Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study
Transportation of patients is a key hospital operational activity. During a large construction project, our patient admission and prep area will relocate from immediately adjacent to the operating room suite to another floor of a different building. Transportation will require extra distance and ele...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer-Verlag
2016
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| Online Access: | http://hdl.handle.net/1721.1/104855 https://orcid.org/0000-0002-1994-4875 |
| _version_ | 1826214079246630912 |
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| author | Segev, Danny Dunn, Peter F Sandberg, Warren S Levi, Retsef |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Segev, Danny Dunn, Peter F Sandberg, Warren S Levi, Retsef |
| author_sort | Segev, Danny |
| collection | MIT |
| description | Transportation of patients is a key hospital operational activity. During a large construction project, our patient admission and prep area will relocate from immediately adjacent to the operating room suite to another floor of a different building. Transportation will require extra distance and elevator trips to deliver patients and recycle transporters (specifically: personnel who transport patients). Management intuition suggested that starting all 52 first cases simultaneously would require many of the 18 available elevators. To test this, we developed a data-driven simulation tool to allow decision makers to simultaneously address planning and evaluation questions about patient transportation. We coded a stochastic simulation tool for a generalized model treating all factors contributing to the process as JAVA objects. The model includes elevator steps, explicitly accounting for transporter speed and distance to be covered. We used the model for sensitivity analyses of the number of dedicated elevators, dedicated transporters, transporter speed and the planned process start time on lateness of OR starts and the number of cases with serious delays (i.e., more than 15 min). Allocating two of the 18 elevators and 7 transporters reduced lateness and the number of cases with serious delays. Additional elevators and/or transporters yielded little additional benefit. If the admission process produced ready-for-transport patients 20 min earlier, almost all delays would be eliminated. Modeling results contradicted clinical managers’ intuition that starting all first cases on time requires many dedicated elevators. This is explained by the principle of decreasing marginal returns for increasing capacity when there are other limiting constraints in the system. |
| first_indexed | 2024-09-23T15:59:29Z |
| format | Article |
| id | mit-1721.1/104855 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:59:29Z |
| publishDate | 2016 |
| publisher | Springer-Verlag |
| record_format | dspace |
| spelling | mit-1721.1/1048552022-10-02T05:34:50Z Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study Segev, Danny Dunn, Peter F Sandberg, Warren S Levi, Retsef Sloan School of Management Levi, Retsef Transportation of patients is a key hospital operational activity. During a large construction project, our patient admission and prep area will relocate from immediately adjacent to the operating room suite to another floor of a different building. Transportation will require extra distance and elevator trips to deliver patients and recycle transporters (specifically: personnel who transport patients). Management intuition suggested that starting all 52 first cases simultaneously would require many of the 18 available elevators. To test this, we developed a data-driven simulation tool to allow decision makers to simultaneously address planning and evaluation questions about patient transportation. We coded a stochastic simulation tool for a generalized model treating all factors contributing to the process as JAVA objects. The model includes elevator steps, explicitly accounting for transporter speed and distance to be covered. We used the model for sensitivity analyses of the number of dedicated elevators, dedicated transporters, transporter speed and the planned process start time on lateness of OR starts and the number of cases with serious delays (i.e., more than 15 min). Allocating two of the 18 elevators and 7 transporters reduced lateness and the number of cases with serious delays. Additional elevators and/or transporters yielded little additional benefit. If the admission process produced ready-for-transport patients 20 min earlier, almost all delays would be eliminated. Modeling results contradicted clinical managers’ intuition that starting all first cases on time requires many dedicated elevators. This is explained by the principle of decreasing marginal returns for increasing capacity when there are other limiting constraints in the system. National Science Foundation (U.S.) (DMS-0732175) National Science Foundation (U.S.) (CMMI-0846554) United States. Air Force Office of Scientific Research (FA9550-08-1-0369) Singapore-MIT Alliance Massachusetts Institute of Technology. Buschbaum Research Fund. 2016-10-19T18:07:42Z 2016-10-19T18:07:42Z 2012-02 2011-06 2016-08-18T15:44:50Z Article http://purl.org/eprint/type/JournalArticle 1386-9620 1572-9389 http://hdl.handle.net/1721.1/104855 Segev, Danny, Levi Retsef, Peter F. Dunn, and Warren S. Sandberg. “Modeling the Impact of Changing Patient Transportation Systems on Peri-Operative Process Performance in a Large Hospital: Insights from a Computer Simulation Study.” Health Care Management Science vol. 15, no. 2 February 2012, pp. 155–169. https://orcid.org/0000-0002-1994-4875 en http://dx.doi.org/10.1007/s10729-012-9191-1 Health Care Management Science Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ Springer Science+Business Media, LLC application/pdf Springer-Verlag Springer US |
| spellingShingle | Segev, Danny Dunn, Peter F Sandberg, Warren S Levi, Retsef Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study |
| title | Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study |
| title_full | Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study |
| title_fullStr | Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study |
| title_full_unstemmed | Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study |
| title_short | Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study |
| title_sort | modeling the impact of changing patient transportation systems on peri operative process performance in a large hospital insights from a computer simulation study |
| url | http://hdl.handle.net/1721.1/104855 https://orcid.org/0000-0002-1994-4875 |
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