Introduction: Emergency Medical Services (EMS) systems often utilize a structured approach to 911 call-taking and emergency medical dispatch (EMD). One such system, Medical Priority Dispatch System (MPDS®), categorizes 9-1-1 calls into EMD codes based on problem and severity. Response priorities and resources dispatched are determined at the local level through a predetermined response matrix, which is often determined without utilizing outcome-based criteria.
Objectives: The primary objective was to use historical clinical data to develop a methodology to increase the number of patients with time-sensitive critical illness who receive the highest-priority response. The secondary objective was to decrease the number of Priority 1 responses to patients who do not have time-sensitive critical illness. Additional objectives included increasing the number of patients with unstable vital signs who receive the second-highest priority response (Priority 2), as well as decreasing the number of Priority 2 responses to patients who do not have unstable vital signs.
Methods: This was a retrospective descriptive study analyzing electronic patient care reports (ePCRs) data for all 911 calls-for-service (between December 1, 2015 – November 30, 2016 period) for any patients who required cardiopulmonary resuscitation (CPR), assisted ventilations or airway management, and/or electrical therapy. Unstable vital signs were also assessed (i.e., Systolic Blood Pressure <90 mmHG, Heart Rate < 40 or > 160 beats per minute [bpm], and Respiratory Rate < 8 bpm).
Results: Out of a total of 119,289 actual calls-for-service, 30,123 (25.2%) were assigned a Priority 1 response through the currently utilized response matrix; 1,205 (4.0%) of these patients had time-sensitive critical illness and 4,687 (15.5%) had unstable vital signs. Utilizing our proposed methodology, these same calls-for-service would have resulted in 25,441 (21.3%) Priority 1 responses, including 1,333 (5.2%) patients with time-sensitive critical illness and 4,849 (19.0%) with unstable vital signs. The net result would have been an overall 15.5% decrease in Priority 1 responses, with a 10.6% and 3.4% increase in Priority 1 responses to patients with time-sensitive critical illness and unstable vital signs, respectively. Further, the new response matrix would increase the number of patients who receive a Priority 2 response by 3.6%, but this would include 3.4% with time-sensitive critical illness and 30.9% more with unstable vital signs.
Conclusions: Historical clinical data may be used to develop a methodology to increase the accuracy of call prioritization for patients with time-sensitive critical illness. By limiting the number of high-priority responses to lower-acuity calls, this methodology may also lead to optimal operational efficiency and emergency resource use.