Establishing a Healthcare Data Quality Assurance Initiative. Session 410, March 7, 2018 Omid Shabestari, MD, PhD Tonja Locklear, PhD

Transcription

1 Establishing a Healthcare Data Quality Assurance Initiative Session 410, March 7, 2018 Omid Shabestari, MD, PhD Tonja Locklear, PhD Director of Health Analytics Healthcare Statistician Carilion Clinic Carilion Clinic 1

2 Conflict of Interest Omid Shabestari, MD PhD and Tonja Locklear, PhD have no real or apparent conflicts of interest to report. 2

3 Agenda 1) Learning Objectives 4) Challenges/Barriers Explanation Q & A (5 min) 2) Topic/Issue Explanation Q & A (5 min) 5) Conclusions/Outcomes Explanation Q & A (5 min) 3) Approach Explanation Q & A (5 min) 6) Recommendations Explanation Q & A (5 min) 3

4 Learning Objectives Describe the data quality initiative established through the data governance charter Identify the various responsibilities and deliverables associated with the three organizational units Evaluate the progress of the data quality initiative 4

5 Topic: Stronger data-driven focus with emphasis on research Impact on healthcare organization Direction of the organization Effectiveness of the organization Issues for healthcare organization Multiple data sources and data stored in multiple areas Limits scope of data analysis (Analytics Cube outside the scope of this presentation) Quality of data Missing values, typos, incomplete information, etc. Limits reliability of analytical results (Focus of this presentation) 5

6 Q & A (5 Minutes) 6

7 Approach: Strategic Plan for Data Governance Data Governance the collection of activities related to management and oversight of an organization s data assets to help provide business users with high-quality data that is easily accessible in a consistent manner Appointed and/or Created Organizational Units 1) Data Governance Council 2) Data Stewardship Committee 3) Others responsible for quality of individual data elements 7

8 Approach: Development of the Data Quality Assurance Initiative Step 1: Formalizing the Data Governance Council and Data Stewardship Committee Step 2: Creating and organizing a comprehensive organizational business glossary Data Stewards a. define and create terms in the sandbox glossary b. propose terms to Data Governance Council Data Governance Council a. approve terms for inclusion in the Enterprise Glossary b. retire terms from the Enterprise Glossary 8

9 Example: Business Glossary Term 9

10 Approach: Development of the Data Quality Assurance Initiative Step 3: Providing data quality reports and KPIs for data generated from analytics cube to Data Governance Council Data Stewards a. scope items for data quality assurance b. ensure data is used properly within the organization Data Governance Council a. define the targets and limits for each data quality item b. monitor improvements of data quality c. training on data quality improvement initiatives Step 4: Prioritizing initiatives based on availability of resources and organizational needs using the Responsible, Accountable, Consulted, and Informed (RACI) model (Data Governance Council) 10

11 Example: Data Quality Reports and KPIs 11

12 Q & A (5 Minutes) 12

13 Challenges/Barriers Understanding the need for this type of data quality assurance initiative Buy-in from all areas of the organization Obtaining the resources needed for the initiative Analytics Cube Business Glossary Program Reporting Tool Training on the respective tools and programs 13

14 Q & A (5 Minutes) 14

15 Conclusions/Outcomes 1) Redefined the roles and responsibilities of the Data Governance Council and the Data Stewardship Committee 2) Created the organization s business glossary 3) Identified the data sources related to the terms when appropriate 4) Incorporated the data from various sources into the analytics cube 5) Data completeness was one of the starting initiatives for the Data Governance Council Data quality reports and KPIs were created based on data completeness Data sources were identified for cross validation Action plans were defined for data quality improvement RACI model roles were identified for each entity 15

16 Q & A (5 Minutes) 16

17 Recommendations Acknowledge the impact of data quality on the organization (direction & effectiveness) Establish a data quality assurance initiative of your own Be prepared for variations in data from different sources and choose the source with the highest quality as the source of truth Deliverables (business glossary & quality reports on completeness of data) keep data quality at the forefront of the organization Assigning RACI roles helps connect the data quality issues with those who can intervene and create positive change in the overall quality of data Regularly scheduled meetings for Data Stewards and Data Governance (monthly) Most important not a once-and-done process 17

18 Q & A (5 Minutes) 18

19 Questions Contact Information: Omid Shabestari, MD PhD Tonja Locklear, PhD Reminder: Please complete online session evaluation form. 19