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Department of Anesthesiology, University Health Network, Toronto, Ontario, CanadaToronto Lung Transplant Program, University Health Network, Toronto, Ontario, CanadaInstitute of Health Policy, Management and Evaluation, Dalla Lana School for Public Health, University of Toronto, Toronto, Ontario, Canada
Toronto Lung Transplant Program, University Health Network, Toronto, Ontario, CanadaDivision of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, Ontario, CanadaToronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
Institute of Health Policy, Management and Evaluation, Dalla Lana School for Public Health, University of Toronto, Toronto, Ontario, CanadaDivision of Nephrology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
Toronto Lung Transplant Program, University Health Network, Toronto, Ontario, CanadaDivision of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, Ontario, CanadaToronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
Toronto Lung Transplant Program, University Health Network, Toronto, Ontario, CanadaToronto General Hospital Research Institute, University Health Network, Toronto, Ontario, CanadaInterdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
Toronto Lung Transplant Program, University Health Network, Toronto, Ontario, CanadaDivision of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, Ontario, CanadaToronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
Institute of Health Policy, Management and Evaluation, Dalla Lana School for Public Health, University of Toronto, Toronto, Ontario, CanadaInterdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
Institute of Health Policy, Management and Evaluation, Dalla Lana School for Public Health, University of Toronto, Toronto, Ontario, CanadaThe Hospital for Sick Children, Toronto, Ontario, Canada
Institute of Health Policy, Management and Evaluation, Dalla Lana School for Public Health, University of Toronto, Toronto, Ontario, CanadaToronto General Hospital Research Institute, University Health Network, Toronto, Ontario, CanadaICES, Ontario, CanadaPublic Health Ontario, Ontario, Canada
Ex-vivo lung perfusion (EVLP) has improved organ utilization for lung transplantation, but it is not yet known whether the benefits of this technology offset its additional costs. We compared the institutional costs of lung transplantation before vs after EVLP was available to identify predictors of costs and determine the health-economic impact of EVLP.
Methods
We performed a retrospective, before-after, propensity-score weighted cohort study of patients wait-listed for lung transplant at University Health Network (UHN) in Ontario, Canada, between January 2005 and December 2019 using institutional administrative data. We compared costs, in 2019 Canadian Dollars ($), between patients referred for transplant before EVLP was available (Pre-EVLP) to after (Modern EVLP). Cumulative costs were estimated using a novel application of multistate survival models. Predictors of costs were identified using weighted log-gamma generalized linear regression.
Results
A total of 1,199 patients met inclusion criteria (352 Pre-EVLP; 847 Modern EVLP). Mean total costs for the transplant hospitalization were $111,878 ($94,123-$130,767) in the Pre-EVLP era and $110,969 ($87,714-$136,000) in the Modern EVLP era. Cumulative five-year costs since referral were $278,777 ($82,575-$298,135) in the Pre-EVLP era and $293,680 ($252,832-$317,599) in the Modern EVLP era. We observed faster progression to transplantation when EVLP was available. EVLP availability was not a predictor of waitlist (cost ratio [CR] 1.04 [0.81-1.37]; p = 0.354) or transplant costs (CR 1.02 [0.80-1.29]; p = 0.425) but was associated with lower costs during posttransplant years 1&2 (CR 0.75 [0.58-1.06]; p = 0.05) and posttransplant years 3+ (CR 0.43 [0.26-0.74]; p = 0.001).
Conclusions
At our center, EVLP availability was associated with faster progression to transplantation at no significant marginal cost.
Canadian Institute for Health Information /Institut canadien d'information sur la santé. Annual Statistics on Organ Replacement in Canada: Dialysis, Transplantation and Donation, 2010 to 2019. 2020:1-6.
This organ scarcity renders lung transplantation an interesting health economic case: transplant programs aim to maximize population health using limited available organs.
Health economic evaluation measures the value added by a technology by assessing costs and outcomes at the population level. Economic evaluation helps to quantify the health gained by transplantation and related technologies to facilitate judicious resource allocation, but at present, insufficient evidence exists for this purpose.
Ex-vivo lung perfusion (EVLP) is a technology that may help relieve resource constraints and improve organ availability by sustaining potentially-useable donor lungs outside the body before transplant.
EVLP is a major change in the practice of lung transplantation: between 69% and 79% of conventionally unusable organs have been successfully transplanted after EVLP, corresponding to a 30% increase in transplants at these centers.
Clinical outcomes after transplantation of EVLP-treated organs are promising, with generally no difference in hospital length-of-stay, graft dysfunction, or mortality between patients receiving EVLP-treated vs conventionally-treated organs.
Health systems are facing challenging decisions about how to incorporate EVLP. Concerns about the expense of EVLP impede its uptake, but the benefit of adding EVLP to lung transplantation programs may offset the additional costs required. Economic evaluation of lung transplant with, vs without, EVLP is crucial for evidence-informed allocation of healthcare resources to this technology.
Our primary objective was to compare the costs of lung transplantation, from the hospital perspective, of adults who were referred for transplant in Ontario before, vs after, EVLP was clinically available. A secondary objective was to identify predictors of costs, focusing on EVLP-availability.
Methods
Study overview
We performed a retrospective, before-after cohort study of patients wait-listed for first lung transplant in the Toronto Lung Transplant Program, University Health Network (UHN) in Ontario, Canada, between January 1, 2005 and December 1, 2019. UHN is the only lung transplant program in Ontario, 1 of 4 in Canada, and is the largest in the world. This study received institutional ethics approval (REB #20-5888). We adhered to the STROBE and RECORD reporting guidelines.
Clinical data was derived from the Organ Transplant Tracking Record, the Electronic Patient Record, and Toronto Lung Transplant Program Databases at UHN. Resource use and costs were accessed from the UHN's cost-coding department. Records were linked deterministically by medical record number.
Population
We included adults who were wait-listed for first lung transplant in Ontario during the study period. We excluded patients who were under 16 years old at referral, referred for combined multiorgan transplant or retransplant, or referred but not wait-listed (incomplete or inappropriate referrals).
Exposure
Our exposure variable was EVLP availability at the time of referral. The introduction of EVLP into clinical practice represented a system-level change, impacting patients awaiting transplant as well as those undergoing the procedure. A comparison of recipients of EVLP-treated vs cold-static preservation alone-treated organs would not capture the system-level effect of this technology, nor would it allow for analysis of pretransplant outcomes. We therefore stratified patients into “eras” based on referral date: pre-EVLP (2005-2008), early (2009-2012), and modern (2013-2019). The early era was thought to predominantly reflect the transition and consequences of EVLP implementation and was therefore excluded from analysis. To minimize misclassification, outcomes in the pre-EVLP era were censored on January 1, 2013. Where possible, we further stratified the modern era into recipients of lungs managed by cold-static preservation only (No EVLP) vs recipients of EVLP-treated lungs (EVLP). The study period was ended on December 1, 2019, because of the COVID-19 pandemic. All EVLP cases were performed using the Toronto EVLP protocol.
Observations were pieced into clinically meaningful, sequential “phases”, defined by event dates: referral, wait-list, transplant hospitalization, posttransplant years 1 & 2, and posttransplant years 3+ (Figure 1). The posttransplant period was divided into 2 phases (years 1 & 2, years 3+) because posttransplant surveillance at our center involves frequent evaluation for the first 2 postoperative years, with decreased intensity of follow-up thereafter.
Figure 1Schematic of multistate model. For each patient in the study, observations were pieced into clinically meaningful phases: referral, wait-list, transplant hospitalization, posttransplant years 1 &2, and posttransplant years 3+. At any point during the study, patients could be transitioned to end-of-life care and die. These phases of care exist along a continuum, and transition from one to the next occurred on specific event dates. We modeled this continuum as a k-progressive multistate model, with the structure shown in this figure. Transition intensity () indicates the instantaneous hazard of progression between states.
To account for censoring between phases and higher costs around end-of-life, we organized costs accrued during the final days-of-life into separate perimortem phases. Perimortem phase durations were determined empirically by segmented regression of log-adjusted costs for the final year-of-life, stratified by EVLP era and the phase occupied at the time of death.
Chan BC-F, Cadarette SM, Wodchis WP, Krahn MD, Mittmann N. The lifetime cost of spinal cord injury in Ontario, Canada: a population-based study from the perspective of the public health care payer. 2019:1-11. doi:10.1080/10790268.2018.1486622.
To account for baseline covariates differences across eras, we performed inverse probability of treatment weighted (IPTW) analysis. Weights were calculated using propensity scores derived from a generalized boosted model accounting for age at referral, sex, ABO blood group, smoking history, hypertension, diabetes, estimated glomerular filtration rate (eGFR), transplantation from home vs hospital, and pretransplant life-support requirement.
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.
The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments.
Variables were selected a priori for their known or anticipated association with transplant outcomes. We did not adjust for donor organ characteristics because they are along the causal pathway for the associations of interest. Balance was assessed using density plots of propensity scores before vs after weighting, and standardized mean difference and Kolmogorov-Smirnov statistics for pairwise comparisons.
(Supplemental Figures 1 and 2) Weighted analyses were performed using the Average Treatment effect on the Treated (ATT) estimand, which allowed us to draw inferences about the consequence of withholding EVLP availability from those in the modern era, thus better accounting for selection-maturation bias.
Our primary outcomes were the phase-specific and cumulative costs for lung transplantation before vs after EVLP was available. Economic analyses were conducted from the hospital perspective. Consistent with this perspective, we included direct patient and program costs borne by the transplant institution, including labor and supply costs pertaining to EVLP. These costs did not include provincially-covered physician costs, costs for hospitalization at outside centers, costs for provincial transplant coordination, nor out-of-pocket and indirect costs borne by patients. The rationale for a hospital perspective was 3-fold: (1) lung transplantation is a centralized service in Ontario, with the majority of adult lung transplantation-related health resource use coordinated by, and accessed at, a single institution, so the institutional perspective would most directly capture these transplantation-specific costs; (2) EVLP implementation is primarily the decision of institutional stakeholders and administrators, so the hospital perspective would provide these decision-makers with directly relevant information; (3) UHN receives a high volume of referrals from jurisdictions outside of Ontario, representing patients who are not covered under provincial health insurance coverage, so the hospital perspective would capture the costs for these patients that would not be captured by analysis from the provincial perspective. All costs were inflated to 2019 Canadian Dollars ($) using the Consumer Price Index for healthcare.
Government of Canada, Statistics Canada. Consumer Price Index, annual average, not seasonally adjusted. 2020. doi:https://doi.org/10.25318/1810000501-eng.
Intensive care unit (ICU) costs represented expenditure paid out of the hospital ICU's budget; costs accrued by ICU patients but paid from other budgets were captured in estimates for total, but not ICU, costs. The cost of EVLP was corrected to account for the cost of EVLP cases that were declined for transplant. IPTW-weighted means for phase-specific total and component costs were calculated, with 95% confidence intervals (95% CI) derived from 1000 bootstrap iterations.
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.
Manca A, Austin PC. Using propensity score methods to analyse individual patient level cost effectiveness data from observational studies. yorkacuk. 2008.
We developed a novel approach to estimate cumulative costs from referral to a 5-year time-horizon. Typically, cumulative cost estimation using phase-based costs involves projection of lifetime survival duration using parametric survival regression, over which cumulative costs are summed. Phase durations in conventional analyses are determined empirically at the population-level using piecewise linear regression.
Chan BC-F, Cadarette SM, Wodchis WP, Krahn MD, Mittmann N. The lifetime cost of spinal cord injury in Ontario, Canada: a population-based study from the perspective of the public health care payer. 2019:1-11. doi:10.1080/10790268.2018.1486622.
A limitation of this approach is that phases are not bounded by an individual's event dates (i.e., a phase may be “days 0-30 from referral” rather than the period between referral and wait-list entry dates). To overcome this limitation, our novel phase-based costing methodology employs multistate modeling. First, we constructed an IPTW-weighted multistate model of the phases between referral and death using individual-level data.
(Figure 1) Using this model, we estimated the expected prevalence in each phase (state-occupancy probabilities) at 10-day intervals up to a 5-year time-horizon using the Landmark Aalen-Johansen estimator.
Cumulative costs were then calculated by multiplying these state-occupancy probabilities by the mean 10-day cost for each phase, and then summing those 10-day costs up to the time-horizon
Chan BC-F, Cadarette SM, Wodchis WP, Krahn MD, Mittmann N. The lifetime cost of spinal cord injury in Ontario, Canada: a population-based study from the perspective of the public health care payer. 2019:1-11. doi:10.1080/10790268.2018.1486622.
; 95% CI were derived from 2000 bootstrap iterations.
To confirm that differences in costs between eras were due to EVLP availability, and not maturation or history biases, we performed an interrupted time-series analysis.
A secondary objective of this study was to identify predictors of costs. We constructed multivariable, IPTW-weighted log-gamma generalized linear regressions to estimate the effect of EVLP era, primary diagnosis (Table S1), single vs bilateral transplant, donor type (donation after circulatory death (DCD) vs donation after neurologically defined death (NDD)), extended vs standard-criteria donor, waitlist duration (per-day), posttransplant mechanical ventilation >72 hours, and chronic lung allograft dysfunction (CLAD) on phase-specific costs.
Ninety-five percent CI were constructed using 1000 bootstrap replicates. One-tailed nonparametric p-values were estimated as the probability of sampling bootstrapped regression coefficients equal to, or more extreme than, the nil-effect value.
Statistical analysis
Analysis of variance (ANOVA) and chi-square tests were used for unadjusted descriptive analyses of continuous and categorical variables, respectively. All analyses were performed in R (R-project, ver. 4.0.1), with a 2-sided level of significance of 0.05 unless otherwise specified.
We performed sensitivity analyses comparing recipients of EVLP-treated organs to recipients of cold-static preserved (non-EVLP) organs (Figures S4-6 & Table S2).
Results
Patient characteristics
A total of 1,199 patients met the inclusion criteria: 352 were referred during the pre-EVLP era and 847 were referred during the modern era. In the modern era, 755 patients received an organ, 263 (35%) of whom received an EVLP-treated lung. Fewer patients in the modern era experienced posttransplant mechanical ventilation >72 hours (287 [38%] vs 133 [47%]; p = 0.029).
In unadjusted analysis, patients in the modern era tended to be older (56 ±14 years vs 51 ±14 years; p < 0.001), and greater proportions of patients in the modern era had a smoking history (498 [59%] vs 172 [49%]; p = 0.002) or required pretransplant life-support (198 [24%] vs 30 [9%], p < 0.001). A larger proportion of patients in the modern era were status 3 (high) urgency (100 [12%] vs 3 [1%]; p < 0.001). We observed relatively more patients with restrictive lung disease, and fewer with suppurative disease, in the modern era. However, because the overall number of patients in the modern era increased, this observation may be due to increased referral of patients with restrictive disease rather than a relative decrease in enrollment of patients with suppurative disease. These results suggest that patient selection in the modern era entertained wait-list entry of more complex patients than in earlier eras. (Table 1).
Table 1Description of Study Cohort
Waitlist
Transplant
Posttransplant
Pre-EVLP
Modern era (No EVLP)
Modern era (EVLP)
p-value
Pre-EVLP
Modern era (No EVLP)
Modern era (EVLP)
p-value
Pre-EVLP
Modern era (No EVLP)
Modern era (EVLP)
p-value
Number of patients
(N = 352)
(N = 584)
(N = 263)
—
(N = 285)
(N = 492)
(N = 263)
—
(N = 279)
(N = 475)
(N = 258)
—
Age
51.4 (13.5)
55.1 (14.0)
57.4 (12.1)
<0.001
50.1 (13.8)
54.5 (14.2)
57.4 (12.1)
<0.001
50.0 (13.7)
54.5 (14.2)
57.3 (12.2)
<0.001
Female
149 (42.3%)
262 (44.9%)
88 (33.5%)
0.007
113 (39.6%)
212 (43.1%)
88 (33.5%)
0.036
110 (39.4%)
207 (43.6%)
84 (32.6%)
0.014
Weight (kg)
68.6 (15.9)
69.4 (16.3)
73.4 (17.1)
<0.001
68.4 (16.4)
69.5 (16.5)
73.4 (17.1)
<0.001
68.5 (16.4)
69.3 (16.5)
73.6 (17.1)
<0.001
Height (cm)
167 (9.30)
166 (10.1)
169 (9.58)
<0.001
168 (9.20)
167 (10.1)
169 (9.58)
<0.001
168 (9.16)
167 (10.1)
169 (9.55)
<0.001
Underweight BMI
37 (10.5%)
49 (8.4%)
16 (6.1%)
0.149
35 (12.3%)
40 (8.1%)
16 (6.1%)
0.03
35 (12.5%)
40 (8.4%)
16 (6.2%)
0.031
Healthy BMI
151 (42.9%)
253 (43.3%)
97 (36.9%)
0.188
128 (44.9%)
224 (45.5%)
97 (36.9%)
0.058
124 (44.4%)
216 (45.5%)
95 (36.8%)
0.066
Overweight BMI
104 (29.5%)
178 (30.5%)
100 (38.0%)
0.05
76 (26.7%)
145 (29.5%)
100 (38.0%)
0.01
75 (26.9%)
140 (29.5%)
97 (37.6%)
0.018
Obese BMI
54 (15.3%)
101 (17.3%)
50 (19.0%)
0.481
46 (16.1%)
82 (16.7%)
50 (19.0%)
0.629
45 (16.1%)
78 (16.4%)
50 (19.4%)
0.526
ABO A
148 (42.0%)
219 (37.5%)
100 (38.0%)
0.362
120 (42.1%)
185 (37.6%)
100 (38.0%)
0.435
117 (41.9%)
180 (37.9%)
99 (38.4%)
0.525
ABO AB
11 (3.1%)
21 (3.6%)
9 (3.4%)
0.929
9 (3.2%)
19 (3.9%)
9 (3.4%)
0.87
9 (3.2%)
18 (3.8%)
9 (3.5%)
0.92
ABO B
44 (12.5%)
76 (13.0%)
21 (8.0%)
0.096
35 (12.3%)
70 (14.2%)
21 (8.0%)
0.043
35 (12.5%)
69 (14.5%)
21 (8.1%)
0.043
ABO O
149 (42.3%)
268 (45.9%)
133 (50.6%)
0.128
121 (42.5%)
218 (44.3%)
133 (50.6%)
0.131
118 (42.3%)
208 (43.8%)
129 (50.0%)
0.156
Obstructive Disease
103 (29.3%)
140 (24.0%)
81 (30.8%)
0.062
95 (33.3%)
126 (25.6%)
81 (30.8%)
0.056
92 (33.0%)
122 (25.7%)
79 (30.6%)
0.082
Restrictive Disease
160 (45.5%)
316 (54.1%)
146 (55.5%)
0.015
114 (40.0%)
258 (52.4%)
146 (55.5%)
<0.001
112 (40.1%)
249 (52.4%)
144 (55.8%)
<0.001
Vascular Disease
23 (6.5%)
42 (7.2%)
10 (3.8%)
0.164
15 (5.3%)
32 (6.5%)
10 (3.8%)
0.294
15 (5.4%)
31 (6.5%)
10 (3.9%)
0.322
Suppurative Disease
60 (17.0%)
78 (13.4%)
24 (9.1%)
0.017
57 (20.0%)
69 (14.0%)
24 (9.1%)
0.001
56 (20.1%)
67 (14.1%)
23 (8.9%)
0.001
Other diagnosis
6 (1.7%)
8 (1.4%)
NR
0.598
NR
7 (1.4%)
NR
0.71
NR
6 (1.3%)
NR
0.763
Total Lung Capacity (L)
5.54 (2.33)
5.00 (2.29)
5.10 (2.31)
<0.001
5.54 (2.33)
5.00 (2.29)
5.10 (2.31)
<0.001
5.54 (2.33)
5.00 (2.31)
5.11 (2.31)
<0.001
Urgency Status 1
168 (47.7%)
200 (34.2%)
129 (49.0%)
<0.001
168 (58.9%)
200 (40.7%)
129 (49.0%)
<0.001
164 (58.8%)
191 (40.2%)
124 (48.1%)
<0.001
Urgency Status 2
114 (32.4%)
216 (37.0%)
108 (41.1%)
0.082
114 (40.0%)
216 (43.9%)
108 (41.1%)
0.526
112 (40.1%)
210 (44.2%)
108 (41.9%)
0.536
Urgency Status 3
NR
74 (12.7%)
26 (9.9%)
<0.001
NR
74 (15.0%)
26 (9.9%)
<0.001
NR
73 (15.4%)
26 (10.1%)
<0.001
Hypertension
239 (67.9%)
401 (68.7%)
215 (81.7%)
<0.001
239 (83.9%)
401 (81.5%)
215 (81.7%)
0.692
238 (85.3%)
397 (83.6%)
211 (81.8%)
0.545
Smoker
172 (48.9%)
316 (54.1%)
182 (69.2%)
<0.001
172 (60.4%)
316 (64.2%)
182 (69.2%)
0.096
170 (60.9%)
308 (64.8%)
178 (69.0%)
0.148
Diabetic
55 (15.6%)
92 (15.8%)
52 (19.8%)
0.293
55 (19.3%)
92 (18.7%)
52 (19.8%)
0.935
54 (19.4%)
91 (19.2%)
52 (20.2%)
0.947
eGFR
94.0 (25.8)
90.7 (24.4)
85.8 (22.9)
<0.001
94.0 (25.8)
90.7 (24.4)
85.8 (22.9)
<0.001
93.8 (25.8)
90.7 (24.4)
85.6 (23.0)
<0.001
Transplant from hospital
61 (17.3%)
112 (19.2%)
43 (16.3%)
0.112
61 (21.4%)
112 (22.8%)
43 (16.3%)
0.112
60 (21.5%)
112 (23.6%)
43 (16.7%)
0.091
Pretransplant life support
30 (8.5%)
133 (22.8%)
65 (24.7%)
<0.001
30 (10.5%)
133 (27.0%)
65 (24.7%)
<0.001
30 (10.8%)
123 (25.9%)
61 (23.6%)
<0.001
Mechanical ventilation >72 hours
-
-
-
-
133 (46.7%)
182 (37.0%)
105 (39.9%)
0.029
130 (46.6%)
176 (37.1%)
102 (39.5%)
0.034
CLAD
-
-
-
-
-
-
-
-
137 (49.1%)
121 (25.5%)
52 (20.2%)
<0.001
ANOVA, analysis of variance; BMI, body mass index; CLAD, chronic lung allograft dysfunction; eGFR, estimated glomerular filtration rate; EVLP, ex-vivo lung perfusion.
Each phase of care represents a unique sub cohort because of the censoring that occurs when some patients proceed to the next steps of care while others do not. For this reason, we present the results separately for each phase of care. The Modern Era (EVLP) group in the waitlist phase represents only those patients who survived the waitlist phase and underwent transplantation. The data in this table are the unweighted values describing the study participants. Comparisons between groups are unadjusted analyses, using ANOVA and chi-square tests for continuous and categorical variables, respectively. Overall, in unadjusted analysis before propensity score adjustment, we observed that patients in the Modern era tended to be older and with higher frequency of comorbid conditions. Fewer patients in the Modern EVLP era required mechanical ventilation >72 hours immediately posttransplant, and fewer patients experienced Chronic Lung Allograft Dysfunction in the Modern EVLP era. Table cells representing data from fewer than 6 patients were not reported (NR) for publication to minimize the risk of reidentification.
IPTW-weighted mean total, component, and perimortem costs for each phase are summarized in Table 2 and Figure 2. In the pre-EVLP era, mean total costs per month for the referral and waitlist phases were $1634 ($694-$2851) and $14,904 ($11,776-$18,622) respectively. Modern era monthly costs for the same pretransplant phases were $2022 ($1607-$2518) and $26,507 ($23,632-$29,465) respectively. Mean total costs for the transplant hospitalization were $111,878 ($94,123-$130,767) in the pre-EVLP era. In the modern era, transplantation with No EVLP cost $122,008 ($91,457-$163,954), while transplantation with EVLP cost $90,923 ($75,788-$109,428), though the median costs for transplantation in this era appeared higher with EVLP vs without. Overall, costs for transplant hospitalization appear similar before vs after EVLP implementation. Costs for ICU care during the transplant hospitalization were $45,461 ($35,990-$56,333) in the pre-EVLP era, $59,890 ($36,061-$91,399) in the modern era with No EVLP, and $24,839 ($18,377-$32,201) in the modern era with EVLP. Posttransplant costs were lower in the modern era. Mean monthly total costs for the first 2 years posttransplant were $3132 ($2339-$4148) vs $2183 ($1919-$2523) in the pre-EVLP and modern eras, respectively. Mean total costs for each month beyond 3 years from discharge were $701 ($476-$1025) in the pre-EVLP era vs $320 ($227-$457) in the modern era.
Table 2Phase-Specific Total and Component Costs
Referral phase
Waitlist phase
Transplant phase
Posttransplant years 1 & 2
Posttransplant years 3+
Pre-EVLP era
Modern era (No EVLP)
Modern era (EVLP)
Modern era
Pre-EVLP era
Modern era (No EVLP)
Modern era (EVLP)
Modern era
Pre-EVLP era
Modern era (No EVLP)
Modern era (EVLP)
Modern era
Pre-EVLP era
Modern era (No EVLP)
Modern era (EVLP)
Modern era
Pre-EVLP era
Modern era (No EVLP)
Modern era (EVLP)
Modern era
Total Cost
$25,498 ($10,821 - $44,468)
$26,681 ($20,239 - $33,500)
$24,771 ($14,880 - $37,673)
$26,081 ($20,731 - $32,482)
$89,919 ($71,051 - $112,353)
$93,006 ($82,211 - $105,304)
$95,026 ($77,048 - $117,292)
$93,658 ($83,501 - $104,110)
$111,878 ($94,123 - $130,767)
$122,008 ($91,457 - $163,954)
$90,923 ($75,788 - $109,428)
$110,969 ($87,714 - $136,000)
$69,105 ($51,620 - $91,543)
$49,412 ($41,673 - $58,135)
$48,587 ($39,838 - $58,889)
$49,121 ($43,177 - $56,778)
$43,435 ($29,462 - $63,498)
$16,082 ($9,806 - $25,224)
$15,062 ($9,438 - $21,976)
$15,734 ($11,194 - $22,494)
Phase duration [days]
468 (406 - 539)
372 (347 - 398)
419 (382 - 456)
387 (366 - 408)
181 (157 - 207)
104 (93 - 116)
110 (93 - 129)
106 (97 - 116)
32 (29 - 36)
45 (38 - 52)
37 (31 - 44)
42 (37 - 47)
662 (634 - 686)
677 (662 - 690)
672 (652 - 690)
675 (663 - 686)
1,858 (1,712 - 1,996)
1,492 (1,437 - 1,546)
1,450 (1,380 - 1,521)
1,477 (1,432 - 1,523)
Monthly Cost
$1,634 ($694 - $2,851)
$2,152 ($1,632 - $2,702)
$1,774 ($1,065 - $2,697)
$2,022 ($1,607 - $2,518)
$14,904 ($11,776 - $18,622)
$26,829 ($23,715 - $30,376)
$25,916 ($21,013 - $31,989)
$26,507 ($23,632 - $29,465)
$104,886 ($88,240 - $122,594)
$81,339 ($60,971 - $109,303)
$73,721 ($61,450 - $88,725)
$79,264 ($62,653 - $97,143)
$3,132 ($2,339 - $4,148)
$2,190 ($1,847 - $2,576)
$2,169 ($1,778 - $2,629)
$2,183 ($1,919 - $2,523)
$701 ($476 - $1,025)
$323 ($197 - $507)
$312 ($195 - $455)
$320 ($227 - $457)
Labor Costs
$13,024 ($4,997 - $24,508)
$14,166 ($10,623 - $18,093)
$13,157 ($7,505 - $19,821)
$13,849 ($10,737 - $17,544)
$47,119 ($36,686 - $59,796)
$50,776 ($44,104 - $57,202)
$52,081 ($42,022 - $64,733)
$51,197 ($45,724 - $57,222)
$57,153 ($47,777 - $66,543)
$67,395 ($48,128 - $92,308)
$40,062 ($31,962 - $48,906)
$57,689 ($46,181 - $73,457)
$34,158 ($24,564 - $46,419)
$26,616 ($22,255 - $31,639)
$26,188 ($21,053 - $31,623)
$26,465 ($23,216 - $30,135)
$23,984 ($15,604 - $35,958)
$9,073 ($5,336 - $14,624)
$8,261 ($5,239 - $12,553)
$8,796 ($6,105 - $12,912)
Supply Costs
$4,158 ($1,918 - $6,885)
$4,590 ($3,518 - $5,914)
$4,311 ($2,431 - $6,359)
$4,502 ($3,546 - $5,623)
$15,492 ($11,907 - $19,757)
$15,896 ($13,926 - $17,800)
$15,921 ($13,110 - $19,206)
$15,904 ($14,300 - $17,542)
$20,164 ($17,119 - $23,356)
$20,527 ($16,101 - $25,997)
$13,624 ($11,162 - $17,170)
$18,076 ($14,727 - $21,785)
$9,817 ($7,224 - $13,008)
$7,150 ($5,856 - $8,626)
$6,838 ($5,438 - $8,561)
$7,040 ($6,003 - $8,101)
$6,064 ($4,013 - $8,582)
$2,050 ($1,287 - $3,256)
$2,068 ($1,291 - $3,091)
$2,056 ($1,427 - $2,819)
Inpatient Costs
$13,863 ($5,220 - $25,500)
$18,531 ($13,305 - $23,989)
$24,655 ($12,977 - $40,146)
$20,524 ($15,691 - $26,071)
$72,511 ($55,831 - $90,506)
$77,512 ($68,840 - $86,668)
$75,994 ($61,587 - $93,434)
$74,879 ($67,549 - $82,677)
NA
NA
NA
NA
$38,175 ($24,107 - $55,232)
$26,105 ($20,471 - $33,293)
$24,784 ($18,461 - $32,061)
$25,622 ($21,088 - $30,709)
$9,898 ($6,018 - $15,240)
$3,893 ($2,219 - $6,656)
$3,894 ($2,192 - $5,899)
$5,439 ($3,534 - $8,097)
Outpatient Costs
$2,967 ($2,639 - $3,281)
$4,777 ($4,299 - $5,403)
$4,871 ($4,466 - $5,354)
$4,117 ($3,816 - $4,525)
$5,060 ($4,314 - $5,714)
$4,193 ($3,810 - $4,642)
$4,077 ($3,526 - $4,634)
$3,826 ($3,516 - $4,137)
NA
NA
NA
NA
$17,823 ($16,438 - $19,249)
$13,424 ($12,702 - $14,157)
$12,774 ($11,786 - $13,818)
$13,195 ($12,627 - $13,778)
$3,654 ($2,907 - $4,551)
$1,248 ($929 - $1,692)
$1,313 ($1,054 - $1,619)
$1,513 ($1,226 - $1,853)
ICU Costs
$10,938 ($2,047 - $21,336)
$6,620 ($4,312 - $9,480)
$8,997 ($3,631 - $15,821)
$5,671 ($3,961 - $7,792)
$31,100 ($21,853 - $42,034)
$25,379 ($21,085 - $30,341)
$24,610 ($17,076 - $33,917)
$22,942 ($19,298 - $27,223)
$45,461 ($35,990 - $56,333)
$59,890 ($36,061 - $91,399)
$24,839 ($18,377 - $32,201)
$47,286 ($32,631 - $69,210)
$8,973 ($3,903 - $18,001)
$5,076 ($2,221 - $8,610)
$3,746 ($1,661 - $6,735)
$4,768 ($2,696 - $7,667)
$1,983 ($930 - $3,273)
$1,247 ($169 - $2,780)
$725 ($61 - $1,548)
$1,980 ($612 - $4,292)
ICU Duration [days]
NA
NA
NA
NA
NA
NA
NA
NA
12 (10 - 15)
10 (9 - 12)
9 (7 - 11)
10 (8 - 11)
NA
NA
NA
NA
NA
NA
NA
NA
Perimortem 10-day Costs
NA
NA
NA
NA
$10,652 ($7,370 - $14,113)
NA
NA
$9,374 ($6,869 - $12,839)
$48,254 ($6,373 - $64,092)
$36,742 ($15,277 - $57,835)
$30,090 ($61 - $60,120)
$34,842 ($11,661 - $53,523)
$18,596 ($12,030 - $25,227)
$12,968 ($8,216 - $18,592)
$4,469 ($2,136 - $7,015)
$8,713 ($5,990 - $12,596)
$5,589 ($2,710 - $9,931)
$6,625 ($2,574 - $10,953)
$16,710 ($16,710 - $16,710)
$7,893 ($3,477 - $12,622)
EVLP, Ex-vivo lung perfusion; ICU, Intensive care unit; IPTW, Inverse-probability of treatment weight.
Total and component costs per patient for each phase of care were estimated as the IPTW-weighted average with 95% confidence intervals (in parentheses) derived using 1000 bootstrap replicates. Inpatient, outpatient, and ICU costs in the pretransplant and posttransplant phases were adjusted by the proportion of patients who experienced these costs. (i.e., since some patients on the wait-list did not accrue inpatient costs, the estimate for inpatient costs was corrected to account for this). Since the labor and supply costs for EVLP were not estimated separately, the specific cost of EVLP was included in the transplant phase, under total costs only. ICU costs reflected all costs paid by the hospital's ICU operating budget and may therefore include ICU outreach activities in hospital as well as true ICU admission. For the transplant operation, ICU length-of-stay is reported as the duration between the transplant operation to first discharge from ICU; readmission to the ICU was not included in this measure. Transplant hospitalization phase length indicates hospital length-of-stay.
This figure depicts the median and IQR for total cost estimates in each phase, stratified by EVLP era and EVLP use. All estimates were IPTW-weighted and inflated to 2019 CAD. Total phase-specific costs were similar across each phase of care. (CAD, Canadian Dollars; EVLP, Ex-vivo lung perfusion; IPTW, Inverse probability of treatment weight; IQR, interquartile range)
In IPTW-weighted interrupted time-series analysis comparing log-adjusted costs from the modern era against projections from the pre-EVLP era, we observed no significant change in trend occurring at the start of the modern era for the referral (p = 0.444), waitlist (p = 0.148), and transplant (p = 0.285) phases
(Figure 3). Conversely, we observed significant reductions in posttransplant log-adjusted costs occurring in the modern era (p < 0.001 for postoperative years 1 & 2; p = 0.003 for postoperative years 3+), and significant changes in trend for postoperative years 1 & 2 (p < 0.001) and postoperative years 3+ (p = 0.003), suggesting that postoperative costs may decline after EVLP becomes available.
Figure 3Time-series plots. Among the greatest threats to validity of before-after studies are the risks of maturation and history biases.
To overcome this, we performed an interrupted time-series analysis using segmented regression. This figure shows the relationship of total phase-specific costs to referral date. The Pre-EVLP era trend (shown in red) is continued with the dashed line, and the Modern EVLP era trend is shown in blue. The p-value at the right of each plot indicates whether the trend in the Modern EVLP era is significantly different from the trend on the Pre-EVLP era. The p-value shown in the middle of the figure (at the breakpoint) indicates whether the mean log costs after the interruption (EVLP implementation) was significantly different from the mean log costs before. EVLP, Ex-vivo lung perfusion. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
A separate IPTW-weighted log-gamma generalized linear model was constructed to identify predictors of total cost in each phase. (Table 3) In the referral and waitlist phases, we did not observe an association between EVLP era and costs (cost ratio [CR] 1.12 [0.66-2.31]; p = 0.346 and 1.04 [0.81-1.37]; p = 0.354, respectively). Restrictive and pulmonary-vascular diseases were associated with pretransplant costs. (Table 3) Multivariable regression of total costs for the transplant hospitalization showed that EVLP era was not associated with costs (1.02 [0.80-1.29]; p = 0.425) whereas mechanical ventilation >72 hours immediately postoperatively was associated with higher costs (CR 2.16 [1.71-2.73]; p < 0.001). The modern era was associated with significantly lower posttransplant years 1 & 2 costs (CR 0.75 [0.58-1.06]; p = 0.05). Accounting for EVLP era and patient characteristics, transplant with an extended-criteria organ was associated with higher posttransplant years 1 & 2 costs (CR 1.29 [1.04-1.64]; p = 0.02). Similarly, the modern era was associated with significantly lower posttransplant years 3+ costs (CR 0.43 [0.26-0.74]; p = 0.001), and CLAD was associated with larger costs in this phase (CR 1.7 [1.0-2.71]; p = 0.026).
Table 3Predictors of Total Cost in Each Phase of Care
Referral
Waitlist
Transplant
Posttransplant years 1&2
Posttransplant years 3+
Modern EVLP Era
1.13 (0.66 - 2.31)
p=0.346
1.04 (0.81 - 1.37)
p=0.354
1.02 (0.8 - 1.29)
p=0.425
0.75 (0.58 - 1.06)
p=0.05
0.43 (0.26 - 0.74)
p=0.001
Pre-EVLP Era
Reference
Reference
Reference
Reference
Reference
Restrictive lung disease
2.81 (1.65 - 4.49)
p=0.001
1.57 (1.19 - 2.06)
p <0.001
0.97 (0.74 - 1.21)
p=0.383
0.85 (0.65 - 1.19)
p=0.18
1.09 (0.63 - 1.89)
p=0.394
Pulmonary vascular disease
3.18 (1.39 - 6.45)
p=0.004
2.16 (1.18 - 3.64)
p=0.003
1.13 (0.77 - 1.62)
p=0.265
1.43 (0.79 - 2.56)
p=0.119
0.58 (0.22 - 1.49)
p=0.126
Suppurative lung disease
2.08 (0.7 - 4.45)
p=0.076
1.51 (1.04 - 2.16)
p=0.01
1.28 (0.92 - 1.75)
p=0.077
1.56 (0.88 - 2.53)
p=0.063
0.57 (0.3 - 1.19)
p=0.066
Other diagnoses
4.3 (0.41 - 13.71)
p=0.351
3.01 (0.29 - 6.1)
p=0.064
3.3 (0.95 - 6.3)
p=0.031
1.07 (0.59 - 1.87)
p=0.421
1.11 (0.08 - 3.16)
p=0.432
Obstructive lung disease
Reference
Reference
Reference
Reference
Reference
DCD Donor
—
—
—
—
0.88 (0.72 - 1.11)
p=0.154
0.95 (0.71 - 1.31)
p=0.336
0.82 (0.41 - 1.53)
p=0.252
NDD Donor
—
—
—
—
Reference
Reference
Reference
Single lung transplant
—
—
—
—
0.94 (0.76 - 1.19)
p=0.306
1.02 (0.79 - 1.3)
p=0.426
0.91 (0.5 - 1.62)
p=0.406
Double lung transplant
—
—
—
—
Reference
Reference
Reference
Extended criteria donor
—
—
—
—
1.15 (0.93 - 1.41)
p=0.093
1.29 (1.04 - 1.64)
p=0.017
1.16 (0.71 - 2.04)
p=0.304
Standard criteria donor
—
—
—
—
Reference
Reference
Reference
Waitlist duration (days)
—
—
—
—
1 (1 - 1)
p=0.205
1 (0.999 - 1)
p=0.444
1 (0.998 - 1.001)
p=0.429
Mechanical ventilation >72 hours
—
—
—
—
2.16 (1.71 - 2.73)
p <0.001
1.24 (0.96 - 1.63)
p=0.06
0.82 (0.49 - 1.39)
p=0.282
Mechanical ventilation <72 hours
—
—
—
—
Reference
Reference
Reference
CLAD
—
—
—
—
—
—
1.24 (0.95 - 1.65)
p=0.063
1.7 (1 - 2.71)
p=0.026
No CLAD
—
—
—
—
—
—
Reference
Reference
CLAD, Chronic Lung Allograft Dysfunction; EVLP, Ex-Vivo Lung Perfusion; DCD, Donation after circulatory death; NDD, Neurologically Defined Donor.
A separate log-gamma generalized linear regression was constructed to identify predictors of total costs in each phase. Results are presented as cost ratios, on the multiplicative scale, with values greater than 1 indicating higher costs. For instance, in the referral phase, restrictive lung disease was associated with costs 2.81 (1.65-4.49) times higher than with obstructive lung disease. 95% Confidence intervals and 1-tailed p-values were derived by nonparametric bootstraps.
Compared with the pre-EVLP era, patients in the modern era were more likely to proceed to the posttransplant phases, and appeared to do so in a shorter time from referral (Figure 4). Accordingly, we observed waitlist occupancy at any 1 time to be lower since EVLP became available. The multistate model suggests shorter time-to-transplant when EVLP was available.
Figure 4Multistate occupancy probabilities. This figure depicts the probability of an individual occupying each phase of care over time since referral in the Pre-EVLP era and the Modern EVLP era. Probabilities were derived using an IPTW-weighted landmark Aalen-Johansen estimator.
Because the Markov assumption was violated for all transitions, the landmark Aalen-Johansen was the preferred estimator, as it does not depend on this assumption.
Compared with the Pre-EVLP, the probability of an individual entering the posttransplant states (red solid [years 1 & 2] and dashed [years 3+]) was higher and occurred earlier in the Modern EVLP era. Accordingly, the probability of being in the wait-list state (green) is lower in Modern EVLP era, indicating that occupancy in the wait list at any one time is lower since EVLP became available. In addition, the overall probability of death (black) is modestly lower in the Modern EVLP era vs the Pre-EVLP era. Together, these suggest shorter time to transplant and more efficient progress through the transplant program when EVLP is available.EVLP, Ex-vivo lung perfusion; IPTW, Inverse probability of treatment weight.
We estimated cumulative costs at 5-years since referral to be $278,777 ($82,575-$298,135) in the pre-EVLP era and $293,680 ($252,832-$317,599) in the modern era. The absolute difference between means was $14,903, reflecting an approximate 5% relative increase.
Discussion
This study estimated costs, from the hospital perspective, for lung transplantation before vs after EVLP was available. Our cost estimates of $110,959 ($87,739-$137,875) for the transplant hospitalization with EVLP available and $108,422 ($93,140-$124,918) without EVLP available are commensurate to the evidence from other jurisdictions. We previously reported that the institutional cost of lung transplantation ranged between $16,748 and $361,959.
Fisher et al (2016) estimated 1-year costs, from the United Kingdom healthcare-payer perspective, for transplant with EVLP as $219,518 ± $92,990, vs $94,082 ± $67,338 without EVLP over the same time-horizon.
However, the DEVELOP-UK study was limited because patient enrollment was stopped early due to excess mortality and because their EVLP protocol deviated from accepted protocols. A study from the United States, published after our review, found higher costs, from the institutional perspective, for the transplant hospitalization with EVLP transplants costing $200,404 (interquartile range IQR $161,966-$362,143) vs cold-static preserved standard criteria organs $154,709 (IQR $137,890-$218,180]).
However, Halpern et al (2021) reported that this difference was not statistically significant, and that the use of EVLP at their center was overall profitable.
Although that study did not adjust for potential confounders and ultimately concluded that further investigation was required, these results appear to complement those of our study. Neither of these studies considered pretransplant or posttransplant costs beyond 1-year; inclusion of these is an added strength of our study.
We observed more complex patient characteristics in the modern era in unadjusted analyses (Table 1), and higher IPTW-weighted mean waitlist costs (Table 2). These findings suggest that EVLP availability has allowed for more complex patients to be considered for transplant, when previously these patients would be considered too high risk. Further, while we observed that posttransplant mechanical ventilation >72 hours was associated with higher costs, significantly fewer patients in the modern era required prolonged ventilation. Taken together, these findings demonstrate that EVLP has increased access to transplantation while improving postoperative outcomes – findings consistent with the evidence that EVLP transforms clinical practice for pretransplant assessment, organ allocation, and postoperative care.
Alongside our finding that EVLP era was not a significant predictor of pretransplant or transplant hospitalization costs (i.e.,: that EVLP implementation did not significantly increase phase-specific costs) (Table 3), these results demonstrate important clinical improvements from EVLP at no significant marginal cost.
Overall, we interpret our results to indicate that the cost of EVLP represents a relatively small contribution to the total costs of transplantation since the addition of EVLP to our lung transplantation program was not associated with higher overall costs. While we observed slightly higher pretransplant costs in the modern era, perhaps attributable to increased care requirements and novel medical therapies for waitlist patients, the shorter waitlist duration afforded by EVLP may be offsetting these costs. Our observation of shorter pretransplant durations in the modern era suggests that the clinical benefit of EVLP may be offsetting some of the costs. Since we observed shorter ICU stay and lower ICU costs among recipients of EVLP-treated lungs, this cost-savings might be offsetting the costs of EVLP in the modern era. Lower posttransplant costs could be a function of truly decreased posttransplant care requirements resulting from improved organ quality at transplantation due to EVLP, but this may also reflect greater comfort at our center in having posttransplant patients evaluated by their community respirologists. Future evaluation of provincial healthcare spending could help determine if posttransplant costs in the modern era are lower, or simply transferred from the transplant institution to the broader healthcare system. While it's possible that transplant hospitalization costs were declining over time, perhaps related to practice changes unrelated to EVLP, and that the implementation of EVLP maintained those costs, we find this explanation unlikely based on our time-series analysis. Interrupted time-series analysis showed no significant increase in pretransplant or transplant phase costs at the time of EVLP implementation, nor did it demonstrate a significantly different slope for changing costs over time. (Figure 3) While the purpose of our study was to measure costs and identify clinical predictors, our study did not produce sufficient evidence to confirm these interpretations: exploration of the mechanisms underlying the economic differences in the pre-EVLP and modern eras should be the focus of future work.
While observational research allows for generalization outside of the clinical trial setting, as it reflects real-world experiences (and expenditure), there are limitations to this methodology. Incomplete data and censoring are inevitable with retrospective studies using routinely-collected data. We mitigated the effect of this by analyzing each phase of care separately, which overcomes this common limitation of administrative data.
Our creation of perimortem phases further reduces bias from censoring due to death. To further reduce the risk of bias by censoring, we constrained the observation window of the pre-EVLP era so that measurements in each EVLP era were collected for a similar duration. Despite this, shorter observation times in the modern era could contribute to the observed lower CLAD incidence and posttransplant years 3+ costs: these observations should be considered circumspectly. A limitation of this study was that EVLP costs were provided from our institutional accounting department as a single value per case: we could not discern from this value what portion of EVLP expenditure represented the specific costs for supplies vs labor. Costs for organ procurement were not included in this analysis, and these costs may be high. However, this is consistent with the perspective of the transplant institution, because organ procurement in Ontario is coordinated by an independent government agency (Trillium Gift of Life Network). This institutional perspective is narrow, which may be considered a limitation, but is nevertheless important: transplant-specific care is provided by a single institution, so institutional economic analysis is directly relevant to transplant program administrators. Evaluation from broader health system perspectives is the focus of ongoing work by our group. Our recent review of economic evaluations and costing studies revealed that a dearth exists of health economic analysis of lung transplantation from both perspectives.
A limitation in the before-after study design is the risk of selection-maturation bias, where baseline covariates and exposure status are a function of the passage of time. We mitigated the risk of this by conducting an interrupted time-series analysis.
We additionally accounted for covariate differences using IPTW, though the risk of unmeasured confounding may persist. While the benefits of IPTW outweigh its drawbacks, this technique is sensitive to model misspecification – particularly with manually-specified models, which tend to be too simple; we, therefore, used a machine-learning tool, generalized boosted models, to estimate propensity scores.
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.
The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments.
Nevertheless, we did not achieve balance for urgency status; the best overall balance was achieved by the present propensity score selection model which did not include this variable. Our study is limited by this imperfect covariate balance. We considered this acceptable since including the urgency status variable resulted in overall worse covariate balance, and because it is a broadly-defined variable. We gave preference to more specific covariates for our selection model that capture the same fundamental idea as the urgency status variable (pretransplant life support, transplant from home-vs-hospital).
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.
Further, since we anticipate that higher urgency patients would accrue higher healthcare costs and we observed a higher proportion of high urgency patients in the modern era, the lack of balance achieved for this covariate should yield higher costs in the modern era. Our finding that the modern era was not associated with significantly higher costs than the pre-EVLP era is thereby a conservative one. A further limitation was that primary graft dysfunction was not reliably available in our dataset, so we could not explicitly incorporate this important variable into the analysis. While the cost estimates for the transplant phase and ICU costs implicitly incorporate the costs associated with primary graft dysfunction for those patients who experienced this outcome, this limitation of our dataset prevented us from incorporating primary graft dysfunction into the analyses more explicitly. We did, however, incorporate graft dysfunction in the form of CLAD, and by the surrogate variable mechanical ventilation >72 hours posttransplant in our analysis of posttransplant costs. Lastly, EVLP costs may change as new devices come to market and EVLP-use increases; generalization of our results to outside jurisdictions with different EVLP devices and protocols should be performed circumspectly.
We estimated cumulative costs from referral using a novel phase-based costing method which employs an IPTW-weighted multistate model to more precisely assign costs to their correct clinical phase and account for confounding and selection biases.
This method is an improvement over conventional phase-based costs-assessments, which require predefined population-level phase durations, and for which uncertainty and subgroup analyses are not straightforward. An advantage of our approach is that phase-specific costs measured in this way map directly onto the health states of a decision-analytic model. An additional strength is that it yields state-occupancy probabilities, from which we may draw inferences about the transplant program.
Conclusions
This study estimated costs, from the institutional perspective, for the transplant hospitalization as $111,878 ($94,123-$130,767) without EVLP available vs $122,008 ($91,457-$163,954) for a non-EVLP transplant in the modern era and $90,923 ($75,788-$109,428 for a transplant of EVLP-treated lungs in the modern era. Posttransplant mechanical ventilation >72 hours is a significant predictor of costs, and significantly fewer patients required prolonged ventilation after EVLP was available. Despite waitlist enrolment of significantly older and more complex patients, access to lung transplantation was shorter in the EVLP era, with no significantly higher IPTW-adjusted phase-specific or cumulative costs: important clinical improvements were achieved with EVLP at no significant marginal cost.
Author contributions
J.K.P. was involved in study design, data analysis, writing of manuscript, and acquisition of funding. E.P. and D.N. were involved in study design, and data analysis. S.K. and B.S. were involved in study design, data analysis, and acquisition of funding. K.B., L.D.S., M.C., and M.L. were involved in data analysis. All authors participated in revision of the manuscript and gave approval for publication. All listed authors contributed sufficiently to qualify for authorship.
Disclosure statement
Dr Peel has been supported by the Canadian Institutes of Health Research (CIHR) CGS-M award, CIHR Fellowship (202012MFE), Ontario Graduate Scholarship, UofT Graduate Fellowship, Dr Brian Kavanagh scholarship from UHN, and PSI Foundation Resident Research grant. Dr Keshavjee is a founder of Perfusix and XOR Laboratories, and has received consulting fees from Lung Bioengineering, outside the submitted work.
We would like to thank Dr Murray Krahn, Dr Lianne Singer, the Toronto Lung Transplant Program research team, and the team at the Toronto Health Economics and Technology Assessment (THETA) collaborative for their mentorship and contribution to the study conceptualization. Privacy legislation prohibits release of our raw data. Please contact the author for example programming code.
Canadian Institute for Health Information /Institut canadien d'information sur la santé. Annual Statistics on Organ Replacement in Canada: Dialysis, Transplantation and Donation, 2010 to 2019. 2020:1-6.
Chan BC-F, Cadarette SM, Wodchis WP, Krahn MD, Mittmann N. The lifetime cost of spinal cord injury in Ontario, Canada: a population-based study from the perspective of the public health care payer. 2019:1-11. doi:10.1080/10790268.2018.1486622.
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.
The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments.
Government of Canada, Statistics Canada. Consumer Price Index, annual average, not seasonally adjusted. 2020. doi:https://doi.org/10.25318/1810000501-eng.
Manca A, Austin PC. Using propensity score methods to analyse individual patient level cost effectiveness data from observational studies. yorkacuk. 2008.
This month’s JHLT: The Podcast is hosted by Digital Media Editor David Schibilsky, MD, who leads a discussion of two studies from the March issue of The Journal of Heart and Lung Transplantation—and the first authors who presented them.
The editors welcome Charaka Hadinnapola, MA, MB, BChir, first author on the CTEPH study, to share the rationale in performing the research, its main findings, the changing understanding of the pathobiology of pulmonary arterial hypertension, and how Ang2 and hsCRP fit into the bigger cytokine picture in CTEPD and CTEPH patients.
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