Skip main navigation

Readmission Rates and Long-Term Hospital Costs Among Survivors of an In-Hospital Cardiac Arrest

and for the American Heart Association’s Get With The Guidelines-Resuscitation Investigators
Originally publishedhttps://doi.org/10.1161/CIRCOUTCOMES.114.000925Circulation: Cardiovascular Quality and Outcomes. 2014;7:889–895

Abstract

Background—

Although an in-hospital cardiac arrest is common, little is known about readmission patterns and an inpatient resource use among survivors of an in-hospital cardiac arrest.

Methods and Results—

Within a large national registry, we examined long-term inpatient use among 6972 adults aged ≥65 years who survived an in-hospital cardiac arrest. We examined 30-day and 1-year readmission rates and inpatient costs, overall and by patient demographics, hospital disposition (discharge destination), and neurological status at discharge. The mean age was 75.8±7.0 years, 56% were men, and 12% were black. There were a total of 2005 readmissions during the first 30 days (cumulative incidence rate, 35 readmissions/100 patients; 95% confidence interval, 33–37) and 8751 readmissions at 1 year (cumulative incidence rate, 185 readmissions/100 patients; 95% confidence interval, 177–190). Overall, mean inpatient costs were $7741±$2323 at 30 days and $18 629±$9411 at 1 year. Thirty-day inpatient costs were higher in patients of younger age (≥85 years, $6052 [reference]; 75–84 years, $7444 [adjusted cost ratio, 1.23; 1.06–1.42; 65–74 years, $8291 [adjusted cost ratio, 1.37; 1.19–1.59; both P<0.001) and black race (whites, $7413; blacks, $9044; adjusted cost ratio, 1.22; 1.05–1.42; P<0.001), as well as those discharged with severe neurological disability or to skilled nursing or rehabilitation facilities. These differences in resource use persisted at 1 year and were largely because of higher readmission rates.

Conclusions—

Survivors of an in-hospital cardiac arrest have frequent readmissions and high follow-up inpatient costs. Readmissions and inpatient costs were higher in certain subgroups, including patients of younger age and black race.

Introduction

WHAT IS KNOWN

  • Most patients who survive a cardiac arrest occurring in the hospital are alive at 1 year. However, little is known about readmission patterns and inpatient resource use among survivors of an in-hospital cardiac arrest.

WHAT THE STUDY ADDS

  • Survivors of an in-hospital cardiac arrest have frequent readmissions and high follow-up inpatient costs, but these rates and costs are similar to patients with decompensated heart failure and stroke with significant disability.

  • Although cardiovascular conditions were the most common reason for readmission, these comprised only one third of all readmissions. Readmission for repeat cardiac arrest was rare (<1%).

  • Readmission rates and an inpatient resource use differed by age, race, hospital discharge disposition, and neurological sequelae after cardiac arrest.

  • As new treatment strategies become adopted (eg, routine cardiac catheterization, and therapeutic hypothermia) in survivors of an in-hospital cardiac arrest, the cost estimates from this study could be used to provide more precise estimates of their cost-effectiveness.

Among survivors of an in-hospital cardiac arrest, little is known about their patterns of readmission and related inpatient resource use after hospital discharge. Although there are an estimated 200 000 in-hospital cardiac arrests annually in the United States,1 previous studies have focused on in-hospital outcomes because of the challenge of collecting longitudinal data on survivors. In a recent study, we were able to overcome this challenge and found that most survivors of an in-hospital cardiac arrest remained alive at 1 year.2 However, whether cardiac arrest survivors experience multiple readmissions after hospital discharge and the principal reasons for readmissions remain unclear. Moreover, characterizing the prognostic effect of key clinical factors, such as race, sex, hospital disposition, and neurological status at discharge, on readmission and inpatient resource use patterns would provide insights into potential opportunities for more aggressive and targeted outpatient surveillance.

To address these gaps in knowledge, we linked data from a large, national in-hospital cardiac arrest registry with Medicare inpatient claims files and examined 30-day and 1-year rates of readmission and an inpatient resource use among patients who survived an in-hospital cardiac arrest. Specifically, we examined whether rates of these outcomes differed by demographic characteristics, neurological status, and disposition at hospital discharge.

Methods

Data Sources and Linkage

Get With The Guidelines (GWTG)-Resuscitation, formerly the National Registry of Cardiopulmonary Resuscitation, is a large prospective quality-improvement registry of in-hospital cardiac arrests. Hospital participation is voluntary, and the registry’s design has been described in detail previously.3 In brief, trained quality-improvement hospital personnel enroll all patients with cardiac arrest (defined as the absence of a palpable central pulse, apnea, and unresponsiveness) and without do-not-resuscitate orders. Cases are identified by multiple methods, including centralized collection of cardiac arrest flow sheets, reviews of hospital paging system logs, and routine checks of code carts, pharmacy tracer drug records, and hospital billing charges for resuscitation medications.3 The registry uses standardized Utstein-style templates to define patient variables and outcomes to facilitate uniform reporting across hospitals.4,5 Data accuracy is further ensured by rigorous certification of hospital staff and the use of standardized software with data checks for completeness and accuracy.6

We linked GWTG-Resuscitation patient-level data from January 1, 2000, to December 31, 2008, with Medicare inpatient files using 6 identifiers: dates of hospital admission and discharge, patient age and sex, admitting hospital (deidentified), and International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis and procedure codes.2,7 We selected Medicare records for the linkage if they included a diagnosis code for cardiac arrest (427.5), ventricular fibrillation (427.41), or ventricular flutter (427.42) or a procedure code for cardiopulmonary resuscitation (99.60), defibrillation (99.62), or closed chest massage (99.63). To optimize the match further, we also selected records containing a diagnosis code for acute respiratory failure (518.81) or shock (785.5x) to identify patients who did not have a diagnosis of cardiac arrest in the Medicare claims data but otherwise were uniquely matched on all other identifiers, including hospital. For each linked patient, we obtained Medicare denominator and inpatient files from 2000 to 2010. Denominator files contain information on all Medicare beneficiaries enrolled in a given year, whereas inpatient files contain information on readmission dates, diagnoses, procedures, diagnosis-related group, and hospital reimbursement.

Study Population

The study cohort included 523 acute-care hospitals that submitted data to GWTG-Resuscitation between January 1, 2000, and December 31, 2008. A total of 19 373 patients aged ≥18 years had a pulseless in-hospital cardiac arrest and survived to discharge (Figure 1). We excluded 9057 patients aged <65 years who were not yet entitled to Medicare benefits, leaving 10 316 Medicare age-eligible patients. Using the method described above, we were able to match 7080 (68.6%) eligible patients to Medicare claims data.2 A GWTG-Resuscitation record was not matched to a Medicare hospitalization (n=3236) when a patient (1) was admitted to a non-Medicare hospital (eg, Veterans Administration hospital), (2) had insurance other than fee-for-service Medicare, (3) was admitted to a hospital with few registry patients (thus precluding a unique match), or (4) lacked a qualifying International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis or procedure code for cardiac arrest in the Medicare files, as described above. Notably, patients who were and were not linked to Medicare files were found to have similar demographic and clinical characteristics (Appendix Table I in the Data Supplement). Finally, for patients who experienced cardiac arrest during multiple hospitalizations, we used the first hospitalization as the index hospitalization and categorized 108 cardiac arrests during subsequent hospitalizations as readmissions. The final study cohort comprised 6972 patients who survived an in-hospital cardiac arrest from 401 hospitals. Notably, these hospitals were geographically distributed throughout the United States and represented different hospital bed sizes, with one-half having training programs for residents or fellows and the majority located in urban areas (Appendix Table II in the Data Supplement).

Figure 1.

Figure 1. Study cohort.

Study Outcomes

The outcomes of interest were all-cause readmission and an inpatient resource use. We examined rates of each outcome at 30 days and 1 year after discharge from an in-hospital cardiac arrest. Readmission was determined from the linked Medicare inpatient files, which contained data as to whether and when a patient was readmitted to a hospital and the International Classification of Diseases, Ninth Revision, Clinical Modification code for the principal discharge diagnosis for hospitalization. Cost information was also determined from Medicare Part A inpatient files, which provided the actual Medicare payment to hospitals for each readmission.

Statistical Analysis

Baseline characteristics of the study cohort were described using proportions for categorical variables and means with SDs for continuous variables. We computed cumulative readmission incidence rates at 30 days and 1 year of follow-up. From these rates, the mean number of readmissions per patient-year of follow-up was determined. To determine the reasons for readmission, hospitalizations were further categorized by common diagnosis groups (eg, heart failure, myocardial infarction, infection, pneumonia, etc.) using the International Classification of Diseases, Ninth Revision, Clinical Modification codes for principal discharge diagnosis.

Inpatient resource use for the whole cohort was determined by summing costs for each patient’s rehospitalizations from the linked Medicare inpatient files. We then computed adjusted cost ratios for the following prespecified subgroups: age, sex, race, initial cardiac arrest rhythm, hospital disposition (discharge destination), and neurological status at discharge. Neurological status at discharge was assessed using commonly used cerebral performance categories, which distinguished patients with mild to no neurological disability, moderate neurological disability, severe neurological disability, and coma or vegetative state.8

To determine adjusted costs and cost ratios, because some patients had no follow-up inpatient costs, we constructed a 2-part model conditional on patients having follow-up inpatient costs comprised (1) a logistic regression model predicting the probability of having any follow-up costs9 and (2) a γ regression model with a log link for the costs (for those patients with nonzero follow-up costs),10 with both models adjusted for a patients characteristics and comorbidities (which are collected by GWTG-Resuscitation using standardized registry definitions). From the model, we calculated adjusted costs for each reference group by performing 1000 bootstrap samples and by computing the mean over these 1000 samples. Adjusted cost ratios and 95% confidence intervals (CI) for each subgroup were derived also by performing 1000 bootstrap samples, with the 2.5th and 97.5th percentile cost ratios defined as the 95% CI.11 Finally, the adjusted costs for each subgroup strata were obtained by multiplying the adjusted cost ratio for each strata with the adjusted costs for its reference group, with all other covariates fixed at their mean values in the population.

In these models, besides age (65–74, 75–84, and ≥85 years), sex, race (white, black, and other), initial cardiac arrest rhythm (asystole, pulseless electric activity, ventricular fibrillation, and pulseless ventricular tachycardia), hospital disposition (home without assistance, home with home health care, skilled nursing facility, inpatient rehabilitation, and hospice), and discharge neurological status, we also adjusted for comorbidities or medical conditions present before cardiac arrest (congestive heart failure, myocardial infarction, or diabetes mellitus; renal, hepatic, or respiratory insufficiency; baseline evidence of motor, cognitive, or functional deficits; acute stroke; pneumonia; hypotension; sepsis; major trauma; metabolic or electrolyte abnormality; metastatic or hematologic malignancy; and requirement for mechanical ventilation or hemodialysis) and therapeutic interventions in place at the time of cardiac arrest (antiarrhythmic drugs, intravenous vasopressors, dialysis, pulmonary artery catheter, and intra-aortic balloon pump).

Overall, rates of missing data were low. Race was missing for 396 (5.7%) patients, and discharge neurological status was missing for 858 (12.3%) patients. For the multivariable models, we performed multiple imputation with IVEware software (University of Michigan, Ann Arbor, MI).12 Results with and without imputation were not meaningfully different, so we present the former.

For each subgroup analysis of an inpatient resource use, we evaluated the null hypothesis of no difference in 30-day and 1-year costs at a 2-sided significance level of 0.05 and calculated 95% CIs using robust SEs. All analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC) and R version 2.10.0 (R Foundation for Statistical Computing, Vienna, Austria).13

The Institutional Review Boards of the Duke University Health System and the Mid America Heart Institute approved the study. Dr Chan took the responsibility for the accuracy of the data and all analyses, and the final article draft was reviewed and approved by the GWTG-Resuscitation research and publications committee and the American Heart Association’s Executive Database Steering Committee.

Results

Of the 6972 patients who survived an in-hospital cardiac arrest in our study, the mean age was 75.8±7.0 years and 56% were men (Table 1). Approximately 12% of patients were of black race, and nearly half (46.4%) had an initial cardiac arrest rhythm of ventricular fibrillation or pulseless ventricular tachycardia that was amenable to defibrillation. One quarter of patients had an incident myocardial infarction or heart failure exacerbation during the index hospitalization, and nearly one fifth of patients were hypotensive or on mechanical ventilation at the time of cardiac arrest. The principal diagnoses for the index hospitalization in which an in-hospital cardiac arrest occurred are summarized in Appendix Table III in the Data Supplement. Cardiovascular diseases comprised more than half of all index hospitalizations for an in-hospital cardiac arrest (54.5% [3802/6972]), whereas pneumonia and other infections accounted for 1148 (16.5%) of hospitalizations.

Table 1. Characteristics of the Study Cohort

CharacteristicPatients (n=6972)
Demographic characteristics
 Age, y75.8±7.0
 Male sex, n (%)3872 (55.5)
Race, n (%)*
 White5634 (85.7)
 Black778 (11.8)
 Other164 (2.5)
Initial cardiac arrest rhythm, n (%)
 Asystole1707 (24.5)
 Pulseless electric activity2031 (29.1)
 Pulseless ventricular tachycardia1109 (15.9)
 Ventricular fibrillation2125 (30.5)
CPC score at discharge, n (%)†
 1 (mild to no neurological disability)2943 (48.1)
 2 (moderate neurological disability)2097 (34.3)
 3 (severe neurological disability)879 (14.4)
 4 (coma or vegetative state)195 (3.2)
Pre-existing conditions, n (%)
 Acute stroke249 (3.6)
 Baseline depression in CNS function736 (10.6)
 Diabetes mellitus2262 (32.4)
 Heart failure during admission1625 (23.3)
 Heart failure before admission1848 (26.5)
 Hepatic insufficiency143 (2.1)
 Hypotension1313 (18.8)
 Major trauma113 (1.6)
Pre-existing conditions, n (%)
 Metabolic or electrolyte abnormality770 (11.0)
 Metastatic or hematologic malignancy518 (7.4)
 Myocardial infarction during admission1897 (27.2)
 Myocardial infarction before admission1805 (25.9)
 Renal insufficiency1836 (26.3)
 Respiratory insufficiency2368 (34.0)
 Pneumonia725 (10.4)
 Septicemia473 (6.8)
Interventions in place at time of cardiac arrest, n (%)
 Mechanical ventilation1246 (17.9)
 Intravenous vasopressors1203 (17.3)
 Intravenous antiarrhythmics530 (7.6)
 Dialysis136 (2.0)
 Pulmonary artery catheter326 (4.7)
 Intra-aortic balloon pump104 (1.5)

CNS indicates central nervous system; and CPC, Cerebral Performance Category.

*Race was missing for 396 patients.

CPC score was missing for 858 patients.

At hospital discharge, 48.1% of patients had mild to no neurological disability, 34.3% had moderate disability, 14.4% had severe disability, and 3.2% were in a coma or vegetative state. Most (55.3%) patients were discharged to either an inpatient rehabilitation or skilled nursing facility, and 4.8% went to hospice for comfort care. Of the 40% of patients who were discharged home, the majority (62%) did not receive any home health or nursing assistance.

Readmissions

Figure 2 depicts the cumulative incidence for all-cause readmission during the first year after discharge from an in-hospital cardiac arrest. Although 18.0% of patients died within the first 30 days after discharge, there were a total of 2005 readmission, yielding a 30-day mean cumulative incidence rate of 35 readmissions per 100 patients (95% CI, 33–37). By 1 year, there were a total of 8751 readmissions and 41.5% of patients had died (mean follow-up time of 248±152 days), yielding a 1-year mean cumulative incidence rate of 185 readmissions per 100 patients (95% CI, 177–190). Notably, nearly half of patients were not readmitted during the first year, and 30% were readmitted more than once (Table 2).

Table 2. Distribution of Readmission Frequency at 1-Year Follow-up

No. of ReadmissionsPatient n%
0318245.6
1170124.4
288412.7
35147.4
42814.0
51752.5
>52353.4

Nearly half of those discharged alive after an in-hospital cardiac arrest were not readmitted during the first year, whereas another 30% were readmitted more than once.

Figure 2.

Figure 2. Mean cumulative incidence for any readmission during follow-up. Cumulative incidence rate represented by solid line and 95% confidence intervals by dashed lines.

Table 3 summarizes the primary reasons for readmission. Of 2005 readmissions during the first 30 days of follow-up, cardiovascular disease was the predominant reason for readmission, comprising 720 (35.9%) of these hospitalizations. Another 43% of hospitalizations were because of pulmonary disease (n=343 [17.1%]), upper and lower gastrointestinal disease, including bleeding (n=265 [13.2%]), infections other than pneumonia (n=135 [6.7%]), and renal disease (n=118 [5.9%]). Notably, heart failure was the most frequent individual diagnosis-related group, constituting 16.7% of all readmissions. Importantly, recurrent cardiac arrest as the principal reason for readmission was infrequent (11 [0.5%] readmissions). These category percentages were similar when we examined reasons for readmission at 1 year after hospital discharge (Table 3).

Table 3. Principal Reasons for Readmission at 30 Days and 1 Year

30 d1 y
n=2005%n=8751%
Cardiovascular
 Heart failure33516.7137415.7
 Coronary artery disease703.53323.8
 Myocardial infarction592.92072.4
 Chest pain381.91381.6
 Syncope90.4660.8
 Cardiac arrest110.5400.5
 Other cardiac1989.98149.3
Pulmonary
 Pneumonia884.44395.0
 Acute respiratory failure834.12773.2
 Chronic obstructive pulmonary disease241.22312.6
 Other pulmonary1487.44765.4
Gastrointestinal
 Gastrointestinal bleed1587.94355.0
 PUD, liver, and intestinal diseases512.52993.4
 Other gastrointestinal562.82803.2
Infection
 Sepsis1185.94955.7
 Bacteremia and other infections without sepsis170.81011.2
Renal disease1185.95426.2
Medical/surgical complications1276.34925.6
Hematology/oncology
 Malignant cancer221.11571.8
 Anemia50.2340.4
 Other hematologic70.3520.6
 Other cancers20.1200.2
Neurological
 Stroke391.92092.4
 Other neurological251.21241.4
Endocrine
 Diabetes mellitus and complications321.61712.0
 Other endocrine or immune-related110.5490.6
Dehydration and electrolytes381.91852.1
Fracture and other musculoskeletal321.61691.9
Injury or poisoning180.91591.8
Psychiatric80.4720.8
All other causes582.93123.6

PUD indicates peptic ulcer disease.

Inpatient Resource Use

The mean (±SD) length of stay for the index hospitalization for an in-hospital cardiac arrest was 19±16 days, and the mean cost of that stay was $35 808±$38 230. In contrast, the mean cost for readmissions for the whole cohort (including those who were not admitted) was $7741±$2323 at 30 days and $18 629±$9411 at 1 year. On average, a patient was hospitalized for 11±22 days during the first year.

Inpatient resource use was substantially higher in younger than older patients, with 30-day adjusted costs of $6052 in patients aged ≥85 years when compared with $7444 (adjusted cost ratio, 1.23; 95% CI, 1.06–1.42; P<0.001) and $8291 (adjusted cost ratio, 1.37; 95% CI, 1.19–1.59; P<0.001) for patients aged 75 to 84 and 65 to 74 years, respectively (Table 4). Compared with whites (adjusted mean cost of $7413), black patients had higher 30-day adjusted inpatient resource use of $9044 (adjusted cost ratio, 1.22; 95% CI, 1.05–1.42; P<0.001). Patients with an initial cardiac arrest rhythm of ventricular fibrillation had lower adjusted inpatient resource use than those with an initial cardiac arrest rhythm of pulseless electric activity. Similar patterns of inpatient costs were found for each subgroup when the follow-up was extended to 1 year after hospital discharge. In each instance, these differences in inpatient resource use were accompanied by parallel differences in readmission rates (eg, those with higher inpatient resource use had higher cumulative readmission incidence rates; Table 4)

Table 4. Long-Term Inpatient Resource Use, Overall and by Patient Subgroup

30 d1 y
Cumulative Readmission IncidenceAdjusted CostsCost Ratio (95% CI)P ValueCumulative Readmission IncidenceAdjusted CostsCost Ratio (95% CI)P Value
All patients0.35$7741*1.85$18 629*
Age groups, y
 65–740.32$82911.37 (1.19–1.59)<0.0011.70$20 6861.40 (1.24–1.60)<0.001
 75–840.33$74441.23 (1.06–1.42)<0.0011.75$17 5831.19 (1.06–1.34)<0.001
 ≥850.36$6052Reference1.92$14 776Reference
Sex
 Men0.31$7706Reference1.64$18 751Reference
 Women0.35$74750.97 (0.87–1.06)0.281.87$18 1880.97 (0.90–1.04)0.20
Race groups
 White0.30$7413Reference1.64$17 687Reference
 Black0.47$90441.22 (1.05–1.42)<0.0012.54$24 5851.39 (1.24–1.54)<0.001
 Other0.45$74871.01 (0.77–1.30)0.502.41$21 9321.24 (0.89–1.61)0.09
Initial rhythm
 Pulseless electric activity0.34$7843Reference1.81$19 785Reference
 Asystole0.37$86271.10 (0.96–1.25)0.081.98$18 7960.95 (0.86–1.04)0.11
 Ventricular fibrillation0.28$66670.85 (0.73–0.96)0.0081.49$17 0150.86 (0.77–0.94)<0.001
 Pulseless VT0.34$76080.97 (0.82–1.16)0.361.81$18 9940.96 (0.86–1.07)0.22
Neurological status
 Mild to no disability0.28$7314Reference1.52$17 980Reference
 Moderate disability0.37$75331.03 (0.91–1.16)0.311.97$19 4181.08 (1.00–1.18)0.03
 Severe disability0.38$95811.31 (1.13–1.53)<0.0012.07$19 9581.11 (1.00–1.25)0.03
 Coma or vegetative state0.36$40960.56 (0.36–0.78)<0.0011.94$93500.52 (0.37–0.69)<0.001
Discharge destination
 Home, without assistance0.26$3232Reference1.39$12 460Reference
 Home, with home health0.31$33611.04 (0.83–1.31)0.391.68$13 9551.12 (0.98–1.28)0.04
 Skilled nursing care0.38$52041.61 (1.34–2.01)<0.0012.04$15 9491.28 (1.13–1.43)<0.001
 Rehabilitation site0.36$28 6038.85 (7.55–10.59)<0.0011.94$40 6203.26 (2.96–3.61)<0.001
 Hospice0.11$1620.05 (0.01–0.10)<0.0010.62$3740.03 (0.01–0.06)<0.001

Thirty-day and 1-year inpatient resource use for the overall cohort and prespecified patient subgroups were determined from multivariable models and are summarized. VT indicates ventricular tachycardia.

*Costs for the whole cohort (all patients) are crude costs. All subgroup costs were model adjusted.

At 1 year, patients discharged with moderate or severe neurological disability had much higher inpatient resource use when compared with patients with mild to no neurological deficits or in a coma or vegetative state. Compared with those who were able to be discharged home without any nursing assistance, patients who required home health nursing care, inpatient skilled nursing care, and inpatient rehabilitation after discharge had higher inpatient costs at 1 year. Not surprisingly, patients discharged to hospice care had minimal 1-year costs (adjusted costs, $374). Notably, there were no differences in an inpatient resource use by sex. These subgroup patterns were similar when examining cost ratios at 30 days. Finally, in contrast to follow-up inpatient costs, there were no cost differences for the index hospitalization by race, and initial hospitalization costs were higher for patients with coma or vegetative state (Appendix Table IV in the Data Supplement).

Discussion

Among patients who survived to discharge after an in-hospital cardiac arrest, we found that readmissions occurred frequently, especially during the first 30 days (rate of 35 readmissions per 100 patients). On average, subsequent inpatient resource use was >$7800 during the first 30 days and nearly $19 000 during the first year. Cardiovascular disease was the most common reason for readmission, but this category comprised only one third of all readmissions. There were important differences in readmission rates and inpatient costs, especially by age group, race, hospital disposition, and neurological status at discharge. Collectively, these findings provide important insights into the patterns of readmission and an inpatient resource use by survivors of an in-hospital cardiac arrest.

Because there are an estimated 200 000 in-hospital cardiac arrests annually in the United States1 and because temporal trends suggest that survival rates have improved substantially during the past decade,14 there is growing interest in the morbidity and mortality of survivors of an in-hospital cardiac arrest. Indeed, a recent study has found that the majority of hospitalized elderly patients who survive a cardiac arrest remain alive at 1 year.2 However, there has not been, to date, a systematic evaluation of readmission patterns and inpatient resource use of survivors of an in-hospital cardiac arrest. Although 1 previous study quantified inpatient resource use to be ≈$63 000 per patient at a mean of 22 months of follow-up,15 that study comprised 28 survivors from 1 site, reported hospital charges (not actual payments), and included charges from both the index hospitalization and the subsequent readmissions. Another study had found that 71% of patients who survived an in-hospital cardiac arrest were readmitted by 2 years. However, that study included only 79 survivors and examined neither cumulative rates of readmission nor quantified costs.16 By linking data from GWTG-Resuscitation to Medicare files, we were able to leverage rigorous data collection within a multicenter prospective registry with detailed information on inpatient use from a national insurance database. As a result, our study extends the findings of previous studies by providing, to date, the most representative and comprehensive estimates of long-term readmission and inpatient resource use for survivors of an in-hospital cardiac arrest.

Our findings help put into context the notion that survivors of an in-hospital cardiac arrest have extraordinarily high morbidity and mortality. In a recent study, we found that survivors of an in-hospital cardiac arrest have a similar 3-year mortality rate as Medicare-matched patients hospitalized with heart failure.2 In this present study, we found that an inpatient resource use during the first year for in-hospital cardiac arrest survivors was similar to 1-year costs for patients with systolic heart failure and poor health status (eg, eplerenone post-acute myocardial infarction heart failure efficacy and survival study [EPHESUS] trial: $18 476)17 and those with moderate to severe neurological disability after cardioembolic stroke ($23 000).18 Therefore, although survivors of an in-hospital cardiac arrest have significant morbidity and mortality after hospital discharge, these rates are not substantially different from those of other highly morbid cardiac conditions. Interestingly, rehospitalization for cardiac arrest was rare, occurring in <1% of readmissions.

Our study was also able to examine whether differences in inpatient resource use differed by important subgroups. Black patients who survive an in-hospital cardiac arrest are known to have lower survival rates after hospital discharge than white patients.2 We found that they also had higher rates of readmissions and subsequent inpatient resource use, which is consistent with their higher long-term mortality rate. We also found significant differences by age group, with fewer readmissions and lower inpatient resource use among more elderly survivors. Although the reasons for the lower rate are not altogether clear, it may be related to age differences in the use of advanced directives (particularly concerning resuscitations) and decisions about palliative care after surviving a cardiac arrest. There was also a gradient of inpatient resource use by hospital disposition. Patients discharged home had the lowest rate of readmissions and inpatient resource use, whereas patients sent to rehabilitation centers had the highest, with 44% higher 1-year inpatient costs. Finally, there was a notable step-wise gradient in readmission rates and long-term inpatient resource use by discharge neurological status, with higher use among those with greater neurological disability at hospital discharge.

The cost data from this study provide important postdischarge information for the overall cohort and for specific subgroups—information that before our analysis has been missing from the literature. Although we did not conduct assessments of cost-effectiveness in this article, previous cost-effectiveness studies (eg, hypothermia in cardiac arrest survivors) have lacked reliable estimates of long-term costs among cardiac arrest survivors. As new technologies and treatment strategies become adopted (eg, routine cardiac catheterization of cardiac arrest survivors, therapeutic hypothermia, and implantable cardioverter-defibrillators) in survivors of an in-hospital cardiac arrest, we think that the specific cost estimates from this study could be used to provide more precise estimates of their cost-effectiveness. Finally, our readmission and cost findings suggest a critical need for the development and testing of strategies, which can reduce neurological disability during the acute resuscitation period and improve postdischarge recovery in these high-risk patients. If such strategies were found to be successful, they would not only reduce morbidity but also substantial downstream costs.

Our study should be interpreted in the context of the following potential limitations. First, GWTG-Resuscitation is a quality-improvement registry. Although it collects data from a diverse group of hospitals, our findings may not be generalizable to all US hospitals, including non-Medicare (eg, Veteran Administration) hospitals. Second, we restricted the analysis to fee-for-service Medicare beneficiaries who could be matched to Medicare files; therefore, readmission patterns and inpatient resource use in patients aged <65 years and those with Medicare Advantage plans may differ. Third, our cost data for readmissions were based on Medicare payments to hospitals, which reimburse at lower rates than private insurers and may underestimate inpatient resource use for all patients. Fourth, we did not have cost data for other types of nonacute care, such as skilled nursing and outpatient rehabilitation, which would have underestimated the cost ratios for patients with neurological disability. Fifth, we did not have information on outpatient use, such as medications and clinic visits, and we, therefore, only examined an inpatient resource use. However, because the vast majority of total resource use comprised inpatient hospitalizations, our findings likely parallel patterns for total resource use. Sixth, our findings were restricted to survivors of an in-hospital cardiac arrest and, therefore, do not apply to those with out-of-hospital cardiac arrest. Seventh, we excluded patients for whom a GWTG-Resuscitation record could not be linked to a Medicare hospitalization. Nonetheless, excluded patients were similar to patients in the study cohort; therefore, their exclusion was unlikely to bias our results significantly. Finally, our study was based on observational data; therefore, although we were able to adjust for several confounders, we were unable to account for certain factors, such as left ventricular ejection fraction, which may have influenced readmission rates or inpatient resource use.

In conclusion, we found that elderly survivors of an in-hospital cardiac arrest were frequently readmitted, with high costs for an inpatient care during follow-up. Readmission rates and inpatient costs differed by patient age, race, hospital disposition, and neurological status at discharge.

Acknowledgments

Dr Chan had full access to all of the data in the study, and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr Chan helped in study concept and design. Drs Chan and Curtis helped in acquisition of data. Dr Li and B.G. Hammill helped in statistical analysis. Dr Chan, Dr Nallamothu, Dr Krumholz, Dr Curtis, Dr Li, B.G. Hammill, and Dr Spertus helped in analysis and interpretation of data. Dr Chan helped in drafting of the article. Dr Chan, Dr Nallamothu, Dr Krumholz, Dr Curtis, Dr Li, B.G. Hammill, and Dr Spertus helped in critical revision of the article for important intellectual content. Dr Chan helped in study supervision.

Footnotes

*This article includes an Appendix in the Data Supplement that lists the American Heart Association’s Get With The Guidelines-Resuscitation Investigators.

This article was handled independently by Karin H. Humphries, DSc, as a Guest Editor. The editors had no role in the evaluation of the article or in the decision about its acceptance.

The Data Supplement is available at http://circoutcomes.ahajournals.org/lookup/suppl/doi:10.1161/CIRCOUTCOMES.114.000925/-/DC1.

Correspondence to Paul S. Chan, MD, MSc, Mid America Heart Institute, 5th Floor, 4401 Wornall Rd, Kansas City, MO 64111. E-mail

References

  • 1. Merchant RM, Yang L, Becker LB, Berg RA, Nadkarni V, Nichol G, Carr BG, Mitra N, Bradley SM, Abella BS, Groeneveld PW; American Heart Association Get With The Guidelines-Resuscitation Investigators. Incidence of treated cardiac arrest in hospitalized patients in the United States.Crit Care Med. 2011; 39:2401–2406.CrossrefMedlineGoogle Scholar
  • 2. Chan PS, Nallamothu BK, Krumholz HK, Spertus JA, Li Y, Hammill BG, Curtis LH. Long-term outcomes of elderly survivors of in-hospital cardiac arrest.N Engl J Med. 2013; 368:1019–1026.CrossrefMedlineGoogle Scholar
  • 3. Peberdy MA, Kaye W, Ornato JP, Larkin GL, Nadkarni V, Mancini ME, Berg RA, Nichol G, Lane-Trultt T. Cardiopulmonary resuscitation of adults in the hospital: a report of 14720 cardiac arrests from the National Registry of Cardiopulmonary Resuscitation.Resuscitation. 2003; 58:297–308.CrossrefMedlineGoogle Scholar
  • 4. Cummins RO, Chamberlain D, Hazinski MF, Nadkarni V, Kloeck W, Kramer E, Becker L, Robertson C, Koster R, Zaritsky A, Bossaert L, Ornato JP, Callanan V, Allen M, Steen P, Connolly B, Sanders A, Idris A, Cobbe S. Recommended guidelines for reviewing, reporting, and conducting research on in-hospital resuscitation: the in-hospital ‘Utstein style’. American Heart Association.Circulation. 1997; 95:2213–2239.LinkGoogle Scholar
  • 5. Jacobs I, Nadkarni V, Bahr J, Berg RA, Billi JE, Bossaert L, Cassan P, Coovadia A, D’Este K, Finn J, Halperin H, Handley A, Herlitz J, Hickey R, Idris A, Kloeck W, Larkin GL, Mancini ME, Mason P, Mears G, Monsieurs K, Montgomery W, Morley P, Nichol G, Nolan J, Okada K, Perlman J, Shuster M, Steen PA, Sterz F, Tibballs J, Timerman S, Truitt T, Zideman D. Cardiac arrest and cardiopulmonary resuscitation outcome reports: update and simplification of the Utstein templates for resuscitation registries: a statement for healthcare professionals from a task force of the International Liaison Committee on Resuscitation (American Heart Association, European Resuscitation Council, Australian Resuscitation Council, New Zealand Resuscitation Council, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Councils of Southern Africa).Circulation. 2004; 110:3385–3397.LinkGoogle Scholar
  • 6. Peberdy MA, Ornato JP, Larkin GL, Braithwaite RS, Kashner TM, Carey SM, Meaney PA, Cen L, Nadkarni VM, Praestgaard AH, Berg RA; National Registry of Cardiopulmonary Resuscitation Investigators. Survival from in-hospital cardiac arrest during nights and weekends.JAMA. 2008; 299:785–792.CrossrefMedlineGoogle Scholar
  • 7. Hammill BG, Hernandez AF, Peterson ED, Fonarow GC, Schulman KA, Curtis LH. Linking inpatient clinical registry data to Medicare claims data using indirect identifiers.Am Heart J. 2009; 157:995–1000.CrossrefMedlineGoogle Scholar
  • 8. Jennett B, Bond M. Assessment of outcome after severe brain damage.Lancet. 1975; 1:480–484.CrossrefMedlineGoogle Scholar
  • 9. Heilbron DC. Zero-altered and other regression models for count data with extra zeros.Boimetrical J. 1994; 36:531–547.CrossrefGoogle Scholar
  • 10. Blough DK, Ramsey SD. Using generalized linear models to assess medical care costs.Health Serv Outcomes Res Methodol. 2000; 1:185–202.CrossrefGoogle Scholar
  • 11. Shao J, Tu DThe Jackknife and Bootstrap. New York: Springer Verlag; 1995.CrossrefGoogle Scholar
  • 12. Raghunathan TE, Solenberger PW, Van Hoeyk JIVEware: Imputation and Variance Estimation Software—User Guide. Ann Arbor, MI: Survey Research Center, Institute for Social Research University of Michigan; 2002.Google Scholar
  • 13. R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing V, Austria. ISBN 3-900051-07-0. http://www.R-project.org.Google Scholar
  • 14. Girotra S, Nallamothu BK, Spertus JA, Li Y, Krumholz HM, Chan PS; American Heart Association Get with the Guidelines–Resuscitation Investigators. Trends in survival after in-hospital cardiac arrest.N Engl J Med. 2012; 367:1912–1920.CrossrefMedlineGoogle Scholar
  • 15. Berger R, Kelley M. Survival after in-hospital cardiopulmonary arrest of noncritically ill patients. A prospective study.Chest. 1994; 106:872–879.CrossrefMedlineGoogle Scholar
  • 16. Herlitz J, Andréasson AC, Bång A, Aune S, Lindqvist J. Long-term prognosis among survivors after in-hospital cardiac arrest.Resuscitation. 2000; 45:167–171.CrossrefMedlineGoogle Scholar
  • 17. Chan PS, Soto G, Jones PG, Nallamothu BK, Zhang Z, Weintraub WS, Spertus JA. Patient health status and costs in heart failure: insights from the eplerenone post-acute myocardial infarction heart failure efficacy and survival study (EPHESUS).Circulation. 2009; 119:398–407.LinkGoogle Scholar
  • 18. Chan PS, Vijan S, Morady F, Oral H. Cost-effectiveness of radiofrequency catheter ablation for atrial fibrillation.J Am Coll Cardiol. 2006; 47:2513–2520.CrossrefMedlineGoogle Scholar