OBJECTIVES: The purpose of this study was to derive and validate a rule for duration of search (ie, search time) that maximizes survivors and after which a search and rescue (SAR) mission may be considered for termination. METHODS: This was a retrospective cohort study of all SAR missions initiated in Oregon over a 7-year period, which were documented in a population-based administrative database. The following types of search missions were excluded from analysis: redundant reports of a single search; lost helicopters and airplanes; support of organized events; law-enforcement searches; searches for persons actively avoiding rescue; body recovery missions; and cases without outcome information. The cohort was divided into a derivation cohort (searches from 1997-2000) and a validation cohort (2001-2003). The primary outcome was survival. Variables considered in the model included age, gender, minimum and maximum daily temperatures, precipitation, search time, and whether the search involved an air or water incident. Missing data were handled using multiple imputation. Classification and regression tree (CART) methods were used to derive the model. RESULTS: The derivation cohort included 1040 searches involving 1509 victims, 70 (4.6%) of whom died. The validation cohort included 1262 searches involving 1778 victims; 115 (6.5%) died. Search time was the only variable retained in the final model, with a cut-point of 51 hours. The derivation model was 98.9% sensitive; the same model run using the validation cohort was 99.3% sensitive. CONCLUSIONS: This time-based model may aid search managers in the decision about starting a search or changing search tactics for missing persons.
OBJECTIVES: The purpose of this study was to derive and validate a rule for duration of search (ie, search time) that maximizes survivors and after which a search and rescue (SAR) mission may be considered for termination. METHODS: This was a retrospective cohort study of all SAR missions initiated in Oregon over a 7-year period, which were documented in a population-based administrative database. The following types of search missions were excluded from analysis: redundant reports of a single search; lost helicopters and airplanes; support of organized events; law-enforcement searches; searches for persons actively avoiding rescue; body recovery missions; and cases without outcome information. The cohort was divided into a derivation cohort (searches from 1997-2000) and a validation cohort (2001-2003). The primary outcome was survival. Variables considered in the model included age, gender, minimum and maximum daily temperatures, precipitation, search time, and whether the search involved an air or water incident. Missing data were handled using multiple imputation. Classification and regression tree (CART) methods were used to derive the model. RESULTS: The derivation cohort included 1040 searches involving 1509 victims, 70 (4.6%) of whom died. The validation cohort included 1262 searches involving 1778 victims; 115 (6.5%) died. Search time was the only variable retained in the final model, with a cut-point of 51 hours. The derivation model was 98.9% sensitive; the same model run using the validation cohort was 99.3% sensitive. CONCLUSIONS: This time-based model may aid search managers in the decision about starting a search or changing search tactics for missing persons.