doi: 10.1161/CIRCHEARTFAILURE.107.748376
Original Articles |
Day of Admission and Clinical Outcomes for Patients Hospitalized for Heart Failure
Findings From the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF)
From the Department of Medicine, University of California Los Angeles Medical Center, Los Angeles (G.C.F.); Division of Cardiology, Ohio State University, Columbus (W.T.A.); George M. and Linda H. Kaufman Center for Heart Failure, Cleveland Clinic Foundation, Cleveland, Ohio (N.M.A.); Department of Medicine, Duke University Medical Center, Durham, NC, and Department of Clinical Research, Campbell University School of Pharmacy, Research Triangle Park, NC (W.G.S.); Division of Cardiology, Feinberg School of Medicine, Northwestern University, Chicago, Ill (M.G.); Department of Medicine, University of California San Diego Medical Center, San Diego (B.H.G.); Division of Cardiology, Duke University Medical Center/Duke Clinical Research Institute, Durham, NC (C.M.O.); GlaxoSmithKline, Philadelphia, Penn (E.N.); Baylor Heart and Vascular Institute, Baylor University Medical Center, Dallas, Tex (C.W.Y.); and Department of Cardiovascular Medicine, Heart Failure Section, Cleveland Clinic Foundation, Cleveland, Ohio (J.B.Y.).
Correspondence to Gregg C. Fonarow, MD, Ahmanson–UCLA Cardiomyopathy Center, UCLA Medical Center, 10833 LeConte Ave, Room 47-123 CHS, Los Angeles, CA 90095-1679. E-mail gfonarow{at}mednet.ucla.edu
Received October 25, 2007; accepted February 1, 2008.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Background— Differences in hospital staffing may influence outcomes for patients with acute conditions, including heart failure (HF), depending on which day of the week the patients are admitted. This study examined the relationship between the day of the week patients are hospitalized for HF and death rate, length of stay (LOS), and rehospitalization rate.
Methods and Results— A total of 259 US hospitals participating in the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) submitted data on 48 612 patients with HF. Sixty- to 90-day postdischarge follow-up data were collected prospectively in a prespecified 10% sample. We analyzed day of admission and discharge, demographic, medical history, medication use, laboratory, and in-hospital procedure data for their association with hospital LOS and death rate. Patient characteristics were similar for weekday and weekend presentation. LOS was a median of 4.0 days and a mean of 5.7±5.7 days; in-hospital death rate was 3.8%. In-hospital and postdischarge risk of death were similar for each day of the week in the hospital and follow-up cohorts, respectively. LOS, however, was significantly influenced by day of admission, even after adjustment for other LOS risk factors. The shortest LOS by admission day of the week was Tuesday (5.39 days), and the longest was Friday (5.88 days; P<0.001).
Conclusions— No differences in death rate by day of admission or discharge for HF hospitalizations were evident. Hospitalizations for HF on Thursday and Friday were associated with prolonged LOS. Understanding the factors responsible for the increased LOS and potential adjustments in staffing to facilitate weekend discharges may improve the efficiency of HF hospital care.
Key Words: heart failure • length of stay • registries • mortality • hospitalization
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Heart failure (HF) is among the leading cause of hospitalizations, and these hospitalizations contribute substantially to the high costs of the disease. There are at least 3.6 million hospitalizations with HF as the primary or a secondary cause each year in the United States.1,2 The estimated annual cost of HF is $33.2 billion, with much of this attributable to the costs of hospitalization.1 HF hospitalizations are also associated with substantial morbidity and mortality.3,4 Understanding factors that influence care and clinical outcomes for patients hospitalized with HF, particularly those that are modifiable, is important and may identify strategies to improve HF outcomes.
Clinical Perspective p 57
Most acute-care hospitals provide routine care with full staff on the weekdays and work on a more limited or reduced staff complement on weekends.5 Furthermore, there are differences in physician coverage of patients on weekdays compared with weekends. Recent studies suggest admission on the weekends is associated with a higher death rate than weekday admissions for acute myocardial infarctions and other serious medical conditions.6,7 Admission and discharge day of the week may also influence hospital length of stay (LOS).8 These studies underscore potential adverse consequences of reduced hospital and physician staffing on weekends. Little is known, however, as to whether the day of the week on which patients are hospitalized for HF is associated with differences in clinical outcomes.
The Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) is a registry and performance-improvement program for patients hospitalized with HF.9 The objectives of the present analysis of OPTIMIZE-HF data are to determine the relationship between the day of the week patients are hospitalized with HF and clinical outcomes, including hospital LOS, in-hospital death, and early postdischarge death and death/rehospitalization. We also assessed the relationship of day of hospital discharge with postdischarge clinical outcomes.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
OPTIMIZE-HF is a comprehensive, hospital-based registry and process-of-case improvement program designed to provide optimal medical care and education to patients hospitalized for HF. The OPTIMIZE-HF program has been described in detail previously9–12 and will be summarized briefly here. Patients qualified for enrollment if they were hospitalized for episodes of new or worsening HF as the primary cause of admission or if significant HF symptoms developed during hospitalization for another primary diagnosis, with HF being the primary discharge diagnosis.9–12 Consecutive patients were enrolled irrespective of their ventricular function, including systolic dysfunction documented by a left ventricular ejection fraction <40%, HF symptoms in the setting of preserved left ventricular systolic function (diastolic dysfunction HF), or HF without left ventricular function measurement.9–12 Hospital teams used HF case-ascertainment methods similar to those of the Joint Commission on Accreditation of Healthcare Organizations.13
From March 1, 2003, to December 31, 2004, 48 612 patients hospitalized at 259 centers in the United States were enrolled in the OPTIMIZE-HF registry. All regions of the United States were represented, and institutions from community hospitals to large tertiary medical centers participated.9–11 A prespecified patient subgroup (10%) was followed up for 60 to 90 days after discharge for the collection of outcomes data. The protocol was approved by each participating center’s institutional review board or through use of a central institutional review board. Written informed consent was obtained before enrollment from patients who participated in the follow-up data collection. Sites had the option of participating in the follow-up data collection, as described previously.9–12 There were 91 hospitals that provided 60- to 90-day follow-up data, and this cohort was demographically similar to patients in the overall registry.9–12
The registry captured data on important characteristics (demographic, pathophysiological, and clinical), treatment patterns, and outcomes of patients hospitalized for HF using the World Wide Web–based case report form. Data on the date of admission and date of discharge were collected. Admission staff, medical staff, or both recorded race/ethnicity, usually as the patient was being registered. Automated electronic data checks were used to prevent out-of-range entry or duplicate patients. Dates of admission and discharge were available in >99.5% of patient records. A database audit of a random sample of 5% of the first 10 000 patients, verified against source documents, was performed on the basis of predetermined criteria.10,11 The registry coordinating center was Outcome Sciences, Inc (Cambridge, Mass).
Statistical Analysis
The data are reported as mean±standard deviation or median (interquartile range) when appropriate for continuous variables and percentages of nonmissing values for categorical variables. Patient characteristics and evidence-based treatments at hospital discharge were compared with Pearson 
2 test for categorical variables and parametric methods (unpaired t test or 1-way analysis of variance) for continuous variables. For variables with significant departure from normality, nonparametric methods were used (Wilcoxon rank sum test or Kruskal-Wallis test). Transfer patients were excluded from analyses that assessed LOS. Multivariable models of in-hospital death, postdischarge death, and postdischarge death or rehospitalization were developed as described previously.10–12 The types of models were logistic for in-hospital death, Cox proportional hazards for postdischarge death, and logistic for postdischarge rehospitalization and death and rehospitalization combined (date of rehospitalization was not available for survival modeling). Clustering within hospital sites was accounted for in all regression models. Because LOS was treated as a count instead of a continuous parameter, zero-truncated negative binomial regression was used, and estimates are reported as incident rate ratios. Separate analyses were constructed for day of the week and for weekend (Saturday/Sunday) versus weekday (Monday through Friday) admission.
The generalized estimating equation logistic model for in-hospital death included the following variables: age; race; prior history of smoking, acute renal failure, cerebrovascular accident, dialysis, hyperlipidemia, hypertension, chronic obstructive pulmonary disease, pulmonary hypertension, peripheral vascular disease, and liver disease; admission medication, including β-blocker, angiotensin-converting enzyme inhibitor, loop diuretic, and statins; admission vital signs, including weight, heart rate, systolic blood pressure, and diastolic blood pressure; admission laboratory values, including elevated troponin I, sodium, hemoglobin, and creatinine; and left ventricular systolic dysfunction status. The generalized estimating equation logistic model for postdischarge death or rehospitalization included the following variables: LOS; prior history of chronic obstructive pulmonary disease and diabetes mellitus; procedures, including coronary angiography, mechanical ventilation, and cardiac resynchronization therapy placement; discharge medications, including angiotensin-converting enzyme inhibitor, angiotensin receptor blocker, hydralazine, and lipid-lowering agent; discharge vital signs, including heart rate and systolic blood pressure; admission laboratory values, including serum sodium and hemoglobin; discharge laboratory values, including serum creatinine; no prior history of heart failure; left ventricular systolic dysfunction; and ischemic etiology status. The Cox proportional model (with shared frailty on hospital site) for postdischarge death included the following variables: LOS, age, race; prior history of depression, hypertension, and diabetes mellitus; procedures, including revascularization procedures (percutaneous coronary intervention or coronary artery bypass surgery); parenteral therapies, including dobutamine; discharge medications, including angiotensin-converting enzyme inhibitor, aldosterone antagonist, digoxin, diuretic, and lipid-lowering agent; discharge vital signs, including weight, heart rate, systolic blood pressure, and diastolic blood pressure; discharge laboratory values, including serum sodium and serum creatinine; left ventricular systolic dysfunction; and ischemic etiology status. Adjusted odds ratios (ORs)/hazard ratios (HRs) were presented with their respective 95% confidence intervals (CIs). The predictive ability of the multivariable models was assessed by estimating the receiver operator characteristic area under the curve. The areas under the curve for the in-hospital death, postdischarge death, rehospitalization, and postdischarge death/rehospitalization models were 0.79, 0.75, 0.62, and 0.65, respectively. Stata version 10 was used for all statistical analyses (StataCorp, College Station, Tex).
The authors had full access to the data and take full responsibility for the integrity of the data. All authors have read and agreed to the manuscript as written.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Clinical Characteristics of Patients Hospitalized for HF
OPTIMIZE-HF enrolled a total of 48 612 patients hospitalized for HF at 259 academic and community hospitals of various sizes from all regions of the United States. The patient characteristics and institutional demographics of hospitals participating in the hospital and follow-up cohorts have been published previously and were similar.10–12 Mean patient age was 73.1 years; 52% of patients were female, and 74% were white (Table 1). Comorbidities were frequent, including hypertension in 71%, diabetes mellitus in 42%, and chronic obstructive pulmonary disease in 28%. HF origin was ischemic in 46% of enrolled patients, and the mean left ventricular ejection fraction was 39%. Of those patients assessed, 48.8% had documented left ventricular systolic dysfunction, and 51.2% had HF with preserved systolic function. The follow-up cohort included 5791 patients, whose characteristics were similar to those of the overall registry. Patient characteristics were similar for those admitted by day of the week (Table 1). Patient characteristics were also similar when patients admitted on weekdays were compared with those admitted on weekdays (data not shown).
|
The distributions of hospitalizations by the admission and discharge day of the week are shown in Figure 1. The frequency of admission and discharge varied significantly by day of the week (both P<0.0001). Monday was the most frequent day of admission for heart failure (17.8%) and Saturday the least frequent day (10.8%). The majority of patients were admitted to the hospital from the emergency department (74.4%), which ranged from 69.9% on Thursday to 89.5% on Sunday (Table 1). Friday was the most frequent day of discharge (19.4%), and Sunday was the least frequent (7.1%). There were 37 866 (77.9%) of 48 612 of patients admitted to the hospital on a weekday, and 10 746 (22.1%) of 48 612 hospitalized on a weekend. Hospital discharges on weekends were modestly less frequent than admissions (absolute difference 4.1%, P<0.001), with 37 293 (82.0%) of 45 469 of patients discharged from the hospital on a weekday and 8176 (18.0%) of 45 469 discharged during the weekend.
|
In-Hospital Deaths
There were 1834 in-hospital deaths reported among 48 612 enrolled patients (3.8%). In-hospital death rates did not substantially differ by admission day of the week, ranging from 3.4% to 4.1% (P=0.19) as shown in Table 2. On multivariable analysis, admission day of the week was not predictive of in-hospital death (Table 2). When analyzed by admission on a weekend versus weekday, the in-hospital death rates did not significantly differ. Weekend admission was not associated with an increase for in-hospital death rate on multivariable analysis compared with weekday admission (OR 0.99, 95% CI 0.84 to 1.17).
|
Hospital LOS
The median hospital LOS was 4.0 days (25th to 75th percentile interquartile range 3.0 to 7.0), and mean LOS was 5.7±5.7 days. Hospital LOS varied significantly by the day of admission. Hospitalizations for HF on Sunday, Monday, and Tuesday resulted in the shortest hospital LOS, whereas hospitalizations on Thursday and Friday were associated with the longest LOS (Table 2). The shortest LOS by admission day of the week was Tuesday (5.39 days), and the longest was Friday (5.88 days; P<0.001). On adjusted analyses, admission days Thursday and Friday were independent predictors of longer LOS. No other admission day was associated with shorter or longer LOS (Figure 2). When analyzed for weekend versus weekday admission day, no significant differences were found for LOS on unadjusted or adjusted analyses.
|
Sixty- to 90-Day Postdischarge Outcomes
During the 60- to 90-day period after hospital discharge, there were 481 deaths in the follow-up cohort (6.7%), which occurred a median of 42 days (25th to 75th percentile interquartile range 24 to 66 days) after discharge. Rehospitalization within the follow-up period occurred in 1715 patients (29.6%). The combined end point of death/rehospitalization was met in 1909 (34.9% of patients). Postdischarge death, death/rehospitalization, and rehospitalization rates did not differ by admission day of the week (Table 3). On adjusted analyses, admission day of the week was also not predictive of postdischarge death, death/rehospitalization, or rehospitalization (Table 3). When analyzed by admission on a weekend versus weekday, postdischarge death, death/rehospitalization, and rehospitalization rates did not differ significantly. Weekend admission was not associated with a significant increase in postdischarge death, death/rehospitalization, or rehospitalization rates on multivariable analysis (HR 1.16, 95% CI 0.87 to 1.55; OR 1.03, 95% CI 0.91 to 1.18, and OR 1.07, 95% CI 0.91 to 1.26, respectively).
|
Discharge day of the week was not associated with significantly different postdischarge death, death/rehospitalization, or rehospitalization rates on unadjusted or adjusted analyses (Table 4). Weekend versus weekday discharge was also not associated with a significant increase in postdischarge death, death/rehospitalization, or rehospitalization rates on multivariable analysis (HR 1.21, 95% CI 0.88 to 1.67; OR 1.05, 95% CI 0.88 to 1.24 and OR 1.10, 95% CI 0.92 to 1.31, respectively).
|
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
OPTIMIZE-HF has demonstrated that among a large, representative population of patients admitted to the hospital for HF, no differences in in-hospital or early postdischarge death rates by the day of admission were evident. The risk of postdischarge death/rehospitalization or rehospitalization also did not differ by day of admission. Furthermore, the day of the week in which hospital discharge occurred did not appear to influence postdischarge clinical outcomes. The day of the week patients were hospitalized for HF did, however, significantly influence hospital LOS. Hospitalizations for HF on Thursday and Friday were associated with prolonged LOS. These findings provide important insights into factors that may or may not influence the quality and efficiency of hospital care and outcomes for HF patients.
Hospital staffing is reduced on Saturdays and Sundays in both the number of staff and level of experience.5,14 Also, fewer supervisors are present in the hospital on weekends.14 In addition, the level of physician coverage for patients also differs on weekends in most hospital settings, and the weekend physician staff frequently provide coverage for other health professionals and thus may be less familiar with the patients under their care.15,16 These differences in hospital and physician staffing may result in shortfalls in quality of care and outcomes depending on the admission day of the week. Even small differences in clinical outcomes between weekday and weekend admission of patients with HF could translate into substantial numbers of deaths and recurrent hospitalizations for this patient population because of the large number of patients hospitalized with HF each year.
Differences in clinical outcomes by the admission day of the week could reflect differences in the characteristics of patients hospitalized. Prior studies have suggested that the rate of admission and the severity of acute coronary syndromes may vary according to the day of the week,17 but comparable studies for HF have not been performed. Because almost all scheduled outpatient HF visits occur during the week, direct admissions with less severe decompensations of HF would be more likely to occur on weekdays, which would result in patients admitted on the weekend who were sicker than those admitted during the week. In the present study, patients admitted on weekends for HF did not appear to be sicker than those admitted on weekdays, as judged by the severity of symptoms and multiple prognostic variables. Thus, any detected difference in clinical outcomes would be more likely to reflect different care.
Evidence is inconsistent with regard to the relationships between weekend hospitalization, treatment decisions, quality of care, and clinical outcomes.6,7,16,18,19 One study of close to 4 million hospitalizations in Ontario, Canada, from 1988 to 1997 found that for certain medical conditions, patients admitted on the weekend were >15% more likely to die in the hospital than were patients admitted during the week.7 Another study observed that there was a 9% increase in risk-adjusted death rate among patients admitted to intensive care units on weekends compared with weekdays.18 The Myocardial Infarction Data Acquisition System (MIDAS) study reported an increase of in-hospital risk of death that persisted up to 1 year for patients admitted during weekends.6 A large analysis of hospitals participating in the National Registry of Myocardial Infarction (NRMI) also suggested that off-hours presentation for acute myocardial infarction was associated with a higher in-hospital death rate.19 For patients hospitalized with HF, admission on weekends compared with weekdays has not been associated with an increase in deaths in prior studies. Among the 141 687 HF hospitalizations included in the Canadian study, the in-hospital death rate did not differ by weekday compared with weekends (10.8% versus 11.0%, adjusted HR 1.00, 95% CI 0.96 to 1.04).7 An unadjusted analysis of administrative records for patients hospitalized in California in 1998 revealed that for patients with HF (n=55 835), there was no difference in death rate for weekend admission (OR 1.03, 95% CI 0.96 to 1.12).16 In the present study, we did not find that risk of death among patients hospitalized with HF varied by admission day of the week or by weekday/weekend admission. These findings suggest that for HF patients, there may be adequate medical care and staffing without significant weekend treatment differences that would lead to higher rates of death.
Prior studies have suggested that the day of the week may influence hospital LOS. Perhaps as a result of decreased staffing on weekends and physician cross-coverage, patients may be preferentially discharged on Fridays rather than on subsequent weekend days. In a study of 2.4 million medical and surgical hospitalizations, Friday was the most frequent day of discharge, occurring in 19% of hospitalizations, whereas only 8% of discharges occurred on Sunday.20 The day-of-the-week distribution of hospital discharges for HF patients in OPTIMIZE-HF was thus nearly identical to that observed for overall hospitalizations. One other study examined the effects of weekend hospital service reductions on the treatment of patients with acute myocardial infarction in a British hospital.8 The authors observed substantially lower rates of discharge on weekends. Together, these studies may suggest that physicians and perhaps nursing staff, patients, and their families prefer weekday discharge. This may raise the possibility that a portion of HF patients discharged on Fridays could be leaving the hospital before they are fully stabilized. In addition, home health and other support services for Friday or weekend discharges would most often not be initiated until the following Monday. However, we found no evidence that different days of the week for HF admissions or discharges were associated with differences in postdischarge clinical outcomes. Either hospital care for HF is of similar quality irrespective of day of the week, or alternatively, there is not a strong relationship between inpatient care processes and early postdischarge clinical outcomes for HF.11
The strengths of the present study include that it was performed by use of a systematic approach to data collection and was conducted in 259 US hospitals from all regions of the country using a well-defined cohort of HF patients.10–12 Another important feature of the present study is that it is the first that assessed the relationship between day of admission and clinical outcomes independent of other prognostic variables. The knowledge provided by the present study may help guide clinicians and hospital administrators in implementing more effective staffing and management strategies for hospitalized HF patients.3 Although day of the week for admission or discharge did not influence death or rehospitalization risk, there was a significant and independent influence on efficiency of care. The present study demonstrates that LOS was significantly influenced by day of admission, even after adjustment for other LOS risk factors. Approximately $360 million in direct costs could be eliminated each year without patients being exposed to higher risk of early death or rehospitalization. For a hospital with 1000 HF hospitalizations annually, this could translate into $330 000 or more a year in reduced costs. Future studies should be designed to prospectively test whether different weekend staffing models and other interventions to facilitate weekend hospital discharges can favorably impact hospital LOS without exposing patients to lower quality of care or higher risk of postdischarge death/rehospitalization.
Study Limitations
The present analysis of OPTIMIZE-HF may be influenced by several limitations. Follow-up data were obtained in a subset of patients and were limited to 60 to 90 days. We do not have data on patients who may have died before reaching the hospital or who presented to the emergency department with HF but were released without admission. These findings may not apply to hospitals that differ in patient characteristics or care patterns from OPTIMIZE-HF hospitals, although a recent study suggests patients enrolled in OPTIMIZE-HF are nationally representative.21 The patient data on no prior history of HF were collected in OPTIMIZE-HF in a different format than in other studies and are likely an underestimate of the proportion of patients with a new diagnosis of HF. Given the overall large number of patients observed, some differences, although statistically significant, may not be clinically relevant. Also, despite multivariable analyses, we cannot exclude that residual measured and unmeasured confounding account for some of these observations. Despite these limitations, the present analysis provides new insights into the relationship between day of admission and discharge for HF hospitalization and clinical outcomes from a large, representative data set of patients hospitalized with HF from all regions of the country, including patients with preserved systolic function and multiple comorbidities.
Conclusions
No differences in either in-hospital or postdischarge death rate for patients hospitalized with HF by day of admission were evident. Postdischarge clinical outcomes also did not significantly vary by day of hospital discharge. In contrast to studies of patients hospitalized with acute myocardial infarction, these findings suggest that that the level of access to care on weekends does not appear to adversely affect risk of death for patients hospitalized with HF. However, day of the week for hospital admission does significantly influence hospital LOS. Hospitalizations for HF on Sunday, Monday, and Tuesday are associated with the shortest hospital LOS, whereas hospitalizations on Thursday and Friday are associated with the longest LOS. Patients hospitalized with HF are most frequently discharged on Friday and least frequently discharged on Sunday. Understanding the factors responsible for the increased LOS and making potential adjustments in staffing to facilitate weekend discharges may improve the efficiency of HF hospital care.
|
Acknowledgments |
|---|
Source of Funding
GlaxoSmithKline funded the OPTIMIZE-HF registry under the guidance of the OPTIMIZE-HF Steering Committee and funded data collection and management by Outcome, Inc.
Disclosures
Drs Fonarow, Abraham, Gheorghiade, Greenberg, O’Connor, Yancy, and Young and W. Gattis Stough have received research grants and honoraria from and have served as consultants and/or speakers for GlaxoSmithKline. Dr Albert is a consultant for GlaxoSmithKline. Dr Nunez was an employee of GlaxoSmithKline.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Rosamond W, Flegal K, Friday G, Furie K, Go A, Greenlund K, Haase N, Ho M, Howard V, Kissela B, Kittner S, Lloyd-Jones D, McDermott M, Meigs J, Moy C, Nichol G, O’Donnell CJ, Roger V, Rumsfeld J, Sorlie P, Steinberger J, Thom T, Wasserthiel-Smoller S, Hong Y. Heart disease and stroke statistics: 2007 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2007; 115: e69–e171.
2. Hunt SA, Abraham WT, Chin MH, Feldman AM, Francis GS, Ganiats TG, Jessup M, Konstam MA, Mancini DM, Michl K, Oates JA, Rahko PS, Silver MA, Stevenson LW, Yancy CW. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2005; 46: e1–e82.
3. Adams KF, Lindenfeld J, Arnold JMO, Baker DW, Barnard DH, Baughman KL, Boehmer JP, Deedwania P, Dunbar SB, Elkayam U, Gheorghiade M, Howlett JG, Konstam MA, Kronenberg MW, Massie BM, Mehra MR, Miller AB, Moser DK, Patterson JH, Rodeheffer RJ, Sackner-Bernstein J, Silver MA, Starling RC, Stevenson LW, Wagoner LE. HFSA 2006 comprehensive heart failure practice guideline. J Card Fail. 2006; 12: e1–e122.[CrossRef][Medline]
4. Gheorghiade M, Zannad F, Sopko G, Klein L, Piña IL, Konstam MA, Massie BM, Roland E, Targum S, Collins SP, Filippatos G, Tavazzi L. Acute heart failure syndromes: current state and framework for future research. Circulation. 2005; 112: 3958–3968.
5. Angus DC, Shorr AF, White A, Dremsizov TT, Schmitz RJ, Kelley MA. Critical care delivery in the United States: distribution of services and compliance with Leapfrog recommendations. Crit Care Med. 2006; 34: 1016–1024.[CrossRef][Medline]
6. Kostis WJ, Demissie K, Marcella SW, Shao YH, Wilson AC, Moreyra AE. Weekend versus weekday admission and mortality from myocardial infarction. N Engl J Med. 2007; 356: 1099–1109.
7. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001; 345: 663–668.
8. Varnava AM, Sedgwick JEC, Deaner A, Ranjadayalan K, Timmis AD. Restricted weekend service inappropriately delays discharge after acute myocardial infarction. Heart. 2002; 87: 216–219.
9. Fonarow GC, Abraham WT, Albert NM, Gattis WA, Gheorghiade M, Greenberg B, O’Connor CM, Yancy CW, Young J. Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF): rationale and design. Am Heart J. 2004; 148: 43–51.[CrossRef][Medline]
10. Gheorghiade M, Abraham WT, Albert NM, Greenberg BH, O’Connor CM, She L, Stough WG, Yancy CW, Young JB, Fonarow GC. Systolic blood pressure at admission, clinical characteristics, and outcomes in patients hospitalized with acute heart failure. JAMA. 2006; 296: 2217–2226.
11. Fonarow GC, Abraham WT, Albert NM, Stough WG, Gheorghiade M, Greenberg BH, O’Connor CM, Pieper K, Sun JL, Yancy C, Young JB. Association between performance measures and clinical outcomes for patients hospitalized with heart failure. JAMA. 2007; 297: 61–70.
12. Fonarow GC, Abraham WT, Albert NM, Gattis Stough W, Gheorghiade M, Greenberg BH, O’Connor CM, Pieper K, Sun JL, Yancy CW, Young JB. Influence of a performance-improvement initiative on quality of care for patients hospitalized with heart failure: results of the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF). Arch Intern Med. 2007; 167: 1493–1502.
13. Joint Commission on Accreditation of Healthcare Organizations. Specification Manual for National Implementation of Hospital Core Measures. Oakbrook Terrace, Ill: Joint Commission on Accreditation of Healthcare Organizations; 2004.
14. Czaplinski C, Diers D. The effect of staff nursing on length of stay and mortality. Med Care. 1998; 36: 1626–1638.[CrossRef][Medline]
15. Petersen LA, Brennan TA, O’Neil AC, Cook EF, Lee TH. Does house staff discontinuity of care increase the risk for preventable adverse events? Ann Intern Med. 1994; 121: 866–872.
16. Cram P, Hillis SL, Barnett M, Rosenthal GE. Effects of weekend admission and hospital teaching status on in-hospital mortality. Am J Med. 2004; 117: 151–157.[CrossRef][Medline]
17. Van der Palen J, Doggen CJ, Beaglehole R. Variation in the time and day of onset of myocardial infarction and sudden death. N Z Med J. 1995; 108: 332–334.[Medline]
18. Barnett MJ, Kaboli PJ, Sirio CA, Rosenthal GE. Day of the week of intensive care admission and patient outcomes. Med Care. 2002; 40: 530–539.[CrossRef][Medline]
19. Magid DJ, Wang Y, Herrin J, McNamara RL, Bradley EH, Curtis JP, Pollack CV Jr, French WJ, Blaney ME, Krumholz HM. Relationship between time of day, day of week, timeliness of reperfusion, and in-hospital mortality for patients with acute ST-segment elevation myocardial infarction. JAMA. 2005; 294: 803–812.
20. Van Walraven C, Bell C. Risk of death or readmission among people discharged from hospital on Fridays. CMAJ. 2002; 166: 1672–1673.
21. Curtis LH, Hernandez AF, Greiner MA, Fonarow GC, Schulman KA. Validity of a national heart failure quality of care registry: comparison of Medicare patients in OPTIMIZE-HF vs. Non-OPTIMIZE-HF hospitals. Circulation. 2007; 115: e595. Abstract.
|
Footnotes |
|---|
An editorial on this article by Kevin G. Volpp, MD, PhD, will appear in the May 20, 2008, issue of Circulation.
Clinical trial registration information—URL: http://www.clinicaltrials.gov. Unique identifier: NCT00344513.
This article has been cited by other articles:
 |
|
 |
|
  H. Wong, R. C. Wu, G. Tomlinson, M. Caesar, H. Abrams, M. W. Carter, and D. Morra How much do operational processes affect hospital inpatient discharge rates? J Public Health, December 1, 2009; 31(4): 546 - 553. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. Aujesky, D. Jimenez, M. K. Mor, M. Geng, M. J. Fine, and S. A. Ibrahim Weekend Versus Weekday Admission and Mortality After Acute Pulmonary Embolism Circulation, February 24, 2009; 119(7): 962 - 968. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. G. Volpp A Delicate Balance: Physician Work Hours, Patient Safety, and Organizational Efficiency Circulation, May 20, 2008; 117(20): 2580 - 2582. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||