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Time-tradeoff utilities for identifying and evaluating a minimum data set for time-critical biosurveillance
Jason N Doctor1, Janet G Baseman, William B Lober
1Department of Clinical Pharmacy and Pharmaceutical Economics and Policy, University of Southern California, Los Angeles, CA 90089-9004, USA. jdoctor@usc.edu
Summary
This study introduces a new method to measure the value of biosurveillance data by trading relevance for time delay. The approach shows promise for evaluating national data sets in public health surveillance.
Area of Science:
- Public Health
- Health Informatics
- Epidemiology
Background:
- Establishing national minimum data sets for biosurveillance is a key goal for researchers and policymakers.
- Current methods for measuring the value of biosurveillance data require further development.
Purpose of the Study:
- To establish and evaluate a novel method for quantifying the utility of biosurveillance data.
- To assess the sensitivity of the proposed method to different data types and time horizons.
Main Methods:
- An expected utility model was developed, valuing data by balancing relevance against time delay.
- A time-tradeoff exercise was conducted with 23 disease surveillance practitioners.
- The study examined tradeoffs between chief complaints and emergency department logs, and evaluated data over 24-hour vs. 48-hour timeframes.
Main Results:
- Chief complaints demonstrated significantly higher utility than emergency department logs, indicating method sensitivity (P < 0.05).
- Data utility was not significantly affected by the time horizon (24 vs. 48 hours).
- A low logical error rate of 5% was observed in the elicited time tradeoffs.
Conclusions:
- A time-tradeoff exercise was successfully established for valuing biosurveillance data.
- The method shows initial promise for evaluating minimum data sets in biosurveillance.
- This approach may be valuable for future disease surveillance planning and evaluation.
