and Predictive modeling in healthcare.
Specific Problems
In a lot of places data storage is going to rapidly
shift to the cloud.
Currently key healthcare providers plan to invest heavily in Electronic Health Records.
Lots of opportunities to work with global healthcare IT firms and build data driven products .
Market Shifts – Promising Beginnings
The market
Market Segmentation:
Enterprise software vendors: Offer tools only specific to their applications.
Technology Vendors: Offer tools to create BI/EPM Solutions but must be custom developed.
Pure Healthcare BI Companies: Subscription based models. Do not provide leading edge technology.
Technology Vendors:
BEA, Cognos, Microsoft
Enterprise Software Vendors:
McKesson, GE, Siemens, Epic,
Cerner
Pure Healthcare BI Companies:
MedeAnalytics, Avega Precision,
CareMedic
Chief Data Officer/Data
Scientist
Data Architect
Project Manager
DataAnalyst
Work with large and complex datasets and
validate predictive models I clinical operational and financial areas for large
healthcare organizations.
Work with understanding the requirements and
assigning the responsibilities for a Data Product.
Plan structure and software design cycles for a Data
Feature/Product.Work with predictive
modeling and automated analysis tools.
Typically work with developing the pieces of
software that are required by the organization.I have worked in this
capacity at GE Healthcare.
Career Path – Where I would want to be?
I would eventually want to be a Data scientist.
