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An Open-Source Simulation Software Platform for Community Research and Development for Liver Allocation Policies

Kilambi, Vikram PhD1,2,3; Bui, Kevin MS1,2; Mehrotra, Sanjay PhD1,2,4

doi: 10.1097/TP.0000000000002000
In Brief

1 Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL.

2 Center for Engineering and Health, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

3 RAND Corporation, Boston Office, Boston, MA.

4 Northwestern University Transplant Outcomes Research Collaborative (NUTORC), Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL.

Received 2 October 2017. Revision received 10 October 2017.

Accepted 14 October 2017.

This work is funded by National Science Foundation award CMMI-1131568 and Agency for Healthcare Research and Quality award 1R36HS024840-01.

The authors declare no conflicts of interest.

V.K. developed the software, debugged the software, and edited the article. K.B. developed the software, debugged the software, and drafted the article. S.M. supervised the software, reviewed the software, and edited the article.

Correspondence: Sanjay Mehrotra, PhD, Industrial Engineering and Management Sciences, 2145 Sheridan Road, Tech C246, Evanston, IL 60208. (

Supplemental digital content (SDC) is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (

We developed LivSim, an open-source software alternative to the Liver Simulated Allocation Model (LSAM v Aug 2014)1 created by the Scientific Registry of Transplant Recipients. Written in Python 3.4.2, LivSim performs discrete-event simulation of liver allocation in the US Organ Procurement Transplantation Network. The software and technical manual are available for download at

LSAM is widely used as a simulation tool to assess alternative liver allocation policies. However, its source code is inaccessible and is difficult to modify when testing new concepts beyond its capabilities. For example, at the time when optimized2 and concentric3 neighborhoods were being developed and analyzed, LSAM’s architecture could not accommodate their designs.

The current LivSim version allows simulation and analysis for donor service area (DSA) level performance of allocation policies. It can be modified to provide transplant center and donor hospital level functionality as in LSAM. The software architecture allows specification of organ sharing prioritization for different match-run environments. For example, LivSim was used to examine the performances of the 8-district redistricting,4 national sharing, optimized neighborhoods,2 and the concentric-neighborhoods solution3 with different allocation rules.

LivSim can use LSAM input data or user-created input data. The LivSim architecture is summarized in Figure S1, LivSim maintains lists of transplant candidates with characteristics including Model for End-Stage Liver Disease (MELD) score, ABO blood type, and status 1 or hepatocellular carcinoma exceptions if applicable. Events are processed in time and include new patient listings/re-listings, organ procurements, and status updates/MELD progressions of candidates. For the (re)listing event, a patient is added to the waitlist and is assigned characteristics and future updates. During the update event, LivSim updates the candidate's MELD score and potentially removes the candidate from the waitlist or indicates the candidate's death. An organ procurement event triggers a match-run to offer the liver to someone in accordance with the specified allocation rules and geographic structure. A statistical model evaluates whether an offer is accepted. If accepted, LivSim determines whether the recipient will relist and, if necessary, return the recipient to the waitlist after calculating graft failure time.

When the simulation finishes, it outputs the following statistics:

  • DSA-average MELD at transplant and standard deviation
  • DSA-median MELD at transplant and standard deviation
  • Number of transplants by year and by DSA
  • Number of waitlist mortalities by year and by DSA
  • Number of waitlist removals by year and by DSA
  • Average transplant waiting time by year and by DSA
  • Number of procured organs sent or received between DSAs

Using the above output and LSAM data, LivSim can also produce statistics on posttransplant mortalities, relisting and retransplant mortalities, and organ transport distances and times.

The LivSim code is extensible and modular: users can include new features (eg, update survival models, allocation rules, and so on) and post them to the software repository that includes version tracking. Open sourcing of LivSim promotes transparency5 and encourages community-wide development of allocation policies that follow robust design principles and potentially lead to saving more lives and reducing geographic disparity. Using the former, results generated by LivSim approximate those of LSAM v Aug 2014.2

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1. Liver Simulated Allocation Model: User's Guide. [computer program]. SRTR; 2014.
2. Kilambi V, Mehrotra S. Improving liver allocation using optimized neighborhoods. Transplantation. 2017;101:350–359.
3. Mehrotra S, Kilambi V, Bui K, et al. A concentric-neighborhoods solution to disparity in liver access that contains current UNOS districts. [published online September 6, 2017]. Transplantation. 2017. doi: 10.1097/TP.0000000000001934.
4. Gentry SE, Massie AB, Cheek SW, et al. Addressing geographic disparities in liver transplantation through redistricting. Am J Transplant. 2013;13:2052–2058.
5. Ladner DP, Mehrotra S. Resolving misconceptions about liver allocation and redistricting methodology—reply. JAMA Surg. 2016;151:992.

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