Design and implementation of an automatic nursing assessment system based on CDSS technology

Ling Dai; Zhijun Wu; Xiaocheng Pan; Dingchang Zheng; Mengli Kang; Mingming Zhou; Guanyu Chen; Haipeng Liu; Xin Tian

doi:10.1016/j.ijmedinf.2023.105323

Design and implementation of an automatic nursing assessment system based on CDSS technology

Ling Dai, Zhijun Wu, Xiaocheng Pan, Dingchang Zheng, Mengli Kang, Mingming Zhou, Guanyu Chen, Haipeng Liu, Xin Tian

Centre for Intelligent Healthcare

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

38 Downloads (Pure)

Abstract

BACKGROUND: Various quantitative and quality assessment tools are currently used in nursing to evaluate a patient's physiological, psychological, and socioeconomic status. The results play important roles in evaluating the efficiency of healthcare, improving the treatment plans, and lowing relevant clinical risks. However, the manual process of the assessment imposes a substantial burden and can lead to errors in digitalization. To fill these gaps, we proposed an automatic nursing assessment system based on clinical decision support system (CDSS). The framework underlying the CDSS included experts, evaluation criteria, and voting roles for selecting electronic assessment sheets over paper ones.

METHODS: We developed the framework based on an expert voting flow to choose electronic assessment sheets. The CDSS was constructed based on a nursing process workflow model. A multilayer architecture with independent modules was used. The performance of the proposed system was evaluated by comparing the adverse events' incidence and the average time for regular daily assessment before and after the implementation.

RESULTS: After implementation of the system, the adverse nursing events' incidence decreased significantly from 0.43 % to 0.37 % in the first year and further to 0.27 % in the second year (p-value: 0.04). Meanwhile, the median time for regular daily assessments further decreased from 63 s to 51 s.

CONCLUSIONS: The automatic assessment system helps to reduce nurses' workload and the incidence of adverse nursing events.

Original language	English
Article number	105323
Number of pages	9
Journal	International Journal of Medical Informatics
Volume	183
Early online date	19 Dec 2023
DOIs	https://doi.org/10.1016/j.ijmedinf.2023.105323
Publication status	Published - Mar 2024

Bibliographical note

Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.
This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited..

Keywords

clinical decision support system (CDSS)
clinical information system
clinical quality management
nursing assessment
nursing informatics

ASJC Scopus subject areas

Health Informatics

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10.1016/j.ijmedinf.2023.105323Licence: CC BY

Pure-Zheng-2023-VoR (2)Final published version, 2.1 MBLicence: CC BY

Cite this

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title = "Design and implementation of an automatic nursing assessment system based on CDSS technology",

abstract = "BACKGROUND: Various quantitative and quality assessment tools are currently used in nursing to evaluate a patient's physiological, psychological, and socioeconomic status. The results play important roles in evaluating the efficiency of healthcare, improving the treatment plans, and lowing relevant clinical risks. However, the manual process of the assessment imposes a substantial burden and can lead to errors in digitalization. To fill these gaps, we proposed an automatic nursing assessment system based on clinical decision support system (CDSS). The framework underlying the CDSS included experts, evaluation criteria, and voting roles for selecting electronic assessment sheets over paper ones.METHODS: We developed the framework based on an expert voting flow to choose electronic assessment sheets. The CDSS was constructed based on a nursing process workflow model. A multilayer architecture with independent modules was used. The performance of the proposed system was evaluated by comparing the adverse events' incidence and the average time for regular daily assessment before and after the implementation.RESULTS: After implementation of the system, the adverse nursing events' incidence decreased significantly from 0.43 % to 0.37 % in the first year and further to 0.27 % in the second year (p-value: 0.04). Meanwhile, the median time for regular daily assessments further decreased from 63 s to 51 s.CONCLUSIONS: The automatic assessment system helps to reduce nurses' workload and the incidence of adverse nursing events.",

keywords = "clinical decision support system (CDSS), clinical information system, clinical quality management, nursing assessment, nursing informatics",

author = "Ling Dai and Zhijun Wu and Xiaocheng Pan and Dingchang Zheng and Mengli Kang and Mingming Zhou and Guanyu Chen and Haipeng Liu and Xin Tian",

note = "Copyright {\textcopyright} 2023 The Author(s). Published by Elsevier B.V. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.. ",

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doi = "10.1016/j.ijmedinf.2023.105323",

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AU - Dai, Ling

AU - Wu, Zhijun

AU - Pan, Xiaocheng

AU - Zheng, Dingchang

AU - Kang, Mengli

AU - Zhou, Mingming

AU - Chen, Guanyu

AU - Liu, Haipeng

AU - Tian, Xin

N1 - Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited..

PY - 2024/3

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N2 - BACKGROUND: Various quantitative and quality assessment tools are currently used in nursing to evaluate a patient's physiological, psychological, and socioeconomic status. The results play important roles in evaluating the efficiency of healthcare, improving the treatment plans, and lowing relevant clinical risks. However, the manual process of the assessment imposes a substantial burden and can lead to errors in digitalization. To fill these gaps, we proposed an automatic nursing assessment system based on clinical decision support system (CDSS). The framework underlying the CDSS included experts, evaluation criteria, and voting roles for selecting electronic assessment sheets over paper ones.METHODS: We developed the framework based on an expert voting flow to choose electronic assessment sheets. The CDSS was constructed based on a nursing process workflow model. A multilayer architecture with independent modules was used. The performance of the proposed system was evaluated by comparing the adverse events' incidence and the average time for regular daily assessment before and after the implementation.RESULTS: After implementation of the system, the adverse nursing events' incidence decreased significantly from 0.43 % to 0.37 % in the first year and further to 0.27 % in the second year (p-value: 0.04). Meanwhile, the median time for regular daily assessments further decreased from 63 s to 51 s.CONCLUSIONS: The automatic assessment system helps to reduce nurses' workload and the incidence of adverse nursing events.

AB - BACKGROUND: Various quantitative and quality assessment tools are currently used in nursing to evaluate a patient's physiological, psychological, and socioeconomic status. The results play important roles in evaluating the efficiency of healthcare, improving the treatment plans, and lowing relevant clinical risks. However, the manual process of the assessment imposes a substantial burden and can lead to errors in digitalization. To fill these gaps, we proposed an automatic nursing assessment system based on clinical decision support system (CDSS). The framework underlying the CDSS included experts, evaluation criteria, and voting roles for selecting electronic assessment sheets over paper ones.METHODS: We developed the framework based on an expert voting flow to choose electronic assessment sheets. The CDSS was constructed based on a nursing process workflow model. A multilayer architecture with independent modules was used. The performance of the proposed system was evaluated by comparing the adverse events' incidence and the average time for regular daily assessment before and after the implementation.RESULTS: After implementation of the system, the adverse nursing events' incidence decreased significantly from 0.43 % to 0.37 % in the first year and further to 0.27 % in the second year (p-value: 0.04). Meanwhile, the median time for regular daily assessments further decreased from 63 s to 51 s.CONCLUSIONS: The automatic assessment system helps to reduce nurses' workload and the incidence of adverse nursing events.

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Design and implementation of an automatic nursing assessment system based on CDSS technology

Abstract

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