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Background and Objectives: Pelvic inflammatory disease (PID) is a clinically diagnosed condition that is preventable and underreported. We developed an electronic emergency department (ED) PID reporting system by using an automatic and secure system to send computerized clinician PID diagnoses to the state health department., Goal: The goal of this study was to assess if electronic transmission of ED PID data could enhance the completeness and timeliness of PID surveillance., Study Design: We conducted a retrospective chart review., Methods: To validate electronic ED diagnoses, we reviewed charts of 157 women with 7 clinicians' diagnoses compatible with PID. We determined which women met the Centers for Disease Control and Prevention (CDC) PID surveillance case definition and determined the positive predictive values of electronic ED diagnoses of PID. We compared completeness of electronic PID reporting with state sexually transmitted disease surveillance., Results: Three diagnoses were appropriate for electronic PID surveillance. Information on women with these diagnoses is sent daily to the health department with no extra effort needed from ED clinicians. Less than 10% of women who met the CDC PID case definition were reported within 6 months through conventional methods., Conclusions: Electronic ED surveillance will improve completeness and timeliness of PID reporting.

Background: Stochastic models of discrete individuals and deterministic models of continuous populations may give different answers to questions about infectious diseases., Goal: Discrete individual model formulations are sought that extend deterministic models of infection transmission systems so that both model forms contribute cooperatively to model-based decision making., Study Design: GERMS models are defined as stochastic processes in continuous time with parameters analogous to those in deterministic models. A GERMS model simulator was developed that insured that the rate of events depended only on the current state of model., Results: The confidence intervals of long-term averages of infection level in simulated GERMS models were shown to contain the deterministic model means., Conclusion: GERMS models provide a convenient framework for testing the sensitivity of model-based decisions to a variety of unrealistic assumptions that are characteristic of differential equation models. GERMS especially facilitates making more realistic assumptions about contact patterns in geographic and social space.