Using behavioral economics to reduce the discard rate of viable kidneys: Validating new methods to identify factors that influence the acceptance of deceased-donor kidneys

Project: Research project

Project Details

Description

While there remains a significant and growing shortage of transplantable organs, nearly 20% of deceased kidney donations are discarded each year in the United States.1 Due to this shortage, patients are removed from the wait list because their health has deteriorated so much that they are no longer qualified to receive a transplant or they die while on the wait list. Patients dying and being taken off the wait list while recovered organs are being discarded highlights the need to improve the allocation and acceptance of viable kidney donations in the United States.
An underlying barrier to improving the allocation and acceptance of deceased kidneys is a lack of a fundamental understanding as to why the refusal rate for similar kidneys is so high for some transplant centers, but not others.2 Our research teams expertise in behavioral economics, survey/experimental design, and kidney transplantation
makes us well suited to develop new methods to refine past models of clinicians decision-making and explain the heterogeneity in acceptance rates. The central hypothesis to our proposed work is that the unexplained heterogeneity in acceptance rates is caused by idiosyncratic preferences and behavioral biases in clinicians decision-making. These preferences and behavioral biases may result in fewer lifesaving transplants, longer wait lists, and ultimately, a decrease in the life expectancy of patients in need of a kidney transplant. Although many preferences and biases have been hypothesized to affect clinicians decisions, researchers lack a
validated instrument to measure them. We will pilot and validate a platform (SimUNetSM) that will allow us to estimate the influence of a wide range preferences and behavioral biases on acceptance rates. Our pilot of the SimUNetSM platform will elicit clinicians risk preferences for accepting deceased-donor kidneys. To validate our platform, we will test for correlations between individuals risk preferences elicited in SimUNetSM to behavior in practice. While acceptance rates vary by many factors, risk preferences serve as a natural candidate for validation given the prominent role they have been shown to play in clinicians decision-making.35
Aim 1: Design an instrument to elicit preferences for risk using the SimUNetSM interface. SimUNetSM is a web-based interface developed by the United Network for Organ Sharing (UNOS) and Co-I Darren Stewart that simulates DonorNet R, the interface surgeons & nephrologist use when making a decision to accept a deceased-donor kidney for transplantation.68 In our first aim, 130 clinicians will be asked to complete 15 standardized patient vignettes in the SimUNetSM platform. The vignettes will systematically vary the risk of accepting a deceased kidney donation relative to dialysis, which will allow us to estimate risk preferences.

Aim 2: Create clinician level data set of deceased kidney turn down rates. Currently, there is no data set that contains individual clinicians decision to accept a deceased donor-kidney. In our second aim, we will collaborate with transplants centers across the US to identify clinician-specific decisions to accept a deceased donor kidneys. We have early letters of support from 8 transplant centers who have committed to provide us with the data necessary to identify individual level decision-making in the Organ Procurement and Transplantation Network (OPTN) data and also, map this data with the observed behavior in Aim 1 (See Section 5.b for more detail).

Aim 3: Validate the use of SimUNetSM by testing for correlations between risk preferences observed in SimUNetSM interface and OPTN data. To evaluate whether the decision to accept a deceased-donor kidney in SimUNetSM reflect the decision-making outside a simulated environment and thereby, validate the use of SimUNetSM, we will test for correlations between choices observed in SimUNetSM and the deceased kidney donation turn down rates collected in Aim 2. If these correlations exist, we will examine whether the measurements from the experiment can independently explain the variation in acceptance rates across centers.
Hypothesis 1: There exists a statistically significant relationship between clinicians deceased kidney turn down rates in practice and risk preferences observed in SimUNetSM. Overall Impact: Through this study, we will have 1. validated the use of SimUNetSM to elicit clinician behavior, 2. created a unique data set of the individual decision-making to accept a deceased kidney donation, and 3. have an understanding of the role risk preferences play in the decision-making process underlying the acceptance of deceased-donor kidneys. With the validation of SimUNetSM, we will have laid the ground work for future studies to evaluate the impact a wide range behavioral biases and preferences have on the likelihood of accepting a deceased-donor kidney. With a refined model of clinical decision-making, we can construct evidence-based policy and clinician decision-aids to improve the quality of care delivered in transplantation as well as increase access to deceased-donor kidneys.
StatusActive
Effective start/end date6/23/215/31/23

Funding

  • HHS: National Institutes of Health (NIH): $449,864.00

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