Values-driven decision support for cadaveric kidney transplant decisions
Abstract/Contents
- Abstract
- Although the demand for kidney transplants continues to greatly exceed supply, most cadaveric kidneys are offered to multiple patients before being accepted or discarded. The decision of whether to accept or decline an offered kidney is difficult because of uncertainty about the quality and length of the patient's remaining life. If they decline the offer, then it is uncertain whether they will ever receive a kidney, let alone one of higher quality than the one currently available. This thesis develops a decision-analytical approach to model the situation facing patients waiting for kidney transplants, based on twenty years of data on patients waiting for transplants in the US. When they are offered a matching kidney, they and their surgeons must decide whether to accept the offer. We model each patient's situation as a one-step decision-making problem that compares the observed remaining lifetime or landmark survival for similar patients who accepted an offered kidney of similar quality and those who declined such an offer. This information can facilitate a meaningful conversation between a patient and their surgeon that can address the particular preferences and circumstances of that patient. Our analysis shows that for patients in almost every situation, the observed remaining lifetime for similar patients was longer if they accepted the offer than if they declined it, and sometimes significantly longer. Because accepting an offer almost always reduces the time a patient will spend on dialysis, it also improves the quality of life for most patients. Therefore, we believe that our results should encourage patients to accept many more offered kidneys than they have in the past.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Diao, Tianhui |
|---|---|
| Degree supervisor | Shachter, Ross D |
| Thesis advisor | Shachter, Ross D |
| Thesis advisor | Kochenderfer, Mykel J, 1980- |
| Thesis advisor | Van Roy, Benjamin |
| Degree committee member | Kochenderfer, Mykel J, 1980- |
| Degree committee member | Van Roy, Benjamin |
| Associated with | Stanford University, Department of Management Science and Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Tina Diao (Tianhui). |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/gk415tq2524 |
Access conditions
- Copyright
- © 2022 by Tianhui Diao
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...