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Julie Welbig Transfusion Safety Officer Fairview Health Services

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Presentation on theme: "Julie Welbig Transfusion Safety Officer Fairview Health Services"— Presentation transcript:

1 Julie Welbig Transfusion Safety Officer Fairview Health Services
Using Data to Improve Safety and Improve Your Patient Blood Management Program Julie Welbig Transfusion Safety Officer Fairview Health Services

2 Conflict of Interest Disclosure Julie Welbig, MLS(ASCP)SBB
Has no real or apparent conflicts of interest to report.

3 6 Hospitals in Fairview System
Mix of teaching/academic and community hospitals Total transfusions in system: RBCs: ~ 30,000/year (2/3 at university hospital) Plasma: ~ 10,000/year (over 2/3 at university hospital) Platelets: ~ 17,000/year (almost entirely at university hospital) Yikes! That is a lot of monitoring and data to collect!

4 Development of Databases
Data is everywhere! Blood bank/laboratory data Information about the transfused blood component EHR data Information about the patient Information about the order Information Technology is your best friend  Continued improvement in the databases – don’t stop developing! *Blood bank data is essential, and most likely starting point, but doesn’t necessarily contain the “whole picture”.


6 Blood Utilization Metrics – What data can I collect?
Total # of transfusions % transfusions given at or below a particular hemoglobin threshold 2 unit red blood cell orders % transfusion appropriateness/within guidelines (subjective metric) Others? Not talking about the metrics used in blood bank, such as outdate rate, that blood bank has control over. These are metrics of provider practice, things that the blood management group can review for performance improvement projects, etc.

7 So what did we do? Discharge Database Daily Transfusion Report

8 Patient Discharge Database
Originally developed as a financial tool Available upon discharge coding of patient’s visit Patient’s transfusion data is coupled with billing codes (DRG, ICD-9, CPT) Semi-automated RBC transfusion audits based on ICD-9 codes (conditions that may create a greater oxygen demand) Marks appropriate based on hemoglobin level and codes Marks “needs review” if does not meet any of the rules Great retrospective review of a patient’s transfusion history during their stay

9 Is the Discharge Database Enough?
Information not available until discharge (challenging if patient’s stay lasts for months) Only includes patients that were transfused Patient’s location/service line/provider at time of transfusion not always correct Limitation of our LIS RBC orders are not interfaced from EHR Was not necessarily developed to use for targeted education, such as particular location or service line

10 Daily Transfusion Report
Developed as a more real-time report Provides information on every transfusion in the last 24 hours Type of transfusion Time of issue Patient location, service line, and attending at time of issue Pertinent pre- and post-laboratory values If transfusion occurred in the operating room Name of surgery, surgeon, and anesthesiologist

11 Daily Transfusion Report cont.
Each daily report is reviewed for RBC transfusion appropriateness (largest hospital only) Semi-automated Rules built to mark RBC transfusions appropriate based on patient’s age, service line, and pre- and post-hemoglobin levels Those transfusions not marked as appropriate are manually reviewed

12 Is the Daily Transfusion Report Enough?
Only includes patients that were transfused No DRG or ICD-9 information

13 Working With the Databases – Data Combination
Create monthly, quarterly, yearly databases Combine daily reports with discharge report Use daily audit results for the “needs review” transfusions in the discharge Combo approach pretty powerful tool

14 Working With the Databases – Pivot Tables
Location focused data (see next slide) Service line focused data (see next slide) Attending focused data Inpatient versus outpatient versus OR focused data

15 Example of why to separate location versus service line data

16 Working With the Databases – Information Mining
Tabulate total number of transfusions Normalize data by census or case mix index Determine % transfusions given at or below a certain threshold Calculate number of 2 unit orders Monitor % appropriate transfusions

17 I have great data, now what?
Share, share, share! Medical directors Nursing leadership Quality department Administration and finance Make the information simple to read and understand Summarize the data Make graphs and reports

18 Dashboards Combined data to provide quarterly % appropriate numbers. Pivoted data to focus on transfusion locations. Allows locations to compare to each other and grand total.

19 Service Line Reports Combined data to provide monthly metrics (total transfusions, % appropriate, # 2 unit orders) to chosen focus service lines.

20 Administration

21 Finance Administration loves to see the money saved! More importantly, increased patient safety.

22 So, Does the Data Collection and Sharing Make a Difference???
Decreased inappropriate transfusions – cost savings Decreased transfusion related adverse events – patient safety Increased inter-departmental team work – trust and better relationships

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