RESUMEN
Rapid ethnography and data mining approaches have been used individually to study clinical workflows, but have seldom been used together to overcome the limitations inherent in either type of method. For rapid ethnography, how reliable are the findings drawn from small samples? For data mining, how accurate are the discoveries drawn from automatic analysis of big data, when compared with observable data? This paper explores the combined use of rapid ethnography and process mining, aka ethno-mining, to study and compare metrics of a typical clinical documentation task, vital signs charting. The task was performed with different electronic health records (EHRs) used in three different hospital sites. The individual methods revealed substantial discrepancies in task duration between sites. Specifically, means of 159.6(78.55), 38.2(34.9), and 431.3(283.04) seconds were captured with rapid ethnography. When process mining was used, means of 518.6(3,808), 345.5(660.6), and 119.74(210.3) seconds were found. When ethno-mining was applied instead, outliers could be identified, explained and removed. Without outliers, mean task duration was similar between sites (78.1(66.7), 72.5(78.5), and 71.7(75) seconds). Results from this work suggest that integrating rapid ethnography and data mining into a single process may provide more meaningful results than a siloed approach when studying of workflow.
Asunto(s)
Documentación , Registros Electrónicos de Salud , Antropología Cultural , Minería de Datos , Humanos , Flujo de TrabajoRESUMEN
Clinician task performance is significantly impacted by the navigational efficiency of the system interface. Here we propose and evaluate a navigational complexity framework useful for examining differences in electronic health record (EHR) interface systems and their impact on task performance. The methodological approach includes 1) expert-based methods-specifically, representational analysis (focused on interface elements), keystroke level modeling (KLM), and cognitive walkthrough; and 2) quantitative analysis of interactive behaviors based on video-captured observations. Medication administration record (MAR) tasks completed by nurses during preoperative (PreOp) patient assessment were studied across three Mayo Clinic regional campuses and three different EHR systems. By analyzing the steps executed within the interfaces involved to complete the MAR tasks, we characterized complexities in EHR navigation. These complexities were reflected in time spent on task, click counts, and screen transitions, and were found to potentially influence nurses' performance. Two of the EHR systems, employing a single screen format, required less time to complete (mean 101.5, range 106-97 s), respectively, compared to one system employing multiple screens (176 s, 73% increase). These complexities surfaced through trade-offs in cognitive processes that could potentially influence nurses' performance. Factors such as perceptual-motor activity, visual search, and memory load impacted navigational complexity. An implication of this work is that small tractable changes in interface design can substantially improve EHR navigation, overall usability, and workflow.
Asunto(s)
Registros Electrónicos de Salud , Interfaz Usuario-Computador , Humanos , Análisis y Desempeño de Tareas , Flujo de TrabajoRESUMEN
Preoperative care is a critical, yet complex, time-sensitive process. Optimization of workflow is challenging for many reasons, including a lack of standard workflow analysis methods. We sought to comprehensively characterize electronic health record-mediated preoperative nursing workflow. We employed a structured methodological framework to investigate and explain variations in the workflow. Video recording software captured 10 preoperative cases at Arizona and Florida regional referral centers. We compared the distribution of work for electronic health record tasks and off-screen tasks through quantitative analysis. Suboptimal patterns and reasons for variation were explored through qualitative analysis. Although both settings used the same electronic health record system, electronic health record tasks and off-screen tasks time distribution and patterns were notably different across two sites. Arizona nurses spent a longer time completing preoperative assessment. Electronic health record tasks occupied a higher proportion of time in Arizona, while off-screen tasks occupied a higher proportion in Florida. The contextual analysis helped to identify the variation associated with the documentation workload, preparation of the patient, and regional differences. These findings should seed hypotheses for future optimization efforts and research supporting standardization and harmonization of workflow across settings, post-electronic health record conversion.
Asunto(s)
Registros Electrónicos de Salud , Personal de Enfermería en Hospital , Atención Perioperativa , Análisis y Desempeño de Tareas , Flujo de Trabajo , Arizona , Documentación , Florida , Humanos , Grabación en VideoRESUMEN
Patient order management (POM) is a mission-critical task for perioperative workflow. Interface complexity within different EHR systems result in poor usability, increasing documentation burden. POM interfaces were compared across two systems prior to (Cerner SurgiNet) and subsequent to an EHR conversion (Epic). Here we employ a navigational complexity framework useful for examining differences in EHR interface systems. The methodological approach includes 1) expert-based methods-specifically, functional analysis, keystroke level model (KLM) and cognitive walkthrough, and 2) quantitative analysis of observed interactive user behaviors. We found differences in relation to navigational complexity with the SurgiNet interface displaying a higher number of unused POM functions, with 12 in total whereas Epic displayed 7 total functions. As reflected in all measures, Epic facilitated a more streamlined task-focused user experience. The approach enabled us to scrutinize the impact of different EHR interfaces on task performance and usability barriers subsequent to system implementation.
Asunto(s)
Registros Electrónicos de Salud , Periodo Perioperatorio , Análisis y Desempeño de Tareas , Interfaz Usuario-Computador , Flujo de Trabajo , Cognición , Documentación , HumanosRESUMEN
The impact of EHRs conversion on clinicians' daily work is crucial to evaluate the success of the intervention for Hospitals and to yield valuable insights into quality improvement. To assess the impact of different EHR systems on the preoperative nursing workflow, we used a structured framework combining quantitative time and motion study and qualitative cognitive analysis to characterize, visualize and explain the differences before and after an EHR conversion. The results showed that the EHR conversion brought a significant decrease in the patient case time and a reduced percentage of time using EHR. PreOp nurses spent a higher proportion of time caring for the patient, while the important tasks were completed in a more continuous pattern after the EHR conversion. The workflow variance was due to different nurse's cognitive process and the task time change was reduced because of some new interface features in the new EHR systems.
Asunto(s)
Flujo de Trabajo , Registros Electrónicos de Salud , Humanos , Estudios de Tiempo y MovimientoRESUMEN
Vital sign documentation is an essential part of perioperative workflow. Health information technology can introduce complexity into all facets of documentation and burden clinicians with high cognitive load3-4. The Mayo Clinic enterprise is in the process of documenting current EHR-mediated workflow prior to a system-wide EHR conversion. We compared and evaluated three different vital sign documentation interfaces in pre-operative nursing assessments at three different Mayo Clinic sites. The interfaces differed in their modes of interaction, organization of patient information and cognitive support. Analyses revealed that accessing displays and the organization of interface elements are often unintuitive and inefficient, creating unnecessary complexities when interacting with the system. These differences surface through interface workflow models and interactive behavior measures for accessing, logging and reviewing patient information. Different designs differentially mediate task performance, which can ultimately mitigate errors for complex cognitive tasks, risking patient safety. Identifying barriers to interface usability and bottlenecks in EHR-mediated workflow can lead to system redesigns that minimize cognitive load while improving patient safety and efficiency.