For over 10 years, the International Academies of Emergency Dispatch has been collecting data from emergency dispatch agencies across North America and has amassed one of the largest and most detailed sets of emergency medical dispatch calltaking data available. As of the writing of this report, 262 agencies using the electronic version of the Medical Priority Dispatch System (MPDS®), known as ProQA™ have shared over 30 million cases of detailed, deidentified calltaking data with the IAED. This data is aggregated and made publicly available in a set of interactive dashboards.1
One of the more expansive emergency medical dispatcher (EMD) performance-reporting sections of the IAED data center are the dashboards specific to Dispatcher-Directed CPR (DD-CPR) metrics.
The American Heart Association (AHA) has established CPR performance measures for emergency medical dispatchers (EMDs) that focus on several performance goals: correctly identifying a cardiac arrest within 90 seconds of answering the emergency call, delivery of pre-arrival CPR instructions 75% of the time for field-provider confirmed arrests and delivery of chest compression instructions within 150 seconds of answering the emergency call.2 Notably, the AHA performance standards provide for a number of exclusions—cases that are not included in the denominator to determine overall agency compliance. These exclusions include language barriers, hysteria, third-party caller, hang-up calls, and other circumstances defined by the center supervisor.
While the IAED does not support the practice of excluding any Dispatcher-Directed CPR data—including those mentioned by the AHA—in recognition of AHA standards, it has segregated its arrest data into different categories—including those cases with barriers that cause substantial delays. So, although the IAED does not exclude barrier calls from its data set as AHA allows, separating the most likely barrier calls allows for a reasonably equitable comparison to the AHA standards while still providing all Dispatcher-Directed CPR data for study—so dispatch practices can be improved to reduce CPR delivery time, including those cases with barriers.
Because ProQA contains standardized timestamping for nearly all EMD actions within the MPDS CPR instruction sequences, elapsed times for completing each CPR step can be measured and extracted for reporting purposes. Several internal studies, including audio case comparisons and observed simulated calls, have confirmed that the ProQA software is accurately recording the real-time progression of the CPR call at each step—including correctly time stamping the identification of an arrest, the start of CPR instructions, instructions to give hand placement for compression (CPR landmark), and start of first compression within a 3 to 4 second margin.3
Consequently, the IAED data center’s aggregate data dashboards can tell us much about how MPDS user-agencies perform in managing their cases of reported arrests—and the results are very encouraging. Since address verification is the first step in answering the emergency phone call, and the second step is launching the (MPDS) ProQA software application to complete patient assessment and DD-CPR, ProQA software does not contain the initial time stamp used by the AHA to start its elapsed time clock: the time the phone is answered by the EMD. Hence this time is not reflected in the IAED data dashboards. Typically, this is accounted for by the local agency by adding in a median time for address verification of between 30 and 45 seconds, depending on the agency. For comparison purposes, the IAED generally uses 45 seconds—the upper limit of the average address verification time frame.
For example, looking at the arrest recognition time in the IAED Data Center dashboard, a median time of 28 seconds is recorded (from time the ProQA software is launched until arrest recognition achieved—noted by the timestamp of the MPDS determinant code). In AHA terms, this translates to a median arrest recognition time of 73 seconds (45 seconds plus 28 seconds)—well within the AHA standard of 90 seconds.
For cases with no barriers and the arrest occurred before the call was answered by the EMD, the median time to start of compressions is 137 seconds, or 182 seconds when comparing to the AHA standard (adding 45 seconds for address verification). While this is somewhat above the AHA goal of 150 seconds, given that this median time is an aggregate for all agencies and that the AHA excludes many calls that are not excluded by default in the IAED reporting (such as language barriers and emotional callers), it is likely that many high performing MPDS agencies currently sharing data are at or near the 150 second cutoff set by the AHA.
The Dispatcher-Directed median resuscitation time is a critical measure that is not publicly reported anywhere else. This is a measure of how long the 911 caller did DD-CPR before the first field responder arrived at the patient’s side. For the most recent three-year period that included over 126,000 cardiac arrest cases for the six most common arrest codes in the MPDS, the median resuscitation time was 235 seconds (3.9 minutes) overall for the 262 agencies reporting. This one measure demonstrates the essential and lifesaving role the EMD plays in the chain of survival after a cardiac or respiratory arrest. Some years ago, Cummins established that cardiac arrest survival improves by 10% when bystander-initiated CPR is done before arrival of trained field responders.3 Further, that study determined the average elapsed time that bystander-initiated CPR was done before trained field responders started their patient care was 3.8 minutes—nearly the same as the 3.9 minutes reported in the IAED CPR report. A number of more recent studies have demonstrated the value DD-CPR in improving bystander-initiated CPR rates and survival.4-8
Let’s examine how many lives can be saved among MPDS user-agencies simply by completing MPDS DD-CPR protocols. Assuming the same 10% improvement in survival determined by Cummins, applying it to the annual IAED reported cases of DD-CPR in the data center for the six most common arrest codes—42,187 (126,561/3 for the 3 most recent years reported)—we get 4,219 lives saved each year (42,187 x .10) with MPDS DD-CPR. Considering that only about 8% of all MPDS users worldwide are sharing data in the IAED Data Center (with many large international sites not yet sharing their data), we can then extrapolate to the rest of the non-sharing agencies by using a multiplier of 12.5 (100%/8%). That comes to 52,738 lives saved annually by MPDS user-agencies worldwide, simply by doing DD-CPR.
Certainly, there are other lifesaving instructions in the MPDS that have yet to be studied in-depth for their benefit on patient outcomes: checking and securing an open airway; bleeding control with direct pressure and use of a tourniquet; aspirin delivery for heart attack patients; naloxone delivery instructions for opioid overdoses, to name a few. While future studies of these treatments are needed, one thing is already clear— remote, early DD-CPR provided by trained EMDs is critical to improving patient outcomes and an essential component of a high-performance emergency medical services (EMS) system.
1. International Academies of Emergency Dispatch. Emergency Medical Dispatch Dashboard. https://www.aedrjournal.org/analytics-dashboard-emd. Accessed July 6, 2023.
2. American Heart Association. Telecommunicator CPR Recommendations and Performance Measures. https://cpr.heart.org/en/resuscitation-science/telecommunicator-cpr/telecommunicator-cpr-recommendations-and-performance-measures. Accessed July 6, 2023.
3. Scott G, Barron T, Gardett I, Broadbent M, Downs H, Devey L, Hinterman EJ, Clawson JJ, Olola C. Can a Software-Based Metronome Tool Enhance Compression Rate in a Realistic 911 Call Scenario Without Adversely Impacting Compression Depth for Dispatcher-Assisted CPR? Prehospital and Disaster Medicine. 2018 Jul. 23. Cambridge University Press
4. Cummins RO, Eisenberg MS, Hallstrom AP, Litwin PE. Survival of out-of-hospital cardiac arrest with early initiation of cardiopulmonary resuscitation. Am J Emerg Med. 1985 Mar;3(2):114-9. doi: 10.1016/0735-6757(85)90032-4. PMID: 3970766.
5. Pek PP, Lim JYY, Leong BS, Mao DR, Chia MY, Cheah SO, Gan HN, Ng YY, Tham LP, Arulanandam S, Shahidah N, Lin X, Ho AFW, Ong MEH. Improved Out-of-Hospital Cardiac Arrest Survival with a Comprehensive Dispatcher-Assisted CPR Program in a Developing Emergency Care System. Prehosp Emerg Care. 2021 Nov-Dec;25(6):802-811. doi: 10.1080/10903127.2020.1846824. Epub 2020 Dec 4. PMID: 33151108.
6. Eberhard KE, Linderoth G, Gregers MCT, Lippert F, Folke F. Impact of dispatcher-assisted cardiopulmonary resuscitation on neurologically intact survival in out-of-hospital cardiac arrest: a systematic review. Scand J Trauma Resusc Emerg Med. 2021 May 24;29(1):70. doi: 10.1186/s13049-021-00875-5. PMID: 34030706; PMCID: PMC8147398.
7. Ro YS, Shin SD, Lee YJ, Lee SC, Song KJ, Ryoo HW, Ong MEH, McNally B, Bobrow B, Tanaka H, Myklebust H, Birkenes TS. Effect of Dispatcher-Assisted Cardiopulmonary Resuscitation Program and Location of Out-of-Hospital Cardiac Arrest on Survival and Neurologic Outcome. Ann Emerg Med. 2017 Jan;69(1):52-61.e1. doi: 10.1016/j.annemergmed.2016.07.028. Epub 2016 Sep 21. PMID: 27665488.
8. Yoshikazu Goto, Akira Funada, Tetsuo Maeda, Yumiko Goto, Dispatcher-assisted conventional cardiopulmonary resuscitation and outcomes for pediatric out-of-hospital cardiac arrests. Resuscitation. 2022, Vol 172, Pages 106-114. ISSN 0300-9572. https://doi.org/10.1016/j.resuscitation.2021.10.003.