This document summarizes the goals and progress of data stewardship efforts over the first year. It outlines four objectives: implementing a data quality program, information stewardship, educating on information assets, and expanding documentation. For each, tasks are defined and status provided. Key accomplishments include establishing data management groups, drafting policies and templates, training teams on documentation tools, and gathering clinical data for interfaces. The summary reiterates that data stewardship improves efficiencies through local and collaborative efforts to manage data as a valuable asset.

1. Data Stewardship
Year One
Excerpt of Goals and Completed Tasks

2. Data Stewardship
 Overview of Four Objectives
 Tasks and Progress of each Objectives
 Demonstration of Completed Tasks (Removed from this
Slideshow)
 Information Stewardship using SAP Sybase PowerDesigner
tool
 Summary of Data Stewardship

3. Data Stewardship –
Objectives
 Data Quality Program – Collaborate with Enterprise
Database team members to begin formal data quality
processes regarding all aspects of data handling
 Information Stewardship – Facilitate forming
processes to manage data as an asset
 Information Asset Orientation – Educate all levels of
organization on the need to improve quality of the
crucial data assets
 Information Documentation – Continue proof of
concept and expand into other clinical data areas

4. Data Stewardship – Tasks & Progress
1. Development of Data Quality Program(s) for the Enterprise:
Tasks: Status/Progress:
1. Collaborate with Enterprise Database
teams
2. Establish policies and procedures
3. Document best practices and data
flows/interfaces to better understand
and share data
4. Develop metrics to measure data
quality and identify issues proactively
5. Improve data quality and usability
within the enterprise
Began Data Management Work Group
meetings to engage five teams
Drafts in Progress
Templates in Progress
Test Case developed to measure clinical
data quality across enterprise
Data Quality Test Results to be delivered to
Leadership to support Data Quality Program
recommendations

5. Data Stewardship – Tasks & Progress
2. Information Stewardship:
Tasks: Status/Progress:
1. Establish the requirements for
documentation of data flows across
enterprise
2. Create templates for populating
data flow documentation
3. Create documentation for how to
document data flows
4. Train enterprise database team
members to use PowerDesigner to
document data flows/interfaces
Representatives from the four
databases agreed on meta data
requirements
Templates were completed in
PowerDesigner
Two Teams trained to populate
templates
Two Additional Teams to be trained to
populate templates

6. Data Stewardship – Tasks & Progress
3. Information Asset Orientation:
Tasks: Status/Progress:
1. Meet with Consultant, Teams to
develop a Metric Template in excel for
Enterprise/Scorecard use
2. Model the Metric Template in
PowerDesigner
3. Populate the Metric Template with
Measures and Data Elements
Began meeting with teams to develop
template guidelines for Project
Completed meetings and template in
excel
Metric Template to be modeled in
PowerDesigner

7. Data Stewardship – Tasks & Progress
4. Information Documentation:
Tasks: Status/Progress:
1. Determine Data Elements needed for
Measures
2. Meet with Teams from Academic and
Community Facilities to gather data and
work flow information
3. Document data elements information for the
Interface Development Team
4. Facilitate the testing and documentation of
new interfaces within enterprise
Data elements determined and meetings
scheduled with clinical teams to gather
documentation
Completed meetings with Clinical IS Teams
Handed off documentation of Data Element
documentation to Interface Development Team
Currently awaiting completion of interface
specifications

8. Data Stewardship - Summary
 Principles of Data Stewardship are designed to improve
efficiencies across the Enterprise.
 Data Stewardship occurs ‘locally’, and has begun within
proof of concept.
 Data Stewardship is a collaborative effort. Everyone
that touches data will be involved and share the
benefits of improved data management/quality.