L Hua, S Wang1, Y Gong2. 1. Department of Nursing, Tianjin First Central Hospital , Tianjin, China. 2. School of Biomedical Informatics, University of Texas Health Science Center , Houston, TX, USA.
Abstract
BACKGROUND: Structured data entry pervades computerized patient safety event reporting systems and serves as a key component in collecting patient-related information in electronic health records. Clinicians would spend more time being with patients and arrive at a high probability of proper diagnosis and treatment, if data entry can be completed efficiently and effectively. Historically it has been proven text prediction holds potential for human performance regarding data entry in a variety of research areas. OBJECTIVE: This study aimed at examining a function of text prediction proposed for increasing efficiency and data quality in structured data entry. METHODS: We employed a two-group randomized design with fifty-two nurses in this usability study. Each participant was assigned the task of reporting patient falls by answering multiple choice questions either with or without the text prediction function. t-test statistics and linear regression model were applied to analyzing the results of the two groups. RESULTS: While both groups of participants exhibited a good capacity of accomplishing the assigned task, the results were an overall 13.0% time reduction and 3.9% increase of response accuracy for the group utilizing the prediction function. CONCLUSION: As a primary attempt investigating the effectiveness of text prediction in healthcare, study findings validated the necessity of text prediction to structured date entry, and laid the ground for further research improving the effectiveness of text prediction in clinical settings.
RCT Entities:
BACKGROUND: Structured data entry pervades computerized patient safety event reporting systems and serves as a key component in collecting patient-related information in electronic health records. Clinicians would spend more time being with patients and arrive at a high probability of proper diagnosis and treatment, if data entry can be completed efficiently and effectively. Historically it has been proven text prediction holds potential for human performance regarding data entry in a variety of research areas. OBJECTIVE: This study aimed at examining a function of text prediction proposed for increasing efficiency and data quality in structured data entry. METHODS: We employed a two-group randomized design with fifty-two nurses in this usability study. Each participant was assigned the task of reporting patient falls by answering multiple choice questions either with or without the text prediction function. t-test statistics and linear regression model were applied to analyzing the results of the two groups. RESULTS: While both groups of participants exhibited a good capacity of accomplishing the assigned task, the results were an overall 13.0% time reduction and 3.9% increase of response accuracy for the group utilizing the prediction function. CONCLUSION: As a primary attempt investigating the effectiveness of text prediction in healthcare, study findings validated the necessity of text prediction to structured date entry, and laid the ground for further research improving the effectiveness of text prediction in clinical settings.
Entities:
Keywords:
Structured data entry; patient safety event reporting; performance measurement; text prediction; usability
Authors: Cindy Gevarter; Mark F O'Reilly; Laura Rojeski; Nicolette Sammarco; Russell Lang; Giulio E Lancioni; Jeff Sigafoos Journal: Res Dev Disabil Date: 2013-10-18
Authors: M S Tuttle; N E Olson; K D Keck; W G Cole; M S Erlbaum; D D Sherertz; C G Chute; P L Elkin; G E Atkin; B H Kaihoi; C Safran; D Rind; V Law Journal: Methods Inf Med Date: 1998-11 Impact factor: 2.176