{"title":"Managing virtual appointments in chronic care","authors":"A. Bayram, S. Deo, S. Iravani, K. Smilowitz","doi":"10.1080/24725579.2019.1638849","DOIUrl":null,"url":null,"abstract":"Abstract Virtual appointments between patients and healthcare providers can offer a cost-effective alternative to traditional office appointments for managing chronic conditions. Virtual appointments increase contact with the physician by either substituting or complementing office appointments, leading to improved health outcomes. The true value of virtual appointments cannot be realized until they are truly integrated with the office appointment systems. In this study, we introduce a capacity allocation model to study the use of virtual appointments in a chronic care setting. Specifically, we develop a finite horizon stochastic dynamic program to determine which patients to schedule for office and virtual appointments that maximizes aggregate health benefits across a cohort of patients. Optimal policy characterization for this problem is challenging. We find that, under certain conditions, a myopic heuristic, where the sickest patients are scheduled for office appointments and the next sickest patients are scheduled for virtual appointments, is optimal. We show that the myopic heuristic performs well even in more general settings. Our findings further show that virtual appointments serve a dual purpose: they may reduce the number of office appointments and may trigger follow-up office appointments.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"1 - 17"},"PeriodicalIF":1.5000,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2019.1638849","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IISE Transactions on Healthcare Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24725579.2019.1638849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 6
Abstract
Abstract Virtual appointments between patients and healthcare providers can offer a cost-effective alternative to traditional office appointments for managing chronic conditions. Virtual appointments increase contact with the physician by either substituting or complementing office appointments, leading to improved health outcomes. The true value of virtual appointments cannot be realized until they are truly integrated with the office appointment systems. In this study, we introduce a capacity allocation model to study the use of virtual appointments in a chronic care setting. Specifically, we develop a finite horizon stochastic dynamic program to determine which patients to schedule for office and virtual appointments that maximizes aggregate health benefits across a cohort of patients. Optimal policy characterization for this problem is challenging. We find that, under certain conditions, a myopic heuristic, where the sickest patients are scheduled for office appointments and the next sickest patients are scheduled for virtual appointments, is optimal. We show that the myopic heuristic performs well even in more general settings. Our findings further show that virtual appointments serve a dual purpose: they may reduce the number of office appointments and may trigger follow-up office appointments.
期刊介绍:
IISE Transactions on Healthcare Systems Engineering aims to foster the healthcare systems community by publishing high quality papers that have a strong methodological focus and direct applicability to healthcare systems. Published quarterly, the journal supports research that explores: · Healthcare Operations Management · Medical Decision Making · Socio-Technical Systems Analysis related to healthcare · Quality Engineering · Healthcare Informatics · Healthcare Policy We are looking forward to accepting submissions that document the development and use of industrial and systems engineering tools and techniques including: · Healthcare operations research · Healthcare statistics · Healthcare information systems · Healthcare work measurement · Human factors/ergonomics applied to healthcare systems Research that explores the integration of these tools and techniques with those from other engineering and medical disciplines are also featured. We encourage the submission of clinical notes, or practice notes, to show the impact of contributions that will be published. We also encourage authors to collect an impact statement from their clinical partners to show the impact of research in the clinical practices.