Search Results - "Kannampallil, Thomas"

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  1. 1

    Exposure to COVID-19 patients increases physician trainee stress and burnout by Kannampallil, Thomas G, Goss, Charles W, Evanoff, Bradley A, Strickland, Jaime R, McAlister, Rebecca P, Duncan, Jennifer

    Published in PloS one (06-08-2020)
    “…The coronavirus disease 2019 (COVID-19) pandemic has put considerable physical and emotional strain on frontline healthcare workers. Among frontline healthcare…”
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  2. 2

    Effect of acute postsurgical pain trajectories on 30-day and 1-year pain by Awadalla, Saria S, Winslow, Victoria, Avidan, Michael S, Haroutounian, Simon, Kannampallil, Thomas G

    Published in PloS one (10-06-2022)
    “…Untreated pain after surgery leads to poor patient satisfaction, longer hospital length of stay, lower health-related quality of life, and non-compliance with…”
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  3. 3

    Considering complexity in healthcare systems by Kannampallil, Thomas G., Schauer, Guido F., Cohen, Trevor, Patel, Vimla L.

    Published in Journal of biomedical informatics (01-12-2011)
    “…This figure summarizes the range of complexity of systems, highlighting four extremes as a combination of the number of components and the interrelatedness…”
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  4. 4

    A systematic review of the literature on the evaluation of handoff tools: implications for research and practice by Abraham, Joanna, Kannampallil, Thomas, Patel, Vimla L

    “…Given the complexities of the healthcare environment, efforts to develop standardized handoff practices have led to widely varying manifestations of handoff…”
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  5. 5

    Continuous real-time prediction of surgical case duration using a modular artificial neural network by Jiao, York, Xue, Bing, Lu, Chenyang, Avidan, Michael S, Kannampallil, Thomas

    Published in British journal of anaesthesia : BJA (01-05-2022)
    “…Real-time prediction of surgical duration can inform perioperative decisions and reduce surgical costs. We developed a machine learning approach that…”
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  6. 6

    Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications by Xue, Bing, Li, Dingwen, Lu, Chenyang, King, Christopher R, Wildes, Troy, Avidan, Michael S, Kannampallil, Thomas, Abraham, Joanna

    Published in JAMA network open (30-03-2021)
    “…Postoperative complications can significantly impact perioperative care management and planning. To assess machine learning (ML) models for predicting…”
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  7. 7

    Implementation and prospective performance evaluation of an intraoperative duration prediction model using high throughput real-time data by Jiao, York, Kannampallil, Thomas

    Published in BJA open (01-06-2024)
    “…Accurate real-time prediction of intraoperative duration can contribute to improved perioperative outcomes. We implemented a data pipeline for extraction of…”
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  8. 8

    Characterizing the Patterns of Electronic Health Record–Integrated Secure Messaging Use: Cross-Sectional Study by Baratta, Laura R, Harford, Derek, Sinsky, Christine A, Kannampallil, Thomas, Lou, Sunny S

    Published in Journal of medical Internet research (06-10-2023)
    “…Background Communication among health care professionals is essential for the delivery of safe clinical care. Secure messaging has rapidly emerged as a new…”
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  9. 9

    Probabilistic forecasting of surgical case duration using machine learning: model development and validation by Jiao, York, Sharma, Anshuman, Ben Abdallah, Arbi, Maddox, Thomas M, Kannampallil, Thomas

    “…Abstract Objective Accurate estimations of surgical case durations can lead to the cost-effective utilization of operating rooms. We developed a novel machine…”
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  10. 10

    Role of cognition in generating and mitigating clinical errors by Patel, Vimla L, Kannampallil, Thomas G, Shortliffe, Edward H

    Published in BMJ quality & safety (01-07-2015)
    “…Given the complexities of current clinical practice environments, strategies to reduce clinical error must appreciate that error detection and recovery are…”
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  11. 11

    Reasons for computerised provider order entry (CPOE)-based inpatient medication ordering errors: an observational study of voided orders by Abraham, Joanna, Kannampallil, Thomas G, Jarman, Alan, Sharma, Shivy, Rash, Christine, Schiff, Gordon, Galanter, William

    Published in BMJ quality & safety (01-04-2018)
    “…Medication voiding is a computerised provider order entry (CPOE)-based discontinuation mechanism that allows clinicians to identify erroneous medication…”
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  12. 12

    Bridging gaps in handoffs: A continuity of care based approach by Abraham, Joanna, Kannampallil, Thomas G., Patel, Vimla L.

    Published in Journal of biomedical informatics (01-04-2012)
    “…This represents the information sharing behavior between clinicians (sender and receiver) during handoff activity in a critical care setting. This framework…”
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  13. 13

    Predicting self-intercepted medication ordering errors using machine learning by King, Christopher Ryan, Abraham, Joanna, Fritz, Bradley A, Cui, Zhicheng, Galanter, William, Chen, Yixin, Kannampallil, Thomas

    Published in PloS one (14-07-2021)
    “…Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are…”
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  14. 14

    Cognitive informatics in biomedicine and healthcare by Patel, Vimla L., Kannampallil, Thomas G.

    Published in Journal of biomedical informatics (01-02-2015)
    “…[Display omitted] •Cognitive informatics (CI) research has its foundations in cognitive science.•Transformations seen in CI in JBI reflect the changes seen…”
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  15. 15

    Risk factors associated with physician trainee concern over missed educational opportunities during the COVID-19 pandemic by Lou, Sunny S, Goss, Charles W, Evanoff, Bradley A, Duncan, Jennifer G, Kannampallil, Thomas

    Published in BMC medical education (17-04-2021)
    “…The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in…”
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  16. 16

    Effect of number of open charts on intercepted wrong-patient medication orders in an emergency department by Kannampallil, Thomas G, Manning, John D, Chestek, David W, Adelman, Jason, Salmasian, Hojjat, Lambert, Bruce L, Galanter, William L

    “…To reduce the risk of wrong-patient errors, safety experts recommend allowing only one patient chart to be open at a time. Due to the lack of empirical…”
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  17. 17

    Measuring content overlap during handoff communication using distributional semantics: An exploratory study by Abraham, Joanna, Kannampallil, Thomas G., Srinivasan, Vignesh, Galanter, William L., Tagney, Gail, Cohen, Trevor

    Published in Journal of biomedical informatics (01-01-2017)
    “…[Display omitted] •We developed a semi-automated approach to measure handoff communication content overlap.•The approach combines conversational analysis with…”
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  18. 18

    When past is not a prologue: Adapting informatics practice during a pandemic by Kannampallil, Thomas G, Foraker, Randi E, Lai, Albert M, Woeltje, Keith F, Payne, Philip R O

    “…Abstract Data and information technology are key to every aspect of our response to the current coronavirus disease 2019 (COVID-19) pandemic—including the…”
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  19. 19

    Methodological framework for evaluating clinical processes: A cognitive informatics perspective by Kannampallil, Thomas G., Abraham, Joanna, Patel, Vimla L.

    Published in Journal of biomedical informatics (01-12-2016)
    “…[Display omitted] •Cognitive processes comprise of activities that unfold over time.•Process-based approach helps in discerning patterns of activities…”
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  20. 20

    Characterizing the pain score trajectories of hospitalized adult medical and surgical patients: a retrospective cohort study by Kannampallil, Thomas, Galanter, William L., Falck, Suzanne, Gaunt, Michael J., Gibbons, Robert D., McNutt, Robert, Odwazny, Richard, Schiff, Gordon, Vaida, Allen J., Wilkie, Diana J., Lambert, Bruce L.

    Published in Pain (Amsterdam) (01-12-2016)
    “…Pain care for hospitalized patients is often suboptimal. Representing pain scores as a graphical trajectory may provide insights into the understanding and…”
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