Scoping review exploring the impact of digital systems on processes and outcomes in the care management of acute kidney injury and progress towards establishing learning healthcare systems.
BMJ Health Care Inform
; 28(1)2021 Jul.
Article
in English
| MEDLINE | ID: covidwho-1503762
ABSTRACT
OBJECTIVES:
Digital systems have long been used to improve the quality and safety of care when managing acute kidney injury (AKI). The availability of digitised clinical data can also turn organisations and their networks into learning healthcare systems (LHSs) if used across all levels of health and care. This review explores the impact of digital systems i.e. on patients with AKI care, to gauge progress towards establishing LHSs and to identify existing gaps in the research.METHODS:
Embase, PubMed, MEDLINE, Cochrane, Scopus and Web of Science databases were searched. Studies of real-time or near real-time digital AKI management systems which reported process and outcome measures were included.RESULTS:
Thematic analysis of 43 studies showed that most interventions used real-time serum creatinine levels to trigger responses to enable risk prediction, early recognition of AKI or harm prevention by individual clinicians (micro level) or specialist teams (meso level). Interventions at system (macro level) were rare. There was limited evidence of change in outcomes.DISCUSSION:
While the benefits of real-time digital clinical data at micro level for AKI management have been evident for some time, their application at meso and macro levels is emergent therefore limiting progress towards establishing LHSs. Lack of progress is due to digital maturity, system design, human factors and policy levers.CONCLUSION:
Future approaches need to harness the potential of interoperability, data analytical advances and include multiple stakeholder perspectives to develop effective digital LHSs in order to gain benefits across the system.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Acute Kidney Injury
/
Learning Health System
/
Patient Care
Type of study:
Diagnostic study
/
Experimental Studies
/
Prognostic study
/
Qualitative research
/
Reviews
Topics:
Long Covid
Limits:
Humans
Language:
English
Year:
2021
Document Type:
Article
Affiliation country:
Bmjhci-2021-100345
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