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Abstract

Introduction: Identification of persons based on verbal descriptions is one of the key skills of police work. Gathering as much description information as possible immediately following the event—for example, at the point of emergency police dispatch—could substantially improve the accuracy of suspect descriptions, the ability to locate missing persons quickly, and other key outcomes of effective police work.

Objective: The primary objective of this study was to determine what amount and type of persons description information is collected by Emergency Police Dispatchers (EPDs), both overall and by Chief Complaint Protocol.

Methods: This is a retrospective, descriptive study of the Police Priority Dispatch System (PPDS) data from five emergency communication centers in the United States of America, collected between September 2014 and May 2017.

Results: During the study period, a total of 117,160 (58.1%) calls had at least one item from the Description Essentials (DE) Tool: Person’s Description recorded. The Chief Complaint Protocols that had the highest frequency of person DE collected were Missing/Runaway/Found Person (99.0%), Suicidal Person/Attempted Suicide (97.1%), and Domestic Disturbance/
Violence (90.0%). The most commonly recorded person DE elements were the four required measures: gender, race, age, and clothing. Among non-required DE elements, the most common was name (38.7%), and the least common were demeanor and complexion (1.3% each). By far the most common type of person described was “suspect” (78.4% of cases).

Conclusions: Overall, trained and certified EPDs using the PPDS are effective at collecting information about persons and entering it correctly. Different types of events require somewhat different approaches to description gathering. EPDs appear to discriminate among these different event types while (mostly) making sure to collect required information. Additional
definitions, small changes to when and how the ProQA DE Tool appears, and possible removal of two seldom-used descriptors have been recommended based on these findings.

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