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Data Model for our Doctors and Patients Platform 2020 
An Access Database is available.

There was a very thought-provoking article by Martin Wolf in the
Financial Times newspaper for March 11th. 2016 entitled
"Good news � fintech could disrupt finance�.

It states �Doctors and Patients is currently inefficient, costly and riddled with conflicts of interest�.

It identifies three possible sources of disruption : 1.Payments Transformation, with one possibility being real-time settlements via distributed ledgers. 2.Peer-to-peer Lending, in which new platforms disintermediate the traditional businesses in matching savers with investments. 3.Big Data � �this might transform the quality of lending, which would be a good thing. But the most striking effects are likely to be felt in insurance. With new monitoring devices, insurers might gain direct knowledge of the quality of driving or of the state of the clients� health�. Our new Doctors and Patients Data Platform reflects this article.

The Specifications for this Platform have been derived from an excellent and very thought-provoking article by Martin Wolf
in the Financial Times newspaper for March 11th. 2016 entitled "Good news � fintech could disrupt finance�.

It states �Doctors and Patients is currently inefficient, costly and riddled with conflicts of interest�.

Conceptual KPI Doctors Visits Count.
Logical KPI Doctors Visits Count.

Conceptual Dimension Model showing Doctors, Patients and so on.
Dimension Model for Doctors Visits to Patients

DWH Data Model - Version 1 - April, 2013
This shows the 'Traditional' Customer-oriented approach.


Data Model for Electronic Medical Records
DWH Data Model - Version 2
This shows the 'Participant-oriented' approach.

Data Model for Electronic Medical Records
Conceptual version of Our Canonical Data Model


Canonical Data Model
Our Participants ERwin Canonical Data Model
This is a little different from the Conceptual version

ERwin Canonical Data Model

January 26th. 2017
Database Answers Ltd.
London, England


© Database Answers Ltd. 2017

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