Albutt, A, O'Hara, J orcid.org/0000-0001-5551-9975, Conner, M orcid.org/0000-0002-6229-8143 et al. (1 more author) (2021) Can Routinely Collected, Patient-Reported Wellness Predict National Early Warning Scores? A Multilevel Modeling Approach. Journal of Patient Safety, 17 (8). pp. 548-552. ISSN 1549-8417
Abstract
Objective:
Measures exist to improve early recognition of and response to deteriorating patients in hospital. However, management of critical illness remains a problem globally; in the United Kingdom, 7% of the deaths reported to National Reporting and Learning System from acute hospitals in 2015 related to failure to recognize or respond to deterioration. The current study explored whether routinely recording patient-reported wellness is associated with objective measures of physiology to support early recognition of hospitalized deteriorating patients.
Methods:
A prospective observation study design was used. Nurses on four inpatient wards were invited to participate and record patient-reported wellness during every routine observation (where possible) using an electronic observation system. Linear multilevel modeling was used to examine the relationship between patient-reported wellness, and national early warning scores (NEWS), and whether patient-reported wellness predicted subsequent NEWS.
Results:
A significant positive relationship was found between patient-reported wellness and NEWS recorded at the next observation while controlling for baseline NEWS (β = 0.180, P = 0.033). A significant positive relationship between patient-reported wellness and NEWS (β = 0.229, P = 0.005) recorded during an observation 24 hours later while controlling for baseline NEWS was also found. Patient-reported wellness added to the predictive model for subsequent NEWS.
Conclusion:
The preliminary findings suggest that patient-reported wellness may predict subsequent improvement or decline in their condition as indicated by objective measurements of physiology (NEWS). Routinely recording patient-reported wellness during observation shows promise for supporting the early recognition of clinical deterioration in practice, although confirmation in larger-scale studies is required.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) |
Keywords: | clinical deterioration; patient-centered care; multilevel modeling |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Psychology (Leeds) |
Funding Information: | Funder Grant number NIHR National Inst Health Research M24387 |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Feb 2022 14:07 |
Last Modified: | 09 Feb 2022 14:07 |
Status: | Published |
Publisher: | Lippincott, Williams & Wilkins |
Identification Number: | 10.1097/pts.0000000000000672 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:183341 |