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Predicting a donor's likelihood of donating within a preselected time interval.
W A Flegel1, W Besenfelder, F F Wagner
1Department of Transfusion Medicine, University of Ulm, DRK (German Red Cross)-Blood Service Baden-Württemberg, Institute Ulm, Ulm, Germany. waf@ucsd.edu
Transfusion Medicine (Oxford, England)
|September 6, 2000
Summary
Identifying donors likely to return for retesting improves blood component management. A predictive model helps select donors for quarantine, increasing usable plasma units by 30% annually without extra costs.
Area of Science:
- Blood Transfusion Medicine
- Biostatistics
- Health Services Management
Background:
- Procurement of advanced blood components, like quarantined plasma, relies on timely donor retesting.
- Mandatory retesting in healthcare systems necessitates efficient identification of donors likely to return within a specified timeframe.
- Preferential selection of returning donors for quarantine can optimize blood component management.
Purpose of the Study:
- To develop and validate a predictive model for identifying donors likely to return within a specific time frame for retesting.
- To assess the model's effectiveness in improving the selection of donors for plasma quarantine.
- To evaluate the impact of the model on the efficiency and cost-effectiveness of blood component management.
Main Methods:
- Analysis of donation histories from approximately 760,000 donors and 4,910,000 donation attempts.
- Development of a logistic regression model to calculate the probability of donation within a predefined time frame (p(Dts-te)).
- Incorporation of donation history into a predictive score, with distinct parameters for first-time and repeat donors.
Main Results:
- The developed logistic regression model accurately predicts the probability of donor return (p(Dts-te)) within intervals like 6-9 months.
- First-time donors showed a 33% probability of returning within 170-275 days, outperforming certain repeat donor subsets.
- Application of the model to a plasma quarantine program resulted in a 30% increase in retrievable units, equating to approximately 30,000 units annually, without additional costs.
Conclusions:
- The predictive model offers a practical solution for identifying donors likely to return for retesting, crucial for blood component management.
- Implementing this model enhances the efficiency of plasma quarantine programs, leading to significant increases in usable units.
- The findings have broad implications for blood collection strategies, blood drive planning, and improving the cost-efficiency of healthcare systems relying on quarantined plasma.