BACKGROUND: Early warning scores (EWS) are an integral part of the care of acutely ill patients. Unfortunately, in the few studies where the accuracy of EWS has been tested it has been found to be lacking, with serious implications for quality of care. AIM: To determine if the provision of computer-aided scoring could increase the accuracy and efficiency of EWS calculations, when compared with the traditional pen-and-paper method, and to determine if it was acceptable to users. DESIGN: 26 nurses from two surgical assessment wards in two hospitals were studied. The study was conducted in three phases. Phase 1--a classroom-based exercise where nurses were given ten patient vignettes and asked to derive EWS using traditional pen-and-paper methods; Phase 2--the same as phase 1, but using a hand-held computer to derive EWS; Phase 3--the same as phase 2, but was a follow-up exercise undertaken in the ward environment, 4 weeks after computer-aided scoring was implemented in the two wards. Each phase closed with a user perception/attitudes questionnaire. RESULTS: Accuracy and efficiency--phase 1 was associated with a significantly lower overall accuracy (152/260, 58%) compared with phase 2 (96%; difference in proportions 38%, 95% confidence interval 31-44%, P < 0.0001). There was a small but significant reduction in accuracy from phase 2 (96%) to phase 3 (88%) (8% difference, P=0.006). The mean time to derive an EWS reduced from 37.9 seconds in phase 1 to 35.1 seconds in phase 2 (P=0.016), down to 24.0 seconds in phase 3 (P<0.0001). User acceptability: in phase 1, nurses favoured the pen-and-paper method in all respects except accuracy. In phase 2, nurses' views shifted significantly in favour of the hand-held computer, with little deterioration in the follow-up phase 3. CONCLUSIONS: A hand-held computer helps to improve the accuracy and efficiency of EWS in acute hospital care and is acceptable to nurses.
BACKGROUND: Early warning scores (EWS) are an integral part of the care of acutely ill patients. Unfortunately, in the few studies where the accuracy of EWS has been tested it has been found to be lacking, with serious implications for quality of care. AIM: To determine if the provision of computer-aided scoring could increase the accuracy and efficiency of EWS calculations, when compared with the traditional pen-and-paper method, and to determine if it was acceptable to users. DESIGN: 26 nurses from two surgical assessment wards in two hospitals were studied. The study was conducted in three phases. Phase 1--a classroom-based exercise where nurses were given ten patient vignettes and asked to derive EWS using traditional pen-and-paper methods; Phase 2--the same as phase 1, but using a hand-held computer to derive EWS; Phase 3--the same as phase 2, but was a follow-up exercise undertaken in the ward environment, 4 weeks after computer-aided scoring was implemented in the two wards. Each phase closed with a user perception/attitudes questionnaire. RESULTS: Accuracy and efficiency--phase 1 was associated with a significantly lower overall accuracy (152/260, 58%) compared with phase 2 (96%; difference in proportions 38%, 95% confidence interval 31-44%, P < 0.0001). There was a small but significant reduction in accuracy from phase 2 (96%) to phase 3 (88%) (8% difference, P=0.006). The mean time to derive an EWS reduced from 37.9 seconds in phase 1 to 35.1 seconds in phase 2 (P=0.016), down to 24.0 seconds in phase 3 (P<0.0001). User acceptability: in phase 1, nurses favoured the pen-and-paper method in all respects except accuracy. In phase 2, nurses' views shifted significantly in favour of the hand-held computer, with little deterioration in the follow-up phase 3. CONCLUSIONS: A hand-held computer helps to improve the accuracy and efficiency of EWS in acute hospital care and is acceptable to nurses.
Authors: Muhammad Faisal; Donald Richardson; Andrew J Scally; Robin Howes; Kevin Beatson; Kevin Speed; Mohammed A Mohammed Journal: CMAJ Date: 2019-04-08 Impact factor: 8.262
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Authors: Muhammad Faisal; Andrew J Scally; Natalie Jackson; Donald Richardson; Kevin Beatson; Robin Howes; Kevin Speed; Madhav Menon; Jeremey Daws; Judith Dyson; Claire Marsh; Mohammed A Mohammed Journal: BMJ Open Date: 2018-12-06 Impact factor: 2.692
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