we cannot improve that which we do not measure
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Resuscitation 84 (2013) 1015 1016
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e cannot improve that which we do not measureeywords:ut-of-hospital cardiac arrestmergency medical servicesesuscitation
Out-of-hospital cardiac arrest (OHCA) continues to be a leadingublic heath issue, occurring more than 350,000 times in the Unitedtates annually.1 While nationwide survival has improved little andemains low, municipal survival can be quite variable.2 In 2004,he cardiac arrest registry to enhance survival (CARES) was formedrom a publicprivate partnership with the purpose of conductingurveillance, providing data and quality benchmarks, and identify-ng best practices for OHCA.3 Emphasis was placed upon ease of use,niformity of data, HIPPA compliance, and emergency medical ser-ices (EMS) reporting utility. Since its inception in Atlanta, Georgia,nd the surrounding counties, CARES has expanded rapidly andow provides surveillance in forty communities across twenty-fivetates, statewide surveillance in six of those, and internationallyia collaboration with the Pan Asian Resuscitation Outcomes StudyPAROS).4
In this issue of Resuscitation, Abrams et al. leverage the strengthsf CARES to model survival from OHCA.5 In contrast to contempo-ary approaches using similar predictors and outcome, the authorsmploy a two equation model to simultaneously demonstrate theirect effects of pre-hospital variables upon survival (parallel asso-iation with survival) and the effect of those same variables uponn initial shockable rhythm and pre-hospital ROSC (serial causal-ty of the outcome in question). The latter equation ensures thathe contribution of variables that improve the probability of pre-ospital ROSC or VT/VF is not overshadowed by the relative lackf direct effect on survival when compared to the two most potentredictors, VT/VF or pre-hospital ROSC. This construct is not justemantic, as ROSC at any location is a necessary precursor for theltimate outcome studied, survival to discharge.While many of Dr. Abrams findings have been previously
emonstrated, the novel conceptual model employed is able to suc-inctly quantify the return on investment for various public healthroposals relating to OHCA. For example, this work allows a munici-ality to extrapolate the relative cost of improving survival throughhe universal provision of AEDs or improving EMS response times.hough less of a concern for those of us engaged in resuscitationcience, the ability for policy makers to determine priorities by
ssigning increasingly scarce public health resources for maximalield is invaluable.Furthermore, the use of CARES allows for the examination of
elatively rare events, i.e. survival of the patient who presents with
300-9572/$ see front matter 2013 Elsevier Ireland Ltd. All rights reserved.ttp://dx.doi.org/10.1016/j.resuscitation.2013.05.005a non-shockable rhythm. Such an investigation would be nearlyimpossible at any single institution. With the clear majority ofOHCA presenting in this manner and the prognosis often quite poor,any identifiable opportunity to positively effect outcomes in thiscohort would have substantial impact and would be warmly wel-comed. When leveraging the size of CARES to discover such elusivepredictors, the limitations inherent to the finite dataset becomeapparent.
With a focus upon minimizing the burden of human data entry,CARES has experienced rapid and geographically broad adoption.However, the care provided and equipment employed across thoseagencies varies dramatically. Govindarajan et al. noted in theirsurvey of twenty-five CARES agencies, . . . wide variability inadherence to clinical guidelines for management of OHCA amongagencies.6 While much of this variation is clearly attributableto early adopters of resuscitation techniques that outpaced thequinquennial AHA guidelines, they clearly introduce some biasdespite the inclusion of the Utstein template. The indirect effectsnoted by Dr. Abrams must be viewed in the context of a herteroge-nous landscape of OHCA care despite adherence to the CARES datadictionary.7
Just as variations in pre-hospital care exist,6,8 experience inNorway9 and Sweden demonstrates similar variations among hos-pitals, even when served by the same pre-hospital agency.10
The wide-spread adoption of therapeutic hypothermia has beenslow11,12 despite clear evidence of its efficacy.13,14 Even aspost-resuscitation care becomes more sophisticated and survivalimproves as a result,15 there seems to be little evidence basedagreement upon who should receive post-resuscitation care.16
These variations in hospital practice produce significant differencesin survival well beyond the 16% variation acknowledged by the Dr.Abrams. There is little reason to, assume that such omitted [hos-pital] variables are not highly correlated with the variables in ourmodel. . . as the authors suggest. Such an assumption discounts thefundamental influence of in-hospital care upon the survival ratesof hospitals in CARES.
The challenge of reporting resuscitation science is describinga complex disease state that spans a multiple silos in the houseof Medicine. Following the methodology of the original Utsteinconference, a number of initiatives have been proposed to ensureour literature is comparable across investigations despite theincreasingly complicated science.17,18 In contrast to CARES, thesecomprehensive datasets would track the pre-hospital, emergency
department, in-hospital, and rehabilitation phases with more thanfour hundred variables. Such a robust view of OHCA maybeformidable for all but the most well funded registries, however notimpossible.
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Though labor intensive, other complex disease states haveemonstrated that barriers to investigation beyond the most prox-mal phase of care are not insurmountable, and often quite fruitful.n the case of stroke, pre-hospital identification and pre-hospitalotification has demonstrated improvement in door-to-needleimes resulting in less ischemic time before administration oft-PA.19 Similar acknowledgement and inclusion of pre-hospitalata has lead to EMS recognition and mobilization of the cardiacatheterization laboratory for ST-Segment Elevation Myocardialnfarction (STEMI) and resulted in remarkable improvements inurvival.20 Perhaps the time has come to move beyond the con-enience of measuring out-of-hospital predictors and binaryurvival from OHCA and begin to routinely describe how hospitalharacteristics and treatments delivered effect the patient centeredutcome, neurologically intact survival. To do so would acknowl-dge we cannot improve that which we do not measure.
onflict of interest statement
No conflict of interest on this topic. Dr. Kurz has received modestompensation from AstraZeneca in the last 12 months for advisoryoard participation.
1. Go AS, Mozaffarian D, Roger VL, et al., On behalf of the American Heart Associa-tion Statistics Committee and Stroke Statistics Subcommittee. Heart disease andstroke statistics 2013 update: a report from the American Heart Association.Circulation 2013;127:e6245.
2. Nichol G, Thomas E, Callaway CW, et al. Regional variation in out-of-hospitalcardiac arrest incidence and outcome. JAMA 2008;300:142330.
3. McNally B, Stokes A, Crouch A, et al. CARES: cardiac arrest registry to enhancesurvival. Ann Emerg Med 2009;54:67483.
4. National Center for Chronic Disease Prevention and Health Promotion, Divi-sion for Heart Disease and Stroke Prevention. Cardiac arrest registry to enhancesurvival (CARES); 2013. https://mycares.net/downloads/CARES%20Brochure%20(2.8.11).pdf [accessed 05.05.13].
5. Abrams B, McNally B, Ong M. A composite model of survival from out-of-hospitalcardiac arrest using the cardiac arrest registry to enhance survival (CARES).Resuscitation 2013;84:10938.
6. Govindarajan P, Lin L, Landman A. Practice varaibility among the EMS systemsparticipating in cardiac arrest registry to enhance survival (CARES). Resuscita-tion 2012;83:7680.
7. National Center for Chronic Disease Prevention and Health Promotion, Divisionfor Heart Disease and Stroke Prevention. Cardiac Arrest Registry to EnhanceSurvival (CARES): Data Dictionary 2013; 2013. https://mycares.net/downloads/Data%20Dictionary%20(2013).pdf [accessed 05.05.13].
8. Glover BM, Brown SP, Morrison L. Wide variability in drug use in out-of-hospital
cardiac arrest: a report from the resuscitation outcomes consortium. Resuscita-tion 2012;83:132430.
9. Langhelle A, Tyvold SS, Lexow K, Hapnes S, Sunde K, Steen PA. In-hospital fac-tors associated with improved outcome after out- of-hospital cardiac arrest. Acomparison between four regions in Norway. Resuscitation 2003;56:24763. (2013) 1015 1016
0. Engdahl J, Abrahamsson P, Bang A, et al. Is hospital caremajor importance foroutcome after out-of-hospital cardiac arrest? Experience acquired from patientswith out-of-hospital cardiac arrest resuscitated by the same Emergency Med-ical Service and admitted to one of two hospitals over a 16-year period in themunicipality of Goteborg. Resuscitation 2000;43:20111.
1. Toma A, Bensimon CM, Dainty KN. Perceived barriers to theraputic hypother-mia for patients resuscitated from cardiac arrest: a qualitative study o