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  • 1
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 5 ( 2018-01), p. 205435811774953-
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 2765462-X
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  • 2
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 3 ( 2016-01-01), p. 102-
    Abstract: Acute kidney injury (AKI) is independently associated with the development of chronic kidney disease, endstage kidney disease and increased all-cause and cardiovascular-specific mortality. The severity of the renal insult and the development of multiple AKI episodes increase the risk of occurrence of these outcomes. Despite these long-term effects, only a minority of patients receive nephrologist follow up after an episode of AKI; those that do may have improved outcomes. Furthermore, relatively simple quality improvement strategies have the potential to change this status quo. Methods: On this background, a working group of the 15 th Acute Dialysis Quality Initiative (ADQI) conference applied the consensus-building process informed by review of English language articles identified through PubMed search to address questions related to the opportunities, methodological requirements and barriers for longitudinal follow-up of patients with AKI in the era of electronic health records and Big Data. Results: Four consensus statements answering the key questions identified by the working group are developed. Conclusions: We have identified minimal data elements and potential data sources necessary to trace the natural history of patients from onset of AKI to long-term outcome. Minimum infrastructure and key barriers to achieving these goals are outlined together with proposed solutions.
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2765462-X
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  • 3
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 3 ( 2016-01-01), p. 99-
    Abstract: The data contained within the electronic health record (EHR) is “big” from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI) is a condition well suited to prediction and risk forecasting; not only does the consensus definition for AKI allow temporal anchoring of events, but no treatments exist once AKI develops, underscoring the importance of early identification and prevention. The Acute Dialysis Quality Initiative (ADQI) convened a group of key opinion leaders and stakeholders to consider how best to approach AKI research and care in the “Big Data” era. This manuscript addresses the core elements of AKI risk prediction and outlines potential pathways and processes. We describe AKI prediction targets, feature selection, model development, and data display.
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2765462-X
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  • 4
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 3 ( 2016-01-01), p. 101-
    Abstract: Among hospitalized patients, acute kidney injury is common and associated with significant morbidity and risk for mortality. The use of electronic health records (EHR) for prediction and detection of this important clinical syndrome has grown in the past decade. The steering committee of the 15 th Acute Dialysis Quality Initiative (ADQI) conference dedicated a workgroup with the task of identifying elements that may impact the course of events following Acute Kidney Injury (AKI) e-alert. Sources of information: Following an extensive, non-systematic literature search, we used a modified Delphi process to reach consensus regarding several aspects of the utilization of AKI e-alerts. Findings: Topics discussed in this workgroup included progress in evidence base practices, the characteristics of an optimal e-alert, the measures of efficacy and effectiveness, and finally what responses would be considered best practices following AKI e-alerts. Authors concluded that the current evidence for e-alert system efficacy, although growing, remains insufficient. Technology and human-related factors were found to be crucial elements of any future investigation or implementation of such tools. The group also concluded that implementation of such systems should not be done without a vigorous plan to evaluate the efficacy and effectiveness of e-alerts. Efficacy and effectiveness of e-alerts should be measured by context-specific process and patient outcomes. Finally, the group made several suggestions regarding the clinical decision support that should be considered following successful e-alert implementation. Limitations: This paper reflects the findings of a non-systematic review and expert opinion. Implications: We recommend implementation of the findings of this workgroup report for use of AKI e-alerts.
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
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  • 5
    In: Anaesthesia and Intensive Care, SAGE Publications, Vol. 47, No. 4 ( 2019-07), p. 343-348
    Abstract: Frailty is one of the major challenges for intensive care, affecting one-third of intensive care unit patients and being associated with a range of poor health outcomes. Determination of frailty in critical illness using the Clinical Frailty Scale has recently been adopted by the Australian and New Zealand Intensive Care Society, but it is not known whether this is able to be measured from the clinical record without interviewing patients or their relatives. The aims of this retrospective cohort study were to test whether a Clinical Frailty Scale score could be assigned in an intensive care unit population from the clinical record, and to assess the inter-rater reliability of frailty measured in this manner. A total of 144 patients were enrolled. Of these, 137 (95%) were able to have a Clinical Frailty Scale score assigned, and 22 (15%) were scored as frail (Clinical Frailty Scale ≥5). Cohen’s kappa coefficient for inter-rater reliability between assessors was 0.67, confirming substantial agreement. Consistent with other critically ill cohorts, frailty was associated on multivariate analysis with age, Charlson comorbidity score, dependence with activities of daily living, and limitation of medical treatment, indicating validity of this approach to frailty measurement. Our results imply that frailty measurement is possible and feasible from the intensive care unit clinical record, which is of importance as routine measurement and reporting of frailty in intensive care units in our region increases. Future work should seek to validate an assigned Clinical Frailty Scale score with that obtained directly from patients or their next of kin.
    Type of Medium: Online Resource
    ISSN: 0310-057X , 1448-0271
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2053705-0
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  • 6
    Online Resource
    Online Resource
    SAGE Publications ; 2016
    In:  Canadian Journal of Kidney Health and Disease Vol. 3 ( 2016-01-01), p. 103-
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 3 ( 2016-01-01), p. 103-
    Abstract: The world is immersed in “big data”. Big data has brought about radical innovations in the methods used to capture, transfer, store and analyze the vast quantities of data generated every minute of every day. At the same time; however, it has also become far easier and relatively inexpensive to do so. Rapidly transforming, integrating and applying this large volume and variety of data are what underlie the future of big data. The application of big data and predictive analytics in healthcare holds great promise to drive innovation, reduce cost and improve patient outcomes, health services operations and value. Acute kidney injury (AKI) may be an ideal syndrome from which various dimensions and applications built within the context of big data may influence the structure of services delivery, care processes and outcomes for patients. The use of innovative forms of “information technology” was originally identified by the Acute Dialysis Quality Initiative (ADQI) in 2002 as a core concept in need of attention to improve the care and outcomes for patients with AKI. For this 15 th ADQI consensus meeting held on September 6–8, 2015 in Banff, Canada, five topics focused on AKI and acute renal replacement therapy were developed where extensive applications for use of big data were recognized and/or foreseen. In this series of articles in the Canadian Journal of Kidney Health and Disease, we describe the output from these discussions.
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2765462-X
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  • 7
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 3 ( 2016-01-01), p. 98-
    Abstract: The purpose of this review is to report how administrative data have been used to study AKI, identify current limitations, and suggest how these data sources might be enhanced to address knowledge gaps in the field. Objectives: 1) To review the existing evidence-base on how AKI is coded across administrative datasets, 2) To identify limitations, gaps in knowledge, and major barriers to scientific progress in AKI related to coding in administrative data, 3) To discuss how administrative data for AKI might be enhanced to enable “communication” and “translation” within and across administrative jurisdictions, and 4) To suggest how administrative databases might be configured to inform ‘registry-based’ pragmatic studies. Source of information: Literature review of English language articles through PubMed search for relevant AKI literature focusing on the validation of AKI in administrative data or used administrative data to describe the epidemiology of AKI. Setting: Acute Dialysis Quality Initiative (ADQI) Consensus Conference September 6-7 th , 2015, Banff, Canada Patients: Hospitalized patients with AKI Key messages: The coding structure for AKI in many administrative datasets limits understanding of true disease burden (especially less severe AKI) its temporal trends and clinical phenotyping. Important opportunities exist to improve the quality and coding of AKI data to better address critical knowledge gaps in AKI and improve care. Methods: A modified Delphi consensus building process consisting of review of the literature and summary statements were developed through a series of alternating breakout and plenary sessions. Results: Administrative codes for AKI are limited by poor sensitivity, lack of standardization to classify severity, and poor contextual phenotyping. These limitations are further hampered by reduced awareness of AKI among providers and the subjective nature of reporting. While an idealized definition of AKI may be difficult to implement, improving standardization of reporting by using laboratory-based definitions and providing complementary information on the context in which AKI occurs are possible. Administrative databases may also help enhance the conduct of and inform clinical or registry-based pragmatic studies. Limitations: Data sources largely restricted to North American and Europe Implications: Administrative data are rapidly growing and evolving, and represent an unprecedented opportunity to address knowledge gaps in AKI. Progress will require continued efforts to improve awareness of the impact of AKI on public health, engage key stakeholders, and develop tangible strategies to reconfigure infrastructure to improve the reporting and phenotyping of AKI. Why is this review important?: Rapid growth in the size and availability of administrative data has enhanced the clinical study of acute kidney injury (AKI). However, significant limitations exist in coding that hinder our ability to better understand its epidemiology and address knowledge gaps. The following consensus-based review discusses how administrative data have been used to study AKI, identify current limitations, and suggest how these data sources might be enhanced to improve the future study of this disease. What are the key messages?: The current coding structure of administrative data is hindered by a lack of sensitivity, standardization to properly classify severity, and limited clinical phenotyping. These limitations combined with reduced awareness of AKI and the subjective nature of reporting limit understanding of disease burden across settings and time periods. As administrative data become more sophisticated and complex, important opportunities to employ more objective criteria to diagnose and stage AKI as well as improve contextual phenotyping exist that can help address knowledge gaps and improve care.
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2765462-X
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  • 8
    In: Palliative Medicine, SAGE Publications, Vol. 29, No. 4 ( 2015-04), p. 324-335
    Abstract: Little is known about the perspectives and experiences of family members of very elderly patients who are admitted to the intensive care unit. Aim: To describe family members’ perspectives about care provided to very elderly critically ill patients. Design: Multicenter, prospective, cohort study. Participants and setting: In total, 535 family members of patients aged 80 years or older admitted to 22 intensive care units for more than 24 h. Results: Family members reported that the “patient be comfortable and suffer as little as possible” was their most important value and “the belief that life should be preserved at all costs” was their least important value considered in making treatment decisions. Most family members (57.9%) preferred that life support be used for their family member, whereas 24.1% preferred comfort measures only, and 14.4% were unsure of their treatment preferences. Only 57.3% reported that a doctor had talked to them about treatment options for the patient. Overall, 29.7% of patients received life-sustaining treatments for more than 7 days and 50.3% of these died in hospital. Families were most satisfied with the skill and competency of nurses and least satisfied with being included and supported in the decision-making process and with their sense of control over the patient’s care. Conclusion: There is incongruity between family values and preferences for end-of-life care and actual care received for very elderly patients who are admitted to the intensive care unit. Deficiencies in communication and decision-making may be associated with prolonged use of life-sustaining treatments in very elderly critically ill patients, many of whom ultimately die.
    Type of Medium: Online Resource
    ISSN: 0269-2163 , 1477-030X
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2027566-3
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  • 9
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 4 ( 2017-01), p. 205435811769256-
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
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  • 10
    In: Canadian Journal of Kidney Health and Disease, SAGE Publications, Vol. 3 ( 2016-01-01), p. 100-
    Abstract: Electronic medical records and clinical information systems are increasingly used in hospitals and can be leveraged to improve recognition and care for acute kidney injury. This Acute Dialysis Quality Initiative (ADQI) workgroup was convened to develop consensus around principles for the design of automated AKI detection systems to produce real-time AKI alerts using electronic systems. AKI alerts were recognized by the workgroup as an opportunity to prompt earlier clinical evaluation, further testing and ultimately intervention, rather than as a diagnostic label. Workgroup members agreed with designing AKI alert systems to align with the existing KDIGO classification system, but recommended future work to further refine the appropriateness of AKI alerts and to link these alerts to actionable recommendations for AKI care. The consensus statements developed in this review can be used as a roadmap for development of future electronic applications for automated detection and reporting of AKI.
    Type of Medium: Online Resource
    ISSN: 2054-3581 , 2054-3581
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2765462-X
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