Implementation of an Emergency Department Computer System: Design Features That Users Value

Batley, Nicholas; Kazzi, Amin; Musallam, Khaled M.

doi:10.1016/j.jemermed.2010.05.014

Cited by 34 publications

(45 citation statements)

References 14 publications

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“…Two studies used an interrupted time series design to monitor the effect of introducing the dashboard on outcomes over time [32,33]. Other study designs included before-after studies [34][35][36], non-comparative evaluations [37,38], questionnaire surveys of users of dashboards [2,39] and a usability study [40]. With two exceptions [28,37], the dashboards were evaluated in one organization, where they had been developed and implemented.…”

Section: Study Characteristicsmentioning

confidence: 99%

“…Overall one study was rated as being of high quality [33], four as being fair-good quality [28,32,35,40] and five as low quality [2,34,[37][38][39]. The kappa coefficient between the two raters was 0.92 (95% CI 0.82-1.00) indicating very good agreement.…”

Section: Quality Assessmentmentioning

confidence: 99%

“…Two of the studies appeared to be evaluating the same dashboard for ventilator management introduced into an intensive care unit (ICU) [33,36]. Other clinical areas included the Emergency Department [39] and mental health services [2]. Alternatively, dashboards were focused on specific users;…”

Section: Quality Assessmentmentioning

confidence: 99%

“…provision of information to reduce inappropriate prescribing of antibiotics [28,39] or ensure appropriate prescribing of antibiotics [32]; monitoring of adherence to best practices for managing chronic conditions [37,40] or adherence to the ventilator bundle in ICU [33,36]; improvements in the timeliness of radiology reporting [35]; improving monitoring of potential medication adverse events [38] and for improving information about provision of mental health services [2].…”

Section: Focus Of Decisionsmentioning

confidence: 99%

“…Dashboards designed to provide information to clinicians regarding prescription of antibiotics for respiratory infections were found to have no overall effect on prescribing rates [28,39].…”

Section: Effect On Outcomes and Care Processesmentioning

confidence: 99%

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Dashboards for improving patient care: Review of the literature

Dowding¹,

Randell²,

Gardner³

et al. 2015

International Journal of Medical Informatics

306

294

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Aim: This review aimed to provide a comprehensive overview of the current state of evidence for the use of clinical and quality dashboards in health care environments. Methods:A literature search was performed for the dates 1996 to 2012 on CINAHL, Medline, Embase, Cochrane Library, PsychInfo, Science Direct and ACM Digital Library. A citation search and a hand search of relevant papers were also conducted.Results: One hundred and twenty two full text papers were retrieved of which 11 were included in the review. There was considerable heterogeneity in implementation setting, dashboard users and indicators used. There was evidence that in contexts where dashboards were easily accessible to clinicians (such as in the form of a screen saver) their use was associated with improved care processes and patient outcomes. Conclusion:There is some evidence that implementing clinical and/or quality dashboards that provide immediate access to information for clinicians can improve adherence to quality guidelines and may help improve patient outcomes. However, further high quality detailed research studies need to be conducted to obtain evidence of their efficacy and establish guidelines for their design.4

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Section: Study Characteristicsmentioning

confidence: 99%

Section: Quality Assessmentmentioning

confidence: 99%

Section: Quality Assessmentmentioning

confidence: 99%

Section: Focus Of Decisionsmentioning

confidence: 99%

Section: Effect On Outcomes and Care Processesmentioning

confidence: 99%

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Dashboards for improving patient care: Review of the literature

Dowding¹,

Randell²,

Gardner³

et al. 2015

International Journal of Medical Informatics

306

294

View full text Add to dashboard Cite

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An Electronic Dashboard to Monitor Patient Flow at the Johns Hopkins Hospital: Communication of Key Performance Indicators Using the Donabedian Model

et al. 2018

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Efforts to monitoring and managing hospital capacity depend on the ability to extract relevant time-stamped data from electronic medical records and other information technologies. However, the various characterizations of patient flow, cohort decisions, sub-processes, and the diverse stakeholders requiring data visibility create further overlying complexity. We use the Donabedian model to prioritize patient flow metrics and build an electronic dashboard for enabling communication. Ten metrics were identified as key indicators including outcome (length of stay, 30-day readmission, operating room exit delays, capacity-related diversions), process (timely inpatient unit discharge, emergency department disposition), and structural metrics (occupancy, discharge volume, boarding, bed assignation duration). Dashboard users provided real-life examples of how the tool is assisting capacity improvement efforts, and user traffic data revealed an uptrend in dashboard utilization from May to October 2017 (26 to 148 views per month, respectively). Our main contributions are twofold. The former being the results and methods for selecting key performance indicators for a unit, department, and across the entire hospital (i.e., separating signal from noise). The latter being an electronic dashboard deployed and used at The Johns Hopkins Hospital to visualize these ten metrics and communicate systematically to hospital stakeholders. Integration of diverse information technology may create further opportunities for improved hospital capacity.

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