Itai Gurvich, K. O’Leary, Lu Wang, Jan A. Van Mieghem
{"title":"Collaboration, Interruptions and Changeover Times: Workflow Model and Empirical Study of Hospitalist Charting","authors":"Itai Gurvich, K. O’Leary, Lu Wang, Jan A. Van Mieghem","doi":"10.2139/ssrn.2616926","DOIUrl":null,"url":null,"abstract":"Collaboration is important in services, but may lead to interruptions. Professionals exercise discretion on whether to preempt individual tasks to switch to collaborative tasks. Task switching can introduce setup times, often mental and unobservable, when resuming the preempted task and thus can increase workload.We analyze and quantify how collaboration, through interruptions and setup times, affects workload. We introduce an episodal workflow model that captures the interruption dynamics — each switch and the episode of work it preempts — present in settings where collaboration and multitasking is paramount. We then deploy the model in a field study of hospital medicine physicians — “hospitalists.” A hospitalist’s patient-care routine includes visiting patients and consulting with other caregivers to guide patient diagnosis and treatment.A rigorous empirical analysis is presented using a dataset assembled from direct observation of physician activity and pager-log data. We estimate that a hospitalist incurs a total setup time of 5min per patient per day, which represents a significant 20% of the workload: caring for 14 patients per day, a hospitalist spends more than one hour each day on setups. Switches causally lead to longer documentation time in general but the magnitude of the effect depends on the trigger: when the switch is triggered by the hospitalist the setup time is smaller.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Demand & Supply in Health Economics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2616926","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Collaboration is important in services, but may lead to interruptions. Professionals exercise discretion on whether to preempt individual tasks to switch to collaborative tasks. Task switching can introduce setup times, often mental and unobservable, when resuming the preempted task and thus can increase workload.We analyze and quantify how collaboration, through interruptions and setup times, affects workload. We introduce an episodal workflow model that captures the interruption dynamics — each switch and the episode of work it preempts — present in settings where collaboration and multitasking is paramount. We then deploy the model in a field study of hospital medicine physicians — “hospitalists.” A hospitalist’s patient-care routine includes visiting patients and consulting with other caregivers to guide patient diagnosis and treatment.A rigorous empirical analysis is presented using a dataset assembled from direct observation of physician activity and pager-log data. We estimate that a hospitalist incurs a total setup time of 5min per patient per day, which represents a significant 20% of the workload: caring for 14 patients per day, a hospitalist spends more than one hour each day on setups. Switches causally lead to longer documentation time in general but the magnitude of the effect depends on the trigger: when the switch is triggered by the hospitalist the setup time is smaller.