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Multicenter Study
. 2013 Jul 8;173(13):1186-95.
doi: 10.1001/jamainternmed.2013.1026.

Association between a hospital's rate of cardiac arrest incidence and cardiac arrest survival

Collaborators, Affiliations
Multicenter Study

Association between a hospital's rate of cardiac arrest incidence and cardiac arrest survival

Lena M Chen et al. JAMA Intern Med. .

Abstract

Importance: National efforts to measure hospital performance in treating cardiac arrest have focused on case survival, with the hope of improving survival after cardiac arrest. However, it is plausible that hospitals with high case-survival rates do a poor job of preventing cardiac arrests in the first place.

Objective: To describe the association between inpatient cardiac arrest incidence and survival rates.

Design: Within a large, national registry, we identified hospitals with at least 50 adult in-hospital cardiac arrest cases between January 1, 2000, and November 30, 2009. We used multivariable hierarchical regression to evaluate the correlation between a hospital's cardiac arrest incidence rate and its case-survival rate after adjusting for patient and hospital characteristics.

Main outcomes and measures: The correlation between a hospital's incidence rate and case-survival rate for cardiac arrest.

Results: Of 102,153 cases at 358 hospitals, the median hospital cardiac arrest incidence rate was 4.02 per 1000 admissions (interquartile range, 2.95-5.65 per 1000 admissions), and the median hospital case-survival rate was 18.8% (interquartile range, 14.5%-22.6%). In crude analyses, hospitals with higher case-survival rates also had lower cardiac arrest incidence (r, -0.16; P = .003). This relationship persisted after adjusting for patient characteristics (r, -0.15; P = .004). After adjusting for potential mediators of this relationship (ie, hospital characteristics), the relationship between incidence and case survival was attenuated (r, -0.07; P = .18). The one modifiable hospital factor that most attenuated this relationship was a hospital's nurse-to-bed ratio (r, -0.12; P = .03).

Conclusions and relevance: Hospitals with exceptional rates of survival for in-hospital cardiac arrest are also better at preventing cardiac arrests, even after adjusting for patient case mix. This relationship is partially mediated by measured hospital attributes. Performance measures focused on case-survival rates seem an appropriate first step in quality measurement for in-hospital cardiac arrest.

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Conflict of interest statement

Financial disclosures: I need to consult my co-authors about potential conflicts of interest and will provide details on the journal’s financial disclosure form or in an attachment to the form.

Figures

Figure 1
Figure 1. Study cohort
Figure 2
Figure 2
A. Distribution of unadjusted hospital rates of cardiac arrest incidence B. Distribution of unadjusted hospital rates of in-hospital case-survival
Figure 2
Figure 2
A. Distribution of unadjusted hospital rates of cardiac arrest incidence B. Distribution of unadjusted hospital rates of in-hospital case-survival
Figure 3
Figure 3
A. Correlation between unadjusted hospital rates of cardiac arrest incidence and case-survival B. Correlation between hospital rates of cardiac arrest incidence and case-survival, adjusted for patient factors only Incidence is adjusted for the CMS case mix index for hospital admissions, and case-survival is adjusted for patient factors (i.e., age, gender, race/ethnicity, pre-existing conditions), including event characteristics (i.e., initial arrest rhythm, year of admission, night vs. day, weekend vs. weekday).
Figure 3
Figure 3
A. Correlation between unadjusted hospital rates of cardiac arrest incidence and case-survival B. Correlation between hospital rates of cardiac arrest incidence and case-survival, adjusted for patient factors only Incidence is adjusted for the CMS case mix index for hospital admissions, and case-survival is adjusted for patient factors (i.e., age, gender, race/ethnicity, pre-existing conditions), including event characteristics (i.e., initial arrest rhythm, year of admission, night vs. day, weekend vs. weekday).
Figure 4
Figure 4. Mediation analysis of hospital factors which may account for the correlation between hospital rates of cardiac arrest incidence and case-survival
Regression models were adjusted for both patient and hospital factors to determine if certain hospital factors may, in part, mediate this relationship. Incidence is adjusted for the CMS case mix index for hospital admissions and hospital factors (i.e., teaching status, ownership, geographical region, urban vs. rural, full-time equivalent nurse ratio, number of beds, certification as a trauma center). Case-survival is adjusted for case mix index, patient factors, and the hospital factors described above.

References

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