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Introduction Acute kidney injury following cardiac surgery is a dreaded complication contributing to early mortality. Diagnosing AKI using serum creatinine usually results in a delay. To combat this, certain kidney damage specific biomarkers were investigated to identify if they can serve as early predictors of cardiac surgery-associated AKI (CSA-AKI). This study systematically reviews three such biomarkers; NGAL, tissue inhibitor of matrix metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding protein-7 (IGFBP7) to identify if they can serve as early predictors of CSA-AKI.Methods Systematic search was carried out on literature reporting the diagnostic ability of the three biomarkers from databases in accordance with PRISMA guidelines.Results We found 43 articles reporting urinary-NGAL levels (n = 34 in adults, n = 9 in children) and 10 studies reporting TIMP-2 and IGFBP7 levels among adults. Interestingly, NGAL showed high diagnostic value in predicting AKI in children (seven among nine studies with AUROC > 0.8). The cell cycle arrest biomarkers, namely TIMP-2 and IGFBP7, showed high diagnostic value in predicting AKI in adults (five among ten studies with AUROC > 0.8).Conclusion In predicting CSA-AKI; the diagnostic value of NGAL is high in the paediatric population while the diagnostic value of TIMP-2 and IGFBP7 is high in adults.Electronic health record (EHR)-based interventions to improve patient safety are complex and sensitive to who, what, where, why, when, and how they are delivered. Success or failure depends not only on the characteristics and behaviors of individuals who are targeted by an intervention, but also on the technical characteristics of the intervention and the culture and environment of the health system that implements it. PF-543 clinical trial Current reporting guidelines do not capture the complexity of sociotechnical factors (technical and nontechnical factors, such as workflow and organizational issues) that confound or influence these interventions. This article proposes a methodological reporting framework for EHR interventions targeting patient safety and builds on an 8-dimension sociotechnical model previously developed by the authors for design, development, implementation, use, and evaluation of health information technology. The Safety-related EHR Research (SAFER) Reporting Framework enables reporting of patient safety-focutheir use.Electronic health record (EHR) systems can be configured to deliver novel EHR interventions that influence clinical decision making and to support efficient randomized controlled trials (RCTs) designed to evaluate the effectiveness, safety, and costs of those interventions. In designing RCTs of EHR interventions, one should carefully consider the unit of randomization (for example, patient, encounter, clinician, or clinical unit), balancing concerns about contamination of an intervention across randomization units within clusters (for example, patients within clinical units) against the superior control of measured and unmeasured confounders that comes with randomizing a larger number of units. One should also consider whether the key computational assessment components of the EHR intervention, such as a predictive algorithm used to target a subgroup for decision support, should occur before randomization (so that only 1 subgroup is randomized) or after randomization (including all subgroups). When these components are applied after randomization, one must consider expected heterogeneity in the effect of the differential decision support across subgroups, which has implications for overall impact potential, analytic approach, and sample size planning. Trials of EHR interventions should be reviewed by an institutional review board, but may not require patient-level informed consent when the interventions being tested can be considered minimal risk or quality improvement, and when clinical decision making is supported, rather than controlled, by an EHR intervention. Data and safety monitoring for RCTs of EHR interventions should be conducted to guide institutional pragmatic decision making about implementation and ensure that continuing randomization remains justified. Reporting should follow the CONSORT (Consolidated Standards of Reporting Trials) Statement, with extensions for pragmatic trials and cluster RCTs when applicable, and should include detailed materials to enhance reproducibility.Electronic health records (EHRs) are now widely adopted in the United States, but health systems have barely begun using them to deliver high-value care. More directed and rigorous research is needed to fulfill the promise of EHRs to not only store information but also support the delivery of better care. This article describes 4 potential benefits of EHR-based research improving clinical decisions, supporting triage decisions, enabling collaboration among the care team (including patients), and increasing productivity via automation of tasks. Six recommendations are made for conducting and reporting research to catalyze value creation develop interventions systematically by using user-centered design and a building-block approach; assess value in terms of cost, quality, outcomes, and work required of providers and patients; consider the time horizon for the intervention; test best practices for implementation in a range of real-world contexts; assess subtleties of behavior change tools used to improve high-value behaviors; and report the intervention in enough detail that it can be replicated, including context. Just as research played a critical role in developing early EHR prototypes and demonstrating their value to justify dissemination, research will continue to be essential in the next phase expanding EHR-based interventions and maximizing their role in creating value.Clinical workflow is the enactment of a series of steps to perform a clinical activity. The transition from paper to electronic health records (EHRs) over the past decade has been characterized by profound challenges supporting clinical workflow, impeding frontline clinicians' ability to deliver safe, efficient, and effective care. In response, there has been substantial effort to study clinical workflow as well as workarounds-exceptions to routine workflow-in order to identify opportunities for improvement. This article describes predominant methods of studying workflow and workarounds and provides examples of the applications of these methods along with the resulting insights. Challenges to studying workflow and workarounds are described, and recommendations for how to approach such studies are given. Although there is not yet a set of standard approaches, this article helps advance workflow research that ultimately serves to inform how to coevolve the design of EHR systems and organizational decisions about processes, roles, and responsibilities in order to support clinical workflow that more consistently delivers on the potential benefits of a digitized health care system.