Abstract
Background: Innovative models of health care that involve advanced technology in the form of a digital hospital are emerging globally. Models include technology such as machine learning and smart wearables, that can be used to integrate patient data and improve continuity of care. This model may have benefits in situations where patient deterioration must be detected quickly so that a rapid response can occur such as cardiopulmonary settings. Aim: The purpose of this scoping review was to examine the evidence for a digital hospital model of care, in the context of cardiac and pulmonary settings. Design: Scoping review. Data sources: Databases searched were using PsycInfo, Ovid MEDLINE, and CINAHL. Studies written in English and containing key terms related to digital hospital and cardiopulmonary care were included. The Joanna Briggs Institute methodology for systematic reviews was used to assess the risk of bias. Results: Thirteen (13) studies fulfilled the inclusion criteria. For cardiac conditions, a deep-learning-based rapid response system warning system for predicting patient deterioration leading to cardiac arrest had up to 257% higher sensitivity than conventional methods. There was also a reduction in the number of patients who needed to be examined by a physician. Using continuous telemonitoring with a wireless real-time electrocardiogram compared with non-monitoring, there was improved initial resuscitation and 24-hour post-event survival for high-risk patients. However, there were no benefits for survival to discharge. For pulmonary conditions, a natural language processing algorithm reduced the time to asthma diagnosis, demonstrating high predictive values. Virtual inhaler education was found to be as effective as in-person education, and prescription error was reduced following the implementation of computer-based physician order entry electronic medical records and a clinical decision support tool. Conclusions: While we currently have only a brief glimpse at the impact of technology care delivery for cardiac and respiratory conditions, technology presents an opportunity to improve quality and safety in care, but only with the support of adequate infrastructure and processes. Protocol Registration: Open Science Framework (OSF: DOI 10.17605/OSF.IO/PS6ZU).
Original language | English |
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Pages (from-to) | 1057-1068 |
Number of pages | 12 |
Journal | Heart Lung and Circulation |
Volume | 32 |
Issue number | 9 |
DOIs | |
Publication status | Published - Sept 2023 |
Bibliographical note
Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Artificial intelligence
- Cardiopulmonary
- Digital decision support
- Digital hospital
- Machine learning
- Medication error
- Patient experience