using self-service business intelligence tools and data visualizations to facilitate multicenter...
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Using Self-Service Business Intelligence Tools and Data Visualizations to Facilitate
Multicenter Sleep ResearchRic Miller
COMET - Director of Informatics
Stanford Sleep Medicine Center
Conflict of Interest Disclosures for SpeakersX 1. I do not have any relationships with any entities producing, marketing, re-
selling, or distributing health care goods or services consumed by, or used on, patients, OR
2. I have the following relationships with entities producing, marketing, re-selling, or distributing health care goods or services consumed by, or used on, patients.
Type of Potential Conflict Details of Potential Conflict
Grant/Research Support
Consultant
Speakers’ Bureaus
Financial support
Other
3. The material presented in this lecture has no relationship with any of these potential conflicts, OR
4. This talk presents material that is related to one or more of these potential conflicts, and the following objective references are provided as support for this lecture:
1.
2.
3.
COMET
Comparative Outcomes Management with Electronic data Technology
supported by AHRQ Grant number 1R01HS019738
COMET
1. Multicenter research (Stanford, University of Pennsylvania, University of Wisconsin‐Madison, Harvard) randomized trial comparing obstructive sleep apnea treatments: positive airway pressure (PAP) vs. oral appliance (OA) therapy in 196 randomized participants
2. Informatics platform that facilitates electronic data management for multicenter clinical trials, enabling the generation of meaningful, well‐defined outcomes structured for use with business intelligence (BI) tools
Self-Service Business Intelligence
• Business intelligence (BI) is a set of tools and techniques used to transform datasets into information that is frequently visual in nature.
• “Self-service” refers to the ability of researchers to create their own data visualizations after a dataset has been provided which facilitates low cost, high quality clinical analytics.
• Interactive data visualizations, produced with BI tools are useful in bringing the data closer to the researcher and providing unique insights into the data but require standardized methods to be effective.
Self-Service Business Intelligence
1. Data Pipeline
2. Terminology
3. Data Visualization
Data Pipeline
Data Pipeline
ETL (Extract Transform Load)
Flat File Star Schema
Data Pipeline
RelationalDatabase
ETL (Extract Transform Load)
Terminology
TerminologyHow many SDID by VisitName?
-vs-How many patients by visit?
Terminology
Data Visualization
• Dashboards• KPI (Key Performance Indicators)• Printable Reports• Interactive Data Visualizations
Data Visualization
Data Visualization
Data Visualization
Data Visualization
Data Visualization
Dimensions - Filters Facts - Measures
Data Visualization
Data Visualization
Data Visualization
Data Visualization
Data Visualization
Data Visualization
Data Visualization
COMET Hub
Acknowledgements
• Authors: Miller RA, Nichols, DA, Griffin KS, Benca RM, Kuna ST, Mignot E, Pack AI, Redline S, Yang P, Hyde, PR, Walsh JK, Kushida, CA
• COMET: Supported by AHRQ Grant number 1R01HS019738, Clete Kushida, M.D., Ph.D. ,PI
• SMART DOCS: Supported by PCORI, Clete Kushida, M.D., Ph.D. ,PI
• COMET Hub: Pending evaluation by AHRQ for support, Miller RA, PI
Using Self-Service Business Intelligence Tools and Data Visualizations to Facilitate
Multicenter Sleep ResearchRic Miller
COMET - Director of Informatics
Stanford Sleep Medicine Center