Association between hospital post-resuscitative performance and clinical outcomes after out-of-hospital cardiac arrest

Resuscitation 92 (2015) 45–52

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Clinical paper

Association between hospital post-resuscitative performance and clinical outcomes after out-of-hospital cardiac arrest夽 Dion Stub a,b,f,i , Robert H. Schmicker a , Monique L. Anderson c , Clifton W. Callaway d , Mohamud R. Daya e , Michael R. Sayre a , Jonathan Elmer d , Brian E. Grunau f , Tom P. Aufderheide g , Steve Lin h , Jason E. Buick h , Dana Zive e , Eric D. Peterson c , Graham Nichol a,∗ , ROC Investigators a

University of Washington, Seattle, WA, United States Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia c Duke University, Durham, NC, United States d University of Pittsburgh, Pittsburgh, PA, United States e Oregon Health and Science University, Portland, OR, United States f St Paul’s Hospital University of British Columbia, Vancouver, BC, Canada g Medical College of Wisconsin, Milwaukee, WI, United States h University of Toronto, Toronto, ON, Canada i Alfred Hospital Melbourne, Australia b

a r t i c l e

i n f o

Article history: Received 27 January 2015 Received in revised form 13 April 2015 Accepted 15 April 2015 Keywords: Cardiac arrest Resuscitation Performance score Post resuscitation care

a b s t r a c t Background: Survival varies among those resuscitated from out-of-hospital cardiac arrest (OHCA). Evidence-based performance measures have been used to describe hospital quality of care in conditions such as acute coronary syndrome and major trauma. It remains unclear if adherence to performance measures is associated with better outcome in patients hospitalized after OHCA. Objectives: To assess whether a composite performance score based on evidence-based guidelines for care of patients resuscitated from OHCA was independently associated with clinical outcomes. Methods: Included were 3252 patients with OHCA who received care at 111 U.S. and Canadian hospitals participating in the Resuscitation Outcomes Consortium (ROC-PRIMED) study between June 2007 and October 2009. We calculated composite performance scores for all patients, aggregated these at the hospital level, then associated them with patient mortality and favorable neurological status at discharge. Results: Composite performance scores varied widely (median [IQR] scores from lowest to highest hospital quartiles, 21% [20%, 25%] vs. 59% [55%, 64%]. Adjusted survival to discharge increased with each quartile of performance score (from lowest to highest: 16.2%, 20.8%, 28.5%, 34.8%, P < 0.01), with similar findings for adjusted rates of good neurologic status. Hospital score was significantly associated with outcome after risk adjustment for established baseline factors (highest vs. lowest adherence quartile: adjusted OR of survival 1.64; 95% CI 1.13, 2.38). Conclusions: Greater survival and favorable neurologic status at discharge were associated with greater adherence to recommended hospital based post-resuscitative care guidelines. Consideration should be given to measuring, reporting and improving hospital adherence to guideline-based performance measures, which could improve outcomes following OHCA. © 2015 Elsevier Ireland Ltd. All rights reserved.

1. Introduction

夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at http://dx.doi.org/10.1016/j.resuscitation.2015.04.015. ∗ Corresponding author at: University of Washington, Harborview Center for Prehospital Emergency Care, Seattle, WA, United States. E-mail address: [email protected] (G. Nichol). http://dx.doi.org/10.1016/j.resuscitation.2015.04.015 0300-9572/© 2015 Elsevier Ireland Ltd. All rights reserved.

Out-of-hospital cardiac arrest (OHCA) affects approximately 424,000 people in the USA and millions more around the world annually.1 Despite efforts to improve all aspects of the chain of survival, there is significant and important variation in the process and outcome of care among those treated for OHCA by emergency medical services (EMS) providers or admitted to hospital after successful resuscitation efforts.2–5 This variation is incompletely explained by

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patient and EMS factors typically measured to standardize reporting of the process and outcomes of care for OHCA in an attempt to facilitate comparisons between communities.6 Multiple components of both field and hospital care are associated with improved patient outcomes in this population. In the pre-hospital setting, greater depth of chest compressions, shorter perishock pauses, and optimizing chest compression rate are associated with improved outcomes after OHCA.7–10 Hospital based interventions associated with survival include selective use of early coronary angiography and intervention,11,12 targeted temperature management,13–15 and delayed withdrawal of life sustaining treatment.16 Assessment of quality and performance in health care delivery is an important tool to improve patient outcomes. Agencies involved in medical oversight are increasingly reporting performance indicators that are intended to drive improvements in quality of care.17 Performance measures that are associated with patient outcome18,19 may be used to determine hospital and physician reimbursement as well as permit comparisons between institutions. Importantly whilst hospital factors are associated with survival and outcome after resuscitation from OHCA(3),21–23 hospital-level performance measures have not been used to characterize the quality of processes of care for OHCA patients.20 We characterized the degree to which hospital based post-resuscitative care is provided in a manner consistent with current guideline recommendations, identified hospital characteristics that predict higher adherence to guidelines, and determined whether adherence to guidelines was associated with outcomes.

with cardiac arrest due to exsanguination. Among the trial cohort included in the present analysis, were subjects with the potential to receive hospital based post-resuscitative care. Eligible patients were defined as being delivered to a participating receiving hospital with a pulse, survival for ≥60 min after emergency department arrival, and presence of an advanced airway (as a surrogate marker for arriving to hospital with reduced conscious state).23 Excluded from the analysis were subjects for whom resuscitation efforts were discontinued before hospital arrival or for whom no pulse was established even after hospital arrival. Also excluded were hospitals that treated less than five patients with OHCA per year, to define a minimum threshold of experience in managing patients admitted following OHCA. Patients transferred to a second hospital in the first 24 h following OHCA were classified according to their destination hospital. 2.3. Data collection Research coordinators abstracted data into web-based case report forms from EMS and hospital records as well as from electronic data recordings captured by prehospital monitordefibrillators. The Data Coordinating Center trained coordinators, provided on-line assistance with ambiguous cases, and performed site visits and audits to ensure data integrity. Automated withinform and between-form data checks followed by written resolution of conflicting data were performed to reduce errors. 2.4. Performance measures

2. Methods 2.1. Study design and setting Between June 2007 and October 2009, 10 US and Canadian clinical sites in the Resuscitation Outcomes Consortium (ROC) enrolled consecutive patients with OHCA treated by 150 EMS agencies in a multicenter, randomized controlled trial (ROC-PRIMED; Clinicaltrials.gov NCT00394706). This partial factorial trial evaluated the effect on favorable neurologic status (modified Rankin score ≤3) and survival to hospital discharge of performing EMS cardiopulmonary resuscitation (CPR) for a brief (∼30 s) interval or longer interval (∼3 min) prior to rhythm analysis and defibrillation attempt as required. The trial simultaneously evaluated the effect of using an active or sham impedance threshold device (ITD). Neither the CPR strategies nor the ITD device affected overall survival or functional outcome.21,22 Institutional review boards or research ethics boards at all participating sites and hospitals granted an Exception from Informed Consent for emergency research. As soon as feasible, surviving subjects or their legally authorized representatives were notified about the study and provided with an opportunity to withdraw from continued data collection. Hospital medical records were reviewed for all participating subjects until hospital discharge. Primary outcomes were available for all subjects in this secondary study. This analysis of de-identified data was considered exempt from human subjects research. 2.2. Patient population All EMS screened or randomized subjects for the ROC-PRIMED study were identified. Included in ROC-PRIMED were age ≥18 years and OHCA, defined as receiving chest compressions from a professional provider or a rescue shock from a defibrillator. Excluded from the trial were prisoners, pregnant women, patients with known “do not resuscitate” directives made prior to EMS treatment, patients with blunt, penetrating or burn-related trauma, or patients

We prospectively selected five individual ILCOR/AHA guideline recommended, hospital based post-resuscitative therapies in the performance measure.24 These were (a) coronary angiography within 24 h following hospital arrival; (b) initiation of targeted temperature management (TTM), which was defined as any active attempt to lower core body temperature; (c) whether a target temperature of 32–34 ◦ C was achieved; (d) continuation of TTM for more than 12 h (termination of temperature management defined as the time rewarming commenced); and (e) life sustaining treatment not withdrawn prior to day three following hospital arrival (patients who met brain death criteria, were deemed not to have had early withdrawal of life sustaining treatment, if this occurred less than three day post OHCA). We calculated two post-resuscitation performance scores for each patient. The first score used opportunity based scoring, whereby the proportion of eligible patients who received interventions for which they were eligible was calculated for each hospital. We defined performance as the proportion of patients receiving each of the specified care processes for which they were eligible.25 The second score used all or none scoring. This score was based on the proportion of patients who received all five recommended processes of care. Both scores were scaled from 0 to 1, with higher scores interpreted as reflecting better quality of care. 2.5. Analysis Hospitals were divided for descriptive purposes into quartiles based on their median opportunity composite score. We assessed the association between adherence rates for each component process measure and composite adherence rates using Pearson correlation coefficients. Unadjusted and adjusted survival to hospital discharge and Modified Rankin Score (MRS) were calculated for the overall population and by OHCA composite score quartiles, then compared by using Cochran-Armitage tests for trend and generalized mixed linear model respectively. Survival to hospital discharge was defined as transfer from an acute care hospital to rehabilitation, skilled nursing or home residence. MRS at hospital discharge

D. Stub et al. / Resuscitation 92 (2015) 45–52

47

Fig. 1. Subjects included in analysis.

was determined by review of clinical records using a standardized validated instrument. Generalized linear mixed models used a hierarchical approach to adjustment for both risk factors and within and between hospital effects. We adjusted for both patient and pre-hospital factors including: age, sex, time interval from 911 call to EMS arrival on scene, witnessed event, bystander CPR, location of event, first recorded rhythm, presumed cardiac etiology and CPR quality. A series of sensitivity analyses assessed differential impact on outcomes by a priori subgroups including shockable vs. non-shockable rhythms, witnessed status, bystander CPR status, age <70 years vs. ≥70 years, presence or absence of ST-elevation on initial hospital ECG. Collinearity between covariates was assessed by using variation inflation factor. A two-sided p < 0.05 was considered statistically significant for all tests. Data management was performed in S-PLUS (version 6.2.1, 2003, Insightful Corporation, Seattle, WA), while regression analysis were performed in Stata (Release 11, 2009, StataCorp. College Station, TX). 3. Results Of 15,794 subjects enrolled in the ROC PRIMED study with OHCA, 3252 patients met inclusion criteria for our analysis

(Fig. 1). These patients were treated at 111 different hospitals with a median number of patients treated per center of 20 (IQR 11–40). Overall implementation of the specified post-resuscitative interventions occurred in 50% of eligible subjects. Composite post-resuscitative performance scores varied considerably among participating hospitals (Fig. 2). The hospitals in the highest quartile had a median composite score of 59% (IQR 55%, 64%) compared with 21% (IQR 20%, 25%) in the lowest hospital quartile. Patients treated at hospitals with lower composite performance scores tended to be slightly older, more likely female, and had fewer cardiac arrests in public locations as well as fewer initial shockable rhythms (Table 1). By definition, hospitals with the highest composite performance score had increased average adherence to all five post resuscitative measures (Table 2). Of these, premature withdrawal of life sustaining care exhibited the lowest degree of variance, although the difference between the first and fourth hospital quartiles remained significant. Importantly there was a greater than 5-fold difference in the implementation of TTM and coronary angiography within 24 h of admission. Independent hospital predictors of a higher performance score included the presence of on-site cardiac catheterization facilities and treating more patients per year with OHCA (Table 3). We found

Fig. 2. Frequency distribution of hospital post-resuscitation performance score.

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Table 1 Patient and arrest characteristics according to hospital performance score quartiles. Patients characteristics

OHCA post resuscitation adherence quartile

Overall

1 (lowest)

2

3

4 (highest)

Range N (patients) N (hospitals) Median age (IQR) Male, n (%) Public location, n (%)*

0–0.30 382 29 71 (23) 228 (59.7%) 45 (11.8%)

0.31–0.44 635 27 70 (25) 387 (60.9%) 112 (17.6%)

0.44–0.53 809 27 68 (24) 521 (64.4%) 183 (22.6%)

0.53–1 1426 28 65 (24) 930 (65.2%) 304 (21.3%)

3252 111 67 (24) 2066 (63.5%) 644 (19.8%)

Initial rhythm* VF/VT, n (%) Asystole, n (%) PEA, n (%) AED no shock, no strip, n (%) Unknown, n (%)

111 (29.1%) 122 (31.9%) 114 (29.8%) 28 (7.3%) 3 (0.8%)

202 (31.8%) 178 (28.0%) 198 (31.2%) 50 (7.9%) 1 (0.2%)

345 (42.6%) 207 (25.6%) 189 (23.4%) 59 (7.3%) 0 (0.0%)

610 (42.8%) 375 (26.3%) 326 (22.9%) 91 (6.4%) 3 (0.2%)

1268 (39.0%) 882 (27.1%) 827 (25.4%) 228 (7.0%) 7 (0.2%)

Witnessed status* Bystander, n (%) None, n (%) Unknown, n (%) Bystander CPR, n (%)* Time from 911 call to EMS arrival on scene in min, median (IQR) Time from 911 call to ROSC in min, median (IQR) Transport time, in min, median (IQR)* Chest compression fraction, mean (SD)* Compression rate, mean (SD)* Compression depth in mm, mean (SD)

207 (54.2%) 138 (36.1%) 13 (3.4%) 149 (39.0%) 6.1 (2.7) 25.0 (9.5) 7.2 (4.4) 0.69 (0.16) 113.9 (22.6) 44.2 (11.6)

373 (58.7%) 201 (31.7%) 17 (2.7%) 240 (37.8%) 5.9 (3.4) 25.7 (10.1) 7.4 (5.0) 0.71 (0.17) 108.2 (21.7) 42.0 (11.6)

470 (58.1%) 260 (32.1%) 12 (1.5%) 363 (44.9%) 6.1 (2.5) 24.3 (9.5) 7.8 (5.1) 0.71 (0.16) 110.6 (18.2) 43.7 (11.1)

823 (57.7%) 489 (34.3%) 11 (0.8%) 709 (49.7%) 5.7 (2.6) 23.4 (9.5) 9.0 (6.5) 0.72 (0.15) 107.6 (15.4) 42.8 (10.3)

1873 (57.6%) 1088 (33.5%) 53 (1.6%) 1461 (44.9%) 5.9 (2.8) 24.3 (9.7) 8.2 (5.7) 0.71 (0.16) 109.3 (18.5) 43.0 (11.0)

AED – automated external defibrillator, EMS – emergency medical service, CPR – cardiopulmonary resuscitation. * p (for trend) <0.05, all other results were p > 0.1. Table 2 Variation in care processes by site stratified by hospital performance score quartiles. Care process

OHCA post resuscitation performance quartile

Range N (patients) N (hospitals) Temperature management initiated/continued Target temperature <34 degrees achieved Temperature management continued >12 h Coronary angiogram performed <24 h after post admission Treatment not withdrawn <72 h in those patients who survive first 24 h

1 (lowest)

2

3

4 (highest)

0–0.30 382 29 27 (7.1%) 12 (3.1%) 10 (2.6%) 17 (4.5%) 152 (39.8%)

0.31–0.44 635 27 220 (34.6%) 122 (19.2%) 105 (16.5%) 57 (9.0%) 293 (46.1%)

0.44–0.53 809 27 342 (42.3%) 279 (34.5%) 235 (29.0%) 144 (17.8%) 418 (51.7%)

0.53–1 1426 28 866 (60.7%) 764 (53.6%) 638 (44.7%) 336 (23.6%) 810 (56.8%)

little correlation between a hospital’s performance on a single postresuscitation measure and its performance on another (Pearson correlation <0.4) (Appendix eTable 3). Overall survival to discharge was 28.5%, and 20.6% of patients were discharged with a MRS score ≤3. Unadjusted survival to hospital discharge and functional recovery increased sequentially as a function of post-resuscitative adherence in both patients with initial shockable and non-shockable rhythms (Table 4). Hospital performance score was significantly associated with clinical outcome after adjustment for patient and EMS system factors, including patient age, first recorded rhythm, response times, bystander CPR and prehospital resuscitation quality measures and

Overall

3252 111 1455 (44.7%) 1177 (36.2%) 988 (30.4%) 554 (17.0%) 1673 (51.4%)

resuscitation time (highest performance quartile compared to lowest quartile: adjusted odds ratio of survival 1.64; 95% confidence interval 1.13–2.38) (Fig. 3). Hospital performance score was also strongly associated with good neurologic outcome (highest performance quartile compared to lowest quartile: adjusted odds ratio of survival 2.88; 95% confidence interval 1.81–4.58) (Fig. 2). For every 10% improvement in hospital performance score, there was a 1% improvement in risk-adjusted survival to hospital discharge and a 25% improvement in risk-adjusted rate of neurologic recovery. Sensitivity analyses demonstrated that the associations between hospital performance quartile and clinical outcomes following OHCA were robust when tested in a variety of clinical

Table 3 Univariable and multivariable predictors of hospital characteristics in resuscitation outcomes consortium and performance score. Hospital characteristic

Overall

Unadjusted beta (95% CI)

Adjusted beta (95% CI)

# Hospitals # Beds, median (IQR) No. of episodes annually (per 20 cases), Mean (Sd) Catheterization Laboratory, n (%)

111 279 (179, 439) 17.4 (15.1) 66 (60.6%)

– 0.02 (0.01, 0.03) 12.7 (8.5, 16.9) 10.6 (3.9, 17.2)

– 0.01 (−0.13, 0.02) 9.3 (4.3, 14.4) 5.9 (−1.7, 13.5)

−2.9 (−8.6, 2.7) −4.9 (−7.2, −2.5) Reference 6.4 (0.2, 12.6)

0.2 (−5.5, 6.0) −2.1 (−4.9, 0.8) Reference −3.0 (−8.0, 2.0)

Trauma level Level 1, n (%) Level 2, n (%) Level 3, n (%) Residency/Teaching Program, n (%)

18 (16.5%) 12 (11.0%) 53 (48.6%) 60 (55.0%)

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Table 4 Association between unadjusted outcomes and hospital performance score. Outcomes

OHCA post resuscitation performance quartile 1 (lowest)

Survival to discharge VF/VT PEA/asystole Modified Rankin ≤3 VF/VT PEA/asystole

62 (16.2%) 33 (29.7%) 26 (11.0%) 32 (8.4%) 20 (18.0%) 10 (4.2%)

2 135 (21.3%) 87 (43.1%) 34 (9.0%) 89 (14.0%) 67 (33.2%) 16 (4.3%)

Fig. 3. Adjusted survival and good neurological outcome to hospital discharge according to hospital performance quartile and first presenting rhythm. VF – ventricular fibrillation; VT – ventricular tachycardia; PEA – pulseless electrical activity. *Adjusted for age, cardiac arrest time, witnessed arrest, bystander CPR and location.

situations. There was no effect modification of the association between hospital quartile and survival by initial rhythm (p = 0.06), witness status (p = 0.23), age (p = 0.13) or ST-elevation on initial hospital ECG (p = 0.16). Estimates for hospital quartile for pre-specified groups (patients <70 years of age, EMS or bystander witnessed arrest, patients with a shockable rhythm, patients with a nonshockable rhythms and patients with or without ST-elevation on initial hospital ECG) are provided in the supplementary appendix (eTables 6–10). We performed an additional analysis with removal of treatment not withdrawn prior to day three following hospital admission factor from the performance score to investigate for the possibility of this factor introducing significant selection bias. Hospital performance score remained independently associated with survival (highest performance quartile: adjusted odds ratio of survival 1.43; 95% confidence interval 1.06–1.93). Similarly, given the recent uncertainty regarding optimal target temperature,26 we also performed a secondary analysis of our performance score with removal of the target temperature metric. Hospital performance score remained independently associated with survival (highest performance quartile: adjusted odds ratio of survival 1.70; 95% confidence interval 1.2–2.5). 4. Discussion In this large multicenter study of OHCA, use of recommended post-resuscitative measures occurred in only 50% (5847 out of possible 11,623) of eligible treatment opportunities. Furthermore, after adjustment for patient characteristics, EMS response times, bystander CPR and prehospital resuscitation quality measures and resuscitation time, greater hospital adherence to recommended post-resuscitation care was strongly associated with greater

Overall 3 231 (28.6%) 171 (49.6%) 48 (12.1%) 179 (22.1%) 143 (41.4%) 27 (6.8%)

4 (highest) 500 (35.1%) 353 (57.9%) 118 (16.8%) 371 (26.0%) 281 (46.1%) 70 (10.0%)

928 (28.5%) 644 (50.8%) 226 (13.2%) 671 (20.6%) 511 (40.3%) 123 (7.2%)

likelihood of survival to hospital discharge and good neurologic recovery. To our knowledge this is the first study to associate overall hospital process performance score and outcomes in the post-resuscitative period in patients. Post-resuscitative care is a critical component of cardiac arrest treatment pathways. More than a decade ago, two randomized trials of temperature management (commonly called therapeutic hypothermia) in comatose survivors of out-of-hospital VF arrest demonstrated improved survival and neurological outcomes.13,14 A recent large randomized trial of two varying temperature targets (33 ◦ C vs. 36 ◦ C), raised questions as to the optimal target temperature in the post resuscitative period.15 As a result many hospitals may adopt 36 ◦ C as their new target for temperature management in the post-resuscitative period.27 Importantly our hospital performance score remained a significant predictor of survival and neurologic recovery with removal of the target temperature metric. Other reports have questioned the utility of targeted temperature management (TTM) in patients with non-shockable patients.28 Despite ongoing issues requiring further study including indications, optimal dose, and duration of TTM, it currently remains the foundation of post-resuscitative care in comatose survivors of OHCA. Our study showed that use of TTM was associated with improved survival and good neurological outcomes in patients with a shockable rhythm. Other components of our performance score included coronary angiography within 24 h and life sustaining treatment not withdrawn prior to day three. While there are no randomized trials to support the benefit of these measures, and individual cases may have indications for alternative therapies, international guidelines recommend that both timely coronary angiography and delayed decision to withdraw life support should be considered in the majority of patients following OHCA.24 Coronary artery disease is the most common precipitating factor in OHCA, with an incidence of approximately 70%.29 Routine coronary angiography in the post-resuscitative period has been associated with improved patient outcomes in patients with and without evidence of ST-elevation on initial ECG.11,12,30–33 Our data indicating a significant association between hospital performance score and survival in patients even without ST elevation on the initial ECG (Appendix eTable 10) supports these previous studies, and concurs with findings from observational data that best outcomes are achieved when postresuscitative measures are incorporated as a comprehensive bundle of care.34–37 Our results expand on previous data, illustrating the increased use of each post-resuscitation process in higher performing and higher volume hospitals,23 despite overall use of process measures remaining relatively low. The greatest survival, however, was found in those hospitals with patients receiving all five post-resuscitation measures (Appendix eTable 2), highlighting the potential utility of an all or none scoring component, as a means of promoting increased excellence amongst established high performing hospitals.38 Our data support the recent addition of post-cardiac

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arrest care as the 5th link in the cardiac arrest resuscitation chain of survival.24 Our study showed significant variation in implementation of post resuscitation guideline measures. Previous studies have reported similar degrees of underuse of evidence-based processes in patients hospitalized following OHCA.39–42 Our study is consistent with these earlier findings, and provides corroborating evidence that overall hospital performance in the post-resuscitative period is a significant contributor to the regional variation seen in cardiac arrest outcomes.2,3 However, there was little correlation between a hospital’s performance on a single postresuscitation measure and its implementation of another. Similar to patients with acute coronary syndromes,19 our study would therefore support the concept that a broad range of process metrics may be required, to fully assess hospital care practices in managing patients with OHCA. In our adjusted analysis the only hospital factors predictive of better performance were presence of cardiac catheterization facilities and increased hospital volume of ROC cardiac arrest cases per year. Our study is consistent with earlier findings linking hospital cardiac care capabilities to outcome in patients with OHCA.3,43,44 Whilst our study highlights the potential benefit to establishing regional systems of care, with transport to dedicated high performing ‘cardiac arrest centers’,45 our study also indicates that the evaluation of these potential cardiac arrest centers requires direct measures of care processes, rather than simply relying on institutional structural features. Although hospitals with higher post-resuscitative scores had better unadjusted outcomes for patients with both shockable and non-shockable initial rhythms, hospital performance was only independently associated with those patients with an initial shockable rhythm. The influence of post-resuscitative measures on patients with non-shockable rhythms is controversial.28,46 Although prospective randomized data in this group are sparse, a recent systematic review of both randomized and observational studies highlighted benefits of TTM in patients with non-shockable rhythms.47 Our data indicate an overall benefit to patients in higher performing hospitals and thus we would still advocate measuring performance score regardless of presenting rhythm. In an era of transparent public reporting of outcomes, an adoption of comprehensive post-resuscitative care may have a significant impact on use of coronary angiography and myocardial infarction clinical outcomes. It has been suggested that these patients be excluded from standard outcome reporting.48 The application of additional post-resuscitative hospital performance measures, however, for these complex patients may help to ensure that such patients are not excluded from crucial interventions due to physician concerns regarding the high risk nature of their condition, and of the potential adverse impact of public reporting.49 Our study has some limitations. First it is a secondary observational analysis of a randomized study. The association between care process and outcomes do not prove causality. While significant effort was made to adjust for patient and pre-hospital factors, results may be confounded by unknown factors and influenced by both pre-hospital and in-hospital provider bias to treat the patients with the best chance of recovery more aggressively and conversely the patients with poorer prognosis with less intensive measures. Third, we pre-specified our process performance metrics based on guideline recommendations. It was not the intention of this work to determine which specific measures were most closely associated with outcomes nor if other process measures may also contribute to these findings. Next, our sample did not represent a consecutive sample of OHCA patients treated at receiving hospitals, and thus our composite scores are only reflective of patients enrolled in the ROC PRIMED clinical trial. We do not claim to have the ideal

set of process-performance indicators. We selected those indicators previously defined as useful, efficacious and readily obtainable in clinical auditing and practice. The field of resuscitation medicine constantly evolves. Other indicator sets maybe more or less closely associated with patient outcome. However this is a large multicenter observational analysis with judicious data collection and quality control utilizing standard validated definitions. This work has several important health policy implications. Our study indicates that current post-resuscitative hospital care in North America can be improved significantly, with over 50% of opportunities for implementing comprehensive post-resuscitative care processes being missed. Whilst collaborations such as the Resuscitation Outcomes Consortium use certain benchmarks for pre-hospital cardiac arrest care to determine eligibility for ongoing participation, there are no agreed quality standards for postresuscitation hospital processes. Our data suggest that these are needed. Second our data highlights significant variability in hospitals’ performance on individual elements of care. This highlights the need to characterize hospital performance fully with multiple post-resuscitation metrics. Finally a significant independent association between hospitals’ composite care performance and survival and neurologic recovery was observed. Our work supports the notion that post-resuscitative care is a critical link in the cardiac arrest chain of survival. Furthermore hospital quality improvement, possibly through the establishment of regional systems of care at cardiac arrest centers, including the measuring, reporting and improving adherence guideline-based performance metrics could improve outcomes following OHCA. In conclusion a significant association between hospitals’ overall adherence to recommended post-resuscitative care guidelines and outcomes was demonstrated. This finding would support the consideration of measuring, reporting, and improving adherence guideline-based performance metrics as a means of helping improve hospital quality and potentially clinical outcomes following OHCA.

Conflict of interest statement Dr Stub is supported by a cofounded NHMRC/NHF early career fellowship (#1090302/100516) Award. Prof. Nichol receives salary support from the University of Washington via the Leonard A Cobb Medic One Foundation Endowed Chair in Prehospital Emergency Care. He holds Research Grants from the following: (1) National Heart Lung Blood Institute, Bethesda, MD. Resuscitation Outcomes Consortium (NIH U01 HL077863-05) 2004–2015; CoPI; (2) Food and Drug Administration, Silver Spring, MD; Cardiac Science Corp, Waukesha, WI; Heartsine Technologies Inc., Newtown, PA; Philips Healthcare Inc., Bothell, WA; Physio-Control Inc., Redmond, WA; ZOLL Inc., Chelmsford, MA. University of Washington Dynamic AED Registry, PI. 2013-2015 (4) Velomedix Inc., Menlo Park, CA. Velocity Pilot Study of Ultrafast Hypothermia in Patients with ST-Elevation Myocardial Infarction, National Co-PI. 2014-2015. *Waived personal compensation. He did not receive any other Research Support. He is not a member of Speakers Bureau and does not hold an Honorary post in any company. He has no other conflict of interest to declare. He received travel reimbursement from Abiomed Inc., Danvers, MA. Dr. Aufderheide research is supported by NHLBI: Resuscitation Outcomes Consortium (ROC), NIH Director’s Transformative Research Award; grants from NINDS: Neurological Emergency Treatment Trials (NETT) Network. Prof. Eric Peterson’s research is supported by Eli Lilly and Janssen and acts as a consultant to Janssen, Boehringer Ingelheim, Astra Zeneca, Sanofi. Dr. Daya receives NIH research funding. Dr. Elmer receives research funding from NIH, Laerdal Foundation and Zoll Foundation.

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The ROC is supported by a series of cooperative agreements to nine regional clinical centers and one Data Coordinating Center (5U01 HL077863-University of Washington Data Coordinating Center, HL077866-Medical College of Wisconsin, HL077867-University of Washington, HL077871-University of Pittsburgh, HL077872-St. Michael’s Hospital, HL077873-Oregon Health and Science University, HL077881-University of Alabama at Birmingham, HL077885-Ottawa Hospital Research Institute, HL077887-University of Texas SW Medical Ctr/Dallas, HL077908University of California San Diego) from the National Heart, Lung and Blood Institute in partnership with the National Institute of Neurological Disorders and Stroke, U.S. Army Medical Research & Material Command, The Canadian Institutes of Health Research (CIHR) – Institute of Circulatory and Respiratory Health, Defence Research and Development Canada and the Heart, Stroke Foundation of Canada and the American Heart Association. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung and Blood Institute or the National Institutes of Health. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.resuscitation. 2015.04.015

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21. 22. 23.

24.

25.

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