Original Contribution

cost-effectiveness analysis of ED decision making in patients with non-high-risk heart failure

Sean P. Collins MD, MSc^a,?, Daniel P. Schauer MD, MSc^b, Amit Gupta MD^c, Hermine Brunner MD^d, Alan B. Storrow MD^e, Mark H. Eckman MD, MS^b

^aDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH 45267, USA

^bDivision of General Internal Medicine and Center for Clinical effectiveness, University of Cincinnati, Cincinnati, OH

^cDivision of Hematology/Oncology and Center for Clinical Effectiveness, Department of Internal Medicine,

University of Cincinnati, Cincinnati, OH

^dDivision of Rheumatology, Children’s Hospital Medical Center, Cincinnati, OH

^eDepartment of Emergency Medicine, Vanderbilt University, Nashville, TN

Received 11 January 2008; revised 21 February 2008; accepted 22 February 2008

Abstract

Background: The ED disposition of patients with non-high-risk acute decompensated heart failure (ADHF) is challenging. To help address this problem, we investigated the cost-effectiveness of different ED disposition strategies.

Methods: We constructed a decision analytic model evaluating the cost-effectiveness of 3 possible ED ADHF disposition strategies in a 60-year-old man: (1) Discharge home from the ED; (2) observation unit (OU) admission; (3) inpatient admission. Base case patients had no high-risk features. We used Medicare costs and the national physician fee schedule to capture ED, OU, and hospital costs, including costs of complications and death. All analyses were conducted using Decision Maker software (University of Medicine and Dentistry of New Jersey, Newark, NJ).

Results: Compared to ED discharge, OU admission had a reasonable marginal cost-effectiveness ratio ($44 249/quality adjusted life year), whereas hospital admission had an unacceptably high marginal cost- effectiveness ratio ($684 101/quality adjusted life year). Sensitivity analyses demonstrated that as the risk of early (within 5 days) and late (within 30 days) readmission exceeded 36% and 74%, respectively, in those discharged from the ED, OU admission became less costly and more effective than ED discharge. Similarly, an increase in relative risk of both early and late death in those discharged from the ED improves the marginal cost-effectiveness ratio of OU admission. Finally, as postdischarge event rates increase in those discharged from the OU, hospital admission became more cost-effective.

Conclusion: Observation unit admission for patients with non-high-risk ADHF has a societally acceptable marginal cost-effectiveness ratio compared to ED discharge. However, as ED and OU discharge event rates increase, hospital admission becomes the more cost-effective strategy.

(C) 2009

* Corresponding author.

E-mail addresses: [email protected], [email protected] (S.P. Collins).

0735-6757/$ - see front matter (C) 2009 doi:10.1016/j.ajem.2008.02.025

Introduction

A 60-year old man with nonischemic cardiomyopathy presents to the ED with shortness of breath and the following vital signs: pulse, 90 beats per minute; blood pressure, 170/ 90 mm Hg; respirations, 24 per minute; pulse oximetry, 97% on room air. On evaluation, he has jugular venous distension, an S3 heart sound, and pulmonary edema on his chest radiograph. He was diagnosed as having acute decompen- sated heart failure (ADHF). His electrocardiogram shows no Ischemic changes; his complete blood count, electrolytes,

blood urea nitrogen, and creatinine and cardiac biomarkers are within normal limits. He receives one dose of intravenous furosemide and his Home medications are restarted. After 3 hours he feels significantly better. He has 1 L of urinary output, his second set of cardiac biomarkers are within normal limits, and his repeat blood pressure is 140/80. Should he be admitted to the hospital, managed in an observation unit (OU) or sent home?

With an aging population, improved survival from acute coronary syndromes and improved outpatient treatment, the prevalence of heart failure continues to rise

Fig. 1 Simplified schema for the structure of the decision model for an ED patient with ADHF. @ indicates subtree for inpatient admission; &, subtree for early readmission; !, subtree for 30-day events; #, subtree for inpatient complication.

[1]. Hospitalization accounts for the largest expenditure for care; annual costs are estimated to be $29.6 billion per year, about 3% of the total national health care budget [1-3]. Although the ED is the point of entry for the majority of hospital admissions for ADHF, current guidelines for disposition are based on little or no scientific evidence [4-8]. Patients discharged primarily from the ED have a read- mission rate of 61% at 3 months [9]. As a result, nearly all ED patients diagnosed with ADHF are admitted to the hospital, many for a 4- to 5-day hospital stay [10,11]. Whether admission or ED discharge is the most cost-effective Disposition decision in patients with non-high-risk ED ADHF is unknown.

The advent of OU medicine, under the guidance of emergency physicians, maximizes the clinical applicability of this question to emergency care. Patients traditionally admitted to the hospital for further risk stratification for other medical conditions, such as non-high-risk chest pain, have been safely and efficiently managed in an OU [12]. Preliminary research in ADHF suggests that OU manage- ment is safe and consumes fewer Hospital resources [13-15]. To definitively answer the actual cost-effectiveness of OU management, a large, prospective study is needed. Following non-high risk patients from ED presentation to hospital discharge and through 30 days would be necessary to determine the impact of ADHF management strategies on costs and quality of life.

We used an alternative strategy, development of a decision analytic model, to determine the most cost- effective disposition strategy for ED patients with non- high-risk ADHF.

Methods

Cost-effectiveness model structure

Using the Decision Maker software (2005, Newark, NJ), we constructed a decision analytic model that evaluated the cost-effectiveness of 3 possible ED disposition strategies in a non-high-risk patient with ADHF: (1) discharge home from the ED; (2) OU admission; and (3) inpatient admission.

As shown in Fig. 1, the initial decision node (represented by a square) consists of the 3 strategies described above. After each strategy are round chance nodes that depict the associated risks of death, readmission, and complications. Patients discharged directly from the ED face the risk of early (5-day) Readmission and death (mirroring in-hospital com- plications or death had they been admitted) as well as late readmission and death (mirroring 30-day postdischarge complications and death in those patients initially admitted). Patients admitted to the OU may experience a complication or die in the OU, and if admitted to the hospital, they also may have a hospital complication or die. Those discharged from the OU face the risk of early readmission and death

(mirroring in-hospital complications or death had they been admitted) as well as late readmission and death (mirroring postdischarge complications in those patients initially admitted). Patients admitted to the hospital can experience inpatient complications and death. Patients discharged from the hospital may be rehospitalized for heart failure or may die during the 30-day period after hospitalization. We perform these analyses in accordance with the recommendations of the Panel on Cost-Effectiveness in Health and Medicine by expressing our results in terms of costs, Life expectancy, and marginal cost-effectiveness ratios [16-18]. Marginal cost- effectiveness ratios are presented as both discounted (@ 3%/ y) and nondiscounted. We used a societal perspective for costs and medical outcomes. The time horizon for explicitly modeled events was 30 days, as the impact of this decision on costs and outcomes becomes less clear beyond this point.

Eligibility criteria for cost-effectiveness analysis

Over the past 2 decades, risk factors have been identified for in-hospital complications and death in patients with ADHF [19-28]. Because there is a lack of variables describing the low-risk patient, we chose to identify the variables associated with an increased risk of events and exclude patients with these characteristics from our analysis. Variables associated with a high-risk of morbidity and mortality include Blood urea nitrogen greater than 40 mg/dL, creatinine greater than 2.0 mg/dL, systolic blood pressure less than 100 mm Hg, serum sodium less than 136 mEq/L, and new ischemic electrocardiogram changes. Patients who fulfill any of these criteria are considered high risk and are not eligible for inclusion in this analysis. In addition, we considered patients with positive cardiac biomarkers or requiring an inpatient procedure (dialysis, mechanical ventilation, noninvasive ventilation) to be ineligible for ED discharge and to not be candidates for our cost-effectiveness analysis (CEA) (Table 1). The remainder of ED patients with ADHF were eligible for inclusion.

Table 1 Patients not eligible for introduction to the model because of high-risk features or procedures that would preclude ED discharge

Variable References

High-risk clinical features New ischemic electrocardiogram changes [26,27,60] Systolic blood pressure b100 mm Hg [19,57] Serum sodium b136 mEq/L [22,25,27,61] BUN N40 mg/dL [25,28] Creatinine N2.0 mg/dL [23,28] Positive cardiac biomarkers [62-64] Require inpatient procedure

(continued on next page)

Review of the literature

• • 1. Hospital admissions-complications, death, and readmission

Rates of inpatient complications were obtained from 2 recent large ADHF registries (Table 2) [29-31]. inpatient mortality was 2% to 7%, whereas inpatient complications occurred in 3% to 5% of patients. Although these registries enrolled patients at all levels of risk, our CEA was directed specifically at non-high-risk patients. Therefore, we used conservative estimates of inpatient complications (3%) and mortality (4% in those with complicated admissions and 0.5% in those without complicated admissions). Just as inpatients without complications (0.5%) face a small risk of death, we assumed that 0.5% of patients discharged from the ED and OU die within the first 5 days (depicted as sudden death in Fig. 1).

Readmission after hospitalization is 20% to 30% at 30 days and as high as 50% at 6 months [29,32,33]. Thirty-day mortality rates were based on previous studies that followed inpatients for 30 days after their index admission. Because the majority of these data are based on non-risk-stratified patients (rather than low-risk patients), we chose a more conservative estimate of 30-day mortality (1%) [13,34,35].

• • 1. Emergency department and OU discharges- complications, death, and readmission

Data describing outcomes in patients managed and discharged from the OU or ED are inherently biased and represent an even lower risk population than those considered in our analysis [9,13,36-40]. Currently available data have been able to identify patient characteristics which describe an individual at increased risk of in-hospital and intermediate-term events. Describing the low- or intermedi- ate-risk patient has been much more problematic [41].

Table 2 Parameter estimates for the decision model

Base case value		Range for sensitivity analyses	References
(1) Relative risk of events	2.0	1.0-3.0	[59]
in ED discharges
(2) Relative risk of events	1.5	1.0-3.0	[13,37-39]
in OU discharges
(3) Early readmission/	3%	1%-5%	[29-31]
in-hospital complications
(4) early death/in-hospital	4%	2%-6%	[29-31]
death in complicated
admission
(5) Sudden death as	0.5%	0.0-2.0	[29-31]
outpatient/in-hospital
death in uncomplicated
admission

Diercks et al [42] found that a preserved systolic blood pressure and a normal troponin predicted an ED patient who would be “dischargeable” after an OU stay. Furthermore, Auble et al [43,44] derived and validated a heart failure risk score using a statewide database over 2 different periods. Their complex model suggested that if a blood gas was not available, the most important features to define low risk were BUN, pulse, white blood cell count, and serum sodium. However, even the low-risk cohort had a 2.5% risk of in- hospital death or serious complications and intermediate- term (ie, 5-30 days) events were not captured.

With a lack of low- and intermediate-risk markers available, we took the approach of selecting patients who did not fulfill high-risk features. Therefore, we modeled the risk of outpatient complications and death for patients discharged from the ED and OU to be proportionately larger than that experienced by inpatients through a Relative risk term. More importantly, we explored the assumptions from our theoretical framework using sensitivity analyses to determine which of the assumptions had the most impact on the analysis. Finally, we have linked the ED and OU patients so that as the risk of complications (ie, disease severity) increased in the ED patient considered for discharge, it also increased in the OU patient.

The RR of complications in patients discharged from the ED or OU was assumed to be higher than in inpatients because they were discharged sooner than inpatient admis- sions, minimizing the protective effect of hospitalization (Fig. 1). Furthermore, the limited available data suggest ED or Hospital readmission or mortality for those patients discharged directly from the ED is approximately 2-fold higher (RR = 2.0) than for those discharged after an inpatient admission [9]. Moreover, those patients discharged after 24 hours of OU care have readmission rates that are similar to or slightly higher (RR = 1.5) than inpatient admissions [13]. For example, in patients discharged from the ED, the risk of death or a complication (both early and late) was modeled as the following probability (P):

P death/complicationED discharge

1/4 P death/complicationInpatient admission x RRED discharge

In our base case, we assumed that patients discharged directly from the ED had a 2-fold increased risk (ie, RR = 2.0) of subsequent events, whereas those discharged from the OU had a 1.5-fold increased risk relative to hospitalized patients. Finally, the OU discharge rate in our base case analysis was 75%. All of these assumptions were explored using sensitivity analyses.

Cost and effectiveness of heart failure disposition strategies

We evaluated both the cost and effectiveness of the 3 ED strategies: (1) discharge home; (2) OU management; and (3) inpatient admission. Costs were obtained from several

sources and included hospital and professional cost compo- nents (Table 3).

• • 1. Inpatient costs

Hospital costs for an inpatient admission for ADHF were determined from Medicare reimbursement data for diagnosis related Group (DRG) 127 (Congestive Heart Failure) from fiscal year 2005. Facility costs were based on 2005 national physician fee schedules for evaluation and management-based services and the average length- of-stay for DRG 127. Professional costs for an inpatient admission were level 2 for initial inpatient day 1 and level 2 for subsequent physician visits on days 2 to 5. These costs were also obtained from the national physician fee schedule. We assumed that patients who experienced complications or death would have a longer length of stay and, as a result, would consume more hospital resources. Therefore, we estimated costs for hospitalized patients experiencing complications or death (whether during their index visit or subsequent visit) by assuming a length of stay that was 1 and 2 SDs beyond the mean, respectively.

• • 1. Observation unit and ED costs

The costs of OU visits were based on relative value units from the 2005 national physician fee schedule for profes- sional and facility costs, which distinguishes OU patients who were admitted to the hospital from those who were discharged home. The physician and facility costs of a level 5 ED visit (in those discharged home) were also obtained from the national physician fee schedule.

• • 1. Life expectancy and quality adjustment

We used the declining exponential approximation of life expectancy to determine the life expectancy of patients with heart failure [45,46]. Annual mortality rates (u_ASR) based upon age, sex, and race were calculated from the 2001 United States life tables [47]. Excess mortality due to heart failure (u_HF) was then calculated from large cohort studies of patients with heart failure [48,49]. Total mortality (u_total =

Table 3 Estimates of costs contributing to the CEA

u_ASR + u_HF) was calculated from the combined annual and excess heart failure mortality rates. Patients who survived hospitalization and the 30-day follow-up period were given a life expectancy of 1/u_total, whereas those who died during hospitalization or during follow-up had a life expectancy of 0.

Time spent in the hospital was given a quality adjustment of zero. For instance, if patients were admitted and had an uncomplicated hospital stay, they lost 5/365ths of a quality adjusted life year (QALY) (average length of hospital stay for DRG 127 is 5 days) [50]. A complicated hospital admission lost 9/365ths of a QALY (5 days for the initial stay and an additional 4 days for 1 SD outside the mean length of stay). We present both nondiscounted and discounted results for our base case analysis. Our discounted analysis adjusts for heart failure-related quality of life (quality of well- being index = 0.63) [51] as well as annual heart failure- related expenditures in those patients who survive beyond the time frame of the model (30 days) [52]. We used a

discount rate of 3%.

The cost-effectiveness ratio (CER) is the relationship between the effectiveness gained from a decision and the cost of the decision. The marginal CER (mCER) is the difference in cost-effectiveness as you move from one strategy to the next (ie, from ED discharge to OU admission). The willingness-to-pay threshold is the mCER that one would be willing to pay to move from one strategy to the next.

Assumptions

We made several simplifying assumptions. First, we assumed there was no difference in quality of life between a hospitalization at the index visit vs an admission that occurred during follow-up. Patients experiencing complica- tions incurred added costs and transient loss of quality of life, but if they survived the hospitalization they had the same postdischarge life expectancy as those experiencing uncomplicated hospitalizations. Although the available literature suggests patients with heart failure requiring

Variable	Facility	Physician	Total	Source
Heart failure hospitalization	$5376.00	$336.00	$5712.00	[65] a
OU Discharge	$49.00	$22.00	$71.00	[66] b
OU Admission	$113.00	$45.00	$158.00	[66] b
Cost of ED visit	$116.00	$36.00	$152.00	[66] b
Complication in hospital			$4455.00	AORBOR c
Death in hospital			$8911.00	AORBOR c
Annual long-term cost of heart failure			$6604.00	[52]
a Costs related to heart failure hospitalization were calculated from Medicare reimbursement data for DRG 127 from fiscal year 2005. b Costs related to ED and OU visits were based on relative value units from the national physician fee schedule for professional and facility costs from 2005. Those patients with OU care also received a charge for their ED visit. For example, cost OU discharge indicates cost of OU discharge + cost ED visit; OU admission, patient admitted to hospital after OU stay; OU discharge, patient discharged home after OU stay.

Table 4 Discounted and quality-adjusted results of base case analysis in a 60-year-old man with ADHF (ED discharge RR = 2, OU discharge RR = 1.5)

Strategy Cost (dollars) Effectiveness Marginal cost Marginal effectiveness Marginal cost-effectiveness

(QALY) (dollars) (QALY) (dollars/QALY)

Base case

ED discharge $31 511 2.62

hospitalization are at increased risk of death and read- mission over the subsequent year, we were unable to find data that specifically addressed the 30-day risk after an index hospital stay with a complication [30,53-55]. For this reason, we assumed patients experiencing a complication during hospitalization, while at an increased risk of in- hospital mortality, have a similar risk for outpatient complications and death as those experiencing an uncom- plicated hospital stay.

We also assumed the probability of a complication during hospitalization was the same regardless of whether the patient was from the ED or the OU. Furthermore, a complication occurring in the OU was considered to be equivalent to a complication occurring in the hospital. Finally, we counted 30-day readmissions for heart failure and 30-day deaths as separate events.

Sensitivity analysis

Sensitivity analyses were conducted on all key model parameters. In particular, we anticipated that our results would be sensitive to the RR of early events (readmission and death) and late events (readmission and death) in patients discharged from the ED and OU. We also explored sensitivity analyses on variables that correlate with the underlying acuity of ADHF, including the probability of hospital death and complicated hospital admission, as well as the probability of hospital admission after an OU stay. As these parameters capture the notion of patient selection bias and severity of illness, we have linked the risk of adverse outcomes in ED discharged patients (reflected as early

Table 5 Sensitivity analyses of the RR of complications in those discharged directly from the ED

outpatient death and readmission) to the risk of these events in OU discharged patients.

Results

Base case analysis

We performed our base case analysis on a 60-year-old man lacking any high-risk features of ADHF. This was felt to be representative of many patients who are frequently hospitalized for ADHF. Our base case analysis suggests that OU admission has a reasonable mCER compared to ED discharge ($23 678/life-year gained). Although hospital admission is the most effective strategy (4.56 years), it is also the most costly ($37 621), with a mCER of $246 671/ life-year gained. Emergency department discharge is the cheapest alternative ($33 262), but is the least effective (4.52 years).

Discounted, quality-adjusted results demonstrate de- creased costs and decreased effectiveness for all 3 strategies. Although OU admission remains “cost-effective” in the base case, the mCER has increased to $44 249/QALY in the discounted model (Table 4). Similarly, the mCER of hospital admission has increased to $684 101/QALY.

Sensitivity analysis

All sensitivity analyses were performed using discounted, quality-adjusted costs and effectiveness. Given the lack of

Variable investigated (value)	Cost (dollars)	Effectiveness (QALY)	Marginal cost (dollars)	Marginal effectiveness (QALY)	Marginal cost-effectiveness (dollars/QALY)
RR of early readmission (11.8)
OU Admission	$33 850	2.61
ED Discharge	$33 851	2.56	$1	-0.050	Dominated
Hospital admission	$35 607	2.64	$2175	0.031	$70 802
RR of late readmission (3.7)
OU Admission	$33 533	2.63
ED Discharge	$33 556	2.61	$23	-0.020	Dominated

detailed data describing the risk of subsequent events in those patients discharged directly from the ED and OU, we performed sensitivity analyses exploring the risk of death as well as early and late readmission after ED discharge (RR of readmission within 5 days of ED discharge when compared to in-hospital complications in those admitted to the hospital). This analysis revealed that OU admission dominated the ED discharge strategy (ie, less costly and more effective), if the RR for early readmission exceeded

11.7 corresponding to an absolute risk of early readmission of 36% (Table 5 and Fig. 2). Furthermore, OU admission also dominated ED discharge if the RR of late readmission exceeded 3.6 corresponding to an absolute risk of 74% (Fig. 3). At lower RRs for both early and late readmission, the mCER of OU admission increased, such that below a RR of

1.5 (absolute risk, 4.5%) and 1.8 (absolute risk, 36%), respectively, OU admission cost more than $50 000/QALY. Similarly, an increase in the RR of both early and late death decreased the mCER of OU admission.

The mCER of hospitalization is sensitive to parameters describing the efficacy of the OU strategy in caring for patients with ADHF. For instance, if the RR of early readmission after OU discharge exceeded 1.8 (absolute risk of early readmission, 5.4%) or that of late readmission exceeded 1.6 (absolute risk of 32%), then the mCER of OU admission is greater than $50 000/QALY willingness-to-pay threshold, making it a less reasonable strategy to consider from a societal perspective [56]. Furthermore, if the RR of early death after OU discharge exceeded 2.2 (absolute risk of 0.3%) or that of late death exceeded 1.6 (absolute risk of late death, 2.4%), the mCER of OU admission also exceeded

$50 000/QALY.

We also found that the mCER was sensitive to variables that correlate with the underlying acuity of ADHF. As the probability of inpatient complications increased to above

Fig. 2 Marginal cost-effectiveness ratio as a function of the risk of early readmission to the hospital after ED discharge. The base case is an absolute risk of readmission of 6%.

Fig. 3 Marginal cost-effectiveness ratio as a function of the risk of late readmission to the hospital after ED discharge. The base case is an absolute risk of readmission of 40%.

29%, the mCER of inpatient admission decreased below a societal willingness-to-pay threshold of $50 000/QALY. Finally, as the probability of hospital admission after an OU stay increased beyond 27%, the mCER of OU admission increased above $50 000/QALY. Finally, assumptions with regard to costs of hospitalization, complications, and death were also explored via sensitivity analysis and are displayed in graphical form (Fig. 4). The diagram suggests the RRs of complications after OU and ED discharges have the most impact on the cost-effectiveness of ED decision making.

Limitations

Our analyses are limited by the paucity of data describing outcomes in patients with ADHF after OU and ED discharge. We have explored this uncertainty through sensitivity analyses examining the impact of variations in these parameter values on the overall cost-effectiveness of these strategies. We assumed that patients discharged from the ED or OU would have an increased risk of complications compared to inpatient admissions. This assumption intro- duces a bias against OU management. Even with this bias, OU management has a reasonable mCER. Although there is a possibility that nosocomial complications could make inpatient admission riskier than OU or ED discharge, we felt this was unlikely and did not explore a RR less than 1. A further limitation relates to the assumptions about OU complications and recidivism. Data reported in the literature may be biased by ADHF management expertise encountered at institutions with an OU. This may not be generalizable to other ED and hospital settings.

Another limitation is the assumption that excess mortality related to chronic heart failure does not change after hospitalization for ADHF. The literature suggests that, although most patients return to an asymptomatic baseline after hospital discharge, their overall life expectancy is slightly altered after an acute exacerbation. However, it is

Fig. 4 Deterministic sensitivity analysis for base case. Each parameter is varied across its clinically relevant ranges. ?Beyond an RR of 2.5 for late death after OU discharge, ED discharge becomes the dominant strategy.

unlikely that there are significant long-term differences in ADHF-related excess mortality in 30-day survivors who are discharged home from the ED compared to those who were hospitalized. Therefore this assumption should not affect the marginal effectiveness.

A final limitation in our analysis is the assumption regarding relative Hospitalization costs in patients who experience complications and death. As the inpatient mortality and complication rates are 0.5% to 4% and 3%, respectively, we felt that it was reasonable to estimate the costs of a hospitalization resulting in death or a prolonged complication to be based upon a length of stay 1 and 2 SDs, respectively, beyond the mean.

Discussion

To our knowledge, this is the first CEA of ED patients presenting with ADHF. Our results suggest that OU admission is a cost-effective strategy in ED patients with non-high-risk ADHF. However, as our assumptions are varied, specifically our risk of complications, the marginal cost-effectiveness is impacted. As the risk of complications increases for patients discharged directly from the ED, the mCER of OU admission becomes even less, making it a more attractive option. However, as the risk of complications (5.4% early readmission, 32% late readmission) in those discharged from the OU increases, the mCER of OU admission increases above a societal willingness-to-pay threshold of $50 000/QALY. As the probability of admission

after an OU stay increases, the mCER of the OU strategy increases as well. Fig. 4 suggests ADHF disease severity and complication rates (readmission and death), rather than costs, have the biggest impact on the cost-effectiveness of ED Disposition decisions. The analysis is complicated by the absence of a unified model that captures the underlying severity of illness for these patients that would better link the risk of complications or readmission across all 3 strategies. Patients presenting to the ED with ADHF have significant Short-term morbidity and mortality after hospital discharge. We currently lack prospectively derived decision rules identifying a subgroup of patients at sufficiently low risk who could be considered for discharge from the ED. As a result, the majority of ED presentations result in hospital admission. Observation unit management is a reasonable alternative to inpatient admission; patients receive concurrent risk stratification and treatment, further delineating their Need for hospitalization. Patient education and determination of readiness for discharge (social situation, follow-up visit) also can occur while the patient is being managed in the OU. This analysis provides further evidence supporting OU manage- ment of patients with ADHF as a safe and efficient alternative

to immediate ED discharge or hospitalization [13,38].

We await future prospective data that will accurately categorize ED patients with ADHF as being at low-, medium-, or high risk of subsequent adverse events. Although many retrospective attempts have been undertaken that accurately describe the high-risk patient, prospective analyses that describe the medium- and low-risk patient have yet to be completed [19,25-28,57]. The data being captured as part of an ongoing multicenter prospective ED

investigation will be used to better describe the cost- effectiveness of ED decision-making strategies [58].

In conclusion, our analysis suggests that OU management of ED patients presenting with ADHF represents a reason- able expenditure of health care dollars, having a mCER below the generally accepted societal willingness-to-pay threshold of $50 000/QALY. As the RR of OU complications and readmission increases, as would be the case in a more severely ill and higher risk patient, the mCER of the OU strategy increases, making it a less appealing strategy.

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