{"title":"开发医学试验招聘管理与规划决策支持系统","authors":"Natalie de Bruyn, S. Grobbelaar","doi":"10.1109/SAIBMEC.2018.8363185","DOIUrl":null,"url":null,"abstract":"Randomized Controlled Trials (RCT) are a key method through which the effects of healthcare interventions are evaluated. However, it has been found that the management of such trials are fraught with challenges. Trials take longer than expected to reach completion and many trials fail due to not being able to reach the planned sample size within the set duration and funding allocated to the trial. If a trial is extended to reach a credible sample size, extra funding is required. This lagging of trial conclusion leads to the delay of the use of the trial results in clinical practice. It has also been found that after rapid recruitment, staff and facilities are under pressure to accommodate trial participants returning for follow-up assessments and additional staff must be hired on short notice. The aim of this paper is to present the outcome of a study to develop a decision support system that will aid in the management of a medical trial. The tool is designed and developed by following the system development life cycle (SDLC) methodology. The tool was developed by partnering with the South African Medical Research Council (SAMRC) who is currently conducting a medical trial regarding AIDS and diabetic treatment combined with counseling.","PeriodicalId":165912,"journal":{"name":"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Developing a decision support system for medical trial recruitment management and planning\",\"authors\":\"Natalie de Bruyn, S. Grobbelaar\",\"doi\":\"10.1109/SAIBMEC.2018.8363185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Randomized Controlled Trials (RCT) are a key method through which the effects of healthcare interventions are evaluated. However, it has been found that the management of such trials are fraught with challenges. Trials take longer than expected to reach completion and many trials fail due to not being able to reach the planned sample size within the set duration and funding allocated to the trial. If a trial is extended to reach a credible sample size, extra funding is required. This lagging of trial conclusion leads to the delay of the use of the trial results in clinical practice. It has also been found that after rapid recruitment, staff and facilities are under pressure to accommodate trial participants returning for follow-up assessments and additional staff must be hired on short notice. The aim of this paper is to present the outcome of a study to develop a decision support system that will aid in the management of a medical trial. The tool is designed and developed by following the system development life cycle (SDLC) methodology. The tool was developed by partnering with the South African Medical Research Council (SAMRC) who is currently conducting a medical trial regarding AIDS and diabetic treatment combined with counseling.\",\"PeriodicalId\":165912,\"journal\":{\"name\":\"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAIBMEC.2018.8363185\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAIBMEC.2018.8363185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Developing a decision support system for medical trial recruitment management and planning
Randomized Controlled Trials (RCT) are a key method through which the effects of healthcare interventions are evaluated. However, it has been found that the management of such trials are fraught with challenges. Trials take longer than expected to reach completion and many trials fail due to not being able to reach the planned sample size within the set duration and funding allocated to the trial. If a trial is extended to reach a credible sample size, extra funding is required. This lagging of trial conclusion leads to the delay of the use of the trial results in clinical practice. It has also been found that after rapid recruitment, staff and facilities are under pressure to accommodate trial participants returning for follow-up assessments and additional staff must be hired on short notice. The aim of this paper is to present the outcome of a study to develop a decision support system that will aid in the management of a medical trial. The tool is designed and developed by following the system development life cycle (SDLC) methodology. The tool was developed by partnering with the South African Medical Research Council (SAMRC) who is currently conducting a medical trial regarding AIDS and diabetic treatment combined with counseling.