Temporal Analysis of Physicians' EHR Workflow during Outpatient Visits

Calvitti, Alan; Farber, Neil J.; Chen, Yunan; Zuest, Danielle; Liu, Lin; Bell, Kristin; Gray, Barbara; Agha, Zia

doi:10.1109/hisb.2012.65

Cited by 4 publications

(4 citation statements)

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“…Our software drives data collection from Kinect and Microcone, and it is designed to be extensible, allowing easy integration of additional sensors. 6 Figure 3 shows ChronoSense in action during a recording session. ChronoSense runs on any Windows machine that supports Kinect and Microcone.…”

Section: Morae Recorder (See Footnote 3) This Usabilitymentioning

confidence: 99%

“…What is needed are careful analyses of how the EHR is used by physicians during patient encounters and how physicians and patients communicate. Recent approaches [6] started to analyze and quantify speech, gaze, body movements, etc. and represent very promising ways to complement classic software usability.…”

Section: Introductionmentioning

confidence: 99%

“…http://www.smivision.com/redm 6. Although we are not using any additional devices for sensing activity in the medical office, ChronoSense already supports data collection with LeapMotion for tracking finger movements (http:// leapmotion.com), and the development version of the new Kinect for Windows v2.…”

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confidence: 99%

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LAB-IN-A-BOX: semi-automatic tracking of activity in the medical office

Weibel

Rick

Emmenegger

et al. 2014

Pers Ubiquit Comput

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Patient-centered healthcare and increased efficiency are major goals of modern medicine, and physicianpatient interaction and communication are a cornerstone of clinical encounters. The introduction of the electronic health record (EHR) has been a key component in shaping not only organization, clinical workflow and ultimately physicians' clinical decision making, but also patientphysician communication in the medical office. In order to inform the design of future EHR interfaces and assess their impact on patient-centered healthcare, designers and researchers must understand the multimodal nature of the complex physician-patient-EHR system interaction. However, characterizing multimodal activity is difficult and expensive, often requiring manual coding of hours of video data. We present our Lab-in-a-Box solution that enables the capture of multimodal activity in real-world settings. We focus here on the medical office where our Lab-in-a-Box system exploits a range of sensors to track computer-based activity, speech interaction, visual attention and body movements, and automatically synchronize and segment this data. The fusion of multiple sensors allows us to derive initial activity segmentation and to visualize it for further interactive analysis. By empowering researchers with cutting-edge data collection tools and accelerating analysis of multimodal activity in the medical office, our Lab-in-a-Box has the potential to uncover important insights and inform the next generation of Health IT systems.

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Section: Morae Recorder (See Footnote 3) This Usabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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LAB-IN-A-BOX: semi-automatic tracking of activity in the medical office

Weibel

Rick

Emmenegger

et al. 2014

Pers Ubiquit Comput

Self Cite

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show abstract

“…Because structured and unstructured data can be hard to reconcile, EHRs often store and display information in separate pages or windows, and physicians have to synthesize the patient narrative by navigating across a variety of sources [3,44]. This creates increased cognitive burden to discover unstructured information, and studies have shown that clinicians spend more time reading past notes than doing any other activity in the EHR [12]. Further, the fragmented interfaces hinder comprehensibility and necessitate frequent taskswitching [15,31,63].…”

Section: Introductionmentioning

confidence: 99%

MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records

Murray,

Gopinath,

Agrawal

et al. 2021

Preprint

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Clinical documentation can be transformed by Electronic HealthRecords, yet the documentation process is still a tedious, timeconsuming, and error-prone process. Clinicians are faced with multi-faceted requirements and fragmented interfaces for information exploration and documentation. These challenges are only exacerbated in the Emergency Department-clinicians often see 35 patients in one shift, during which they have to synthesize an often previously unknown patient's medical records in order to reach a tailored diagnosis and treatment plan. To better support this information synthesis, clinical documentation tools must enable rapid contextual access to the patient's medical record. MedKnowts is an integrated note-taking editor and information retrieval system which unifies the documentation and search process and provides concise synthesized concept-oriented slices of the patient's medical record. MedKnowts automatically captures structured data while still allowing users the flexibility of natural language. Med-Knowts leverages this structure to enable easier parsing of long notes, auto-populated text, and proactive information retrieval, easing the documentation burden.

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Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center

Perkins

Markowitz

2020

Methods in Molecular Biology

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Temporal Analysis of Physicians' EHR Workflow during Outpatient Visits

Cited by 4 publications

References 1 publication

LAB-IN-A-BOX: semi-automatic tracking of activity in the medical office

LAB-IN-A-BOX: semi-automatic tracking of activity in the medical office

MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records

Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center

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