Abstract
Aim:
Care by emergency medical service (EMS) agencies is critical for optimizing prehospital outcomes following out-of-hospital cardiac arrest (OHCA). We explored whether substantial differences exist in prehospital outcomes across EMS agencies in Michigan—specifically focusing on rates of sustained return of spontaneous circulation (ROSC) upon emergency department (ED) arrival.
Methods:
Using data from Michigan Cardiac Arrest Registry to Enhance Survival (MI-CARES) for years 2014–2017, we calculated rates of sustained ROSC upon ED arrival across EMS agencies in Michigan. We used hierarchical logistic regression models that accounted for patient, arrest-, community-, and response-level characteristics to determine adjusted rates of sustained ROSC among EMS agencies.
Results:
A total of 103 EMS agencies and 20,897 OHCA cases were included. Average age of the cohort was 62.5 years (SD = 19.6), 39.7% were female, and 17.9% had an initial shockable rhythm due to ventricular fibrillation or pulseless ventricular tachycardia. The adjusted rate of sustained ROSC upon ED arrival across all EMS agencies was 23.8% with notable variation across EMS agencies (interquartile range [IQR], 20.5–29.2%). The top five EMS agencies had mean adjusted rates of sustained ROSC upon ED arrival of 42.7% (95% CI: 34.6–51.1%) while the bottom five had mean adjusted rates of 9.8% (95% CI: 7.6–12.7%).
Conclusions:
Substantial variation in sustained ROSC upon ED arrival exists across EMS agencies in Michigan after adjusting for patient-, arrest, community-, and response-level features. Such differences suggest opportunities to identify and improve best practices in EMS agencies to advance OHCA care.
Keywords: Out-of-hospital, Cardiac arrest, Survival, Sustained ROSC, Prehospital
Introduction
Each year, approximately 400,000 people in the United States experience out-of-hospital cardiac arrests (OHCA).1 OHCA survival at the time of hospital discharge varies by as much as 40% between counties across the U.S.2 A recent National Academy of Medicine (NAM), formerly the Institute of Medicine (IOM), report highlighted that some communities have been consistently more successful in treating OHCA than others,3 with a few high-performing communities reporting survival rates to hospital discharge exceeding 60% for specific types of OHCA such as witnessed ventricular fibrillation and pulseless ventricular tachycardia.4
Given the importance of the first few minutes following OHCA, variation in survival outcomes from these events are likely dependent upon care processes instituted by bystanders, first responders, and EMS in the prehospital setting. Prior literature suggests there is great variability across EMS agencies in terms of their care practices that may relate to OHCA outcomes, including the availability of 9-1-1 dispatcher-assisted bystander CPR and AED use5,6; computer-assisted dispatching7,8; ambulance crew coordination3,9; delivering high performance CPR via manual chest compressions,10,11 or by employing technology-based devices such as mechanical CPR devices12; delivering post-arrest care prior to or during transport13; transitions of care between first-responders and EMS and EMS and hospitals3,14; and continuous quality improvement efforts applicable therein.15 However, there is much less evidence of systematic differences in prehospital OHCA outcomes, and how those are linked to EMS agency practices, which is important to demonstrate if best practices are to be understood.
Accordingly, we used the Michigan Cardiac Arrest Registry to Enhance Survival (MI-CARES) to calculate adjusted rates for prehospital outcomes after OHCA across EMS agencies in Michigan and quantify variability in ROSC rates across EMS agencies.
Methods
Data source
We used data from MI-CARES from 2014 to 2017 to identify patients with OHCA. Through 2017, there were 112 EMS agencies contributing data to the MI-CARES registry — a volunteer registry that collects standardized data elements on OHCA patients. Participating EMS agencies are linked to the national CARES registry developed in partnership with the Centers for Disease Control and Emory University (https://mycares.net/).16
During the study period, the MI-CARES registry contained a broad-based sample of EMS agencies in urban, suburban, and rural areas in MI with geographic representation from various regions of the state, accounting for approximately 7.41 of the total 9.9 million MI residents.17 EMS agencies include those that provide transporting services and advanced life support services (ALS). We excluded observations (n = 22) from 9 agencies with more than five OHCAs over the study period, leaving 103 EMS agencies. We obtained approval from the CARES national office to use data from MI, and the study was approved by the University of Michigan Institutional Review Board.
Outcome measures and other covariates
The prehospital outcome of primary interest in our analyses was sustained return of spontaneous circulation (ROSC), defined as chest compressions not required for 20 or more consecutive minutes to sustain circulation.18 Sustained ROSC was also considered to have occurred when circulation persisted for a shorter duration of time, but the patient was transferred to the ED before 20 min are reached.18 We selected this measure through expert consensus of multiple stakeholders that included prehospital professionals, emergency medicine physicians, cardiologists, and critical care physicians. This measure was deemed to most fully represent the totality of prehospital care provided to OHCA victims by bystanders, first responders, and EMS agencies before they receive care in the ED and/or inpatient setting.
Data on patient-level characteristics included age, gender, and race obtained from the MI-CARES registry. We obtained arrest-level characteristics included arrest location and year, whether the arrest was witnessed (yes/no), and first monitored rhythm (shockable rhythm: [defined as ventricular fibrillation, pulseless ventricular tachycardia, or unknown shockable] or unshockable rhythm [defined as asystole, idioventricular/pulseless electrical activity, or unknown unshockable]). We also included the response-level characteristics regarding who initiated CPR and whether an AED was applied from the MI-CARES registry.16 For these analyses, community-level characteristics included: proportion of individuals based on age (percentage ≥25 years or older), gender, racial composition, GED or higher degree, average household size, median household income, land area, median age, unemployment rate, and population per square mile. Data on community-level characteristics were five-year estimates obtained from the American Community Survey (ACS) 2012 and assessed at the census tract level.17
Statistical analysis
Bivariate analyses of patient-, arrest-, community, and response-level characteristics were performed between those with and without sustained ROSC upon arrival to the ED. In our bivariate analysis, we quantified covariate effects on the unadjusted odds of achieving ROSC using hierarchical logistic regression with EMS agency random intercepts, but did not control for any other covariates. We then fit a multivariable hierarchical logistic regression with clinically and statistically relevant covariates to obtain risk adjusted ROSC rates. We used hierarchical models to account for clustering of patients within EMS agencies. EMS agency-specific risk adjusted ROSC rates and 95% confidence intervals on the rates were calculated. To examine variation in risk adjusted rate of sustained ROSC for each EMS agency, we examined the distribution of these rates using a caterpillar plot. We highlighted extreme differences by calculating and reporting mean adjusted rates of sustained ROSC among the top five and bottom five EMS agencies. All final model information from the hierarchical multivariable logistic regression including parameter estimates are included in the eTable.
We used SAS Version 9.4 (SAS Institute, Cary, NC) for all analyses. All hypothesis testing was performed at a significance level of 0.05.
Results
Descriptive analysis
A total of 103 agencies covering an approximate population of 7.4 million and 20,897 OHCA patients. A total of 4972 (23.8%) achieved sustained ROSC with a pulse present at the time of arrival to the emergency department (ED). Table 1 shows patient-, arrest, and community-level characteristics associated with sustained ROSC with a pulse present at the time of arrival to the ED, stratified by quartiles of performance of EMS agencies. EMS agencies in the highest quartile of performance had OHCA patients with a slightly higher age, but these groups also included more men and Caucasians as well as fewer African Americans. For example, fewer than 10% of OHCA patients treated by EMS agencies in the top quartile were African-American compared with more than 50% in the bottom quartile. We also saw differences in arrest- (e.g., presence of a shockable rhythm) and community-level features (e.g., socioeconomic features). For example, EMS agencies in the highest quartile of performance had patients who lived in communities with higher rates of education and higher household incomes than those in the bottom quartile.
Table 1 -.
Patient-, arrest, and community-level characteristics for primary outcome of sustained ROSC with pulse upon emergency department arrival stratified by bottom-performing quartile of EMS agencies, 2 middle-performing quartiles of EMS agencies, and top-performing quartile of EMS agencies.
| Variable name | All patients (N = 20,897) | Bottom-performing (N = 6206) | Middle-performing (N = 9883) | Top-performing (N = 4808) | p-Value | |
|---|---|---|---|---|---|---|
| Patient level | Age (years) (M, SD) | 62.5 (19.6) | 61.6 (20.2) | 62.9 (19.4) | 63.0 (19.3) | 0.0001 |
| Gender, n (%) | ||||||
| Female | 8293 (39.7) | 2698 (43.5) | 3810 (38.6) | 1785 (37.1) | <0.0001 | |
| Male | 12,604 (60.3) | 3508 (56.5) | 6073 (61.5) | 3023 (62.0) | <0.0001 | |
| Race, n (%) | ||||||
| American Indian/Alaskan | 58 (.3) | 33 (.5) | 18 (.2) | 7 (.2) | <0.0001 | |
| Asian | 108 (.5) | 14 (.2) | 70 (.7) | 24 (.5) | 0.0002 | |
| Black/African-American | 5084 (24.3) | 3144 (50.7) | 1542 (15.6) | 398 (8.3) | <0.0001 | |
| Hispanic/Latino | 224 (1.07) | 39 (.6) | 125 (1.3) | 60 (1.3) | 0.0003 | |
| Native Hawaiian/Pacific Islander | 15 (.1) | 6 (.1) | 6 (.1) | 3 (.1) | 0.6824 | |
| Unknown | 4585 (21.9) | 1703 (27.4) | 1895 (19.1) | 987 (20.5) | <0.0001 | |
| White | 10,823 (51.8) | 1267 (20.4) | 6227 (63.0) | 3329 (69.2) | <0.0001 | |
| Arrest level | Location type, n (%) | |||||
| Healthcare facility | 615 (2.9) | 211 (3.4) | 276 (2.8) | 128 (2.7) | 0.0361 | |
| Home/residence | 14,849 (71.1) | 4473 (72.1) | 6893 (70.0) | 3483 (72.4) | 0.0004 | |
| Industrial place | 118 (.6) | 23 (.4) | 56 (.6) | 39 (.8) | 0.0093 | |
| Nursing home | 3073 (14.7) | 920 (14.8) | 1530 (15.5) | 623 (13.0) | 0.0003 | |
| Other | 73 (.4) | 24 (.4) | 32 (.3) | 17 (.4) | 0.8037 | |
| Place of recreation | 228 (1.1) | 40 (.6) | 120 (1.2) | 68 (1.4) | 0.0002 | |
| Public/commercial building | 1185 (5.7) | 270 (4.4) | 618 (6.3) | 297 (6.2) | <0.0001 | |
| Street/Hwy | 749 (3.6) | 245 (4) | 352 (3.6) | 152 (3.2) | 0.0873 | |
| Transport center | 7 (<0.1) | 0(0) | 6 (.1) | 1 (<0.1) | 0.1056 | |
| Arrest witness status, n (%) | ||||||
| Unwitnessed | 11,225 (53.7) | 3529 (56.9) | 5250 (53.1) | 2446 (50.9) | <0.0001 | |
| 9-1-1 responder witnessed | 2321 (11.1) | 646 (10.4) | 1121 (11.3) | 554 (11.5) | 0.1077 | |
| Bystander witnessed | 7351 (35.2) | 2031 (32.7) | 3512 (35.5) | 1808 (37.6) | <0.0001 | |
| First rhythm type, n (%) | ||||||
| Non-shockable | 17,161 (82.1) | 5298 (85.4) | 8052 (81.5) | 3811 (79.3) | <0.0001 | |
| Shockable | 3736 (17.9) | 908 (14.6) | 1831 (18.5) | 997 (20.7) | <0.0001 | |
| First monitored rhythm, n (%) | ||||||
| (Non-shockable), n (%) | ||||||
| Asystole | 9918 (47.5) | 2321 (37.4) | 5196 (52.6) | 2401 (49.9) | <0.0001 | |
| Idioventricular/PEA | 3710 (17.8) | 805 (13.0) | 1920 (19.4) | 985 (20.5) | <0.0001 | |
| Unknown unshockable rhythm | 3533 (16.9) | 2172 (35.0) | 936 (9.5) | 425 (8.8) | <0.0001 | |
| (Shockable), n (%) | ||||||
| Unknown shockable rhythm | 1150 (5.5) | 421 (6.8) | 494 (5.0) | 235 (4.9) | <0.0001 | |
| Ventricular fibrillation | 2385 (11.4) | 457 (7.4) | 1219 (12.3) | 709 (14.8) | <0.0001 | |
| Ventricular tachycardia | 201 (1) | 30(.5) | 118 (1.2) | 53 (1.1) | <0.0001 | |
| Year of arrest, n (%) | ||||||
| 2014 | 3227 (15.4) | 1077 (17.3) | 1335 (13.5) | 815 (17.0) | <0.0001 | |
| 2015 | 4917 (23.5) | 1595 (25.7) | 2163 (21.9) | 1159 (24.1) | <0.0001 | |
| 2016 | 5951 (28.5) | 1638 (26.4) | 3037 (30.7) | 1276(26.5) | <0.0001 | |
| 2017 | 6802 (32.6) | 1896 (30.6) | 3348 (33.9) | 1558 (32.4) | <0.0001 | |
| Community- levela | Median age (M,SD) | 39.4 (6.7) | 38.4 (6.8) | 39.8 (6.7) | 39.3 (6.2) | <0.0001 |
| Percentage male (M,SD) | 48.8 (3.8) | 48.0 (4.6) | 49.0 (3.6) | 49.3 (3.2) | <0.0001 | |
| Percentage Native American (M,SD) | .4 (1.2) | .4 (.9) | 5 (1.5) | .3 (.7) | 0.001 | |
| Percentage Asian (M,SD) | 2.9 (5.7) | 2.0 (5.1) | 3.1 (6.0) | 3.0 (4.7) | 0.0001 | |
| Percentage Black/African American (M,SD) | 21.8 (31.4) | 53.3 (39.0) | 12.0 (18.9) | 8.5 (13.8) | <0.0001 | |
| Percentage Pacific Islander (M,SD) | <0.1 (.2) | <0.1 (.1) | <0.1 (.2) | <0.1 (.3) | 0.1548 | |
| Percentage Other Race (M,SD) | 1.3 (3.4) | 1.8 (5.1) | 1.2 (2.7) | 1.1 (3.0) | <0.0001 | |
| Percentage Mixed Race (M,SD) | 2.8 (2.5) | 2.3 (2) | 3 (2.4) | 3.1 (2.9) | <0.0001 | |
| Percentage of population with GED or higher (M,SD) | 60 (9.9) | 55.6 (10.8) | 61.1 (9.2) | 61.9 (8.7) | <0.0001 | |
| Percentage population 25 years or older (M,SD) | 67.6 (7.4) | 66.5 (7.6) | 67.9 (7.4) | 67.8 (7.0) | <0.0001 | |
| Population per square mile | 3062.1 (2603.1) | 4699.8 (2523.3) | 2608.1 (2442.0) | 2371.3 (2171.1) | <0.0001 | |
| Unemployment rate (M,SD) | 10.2 (7.9) | 16.6 (10.1) | 8.0 (5.1) | 7.6 (5.2) | <0.0001 | |
| Average household size (M,SD) | 2.5 (.4) | 2.6 (.4) | 2.5 (.4) | 2.5 (.4) | 0.1288 | |
| Median income (M,SD) | $54,362.33 (26712.77) | $40,203.61 (23190.29) | $57,997.02 (25969.03) | $60,820.45 (24505.54) | <0.0001 | |
| Land area (square miles) (M,SD) | 10.3 (29.9) | 1.0 (1.6) | 14.4 (37.4) | 9.6 (17.0) | <0.0001 | |
| Response level | Initiated CPR | |||||
| Not applicable or missing | 12 (0.06%) | 2 (<0.1%) | 6 (0.1%) | 4 (0.1%) | 0.5322 | |
| First responder | 5302 (25.37%) | 876 (14.1%) | 2843 (28.8%) | 1583 (32.9%) | <0.0001 | |
| Lay person | 1743 (8.34%) | 341 (5.5%) | 886 (9.0%) | 516 (10.7%) | <0.0001 | |
| Lay person family member | 3066 (14.67%) | 731 (11.8%) | 1529(15.5%) | 806 (16.8%) | <0.0001 | |
| Lay person medical provider | 3283 (15.71%) | 954 (15.4%) | 1619 (16.4%) | 710 (14.8%) | 0.0283 | |
| Responding EMS personnel | 7491 (35.85%) | 3302 (53.2%) | 3000 (30.4%) | 1189 (24.7%) | <0.0001 | |
| Was an AED applied? | ||||||
| No | 14,224 (68.1) | 5253 (84.6) | 6321 (64.0) | 2650 (55.1) | <0.0001 | |
| Yes, with defibrillation | 1606 (7.7) | 229 (3.7) | 829 (8.4) | 548 (11.4) | <0.0001 | |
| Yes, without defibrillation | 5067 (24.3) | 724 (11.7) | 2733 (27.7) | 1610 (33.5) | <0.0001 |
Calculated as a weighted average from values from each census tract of patients contained in the quartile.
From the adjusted hierarchical logistic regression models, the mean adjusted rate of sustained ROSC upon ED arrival across all EMS agencies was 23.8% (95% CI: 18.8%–29.7%). Substantial variation across EMS agencies was noted with mean adjusted ROSC rate estimates ranging from 6.1% to 52.5% (IQR: 24.1–42.5%). Fig. 1 shows that variation graphically by displaying EMS agencies lowest to highest in terms of adjusted rates of sustained ROSC with pulse upon ED arrival. As examples of the broad differences we discovered, we highlighted the top five EMS agencies with a mean adjusted rate of sustained ROSC of 42.7% (95% CI: 34.6–51.1%) while the bottom five had mean adjusted rates of 9.8% (95% CI: 7.6–12.7%). Sensitivity analyses demonstrated EMS agency rankings only minor discrepancies in agency performance when using the alternative outcome of any ROSC.
Fig. 1 -.
Adjusted Rate of Sustained ROSC with pulse upon ED arrival across 103 EMS agencies in Michigan, 2014–2017.
Discussion
Analyzing MI-CARES data for the years 2014–2017, we showed over an 8-fold variation in sustained ROSC with pulse upon ED arrival among MI-CARES participating EMS agencies. The magnitude of variation demonstrated in OHCA survival rates across high- and low-performing EMS agencies points to potential differences in the effectiveness of response protocols to OHCA incidents within the prehospital systems of care. Emergency medical response protocols in Michigan are written and established at the county-level by Medical Control Authorities (MCAs) with the full force and effect of law.19 As a result, emergency medical response protocols can vary both in terms of content and execution of effective response. The degree of variation in OHCA survival rates across high- and low-performing agencies also points to structural and resource differences in served communities that may exist despite adjustment for multiple patient-, arrest-, and community-level features.
In a landmark study from 2008, Nichol et al. found substantial variation across 10 regions of the U.S. in OHCA survival to hospital discharge.20 This report included a variety of regions across North America and focused on the ultimate measure of a system's efficacy — namely, survival to hospital discharge. Similar findings were reported by the CARES registry across even a broader region of the U.S.16,21 Although both studies (and others)22-24 have documented differences in survival to hospital discharge, there are fewer data on immediate outcome measures such as achieving ROSC before arrival to the hospital.25-28 This last measure was the focus of our study and allowed for a more direct examination of effectiveness of the EMS agency. Our findings suggest differences in survival outcomes may result from variability in prehospital factors.
There are several limitations specific to our study design that warrant further discussion. First, this study evaluated variation in outcomes for EMS agencies in Michigan, which may limit generalizability of study findings to other states. However, Michigan has diverse geography in its living environments (including urban, suburban, and rural areas), and its population is diverse across age, race and socioeconomic groups. Second, we also limited our cohort to MI-CARES-participating agencies. The MI-CARES also includes data only from EMS agencies that provide ALS. Thus, we might have missed cases that were evaluated and terminated by EMS agencies that provide only basic life support prior. Although we cannot calculate the number of missed cases directly, this is a relatively uncommon occurrence for cardiac arrests in Michigan (<15%). This may suggest that our findings represent a “best” case scenario if we believe that higher performing EMS agencies are likely to participate in quality improvement efforts like MI-CARES. Third, we are unable to capture all of the critical features that likely explain differences across EMS agencies, including specific prehospital protocols. A benefit of MI-CARES is that it includes high-quality data collection, as participating agencies are also required to conduct routine audits.16,21 In an ongoing mixed-methods study we are exploring additional features that may distinguish higher and lower-performing EMS agencies through detailed site visits.
Conclusions
We found substantial variation in sustained ROSC with pulse upon ED arrival among EMS agencies in MI-CARES data for 2014–2017. This variation suggests potential differences in the effectiveness of pre-hospital systems of care which include the roles, interventions, and coordination of bystanders, alongside 9-1-1 dispatchers,5-8 first responders (i.e. fire, police),3,14 and ambulance crews.3,9-13 Future work will need to explore organizational characteristics and strategies that help or hinder the prehospital OHCA care delivery from a systems of care perspective.29
Acknowledgements
The authors would like to thank Valencia Waller for editorial assistance in preparing the manuscript.
Funding and role of funders
This study was funded by the National Heart, Lung, and Blood Institute (NHLBI) 5R01HL137964-04. The authors declare the study sponsors had no role in the study design, in the collection, analysis and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.resuscitation.2020.11.034.
Footnotes
Declaration of conflicts of interest
Dr. Neumar reports being Co-Chair, International Liaison Committee on Resuscitation, and President and Board Chair, SaveMiHeart. The other authors do not have any relevant conflicts of interest to disclose.
CREDIT AUTHOR STATEMENT
Mahshid Abir: Conceptualization, Writing - Original draft preparation, Writing - Review and Editing, Methodology, Supervision
Sydney Fouche: Writing - Original draft preparation, Writing - Reviewing and Editing, Investigation, Supervision
Jessica Lehrich: Writing – Original draft preparation, Writing - Reviewing and Editing
Jason Goldstick: Writing – Original draft preparation
Neil Kamdar: Formal analysis, Data curation, Investigation, Visualization
Michael O’Leary: Formal analysis, Data curation, Investigation, Visualization
Christopher Nelson: Writing - Reviewing and Editing
Peter Mendel: Writing - Reviewing and Editing
Wilson Nham: Writing - Reviewing and Editing
Claude Setodji: Writing - Reviewing and Editing
Robert Domeier: Writing - Reviewing and Editing
Anthony Hsu: Writing - Reviewing and Editing
Theresa Shields: Writing - Reviewing and Editing
Rama Salhi: Writing - Reviewing and Editing
Robert W. Neumar: Writing - Reviewing and Editing
Brahmajee K. Nallamothu: Conceptualization, Writing - Original draft preparation, Writing - Reviewing and Editing, Methodology, Supervision
Data availability
Data is available for access upon request through the CARES National Office (https://mycares.net).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data is available for access upon request through the CARES National Office (https://mycares.net).