The document outlines a medical data warehouse model developed by Michael R. Blaha, detailing the architecture, data sources, and management practices involved. It emphasizes the reliance on Epic Clarity data, the use of Netezza as the platform, and the implementation of Informatica for ETL and data staging. Additionally, it discusses the data schema, dimensions, facts, and issues encountered during development, such as data errors and the need for SQL validation.

1. © 2017 IDERA, Inc. All rights reserved.
Proprietary and confidential.
A MEDICAL DATA
WAREHOUSE MODEL
Michael R Blaha, DSc.
blaha@computer.org
www.superdataguy.com

2. 2© 2017 IDERA, Inc. All rights reserved. Proprietary and confidential.
WAREHOUSE DATA FLOW

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SOURCE DATA DETAILS
 Epic Clarity is 99+% of source data
• All the data of a major hospital
• Small amount of data from other apps and
external sources
• No scrubbing of source data
• 10,000+ Clarity tables
• Some tables have 200+ columns
• Much redundant data
• Clarity also has both transaction data and rollup data
• No referential integrity
• Odd PKs of many-to-many tables
• Table1 PK + line_number

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OTHER DATA FLOW DETAILS
 Data warehouse platform is Netezza
 The staging tables maintain a history of operational data
• One staging table for each major source
• Staging schema = operational schema + surrogate key
+ effective date + expiration date
 Informatica for staging data + a new commercial tool
 Informatica for ETL + agile SQL queries

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BUS ARCHITECTURE
 Definition: A data warehouse with dimensions that are
consistently defined across facts
 200+ dimensions; 100+ facts; Kimball approach
 Fully commented data model with naming standards
 We created our own DW schema
• This project preceded Epic’s DW schema
 DW has strong correspondence to Clarity
• Little abstraction

6. 6© 2017 IDERA, Inc. All rights reserved. Proprietary and confidential.
PARTIAL BUS ARCHITECTURE
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Account_Coverage X X X X X
Account_Diagnosis X X X X X
Account_Procedure X X X X X X
Account_Summary X X X X X X X X X X X X
Billing_Tx_Detail X X X X X X X X X X
Encounter X X X X X X

7. 7© 2017 IDERA, Inc. All rights reserved. Proprietary and confidential.
PARTIAL BUS ARCHITECTURE (CONT.)
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Order_Medication X X X X X X
Order_Procedure X X X X X X X
Patient_Appt X X X X X X
Provider_Avail X X X X X X
Readmission X X X X X X X X X X
Referral X X X X X X X X X

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SAMPLE DIMENSIONS
 Account
 Appointment
 Benefit_Plan
 Carrier
 Cost_Center
 Coverage
 Date
 Department
 Diagnosis
 DRG
 Encounter

9. 9© 2017 IDERA, Inc. All rights reserved. Proprietary and confidential.
SAMPLE DIMENSIONS (CONT.)
 Medication
 Patient
 Payor
 Pharmacy
 Problem_List
 Procedure
 Provider
 Revenue_Code
 Unavailable_Reason
 Vendor

10. 10© 2017 IDERA, Inc. All rights reserved. Proprietary and confidential.
SAMPLE FACTS
 Account_Coverage – patient account and coverage data
 Account_Diagnosis – data about diagnoses
 Account_Procedure – procedures for an account
 Account_Summary – an accumulating snapshot fact
 Billing_Transaction_Detail – hospital billing transactions
 Encounter – the current state of a patient encounter
 Order_Medication – data for medications
 Order_Procedure – data for procedures and lab orders
 Patient_Appointment – data for appointments
 Provider_Availability – time slots for a provider’s schedule
 Readmission – data for hospital readmission per ACA
 Referral – a patient handoff from one provider to another

11. 11© 2017 IDERA, Inc. All rights reserved. Proprietary and confidential.
SAMPLE SUBJECT AREA

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SAMPLE SUBJECT AREA

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SAMPLE SUBJECT AREA

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STAFFING BREAKDOWN
 4 managers
 2 data modelers + advanced tools/techniques
 6 ETL
 5 business analysts
 1 DBA
 1 metadata
 2 secretary
 2 legacy software

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RETROSPECTIVE
 Too much of “build it and they will come”
 There were errors in staging data!
 There was code review for ETL scripts
• I’m not confident that the ETL scripts were correct
• We should have used SQL to validate ETL scripts
 Agile analytics
• We had complex SQL for calculating readmissions
• The SQL was validated as correct
• The legacy software was wrong!
 Issue of Clarity rollup vs DW rollup

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THANKS!
Any questions?
You can find me at:
@michaelrblaha
blaha@computer.org
www.superdataguy.com