IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v45y2015i5p462-480.html
   My bibliography  Save this article

Gerrymandering for Justice: Redistricting U.S. Liver Allocation

Author

Listed:
  • Sommer Gentry

    (Mathematics Department, United States Naval Academy, Annapolis, Maryland 21402; and Johns Hopkins University School of Medicine, Baltimore, Maryland 21287)

  • Eric Chow

    (Johns Hopkins University School of Medicine, Baltimore, Maryland 21287)

  • Allan Massie

    (Johns Hopkins University School of Medicine, Baltimore, Maryland 21287; and Johns Hopkins University School of Public Health, Baltimore, Maryland 21287)

  • Dorry Segev

    (Johns Hopkins University School of Medicine, Baltimore, Maryland 21287; and Johns Hopkins University School of Public Health, Baltimore, Maryland 21287)

Abstract

U.S. organ allocation policy sequesters livers from deceased donors within arbitrary geographic boundaries, frustrating the intent of those who wish to offer the livers to transplant candidates based on medical urgency. We used a zero-one integer program to partition 58 donor service areas into between four and eight sharing districts that minimize the disparity in liver availability among districts. Because the integer program necessarily suppressed clinically significant differences among patients and organs, we tested the optimized district maps with a discrete-event simulation tool that represents liver allocation at a per-person, per-organ level of detail. In April 2014, the liver committee of the Organ Procurement and Transplantation Network (OPTN) decided in a unanimous vote of 22-0-0 to write a policy proposal based on our eight-district and four-district maps. The OPTN board of directors could implement the policy after the proposal and public-comment period.Redistricting liver allocation would save hundreds of lives over the next five years and would attenuate the serious geographic inequity in liver transplant offers.

Suggested Citation

  • Sommer Gentry & Eric Chow & Allan Massie & Dorry Segev, 2015. "Gerrymandering for Justice: Redistricting U.S. Liver Allocation," Interfaces, INFORMS, vol. 45(5), pages 462-480, October.
    • Handle: RePEc:inm:orinte:v:45:y:2015:i:5:p:462-480
    DOI: 10.1287/inte.2015.0810
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2015.0810
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2015.0810?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Steven M. Shechter & Cindy L. Bryce & Oguzhan Alagoz & Jennifer E. Kreke & James E. Stahl & Andrew J. Schaefer & Derek C. Angus & Mark S. Roberts, 2005. "A Clinically Based Discrete-Event Simulation of End-Stage Liver Disease and the Organ Allocation Process," Medical Decision Making, , vol. 25(2), pages 199-209, March.
    2. Ram Gopalan & Steven O. Kimbrough & Frederic H. Murphy & Nicholas Quintus, 2013. "The Philadelphia Districting Contest: Designing Territories for City Council Based Upon the 2010 Census," Interfaces, INFORMS, vol. 43(5), pages 477-489, October.
    3. Nan Kong & Andrew J. Schaefer & Brady Hunsaker & Mark S. Roberts, 2010. "Maximizing the Efficiency of the U.S. Liver Allocation System Through Region Design," Management Science, INFORMS, vol. 56(12), pages 2111-2122, December.
    4. Takeshi Shirabe, 2009. "Districting Modeling with Exact Contiguity Constraints," Environment and Planning B, , vol. 36(6), pages 1053-1066, December.
    5. Robin Segerblom Liggett, 1973. "The Application of an Implicit Enumeration Algorithm to the School Desegregation Problem," Management Science, INFORMS, vol. 20(2), pages 159-168, October.
    6. GARFINKEL, Robert S. & NEMHAUSER, Geroge L., 1970. "Optimal political districting by implicit enumeration techniques," LIDAM Reprints CORE 54, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Andris A. Zoltners & Prabhakant Sinha, 1983. "Sales Territory Alignment: A Review and Model," Management Science, INFORMS, vol. 29(11), pages 1237-1256, November.
    8. George, John A. & Lamar, Bruce W. & Wallace, Chris A., 1997. "Political district determination using large-scale network optimization," Socio-Economic Planning Sciences, Elsevier, vol. 31(1), pages 11-28, March.
    9. R. S. Garfinkel & G. L. Nemhauser, 1970. "Optimal Political Districting by Implicit Enumeration Techniques," Management Science, INFORMS, vol. 16(8), pages 495-508, April.
    10. Mehmet C. Demirci & Andrew J. Schaefer & H. Edwin Romeijn & Mark S. Roberts, 2012. "An Exact Method for Balancing Efficiency and Equity in the Liver Allocation Hierarchy," INFORMS Journal on Computing, INFORMS, vol. 24(2), pages 260-275, May.
    11. James E. Stahl & Nan Kong & Steven M. Shechter & Andrew J. Schaefer & Mark S. Roberts, 2005. "A Methodological Framework for Optimally Reorganizing Liver Transplant Regions," Medical Decision Making, , vol. 25(1), pages 35-46, January.
    12. Anuj Mehrotra & Ellis L. Johnson & George L. Nemhauser, 1998. "An Optimization Based Heuristic for Political Districting," Management Science, INFORMS, vol. 44(8), pages 1100-1114, August.
    13. Jacques A. Ferland & Gilles Guénette, 1990. "Decision Support System for the School Districting Problem," Operations Research, INFORMS, vol. 38(1), pages 15-21, February.
    14. S. W. Hess & J. B. Weaver & H. J. Siegfeldt & J. N. Whelan & P. A. Zitlau, 1965. "Nonpartisan Political Redistricting by Computer," Operations Research, INFORMS, vol. 13(6), pages 998-1006, December.
    15. Oguzhan Alagoz & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2007. "Determining the Acceptance of Cadaveric Livers Using an Implicit Model of the Waiting List," Operations Research, INFORMS, vol. 55(1), pages 24-36, February.
    16. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sinem Savaşer & Ömer Burak Kınay & Bahar Yetis Kara & Pelin Cay, 2019. "Organ transplantation logistics: a case for Turkey," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 327-356, June.
    2. Shubham Akshat & Sommer E. Gentry & S. Raghavan, 2024. "Heterogeneous donor circles for fair liver transplant allocation," Health Care Management Science, Springer, vol. 27(1), pages 20-45, March.
    3. Ozge Ceren Ersoy & Diwakar Gupta & Timothy Pruett, 2021. "A critical look at the U.S. deceased‐donor organ procurement and utilization system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 3-29, February.
    4. Tinglong Dai & Ronghuo Zheng & Katia Sycara, 2020. "Jumping the Line, Charitably: Analysis and Remedy of Donor-Priority Rule," Management Science, INFORMS, vol. 66(2), pages 622-641, February.
    5. Swamy, Rahul & King, Douglas M. & Ludden, Ian G. & Dobbs, Kiera W. & Jacobson, Sheldon H., 2024. "A practical optimization framework for political redistricting: A case study in Arizona," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    6. Sandoval, M. Gabriela & Álvarez-Miranda, Eduardo & Pereira, Jordi & Ríos-Mercado, Roger Z. & Díaz, Juan A., 2022. "A novel districting design approach for on-time last-mile delivery: An application on an express postal company," Omega, Elsevier, vol. 113(C).
    7. Kargar, Bahareh & Pishvaee, Mir Saman & Jahani, Hamed & Sheu, Jiuh-Biing, 2020. "Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    2. Shubham Akshat & Sommer E. Gentry & S. Raghavan, 2024. "Heterogeneous donor circles for fair liver transplant allocation," Health Care Management Science, Springer, vol. 27(1), pages 20-45, March.
    3. Juan Carlos Duque & Raúl Ramos & Jordi Suriñach, 2007. "Supervised Regionalization Methods: A Survey," International Regional Science Review, , vol. 30(3), pages 195-220, July.
    4. Fernando Tavares-Pereira & José Figueira & Vincent Mousseau & Bernard Roy, 2007. "Multiple criteria districting problems," Annals of Operations Research, Springer, vol. 154(1), pages 69-92, October.
    5. Christian Haas & Lee Hachadoorian & Steven O Kimbrough & Peter Miller & Frederic Murphy, 2020. "Seed-Fill-Shift-Repair: A redistricting heuristic for civic deliberation," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-34, September.
    6. Ram Gopalan & Steven O. Kimbrough & Frederic H. Murphy & Nicholas Quintus, 2013. "The Philadelphia Districting Contest: Designing Territories for City Council Based Upon the 2010 Census," Interfaces, INFORMS, vol. 43(5), pages 477-489, October.
    7. Hyun Kim & Yongwan Chun & Kamyoung Kim, 2015. "Delimitation of Functional Regions Using a p-Regions Problem Approach," International Regional Science Review, , vol. 38(3), pages 235-263, July.
    8. Eduardo Álvarez-Miranda & Camilo Campos-Valdés & Maurcio Morales Quiroga & Matías Moreno-Faguett & Jordi Pereira, 2020. "A Multi-Criteria Pen for Drawing Fair Districts: When Democratic and Demographic Fairness Matter," Mathematics, MDPI, vol. 8(9), pages 1-26, August.
    9. Swamy, Rahul & King, Douglas M. & Ludden, Ian G. & Dobbs, Kiera W. & Jacobson, Sheldon H., 2024. "A practical optimization framework for political redistricting: A case study in Arizona," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    10. Sinem Savaşer & Ömer Burak Kınay & Bahar Yetis Kara & Pelin Cay, 2019. "Organ transplantation logistics: a case for Turkey," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 327-356, June.
    11. Federica Ricca & Andrea Scozzari & Bruno Simeone, 2013. "Political Districting: from classical models to recent approaches," Annals of Operations Research, Springer, vol. 204(1), pages 271-299, April.
    12. Ozge Ceren Ersoy & Diwakar Gupta & Timothy Pruett, 2021. "A critical look at the U.S. deceased‐donor organ procurement and utilization system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 3-29, February.
    13. Han, Jialin & Hu, Yaoguang & Mao, Mingsong & Wan, Shuping, 2020. "A multi-objective districting problem applied to agricultural machinery maintenance service network," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1120-1130.
    14. Sebastián Moreno & Jordi Pereira & Wilfredo Yushimito, 2020. "A hybrid K-means and integer programming method for commercial territory design: a case study in meat distribution," Annals of Operations Research, Springer, vol. 286(1), pages 87-117, March.
    15. Brian Lunday & Hanif Sherali & Kevin Lunday, 2012. "The coastal seaspace patrol sector design and allocation problem," Computational Management Science, Springer, vol. 9(4), pages 483-514, November.
    16. Rui Fragoso & Conceição Rego & Vladimir Bushenkov, 2016. "Clustering of Territorial Areas: A Multi-Criteria Districting Problem," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(2), pages 179-198, December.
    17. Xin Tang & Ameur Soukhal & Vincent T’kindt, 2014. "Preprocessing for a map sectorization problem by means of mathematical programming," Annals of Operations Research, Springer, vol. 222(1), pages 551-569, November.
    18. Sahar Ahmadvand & Mir Saman Pishvaee, 2018. "An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach," Health Care Management Science, Springer, vol. 21(4), pages 587-603, December.
    19. Baghersad, Milad & Emadikhiav, Mohsen & Huang, C. Derrick & Behara, Ravi S., 2023. "Modularity maximization to design contiguous policy zones for pandemic response," European Journal of Operational Research, Elsevier, vol. 304(1), pages 99-112.
    20. Alexander Butsch & Jörg Kalcsics & Gilbert Laporte, 2014. "Districting for Arc Routing," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 809-824, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:45:y:2015:i:5:p:462-480. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.