Heart Transplant Allocation Change Results in Increased Cost and Initial Decrease in Transplant Volume: The Florida Experience

Abstract

Purpose: Patients with end-stage HCM, the most common genetic cardiovascular condition, often require heart transplant (HT) but there is limited data assessing outcomes. We sought to assess the effect of the 2018 UNOS Heart Allocation policy changes on patients with HCM which increased prioritization for this population. Methods: 128 patients with HCM received HT in the year before and after the UNOS policy changes. Pre-(n=65) and post-policy (n=63) cohorts were identified using the UNOS registry. Baseline characteristics were compared using standard statistical analysis. 30-and 180-day outcomes were evaluated using Kaplan Meier survival analysis as well as univariate and multivariate Cox proportional hazards modeling. Results: Baseline characteristics were similar for both groups, but differed in median [IQR] distance (nm) from donor and treatment center (pre: 91 [17, 253]; post: 245 [100.5, 393]; p=0.002) and median PA pressure (mm/ Hg) at registration (pre: 38 [30, 49.2]; post: 45 [31, 58], p=0.036). Donor characteristics differed in mean BMI (pre: 26.1 (SD 7.2); post: 28.9 [SD 7.2]). Pre-and post-policy 30-day survival was 100% (CI 100%, 100%) and 95% (CI 90%, 100%) respectively. Pre-and post-180-day survival was 94% (CI 88%, 100%) and 90% (CI 83%, 98%). Cox univariate hazard ratio (HR) following the UNOS change was 1.62 (CI 0.46, 5.73, p=0.5). Multivariate Cox proportional HR adjusted for recipient age, donor age, serum creatinine, total bilirubin, ischemic time, pre-transplant dialysis, ventilator and ECMO status was 1.54 (CI 0.39, 6.09, p=0.5). Conclusion: UNOS policy changes did not adversely affect survival at 30 and 180 days for patients with HCM receiving HT. Additional research is needed to evaluate the effects these policy changes have on patients with HCM.

Impact of the heart transplant allocation policy change on inpatient cost of index hospitalization

“…8 Rogers and colleagues, using regional data of 759 transplants, showed a significant increase in total hospital charges (un-adjusted for inflation) after the allocation change without changes in LOS. 9 We extend these results using national data with amplified statistical power Limitations of our study include those inherent to the NIS itself and several other considerations. The NIS is an administrative database that lacks granularity and for which there is potential for inaccurate data collection and classification which may have affected results.…”

“…Using game‐theory probability Saltzberg predicted reduced cost effectiveness (cost for year of post‐transplant life expectancy) of HT after the 2018 allocation change due to increased short‐term MCS, increased procurement radius and ischemic times and reduced post‐transplant survival 8 . Rogers and colleagues, using regional data of 759 transplants, showed a significant increase in total hospital charges (un‐adjusted for inflation) after the allocation change without changes in LOS 9 . We extend these results using national data with amplified statistical power and inflation‐adjusted hospital costs to demonstrate an increase in expense.…”