Literature DB >> 29295214

Design a Learning-Oriented Fall Event Reporting System Based on Kirkpatrick Model.

Sicheng Zhou1, Hong Kang1, Yang Gong1.   

Abstract

Patient fall has been a severe problem in healthcare facilities around the world due to its prevalence and cost. Routine fall prevention training programs are not as effective as expected. Using event reporting systems is the trend for reducing patient safety events such as falls, although some limitations of the systems exist at current stage. We summarized these limitations through literature review, and developed an improved web-based fall event reporting system. The Kirkpatrick model, widely used in the business area for training program evaluation, has been integrated during the design of our system. Different from traditional event reporting systems that only collect and store the reports, our system automatically annotates and analyzes the reported events, and provides users with timely knowledge support specific to the reported event. The paper illustrates the design of our system and how its features are intended to reduce patient falls by learning from previous errors.

Entities:  

Keywords:  Accidental Falls; Incidental Findings; Patient Safety

Mesh:

Year:  2017        PMID: 29295214

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  3 in total

1.  Toward safer health care: a review strategy of FDA medical device adverse event database to identify and categorize health information technology related events.

Authors:  Hong Kang; Ju Wang; Bin Yao; Sicheng Zhou; Yang Gong
Journal:  JAMIA Open       Date:  2018-10-12

2.  An automated pipeline for analyzing medication event reports in clinical settings.

Authors:  Sicheng Zhou; Hong Kang; Bin Yao; Yang Gong
Journal:  BMC Med Inform Decis Mak       Date:  2018-12-07       Impact factor: 2.796

3.  A prototype of knowledge-based patient safety event reporting and learning system.

Authors:  Hong Kang; Sicheng Zhou; Bin Yao; Yang Gong
Journal:  BMC Med Inform Decis Mak       Date:  2018-12-07       Impact factor: 2.796

  3 in total

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