Introduction

Each year, ≈209 000 adult in-hospital cardiac arrests (IHCAs) occur in the United States, with survival to hospital discharge rates of 18% to 20%.^1–3 This is in comparison with ≈326 200 adult out-of-hospital cardiac arrests (OHCAs) annually in the United States, with overall survival rates of 10.6%.⁴ IHCA has not received the same level of focused research as OHCA.⁵ Regional differences in early and late survival after OHCA have been well studied.⁶ However, to date, potential regional differences in the incidence and outcomes of IHCA have not been systematically described. Recent data suggest that hospitals with higher survival rates have lower IHCA incidence.⁷ Studies have also shown that significant variability in IHCA survival exists across hospitals and that this variation persists despite adjustment for measured patient and hospital factors and for the duration of hospital participation in IHCA quality improvement programs.^8,9 Similarly, although IHCA survival has improved during the past decade, the magnitude of improvement varies across hospitals.^10,11 However, these studies have been limited largely to data from hospitals participating in a voluntary IHCA quality improvement program and may not be representative of the entire US population. Furthermore, it remains unknown whether hospitals with lower survival rates or smaller improvements in survival rates over time are clustered in specific states or regions in the United States. If regional variation in the incidence, survival, and resource use for IHCA exists, these findings would provide a unique opportunity to identify reasons for these differences and to develop targeted interventions to enhance the quality of resuscitation and postresuscitation care and to improve overall IHCA outcomes in the United States.

Editorial see p 1377

Clinical Perspective on p 1425

We used data from the 2003 to 2011 Nationwide Inpatient Sample (NIS) databases to determine whether regional differences exist in the incidence, survival to hospital discharge, and resource use (total hospital cost and discharge disposition among survivors) for IHCA in the United States and, if so, to examine whether patient- and hospital-level factors can explain these regional differences.

Methods

Data Source

Data were obtained from the 2003 to 2011 NIS databases. The NIS, sponsored by the Agency for Healthcare Research and Quality as a part of the Healthcare Cost and Utilization Project, is the largest publicly available all-payer inpatient care database in the United States. It contains discharge-level data from ≈8 million hospital stays from ≈1000 hospitals designed to approximate a 20% stratified sample of all US community hospitals, representing >95% of the US population. Criteria used for stratified sampling include hospital ownership, bed size, teaching status, urban or rural location, and geographic region. Inpatient stay records in the NIS include clinical and resource use information available from discharge abstracts derived from state-mandated hospital discharge reports. Discharge weights are provided for each patient discharge record and can be used to obtain national estimates. Discharge weights in NIS are calculated for each stratum by first stratifying the NIS hospitals on the same variables used for creating the sample and then dividing the number of universe discharges in that stratum by the number of NIS discharges in the stratum.¹² In NIS, the universe is all inpatient discharges from community hospitals in the United States. Weighted estimates are calculated by uniformly applying stratum weights to the discharges according to the stratum from which the discharge was drawn.

This study was deemed exempt by the New York Medical College Institutional Review Board because the Healthcare Cost and Utilization Project–NIS is a publicly available database that contains deidentified patient information.

Study Population

We used the International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes 99.60 or 99.63 to identify all patients ≥18 years of age who underwent cardiopulmonary resuscitation (CPR) for IHCA (n=838 951). This approach has been used in previous studies using administrative databases to identify patients with IHCA.^1,13,14 Patients who experienced multiple episodes of IHCA and CPR during the same hospitalization were considered a single IHCA case. We did not use ICD-9-CM code 427.5 (cardiac arrest) to identify IHCA cases because this may lead to erroneous estimates. Cardiac arrest (427.5) may be coded in patients who present to the emergency department with OHCA and survive to be admitted to the hospital. Indeed, previous studies have used ICD-9-CM code 427.5 listed as the principal diagnosis to identify OHCA cases.^15,16 Similarly, cardiac arrest may also be coded in patients with do-not-resuscitate (DNR) orders for whom no treatment is attempted. Furthermore, health data coders may not include code 427.5, preferring to rank other diagnoses codes higher (eg, comorbidities), which will skew the coded incidence of IHCA.⁵ We excluded records with missing data on survival or discharge disposition (n=487). This gave us a final study sample of 838 465 IHCA patients. Patients with ventricular tachycardia (VT) or ventricular fibrillation (VF) were identified by ICD-9-CM code 427.1 or 427.41 (n=176 153, 21.0%). Patient records without either of these codes were considered to have pulseless electric activity (PEA) or asystole as the cardiac arrest rhythm (n=662 312, 79.0%) because these diagnoses do not have unique ICD-9-CM codes. Patients with IHCA were divided into 4 groups based on the hospital location: the Northeast, Midwest, South, and West, corresponding to the census regions as defined by the US Census Bureau.¹⁷ For state-level analyses, states with <100 IHCA cases (Alaska and North Dakota) were excluded.

Outcomes Measured

We compared incidence rates of IHCA among the 4 geographic regions and across individual states. Our primary outcome of interest for this study was survival to hospital discharge, defined as the proportion of IHCA patients who did not die during the hospitalization and were discharged alive. We used total hospital cost and discharge disposition among survivors as secondary outcomes. The NIS contains the data element TOTCHG, which represents the total charges for each hospital record.¹⁸ This charge information represents the amount that hospitals billed for the entire hospital stay but does not reflect how much hospital services actually cost. Total hospital charges were converted to costs by use of Healthcare Cost and Utilization Project cost-to-charge ratios on the basis of the hospital accounting reports collected by the Centers for Medicare & Medicaid Services.¹⁹ Cost was calculated as total hospital charges multiplied by cost-to-charge ratio. Costs were adjusted for inflation by use of the region-specific Consumer Price Index provided by the US Bureau of Labor Statistics, with 2014 as the index base.²⁰ Thus, all costs were standardized over the study period and are reported in 2014 US dollars. Data on cost was missing for 60 866 records. Therefore, results of cost analysis are based on a sample size of 777 599 IHCA patients.

Discharge disposition among survivors was classified as home (self-care), short-term hospital, skilled nursing facility, home health care, or other by use of the DISPUNIF variable in the NIS databases.¹⁸ All outcomes are reported for the overall cohort and separately according to the cardiac arrest rhythm.

Patient and Hospital Characteristics

Baseline patient characteristics included were demographics (age, sex, race), primary expected payer, weekday versus weekend admission, median household income for the patient’s ZIP code, 29 Elixhauser comorbidities as defined by the Agency for Healthcare Research and Quality, other clinically relevant comorbidities (smoking, dyslipidemia, known coronary artery disease, family history of coronary artery disease, previous myocardial infarction, previous percutaneous coronary angioplasty, previous coronary artery bypass grafting, previous cardiac arrest, family history of sudden cardiac death, carotid artery disease, dementia, and atrial fibrillation), primary diagnosis of acute myocardial infarction, and cardiac arrest rhythm.^21,22 A list of ICD-9-CM and Clinical Classifications Software codes used to identify comorbidities is provided in Table I in the online-only Data Supplement. Hospital characteristics such as hospital location (rural, urban), bed size (small, medium, and large), and teaching status were also included.

Statistical Analysis

Weighted estimates were calculated by applying discharge weight to the unweighted discharge records. Weighted estimates were used for all statistical analyses. Overall and region- and state-specific IHCA incidence rates were calculated by dividing the number of IHCA cases by the number of total hospitalizations (expressed as cases per 1000 hospital admissions) during the study period. Incidence rates were compared among the 4 census regions by use of Poisson regression for the number of IHCA cases, offset by the log of number of total hospital admissions. The Northeast was used as the reference region.

For descriptive analyses, patient and hospital characteristics were compared among the 4 regions with the Pearson χ² test for categorical variables and 1-way ANOVA for continuous variables. In addition, we used standardized differences, calculated as the difference in means or proportions divided by a pooled estimate of the standard deviation, to compare patient and hospital characteristics across the 4 regions with the Northeast as the reference region. Compared with traditional significance testing, standardized differences are not as sensitive to sample size and are useful in identifying meaningful differences.^23,24 Typically, an absolute standardized difference >10% is considered clinically meaningful.

To examine differences in survival to hospital discharge among the 4 geographic regions, a multivariable logistic regression model was constructed with the use of generalized estimating equations with exchangeable working correlation matrix to account for clustering of outcomes within hospitals. The Northeast was used as the reference region. Variables included in the regression model were age, sex, race, primary expected payer, weekday versus weekend admission, 29 Elixhauser comorbidities, other clinically relevant comorbidities (smoking, dyslipidemia, known coronary artery disease, family history of coronary artery disease, previous myocardial infarction, previous percutaneous coronary intervention, previous coronary artery bypass grafting, previous cardiac arrest, family history of sudden cardiac death, carotid artery disease, dementia, and atrial fibrillation), primary diagnosis of acute myocardial infarction, initial cardiac arrest rhythm (for the overall cohort), and hospital characteristics (location, bed size, and teaching status). These covariates were selected a priori and represent variables known to influence IHCA survival and overall in-hospital mortality.^21,25 We used a similar logistic regression model to calculate risk-adjusted survival rates for individual states using previously described methods.²⁶ For analyzing temporal trends in survival, we added year (continuous variable defined as 2003–2011) as an independent variable to the above logistic regression model to obtain the adjusted odds ratio (OR) per year. This approach has been used in previous studies.^10,27 For comparing total hospital cost among the 4 regions, we used a multivariable linear regression model, adjusting for all the variables mentioned above. Because total hospital cost had a positively skewed distribution, we used logarithmic transformation of cost as the dependent variable in the linear regression model.

We used ArcGIS Online and Esri Maps for Office (Esri, Redlands, CA) to map IHCA incidence and survival to hospital discharge rates in the 4 census regions and in the individual states. We examined the correlation between IHCA incidence rate and survival to discharge at the regional and state levels using linear regression.⁷

Data were complete for all covariates except race (15.7% missing), median household income for patient’s ZIP code (2.6% missing), hospital characteristics (0.5% missing), Elixhauser comorbidities (0.3% missing), primary expected payer (0.1% missing), and sex (<0.1% missing). Additionally, different regions do not compare uniformly for inclusion criteria for the “other” race category in NIS. Hence, the “other” race (2.3%) category was also treated as missing. We performed multiple imputations to impute missing values using the fully conditional specification method (an iterative Markov chain Monte Carlo algorithm) in SPSS 20.0. Results with and without imputation were not meaningfully different, so only the former are presented.

Statistical analysis was performed with IBM SPSS Statistics 20.0 (IBM Corp, Armonk, NY). All P values were 2 sided with a significance threshold of P<0.05. Categorical variables are expressed as percentages and continuous variables as mean±SD or median (interquartile range) as appropriate. The OR and 95% confidence interval (CI) are used to report the results of logistic regression analyses.

Results

IHCA Incidence

From 2003 to 2011, of 838 465 IHCAs included in our study, 162 270 (19.4%) were in the Northeast, 159 581 (19.0%) in the Midwest, 316 201 (37.7%) in the South, and 200 413 (23.9%) in the West. The total number of hospital admissions for patients ≥18 years of age during this period was 293 364 578, giving an overall incidence of adult IHCA of 2.85 per 1000 hospital admissions in the United States. IHCA incidence varied across the 4 geographic regions and was 2.75, 2.33, 2.81, and 3.73 per 1000 admissions in the Northeast, Midwest, South, and West, respectively (P<0.001; Figure 1A). Significant variation in IHCA incidence rates was also seen among individual states (range, 0.86–6.31 per 1000 admissions; Figure 1B).

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Baseline Patient and Hospital Characteristics

The mean±SD age of the overall cohort was 67.2±16.1 years. Compared with the Northeast, patients in the Midwest, South, and West were younger (Table 1). Male predominance was seen in all 4 regions. Compared with the Northeast, the Midwest had a higher proportion of whites, the South had a higher proportion of blacks, and the West had a higher proportion of Hispanics and Asian/Pacific Islanders (Table 1). Patients in the West were less likely to have Medicare and more likely to have Medicaid as the primary expected payer compared with those in Northeast. The South had the highest proportion of patients with a median household income in the lowest quartile. Overall, patients were admitted to large, urban, nonteaching hospitals. The Northeast and Midwest had a higher proportion of teaching hospitals than the South and West (Table 1).

The prevalence of most comorbidities was similar across the 4 regions except for smoking and obesity, which were more prevalent in the Midwest, South, and West compared with the Northeast (Table 1 and Table II in the online-only Data Supplement). Patients in the South and West also had a higher prevalence of deficiency anemias and fluid/electrolyte disorders compared with those in Northeast. In the overall cohort, VT/VF was the cardiac arrest rhythm in 21.0% patients. IHCA patients in the Northeast were less likely to have VT/VF as the cardiac arrest rhythm compared with those in other regions; however, this difference was most significant between the Northeast and Midwest (18.7% versus 23.3%; P<0.001; absolute standardized difference=11.3; Table 1). Similarly, although patients in the Northeast appeared less likely to have acute myocardial infarction as the primary diagnosis compared with those in Midwest and West, this observed difference was not considered meaningful (absolute standardized difference <10).

Survival to Hospital Discharge

In the overall study cohort, survival to hospital discharge was 24.7% (95% CI, 24.6–24.8). Compared with the Northeast, survival to hospital discharge was higher in the Midwest, South, and West (20.7% in the Northeast versus 27.7% in the Midwest, 24.3% in the South, and 26.2% in the West; P<0.001; absolute standardized difference, 16.4, 8.7, and 12.9 for the Midwest, South, and West, respectively, compared with the Northeast; Figure 1C). When adjusted for demographics, comorbidities, hospital characteristics, primary diagnosis of acute myocardial infarction, and initial cardiac arrest rhythm, risk-adjusted survival remained significantly higher in the Midwest (OR, 1.33; 95% CI, 1.31–1.36; P<0.001), South (OR, 1.21; 95% CI, 1.19–1.23; P<0.001), and West (OR, 1.25; 95% CI, 1.23–1.27; P<0.001) compared with the Northeast (Table 2). Trend analysis revealed a significant increase in IHCA survival from 2003 to 2011 in the United States (adjusted OR [per year], 1.05; 95% CI, 1.04–1.05; P_trend<0.001) and in each of the 4 census regions (adjusted OR [per year]: for Northeast, 1.06 [95% CI, 1.06–1.07]; Midwest, 1.04 [95% CI, 1.03–1.04]; South, 1.05 [95% CI, 1.04–1.05]; and West, 1.04 [95% CI, 1.03–1.04]; P_trend<0.001 for all; Figure 2). Significant variation in survival to discharge was also seen across individual states (range, 18.1%–37.9%; Figure 1D). Risk-adjusted survival rate was lowest in New York (20.4%) and highest in Wyoming (40.2%; Table III in the online-only Data Supplement).

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When stratified according to the cardiac arrest rhythm, overall survival to discharge was 22.5% and 33.0% in patients with PEA/asystole and VT/VF, respectively. In patients with PEA/asystole as the cardiac arrest rhythm, survival to discharge was higher in the Midwest, South, and West compared with the Northeast (Table 2). Similar results were seen in patients with VT/VF. However, regional differences in survival were smaller in magnitude in patients with VT/VF compared with those with PEA/asystole (Table 2).

Table IV in the online-only Data Supplement shows differences in hospital and patient characteristics among IHCA survivors and nonsurvivors. In addition to geographic region, several other baseline characteristics were independently associated with increased or decreased risk of survival to hospital discharge among IHCA patients (Table V in the online-only Data Supplement).

Association Between IHCA Incidence and Survival Among Regions and States

Although the Midwest had the lowest IHCA incidence and highest survival rate, there was no association overall between IHCA incidence and survival rate at the regional level (r=0.024, P=0.98; Figure 3A). However, at the state level, there was a significant negative correlation between IHCA incidence and survival (r=−0.50, P=0.001); that is, states with higher survival also had a lower IHCA incidence rate (Figure 3B).

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Total Hospital Cost

The median inflation-adjusted hospital cost for the overall study cohort was US $15 673 (interquartile range, $7164–$35 016). Total hospital cost incurred was lowest in the South and highest in the West (Figure 4A). When adjusted for potential confounding variables, compared with the Northeast, hospital cost was significantly lower in the Midwest (adjusted parameter estimate, 0.88; 95% CI, 0.88–0.89; P<0.001) and South (adjusted parameter estimate, 0.85; 95% CI, 0.84–0.85; P<0.001) and higher in the West (adjusted parameter estimate, 1.27; 95% CI, 1.26–1.28; P<0.001). Similar regional differences in total hospital cost were seen when patients were stratified according to the cardiac arrest rhythm (Table 2 and Figure I in the online-only Data Supplement).

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Discharge Disposition Among Survivors

Overall, among IHCA patients who survived to hospital discharge, the discharge disposition was as follows: home (self-care), 30.2%; short-term hospital, 14.5%; skilled nursing facility, 40.4%; home health care, 13.7%; and other, 1.2%. Compared with the Northeast, survivors of IHCA in the Midwest, South, and West were more likely to be discharged home (self-care) and less likely to require home health care or transfer to skilled nursing facility (P<0.001; Figure 4B). Similar results were seen in patients with PEA/asystole and VT/VF (Figure II in the online-only Data Supplement).

Discussion

In this large, all-payer, nationwide database of hospitalized patients, we observed significant variations in IHCA incidence, survival, and resource use across geographic regions within the United States. The Midwest had the lowest IHCA incidence and highest survival to hospital discharge rate. Total hospital cost was highest in the West, whereas discharge to skilled nursing facility and use of home health care were highest in the Northeast. This variation in survival and resource use was explained only partially by differences in patient case mix or hospital characteristics.

Previous studies have reported large variations in IHCA incidence ranging from 2.5 to 13.1 per 1000 admissions.^1,3,28,29 In our study, the incidence of in-hospital CPR for IHCA was 2.85 per 1000 admissions, which is consistent with that reported by Ehlenbach et al¹ and Kazaure et al.³ IHCA incidence was lowest in the Midwest and highest in the West. IHCA incidence is a function of both the patient’s severity of illness and the institutional response and process of care for treating acutely and chronically ill patients and preventing IHCA. The prevalence of most comorbidities was similar across all regions among patients who experienced an IHCA, suggesting that the burden of comorbidities or illness may contribute little to the regional differences in IHCA rates. In a single-center study, Wallmuller et al³⁰ showed that IHCA is attributable to cardiac causes in 63% of cases with either VF or PEA/asystole as the cardiac arrest rhythm. Regional differences in receipt of guideline-recommended therapies for patients admitted with cardiovascular diseases have been well described and may contribute to some of the regional differences in IHCA, particularly those events related to a cardiac origin.^31–33

Merchant et al³⁴ previously reported that hospital characteristics such as small size, urban location, and high proportion of black patients are independently associated with higher IHCA event rates. In our study, IHCA rates were higher in regions with a greater proportion of nonwhite patients, which may reflect racial disparities in the quality of inpatient care, as reported in several studies.^35,36 Furthermore, a higher proportion of hospitals in the West were medium sized and in urban locations compared with the Midwest (Table 1). Hospital size may be an indirect marker of available resources, with larger hospitals having more resources in place for the early recognition of clinical deterioration and prevention of IHCA. Finally, regional variation in IHCA rates could also be attributable to differences in ICD-9-CM coding, completeness of case ascertainment, and potential for unreported or unrecognized cases.

Previous studies have shown hospital variation in IHCA survival and survival trends.^8,11 However, these studies included only 10% of all hospitals in the United States participating in a voluntary IHCA quality improvement program and may not be representative of the entire population. Furthermore, it is unclear whether hospitals with lower survival rates or smaller improvements in survival rates over time are clustered in specific states or regions in the United States. We observed substantial regional variation in IHCA survival, which was lowest in the Northeast and highest in the Midwest. Although not systematically described, similar regional variation in survival has been observed in previous studies.¹⁰ However, the reasons for these large variations in outcomes across states and regions are less clear. An inverse relationship between a hospital’s IHCA incidence and survival rates has been described.⁷ We found a similar relationship at the state and, to some extent, at the regional level, suggesting that states/regions with higher IHCA survival rates may also be good at preventing IHCA.

In our cohort, 21% of IHCA patients had VT/VF as the cardiac arrest rhythm. Although this proportion is lower than that reported by Merchant et al⁸ (2 of 5 [40%] with VT/VF) and Wallmuller et al³⁰ (39% with VF), our findings correlate well with several other studies using the Get With The Guidelines–Resuscitation registry that showed VT/VF as the cardiac arrest rhythm in 19.2% to 25.8% of IHCA patients.^{7–10,24,30,37} Overall survival to discharge in our study was higher than in previous reports, particularly in patients with PEA/asystole.^9,10,38 Patient who did not have ICD-9-CM codes for VT or VF were presumed to have PEA/asystole in our study. These data should therefore be interpreted with caution because it is possible that this group may have included patients who received CPR when not in PEA/asystole (eg, patients with bradycardia). This may also explain the higher survival rate among patients with IHCA that was not attributable to VT/VF and hence the overall cohort compared with similar patients in previous studies.¹² Regional variation in outcomes was smaller in magnitude in patients with VT/VF compared with those with asystole/PEA as the cardiac arrest rhythm, suggesting that regional differences in resuscitation and postresuscitation care may be variable, depending on the cardiac arrest rhythm.

Other potential reasons for regional variations in IHCA survival may include differences in IHCA preparedness (eg, availability and allocation of resources for preventing and managing IHCA, rapid response or code teams, dedicated nursing staff, routine resuscitation simulations), quality of CPR and postresuscitation care, institutional culture (eg, leadership, participation in quality improvement programs, duration of resuscitation attempt, implementation of DNR orders), and regulatory requirements (eg, mandatory reporting of IHCA incidence and outcomes).^5,37 Despite substantial regional variation in survival, we found a significant temporal improvement in IHCA survival nationally and in all 4 regions from 2003 to 2011. Our results are consistent with a previous smaller study from a volunteer registry involving 374 US hospitals that showed a trend for improved IHCA survival from 2000 to 2009.¹⁰

Another important finding of our study is the regional variation in resource use in IHCA patients. Total hospital cost was highest in the West. On the other hand, the use of post–acute care services (skilled nursing facility and home health care) among survivors was lowest in the West and highest in the Northeast. A recent report from the Institute of Medicine concluded that regional variation in total Medicare spending is driven largely by variation in the use of post–acute care services and, to a lesser extent, by variation in the use of acute care services.³⁹ Data from the Dartmouth Atlas of Health Care have shown that patients treated in regions with higher spending intensity do not have better quality of care or outcomes.^40,41 Thus, it is possible that regional variation in hospital cost and use of post–acute care services by IHCA patients may reflect differences in expenditure of resources with higher spending for acute care (partly as a result of a higher IHCA event rate) and relatively lower spending for post–acute care in the West and vice versa in the Northeast. Other factors that can contribute to regional variation in resource use include differences in primary payer status and advance directives specifying limitations in end-of-life care.⁴² Alternatively, regional differences in discharge disposition may be attributable to differences in the availability of resources (eg, post–acute care services) or level of disability among survivors of IHCA.

Limitations

Our study has important limitations. First, although we adjusted for multiple confounding variables, the possibility of residual measured and unmeasured confounders affecting IHCA outcomes cannot be completely eliminated. Second, because the NIS is an administrative database, the accuracy and consistency of the data depend heavily on the training and expertise of the coders and the coding practices and capabilities of individual hospitals. We may have underestimated the incidence of IHCA because of inconsistent coding of CPR and lack of information on the use of defibrillators. Patients who received open-chest CPR (ICD-9-CM 37.91) and those who may have experienced an IHCA but whose records do not include a code for CPR were not included in our study. It is difficult to validate individual ICD-9-CM codes or to identify IHCA patients for whom CPR was not coded from medical records because the NIS contains deidentified data. Third, the lack of complete information on cardiac arrest rhythm is an important limitation of our study. Because PEA and asystole do not have unique ICD-9-CM codes, the outcome data in this subgroup need to be interpreted with caution. Fourth, there may be variation in survival to discharge with favorable neurological status, which may be a more important outcome than survival to discharge alone. However, data on cerebral performance category on admission and at discharge are not available in the NIS; hence, we were unable to determine the proportion of survivors with good neurological status in the present study. Fifth, the NIS lacks information on certain preresuscitation (eg, location of IHCA, interventions already in place before IHCA such as mechanical ventilation and use of intravenous vasopressors, and presence of a rapid response system) and resuscitation (eg, medication use, time delay between the onset of IHCA and CPR, quality of CPR, and time to defibrillation) variables, which may vary among hospitals and influence IHCA survival.^43,44 Finally, data on patient and family preferences concerning end-of-life care, DNR status, and timing of DNR are not collected in the NIS. Therefore, some of the observed variation in IHCA outcomes may be attributable to systematic regional and institutional differences in initiation of DNR orders.⁴⁵

Conclusions

In this large, all-payer, nationwide database of hospitalized patients, we observed a significant variation in IHCA incidence, survival, and resource use across geographic regions within the United States. This variation was explained only partially by differences in patient case mix or hospital characteristics. We also found significant improvement in IHCA survival nationally and in all regions from 2003 to 2011. A national surveillance program to monitor and report incidence, processes of care, and outcomes at the state, regional, and national levels could help identify additional patient- and hospital-level factors responsible for the observed geographic differences to develop targeted interventions to enhance the overall quality of resuscitation and postresuscitation care and to improve IHCA outcomes.

Footnotes