Abdulrahman A Alhaider, Nathan Lau, Paul B. Davenport, Stimis R. Smith, Darrell W. DeWeese
{"title":"医院内患者运输的态势感知分布和事务建模与仿真","authors":"Abdulrahman A Alhaider, Nathan Lau, Paul B. Davenport, Stimis R. Smith, Darrell W. DeWeese","doi":"10.1177/2327857923121010","DOIUrl":null,"url":null,"abstract":"Intrahospital transports rely on effective transmission of information between medical staff and information systems to support Distributed Situation Awareness (DSA) on patient status and transport requirements. This study presents the preliminary results a simulation model combining discrete event simulation (DES) and agent-based modeling (ABM) to quantify SA distribution and transactions for intrahospital transportation. The simulation model captured the transport requests, transport processes, and knowledge distribution and transactions between (human or machine) agents for intrahospital transports. Specifically, this paper presents the simulation results for the successful patient transport from 17 hospital inpatient units to the radiology department for (1) transport times and (2) transport cancellations. One-way t-tests did not reveal any significant differences in average transport time and number of cancelations between outputs of 100 simulation replications and historical data for 18-month operation. These results indicate that the simulation model represents real-world operation that can subsequently be used to test potential intervention to improve DSA in patient flow.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"40 - 42"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling and simulation for situation awareness distribution and transactions for intrahospital patient transports\",\"authors\":\"Abdulrahman A Alhaider, Nathan Lau, Paul B. Davenport, Stimis R. Smith, Darrell W. DeWeese\",\"doi\":\"10.1177/2327857923121010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intrahospital transports rely on effective transmission of information between medical staff and information systems to support Distributed Situation Awareness (DSA) on patient status and transport requirements. This study presents the preliminary results a simulation model combining discrete event simulation (DES) and agent-based modeling (ABM) to quantify SA distribution and transactions for intrahospital transportation. The simulation model captured the transport requests, transport processes, and knowledge distribution and transactions between (human or machine) agents for intrahospital transports. Specifically, this paper presents the simulation results for the successful patient transport from 17 hospital inpatient units to the radiology department for (1) transport times and (2) transport cancellations. One-way t-tests did not reveal any significant differences in average transport time and number of cancelations between outputs of 100 simulation replications and historical data for 18-month operation. These results indicate that the simulation model represents real-world operation that can subsequently be used to test potential intervention to improve DSA in patient flow.\",\"PeriodicalId\":74550,\"journal\":{\"name\":\"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare\",\"volume\":\"12 1\",\"pages\":\"40 - 42\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/2327857923121010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/2327857923121010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and simulation for situation awareness distribution and transactions for intrahospital patient transports
Intrahospital transports rely on effective transmission of information between medical staff and information systems to support Distributed Situation Awareness (DSA) on patient status and transport requirements. This study presents the preliminary results a simulation model combining discrete event simulation (DES) and agent-based modeling (ABM) to quantify SA distribution and transactions for intrahospital transportation. The simulation model captured the transport requests, transport processes, and knowledge distribution and transactions between (human or machine) agents for intrahospital transports. Specifically, this paper presents the simulation results for the successful patient transport from 17 hospital inpatient units to the radiology department for (1) transport times and (2) transport cancellations. One-way t-tests did not reveal any significant differences in average transport time and number of cancelations between outputs of 100 simulation replications and historical data for 18-month operation. These results indicate that the simulation model represents real-world operation that can subsequently be used to test potential intervention to improve DSA in patient flow.