BACKGROUND AND PURPOSE: Emergency medical dispatchers play an important role in optimizing stroke care if they are able to accurately identify calls regarding acute cerebrovascular disease. This study was undertaken to assess the diagnostic accuracy of the current national protocol guiding dispatcher questioning of 911 callers to identify stroke (QA Guide version 11.1 of the National Academy Medical Priority Dispatch System). METHODS: We identified all Los Angeles Fire Department paramedic transports of patients to University of California Los Angeles Medical Center during the 12-month period from January to December 2005 in a prospectively maintained database. Dispatcher-assigned Medical Priority Dispatch System codes for each of these patient transports were abstracted from the paramedic run sheets and compared to final hospital discharge diagnosis. RESULTS: Among 3474 transported patients, 96 (2.8%) had a final diagnosis of stroke or transient ischemic attack. Dispatchers assigned a code of potential stroke to 44.8% of patients with a final discharge diagnosis of stroke or TIA. Dispatcher identification of stroke showed a sensitivity of 0.41, specificity of 0.96, positive predictive value of 0.45, and negative predictive value of 0.95. CONCLUSIONS: Dispatcher recognition of stroke calls using the widely employed Medical Priority Dispatch System algorithm is suboptimal, with failure to identify more than half of stroke patients as likely stroke. Revisions to the current national dispatcher structured interview and symptom identification algorithm for stroke may facilitate more accurate recognition of stroke by emergency medical dispatchers.
BACKGROUND AND PURPOSE: Emergency medical dispatchers play an important role in optimizing stroke care if they are able to accurately identify calls regarding acute cerebrovascular disease. This study was undertaken to assess the diagnostic accuracy of the current national protocol guiding dispatcher questioning of 911 callers to identify stroke (QA Guide version 11.1 of the National Academy Medical Priority Dispatch System). METHODS: We identified all Los Angeles Fire Department paramedic transports of patients to University of California Los Angeles Medical Center during the 12-month period from January to December 2005 in a prospectively maintained database. Dispatcher-assigned Medical Priority Dispatch System codes for each of these patient transports were abstracted from the paramedic run sheets and compared to final hospital discharge diagnosis. RESULTS: Among 3474 transported patients, 96 (2.8%) had a final diagnosis of stroke or transient ischemic attack. Dispatchers assigned a code of potential stroke to 44.8% of patients with a final discharge diagnosis of stroke or TIA. Dispatcher identification of stroke showed a sensitivity of 0.41, specificity of 0.96, positive predictive value of 0.45, and negative predictive value of 0.95. CONCLUSIONS: Dispatcher recognition of stroke calls using the widely employed Medical Priority Dispatch System algorithm is suboptimal, with failure to identify more than half of strokepatients as likely stroke. Revisions to the current national dispatcher structured interview and symptom identification algorithm for stroke may facilitate more accurate recognition of stroke by emergency medical dispatchers.
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Authors: Vladimir Hachinski; Geoffrey A Donnan; Philip B Gorelick; Werner Hacke; Steven C Cramer; Markku Kaste; Marc Fisher; Michael Brainin; Alastair M Buchan; Eng H Lo; Brett E Skolnick; Karen L Furie; Graeme J Hankey; Miia Kivipelto; John Morris; Peter M Rothwell; Ralph L Sacco; Sidney C Smith; Yulun Wang; Alan Bryer; Gary A Ford; Costantino Iadecola; Sheila C O Martins; Jeff Saver; Veronika Skvortsova; Mark Bayley; Martin M Bednar; Pamela Duncan; Lori Enney; Seth Finklestein; Theresa A Jones; Lalit Kalra; Jeff Kleim; Ralph Nitkin; Robert Teasell; Cornelius Weiller; Bhupat Desai; Mark P Goldberg; Wolf-Dieter Heiss; Osmo Saarelma; Lee H Schwamm; Yukito Shinohara; Bhargava Trivedi; Nils Wahlgren; Lawrence K Wong; Antoine Hakim; Bo Norrving; Stephen Prudhomme; Natan M Bornstein; Stephen M Davis; Larry B Goldstein; Didier Leys; Jaakko Tuomilehto Journal: Stroke Date: 2010-06 Impact factor: 7.914
Authors: Laura C Gioia; Rahel T Zewude; Mahesh P Kate; Kim Liss; Brian H Rowe; Brian Buck; Thomas Jeerakathil; Ken Butcher Journal: Neurology Date: 2016-05-18 Impact factor: 9.910