BMT Data AccuracyFulfilling Audits and Assuring Top Quality Data

Lindsay Dozeman

BMT Database Administrator and Data Coordinator

Blood & Marrow Transplant Program

University of Iowa Hospitals & Clinics

Disclosure

Some of the features I will be discussing today are part of the University of Iowa Blood and Marrow Transplant Database©

which is being licensed through the University of Iowa Research Foundation. (Licensing questions can be directed to Lindsay-dozeman@uiowa.edu)

Background2012 to current

0

50

100

150

200

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

UIHC BMT

CY 2005-2015

ALLO AUTO

Paradox + Paper charts

Excel LandRemedy/Excel

LandAccess

176

356

0

50

100

150

200

250

300

350

400

Revision 2 (2010-2012 Revision 4 (current)

Pre-TED Fields

Data Accuracy Dilemmas

• Can we fulfill reporting requirements and always report accurately?• When meeting CPI trumps reporting data accurately, its time to reevaluate demands and

expectations

• Is maintaining and reporting accurate data a luxury that only programs with adequate data management staff and/or the latest systems can enjoy? (No)

Data Accuracy: Not a Choice

• Maintaining and reporting inaccurate data is not an option• Consequences range from severe to more severe

• New CIBMTR audit requirements June 2015• Reporting accuracy more important than ever before

Quality is More Important than Quantity

• Focus on what is possible with current staff and resources• Maintaining comprehensive forms data on all program transplants when facing a 6+ months

backlog may not be possible with 1.25 data coordinators and/or if we want to meet CPI, fulfill physician requests, and maintain an accurate database

• Focus on critical fields first, additional data collection after

• Determine if requirements can be satisfied with a different approach• Example: Meeting FACT standard regarding TED accuracy

• May not be able to audit all transplants data, but we can approach the process differently to maximize outcome

• Audit data by form section and require all questions to be reported correctly in order for the section to be considered acceptable.

• Fewer errors cause higher error rate percentage, allowing us to identify unacceptable error rates sooner

Clean Data In, Clean Data Out

• User-friendly forms and smart data entry

• Initial data entry generates subsequent entry - cascading drop-downs standardized to CIBMTR options, rules to reject incorrect reporting• Example: Selecting disease cascades specific disease classification, status at transplant and

best response drop-down menus• Example: If in CR at transplant, cannot enter “never in CR” post-transplant

• Strategically placed free-text fields, used sparingly• Allows team to communicate about reporting/documentation issues while keeping critical

fields standardized• Example: Disease status at transplant cannot include notes such as “VGPR – see SPEP”

• Hyperlinks for all supportive documentation used for reporting not found in Epic

• Query-generated HCT-CI score, ASBMT Risk, Disease Risk Index, readmissions, etc.

• Auto populated QA dashboard

• SOP-driven flags to highlight unusual outcomes or outliers

• Example: Greater than 27 days to ANC engraftment

Auditing Macro

• Tracks additions, deletions, changes to critical data fields• Serves multiple purposes

• Highlights what fields are being changed , how often, and when

• Provides insight into possible improvements in documentation

• Activity tracking

• Empowers data staff

Screenshots from the University of Iowa Blood and Marrow Transplant Database©

Tracking Audits and Reviews

• CIBMTR Audits• CIBMTR Error Corrections• TCSA Queries• FACT Audits• TED Accuracy Audits

Screenshots from the University of Iowa Blood and Marrow Transplant Database©

Audit Summaries: View Errors by Coordinator, field, quarter, etc.

•

Screenshots from the University of Iowa Blood and Marrow Transplant Database©

776767361

TED Accuracy Audit Results Generate in QA Dashboard

Screenshots from the University of Iowa Blood and Marrow Transplant Database©

Data Accuracy: Critical and Attainable

Setting realistic expectations and taking advantage of readily available tools can greatly improve accuracy of collected and reported data, allowing staff the ability to fulfill a multitude of demands and requirements with efficiency and ease

Thank you for listening!

Email: Lindsaydozeman@gmail.com