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Adult Circulatory Support

The In-Hospital Cost of Ventricular Assist Device Therapy: Implications for Patient Selection

Iyengar, Amit*; Kwon, Oh Jin†; Tamrat, Msgana†; Salimbangon, Anthony†; Satou, Nancy†; Benharash, Peyman†; Ardehali, Abbas†; Shemin, Richard J.†; Kwon, Murray H.†

Author Information

From the *David Geffen School of Medicine, UCLA Medical Center, Los Angeles, California; and †Division of Cardiac Surgery, UCLA Medical Center, Los Angeles, California.

Disclosure: The authors have no conflicts of interest to report.

Correspondence: Murray H. Kwon, Department of Surgery, David Geffen School of Medicine, UCLA Medical Center, CHS 62–229, Le Conte Avenue, Los Angeles, CA 90095. Email: [email protected].

doi: 10.1097/MAT.0000000000000545
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Abstract

In the United States, roughly 700,000 new patients are diagnosed with heart failure each year.1 It is estimated that heart failure costs our healthcare system approximately $32 billion dollars per annum and this is expected to double by 2030.2 Although orthotopic heart transplantation remains the gold standard for the treatment of end-stage heart failure, the shortage of available donor organs limits this therapy to very select patients.3

Mechanical support of the circulation with the use of ventricular assist devices (VADs) is increasingly utilized for short-term circulatory support in patients with acute decompensation or for long-term support as either a bridge to heart transplantation in eligible patients or as an alternative in transplant-ineligible patients (destination therapy).4,5 Despite important clinical gains with VADs, the high financial cost of VAD care remains particularly worrisome. Ventricular assist device therapy is associated with several components that contribute to cost, including costly complications such as bleeding and infection that require prolonged hospital stays and the fixed costs of individual VADs, which can cost >$100,000 alone.4,6,7 Over the past 10 years, significant clinical achievements have been made in the improvement of device technology, patient selection, and postoperative management, which have led to decreased costs of care. Despite these continuous clinical improvements, mean costs per quality-adjusted years are still estimated at approximately $400,000.7 To date, no study has found that VAD therapy meets commonly accepted willingness-to-pay criteria per survival gained.8–17 Bridging to transplant with a VAD has achieved excellent clinical results when compared with direct heart transplantation, but it still significantly adds to cost and has not been shown to be cost-effective.8–12 Likewise, the use of VAD destination therapy prolongs survival, but it is not economical for the incremental survival gained.13–17

With these issues in mind, it is of prime importance to continuously investigate the costs associated with VAD care. Few studies have identified key factors such as hospitalization length of stay and postoperative complications as significant drivers of cost.9,17,18 However, continuously monitoring how patient factors contribute to cost is important as the quality of VAD care improves over time. The purpose of this study was to model total hospital costs of VAD therapy in the modern era, to identify strategies to reduce VAD costs and improve cost-effectiveness.

Methods

Study Design

This study was a retrospective analysis of all adult patients (age ≥ 18 years) who received a VAD between January 2013 and December 2014. Baseline patient demographic factors were queried from our institution’s prospectively maintained VAD database. Patient cost information was queried from our cardiac surgery division’s finance department. This study was reviewed and approved by the institutional review board at UCLA.

Patient Selection

Ventricular assist device therapy was offered to patients with Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) level 1 or 2 heart failure who were in imminent danger of worsening multiorgan failure despite optimal medical management. Device selection was made by a multidisciplinary team that included a cardiac surgeon and cardiologist. For patients with isolated left-sided failure, either the axial flow HeartMate II (Thoratec Corporation, Pleasanton, CA) or the centrifugal HeartWare HVAD pump (HeartWare, Framingham, MA) was utilized, whereas the CentriMag centrifugal pump (Thoratec) was used for temporary right-sided support when necessary. The TandemHeart (CardiacAssist, Pittsburgh, PA) was used to select patients with isolated right-sided heart failure. For patients presenting with a need for durable biventricular support, Thoratec paracorporeal VADs (Thoratec) were used.

Data End Points

Preoperative data queried from our institution’s Society of Thoracic Surgeons database included the following: demographic factors, urgent/emergent status, cardiac disease etiology, use of preoperative extracorporeal membrane oxygenation (ECMO), type of VAD support (univentricular versus biventricular support [BiVAD]), and hospital length of stay.

Each patient’s total hospital cost information was collected starting from their hospital admission date before their VAD implantation surgery and extending until their discharge. Our institution’s financial policy prevents the presentation of actual cost data to ensure patient privacy. Thus, total hospital cost was normalized to a z score. Normalized total hospital cost during this time period was used as the primary outcome measure in this study.

Statistical Analysis

Perioperative characteristics were expressed as mean ± standard deviation for continuous variables or frequency and percentage of population for categorical variables. Total hospital cost was normalized for all patients to a z score using the following calculation:

Univariate linear regression was performed to determine relationships between all patient variables and normalized total cost. All variables with p < 0.10 were subsequently entered into a multivariable, backwards step-wise elimination model. Comparisons of normalized total cost between categorical variables were performed using the Mann–Whitney U test. All statistical analyses were performed using SPSS 19 software (IBM, Armonk, NY). A p value <0.05 was considered statistically significant.

Results

During the study period, 42 patients received VAD therapy at our center (Table 1). The most common etiology of cardiac disease was ischemic disease (67%), followed by nonischemic dilated cardiomyopathy (10%). Twenty-two patients (52%) received isolated left ventricular support, whereas 19 patients (45%) received biventricular support with concurrent left- and right-sided devices. Of these, five (12%) received bilateral Thoratec PVADs, whereas the remaining 14 (33%) received a durable left-sided device (HeartMate II, HeartWare) and a right-sided CentriMag. Eleven patients (26%) had private insurance and 15 (36%) had Medicare coverage. The remaining 16 patients (38%) had other payors such as Medicaid or other government-sponsored insurance programs.

T1
Table 1.:
Preoperative Demographics

On univariate linear regression, body mass index, biventricular support, time between VAD implantation and discharge, and total hospital length of stay were all significantly associated with increased hospital costs (Table 2; all p < 0.05). The highest R2 value was observed in time between VAD implantation and discharge, which explains ~77% of the observed variance in total costs. Importantly, comorbidities such as preoperative ECMO did not achieve statistical significance, with the exception of biventricular support (p = 0.002).

T2
Table 2.:
Univariate Linear Regression Analysis

After step-wise elimination, only two significant variables remained in the model: biventricular support and time between VAD implantation and discharge (Table 3; both p ≤ 0.001). Overall, the multivariable model achieved an R2 = 0.831, indicating excellent predictive power. The formula for normalized total hospital costs becomes as follows:

T3
Table 3.:
Stepwise-Elimination Multivariable Linear Regression Analysis

where BiVAD equals 0 or 1 if the patient requires univentricular or biventricular support, respectively, and post-VAD implant time is measured in days.

With this formula in mind, we sought to evaluate different payment scenarios to estimate our program’s profitability. In a patient with solely public insurance and no other source of payment, any costs not covered by public programs would be absorbed by the hospital. For each hospitalization, the Centers for Medicare and Medicaid Services (CMS) allocate payments for each patient according to their diagnosis via a grouping system known as the Medicare Severity Diagnosis Related Group (MS-DRG). Most VAD patients are coded under MS-DRG 001 “Heart transplant or implant of heart assist system with major complication or co-morbid condition.” At an urban, tertiary care teaching hospital, the MS-DRG 001 payment in 2014 was approximately $225,191.19 Using our patient distribution, this corresponds to a z score of −0.92453. Assuming no other payment source for each patient, substituting this value into the model, our program profits from Medicare patients under the following conditions:

Figure 1 illustrates graphs of hospital cost for both univentricular (Figure 1A) and biventricular (Figure 1B) patients, with the estimated MS-DRG 001 value shown for reference.

F1
Figure 1.:
Cost vs. time between VAD implantation and discharge among isolated LVAD patients (A) and BiVAD patients (B). BiVAD, biventricular support; LVAD, left ventricular assist device; VAD, ventricular assist device.

Discussion

This study was undertaken to model total hospital costs associated with VAD therapy at our center and determine patient factors associated with higher costs. On multivariable analysis, use of biventricular support and hospital stay post-VAD implantation were most predictive, together explaining 83% of the variance in total hospital costs.

The relationship between length of stay (particularly intensive care unit stay) and cost is well described in many patient populations.9,17,18,20 In a large, retrospective analysis of data from the Healthcare Cost and Utilization Project in 2012, Skinner et al.21 demonstrated that among patients hospitalized for ambulatory-care-sensitive conditions, length of stay is closely associated with total hospital costs, and additional chronic conditions add to this cost by extending the total length of stay. In VAD patients, the introduction of continuous flow devices and improvements in postoperative management has decreased VAD costs over time and mirrored decreases in falling hospital length of stay.22,23 Miller et al.24 reported on 23 patients who received a Heartmate XVE in 2003–2004 and compared their results to the Randomized Evaluation of Mechanical Assistance for the Treatment of Congestive Heart Failure (REMATCH) trial from 2001. They demonstrated a 40% decrease in average costs in their cohort, with a concomitant 25% decrease in average length of stay post-VAD implantation. Slaughter et al.9 reported on cost data from the HeartMate II Destination Therapy Trial (2005–2007) and demonstrated that postoperative bleeding, respiratory failure, and infections after VAD surgery were associated with incrementally increased costs of $20,000–$50,000. Minimizing postoperative complications shortens length of stay and is a likely strategy to reduce VAD programs costs. Murray et al.25 report that hospital length of stay, readmission rates, and total costs were all significantly reduced after the introduction of a multidisciplinary VAD care team comprised of cardiac surgeons, cardiologists, and several ancillary staff. Their team focused on early patient education, physical rehabilitation, and nutritional assessment, and their success highlights the importance of multidisciplinary care for both improved outcomes and lower costs.25

Importantly, no preoperative comorbidity examined in this study was predictive of higher costs. Although comorbidities such as preoperative ECMO undoubtedly carry cost, these appear to be dwarfed in most cases by the costs associated with VAD implantation and postoperative care. Cotts et al.26 performed an analysis of the INTERMACS registry between 2006 and 2010 and found that a multivariable model of preoperative demographic variables only explained 12% of the variance in postimplantation hospital lengths of stay. Taken together, these findings may have implications for patient selection, in that preoperative conditions should be considered as cost drivers only insofar as their propensity to prolong a patients’ postoperative course or increase postoperative complications exists. Otherwise, patients’ comorbidities should not negatively bias programs because of cost concerns.

The use of biventricular support has not been reported previously as a factor increasing costs, but follows from the increased fixed costs associated with implanting an extra device. Additionally, patients requiring biventricular support are sicker and are reported to have increased rate of bleeding, infections, neurologic events, and device failure, all contributing to increased cost.27 Importantly, this finding was significant when controlling for length of stay in a multivariable model, suggesting BiVAD usage adds to cost via a mechanism independent of increased hospital stay. Several risk scores for the development of right ventricle (RV) failure and requirement of BiVAD support have been proposed, and it include obesity, previous cardiac surgery, preoperative medications, hypotension, inotrope requirements, serum bilirubin and creatinine, intra-aortic balloon pump use, and preoperative RV dysfunction.28–30 This may, in part, explain our observation of increased body mass index being a risk factor for higher cost only in our univariate analysis. These risk scores may prove helpful in further characterizing costs amongst VAD patients.

Comparing our derived linear model to an estimate of the MS-DRG, we derived a target postimplant length of stay of ~14 days to profit from each VAD case. As a majority of patients accrued a cost higher than this value, this suggests a number of findings.

First, a successful VAD program requires a diverse mix of payors aside from Medicare. Although public insurance is not a contraindication for receiving a VAD, patients with private insurance providers and correspondingly higher payment rates are necessary to account for losses associated with Medicare patients and yield an overall profitable program. Rajagopalan et al.31 reports on the successful use of left ventricular assist devices in patients without a pre-existing insurance plan, many of whom were subsequently able to receive Medicaid and retroactively cover some of their previous costs. The authors’ efforts in actively seeking coverage for these patients are highly commendable and highlight active steps that can be taken to cover patients. However, in their report, three patients were not covered in a timely manner and had surgery costs that could not be reimbursed.31 These costs would have to be offset by other patients with other payor systems to yield a profitable program.

Second, this model suggests that higher MS-DRG values may be necessary if we as a society choose to allocate VADs to patients without consideration of insurance. The extra costs associated with development and implementation of new technologies are not factored into the DRG calculation, and thus, it can lead to deficits in the introductory period of new programs.32,33

A major limitation of this study is that only index hospitalization costs were available, and we were unable to examine costs related to VAD care after discharge. Mishra et al.32 reported on comprehensive 1 year costs associated with VAD care at their center and highlighted that postoperative readmissions, complications, and device changes all significantly contributed to cost. However, their group reports that for each patient, most of the cost is accrued in the index hospitalization period.32 Furthermore, our study was limited by our institution’s policy requiring that explicit financial costs not be presented, and thus, our cost information was normalized. Normalized values are not directly translatable to other centers; however, the DRG cost comparison allows for a reference when evaluating our normalized data. This study may also be underpowered to adequately assess the effects of multiple variables on cost and selection bias because of careful evaluation of VAD candidates by our multidisciplinary VAD team, which may also confound any actual effects present. Finally, this study carries limitations inherent in the retrospective, single-center design. Thus, larger prospective studies are clearly warranted to accurately identify patient characteristics linked to higher overall costs.

In summary, biventricular support and postimplant length of stay significantly correlate with increased total costs in VAD patients. Costs are independent of preoperative comorbidities including the use of preoperative ECMO. Strategies should be tailored toward decreasing postoperative length of stay and diversifying payors while not necessarily discriminating against patients with significant comorbidities to maintain a profitable, sustainable VAD program.

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Keywords:

costs; ventricular assist device; patient selection

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