scholarly journals Real-time clinical decision support based on recurrent neural networks for in-hospital acute kidney injury: external validation and model interpretation (Preprint)

10.2196/24120 ◽  
2020 ◽  
Author(s):  
Kipyo Kim ◽  
Hyeonsik Yang ◽  
Jinyeong Yi ◽  
Hyung-Eun Son ◽  
Ji-Young Ryu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Acute Kidney Injury ◽  
Decision Support ◽  
Real Time ◽  
Clinical Decision Support ◽  
Recurrent Neural Networks ◽  
External Validation ◽  
Kidney Injury ◽  
Clinical Decision ◽  
Model Interpretation

scholarly journals Acute Kidney Injury in Real Time: Prediction, Alerts, and Clinical Decision Support

Nephron ◽  
2018 ◽  
Vol 140 (2) ◽  
pp. 116-119 ◽  
Author(s):  
F. Perry Wilson ◽  
Jason H. Greenberg
Keyword(s):  
Acute Kidney Injury ◽  
Decision Support ◽  
Real Time ◽  
Clinical Decision Support ◽  
Kidney Injury ◽  
Clinical Decision ◽  
Time Prediction

scholarly journals Implementation of clinical decision support to manage acute kidney injury in secondary care: an ethnographic study

2019 ◽  
Vol 29 (5) ◽  
pp. 382-389
Author(s):  
Simon Bailey ◽  
Carianne Hunt ◽  
Adam Brisley ◽  
Susan Howard ◽  
Lynne Sykes ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Patient Safety ◽  
Quality Improvement ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Kidney Injury ◽  
Clinical Decision ◽  
Ethnographic Study ◽  
Routine Practice ◽  
Trade Offs

BackgroundOver the past decade, acute kidney injury (AKI) has become a global priority for improving patient safety and health outcomes. In the UK, a confidential inquiry into AKI led to the publication of clinical guidance and a range of policy initiatives. National patient safety directives have focused on the mandatory establishment of clinical decision support systems (CDSSs) within all acute National Health Service (NHS) trusts to improve the detection, alerting and response to AKI. We studied the organisational work of implementing AKI CDSSs within routine hospital care.MethodsAn ethnographic study comprising non-participant observation and interviews was conducted in two NHS hospitals, delivering AKI quality improvement programmes, located in one region of England. Three researchers conducted a total of 49 interviews and 150 hours of observation over an 18-month period. Analysis was conducted collaboratively and iteratively around emergent themes, relating to the organisational work of technology adoption.ResultsThe two hospitals developed and implemented AKI CDSSs using very different approaches. Nevertheless, both resulted in adaptive work and trade-offs relating to the technology, the users, the organisation and the wider system of care. A common tension was associated with attempts to maximise benefit while minimise additional burden. In both hospitals, resource pressures exacerbated the tensions of translating AKI recommendations into routine practice.ConclusionsOur analysis highlights a conflicted relationship between external context (policy and resources), and organisational structure and culture (eg, digital capability, attitudes to quality improvement). Greater consideration is required to the long-term effectiveness of the approaches taken, particularly in light of the ongoing need for adaptation to incorporate new practices into routine work.

scholarly journals Sustained effects of a clinical decision support system for acute kidney injury

2020 ◽  
Vol 35 (10) ◽  
pp. 1819-1821
Author(s):  
Ayham Bataineh ◽  
Dilhari Dealmeida ◽  
Andrew Bilderback ◽  
Richard Ambrosino ◽  
Mohammed J Al-Jaghbeer ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Kidney Injury ◽  
Clinical Decision ◽  
Sustained Effects

scholarly journals Computerized clinical decision support for the early recognition and management of acute kidney injury: a qualitative evaluation of end-user experience

2015 ◽  
Vol 9 (1) ◽  
pp. 57-62 ◽  
Author(s):  
Nigel S. Kanagasundaram ◽  
Mark T. Bevan ◽  
Andrew J. Sims ◽  
Andrew Heed ◽  
David A. Price ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Decision Support ◽  
User Experience ◽  
Clinical Decision Support ◽  
Early Recognition ◽  
Kidney Injury ◽  
Qualitative Evaluation ◽  
Clinical Decision ◽  
End User

scholarly journals Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events

2021 ◽  
Author(s):  
Laurine Robert ◽  
Chloé Rousseliere ◽  
Jean-Baptiste Beuscart ◽  
Sophie Gautier ◽  
Emmanuel Chazard ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Health Professionals ◽  
Clinical Decision Support System ◽  
Kidney Injury ◽  
Clinical Decision ◽  
Rule Based

In Clinical Decision Support System (CDSS), relevance of alerts is essential to limit alert fatigue and risk of overriding relevant alerts by health professionals. Detection of acute kidney injury (AKI) situations is of great importance in clinical practice and could improve quality of care. Nevertheless, to our knowledge, no explicit rule has been created to detect AKI situations in CDSS. The objective of the study was to implement an AKI detection rule based on KDIGO criteria in a CDSS and to optimize this rule to increase its relevance in clinical pharmacy use. Two explicit rules were implemented in a CDSS (basic AKI rule and improved AKI rule), based on KDIGO criteria. Only the improved rule was optimized by a group of experts during the two-month study period. The CDSS provided 1,125 alerts on AKI situations (i.e. 643 were triggered for the basic AKI rule and 482 for the improved AKI rule). As the study proceeds, the pharmaceutically and medically relevance of alerts from the improved AKI rule increased. A ten-fold increase was shown for the improved AKI rule compared to the basic AKI rule. The study highlights the usefulness of a multidisciplinary review to enhance explicit rules integrated in CDSS. The improved AKI is able to detect AKI situations and can improve workflow of health professionals.

scholarly journals Real-time pharmacy surveillance and clinical decision support to reduce adverse drug events in acute kidney injury

2012 ◽  
Vol 03 (02) ◽  
pp. 221-238 ◽  
Author(s):  
Z.L. Cox ◽  
E.B. Neal ◽  
L.R. Waitman ◽  
N.B. Peterson ◽  
G. Bhave ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Adverse Drug Events ◽  
Improve Patient Safety ◽  
Tertiary Care ◽  
Intervention Group ◽  
Kidney Injury ◽  
Clinical Decision ◽  
Care Hospital

Summary Objectives: Clinical decision support (CDS), such as computerized alerts, improves prescribing in the setting of acute kidney injury (AKI), but considerable opportunity remains to improve patient safety. The authors sought to determine whether pharmacy surveillance of AKI patients could detect and prevent medication errors that are not corrected by automated interventions. Methods: The authors conducted a randomized clinical trial among 396 patients admitted to an academic, tertiary care hospital between June 1, 2010 and August 31, 2010 with an acute 0.5 mg/dl change in serum creatinine over 48 hours and a nephrotoxic or renally cleared medication order. Patients randomly assigned to the intervention group received surveillance from a clinical pharmacist using a web-based surveillance tool to monitor drug prescribing and kidney function trends. CDS alerting and standard pharmacy services were active in both study arms. Outcome measures included blinded adjudication of potential adverse drug events (pADEs), adverse drug events (ADEs) and time to provider modification or discontinuation of targeted nephrotoxic or renally cleared medications. Results: Potential ADEs or ADEs occurred for 104 (8.0%) of control and 99 (7.1%) of intervention patient-medication pairs (p=0.4). Additionally, the time to provider modification or discontinuation of targeted nephrotoxic or renally cleared medications did not differ between control and intervention patients (33.4 hrs vs. 30.3hrs, p=0.3). Conclusions: Pharmacy surveillance had no incremental benefit over previously implemented CDS alerts

scholarly journals SP228ELECTRONIC CLINICAL DECISION SUPPORT FOR THE EARLY RECOGNITION AND MANAGEMENT OF ACUTE KIDNEY INJURY: QUANTITATIVE EVALUATION OF OUTCOMES

2015 ◽  
Vol 30 (suppl_3) ◽  
pp. iii453-iii453
Author(s):  
Andrew Sims ◽  
Andrew Heed ◽  
Mark Bevan ◽  
Neil S Sheerin ◽  
David A Price ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Decision Support ◽  
Quantitative Evaluation ◽  
Clinical Decision Support ◽  
Early Recognition ◽  
Kidney Injury ◽  
Clinical Decision
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