Clinical dashboard: use in older adult mental health wards

Daley, Kate; Richardson, Jonathan; James, Ian A.; Chambers, Annette; Corbett, David

doi:10.1192/pb.bp.111.035899

Cited by 56 publications

(73 citation statements)

References 4 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%

“…The predominant focus of the dashboards was providing information for clinicians to enable them to make decisions about the clinical management of patients. One study [2] fitted our definition of a quality dashboard, in that it provided data for unit managers regarding quality measures as a way of improving service delivery, but also provided data that was intended to support clinician decision making.…”

Section: Quality Assessmentmentioning

confidence: 99%

“…It enables easy access to multiple sources of data being captured locally, in a visual, concise and usable format." [2] The key characteristics of quality and clinical dashboards, which separate them from computerized decision support systems (CDSS) or data provided by an electronic medical record (EMR) system include a) the provision of summary data on performance measured against metrics (often related to quality of care or productivity) and b) the use of data visualization techniques (such as graphs) to provide feedback to leaders or individual clinicians. With the introduction of Health Information Technology (HIT) the feedback provided by quality and clinical dashboards can be as near to 'real time' as possible; this is in contrast to more traditional methods of feedback on performance which often give data back to a provider or group days or weeks after an event has taken place [3].…”

Section: Introductionmentioning

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: Quality Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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Changes in Primary Care Quality Associated With Implementation of the Veterans Health Administration Preventive Health Inventory

et al. 2023

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ImportanceThe COVID-19 pandemic caused significant disruptions in primary care delivery. The Veterans Health Administration (VHA) launched the Preventive Health Inventory (PHI) program—a multicomponent care management intervention, including a clinical dashboard and templated electronic health record note—to support primary care in delivering chronic disease care and preventive care that had been delayed by the pandemic.ObjectivesTo describe patient, clinician, and clinic correlates of PHI use in primary care clinics and to examine associations between PHI adoption and clinical quality measures.Design, Setting, and ParticipantsThis quality improvement study used VHA administrative data from February 1, 2021, through February 28, 2022, from a national cohort of 216 VHA primary care clinics that have implemented the PHI. Participants comprised 829 527 veterans enrolled in primary care in clinics with the highest and lowest decile of PHI use as of February 2021.ExposureTemplated electronic health record note documenting use of the PHI.Main Outcomes and MeasuresDiabetes and blood pressure clinical quality measures were the primary outcomes. Interrupted time series models were applied to estimate changes in diabetes and hypertension quality measures associated with PHI implementation. Low vs high PHI use was stratified at the facility level to measure whether systematic differences in uptake were associated with quality.ResultsA total of 216 primary clinics caring for 829 527 unique veterans (mean [SD] age, 64.1 [16.9] years; 755 158 of 829 527 [91%] were men) formed the study cohort. Use of the PHI varied considerably across clinics. The clinics in the highest decile of PHI use completed a mean (SD) of 32 997.4 (14 019.3) notes in the electronic health record per 100 000 veterans compared with 56.5 (35.3) notes per 100 000 veterans at the clinics in the lowest decile of use (P &lt; .001). Compared with the clinics with the lowest use of the PHI, clinics with the highest use had a larger mean (SD) clinic size (12 072 [7895] patients vs 5713 [5825] patients; P &lt; .001), were more likely to be urban (91% vs 57%; P &lt; .001), and served more non-Hispanic Black veterans (16% vs 5%; P &lt; .001) and Hispanic veterans (14% vs 4%; P &lt; .001). Staffing did not differ meaningfully between high- and low-use clinics (mean [SD] ratio of full-time equivalent staff to clinician, 3.4 [1.2] vs 3.4 [0.8], respectively; P &lt; .001). After PHI implementation, compared with the clinics with the lowest use, those with the highest use had fewer veterans with a hemoglobin A1c greater than 9% or missing (mean [SD], 6577 [3216] per 100 000 veterans at low-use clinics; 9928 [4236] per 100 000 veterans at high-use clinics), more veterans with an annual hemoglobin A1c measurement (mean [SD], 13 181 [5625] per 100 000 veterans at high-use clinics; 8307 [3539] per 100 000 veterans at low-use clinics), and more veterans with adequate blood pressure control (mean [SD], 20 582 [12 201] per 100 000 veterans at high-use clinics; 12 276 [6850] per 100 000 veterans at low-use clinics).Conclusions and RelevanceThis quality improvement study of the implementation of the VHA PHI suggests that higher use of a multicomponent care management intervention was associated with improved quality-of-care metrics. The study also found significant variation in PHI uptake, with higher uptake associated with clinics with more racial and ethnic diversity and larger, urban clinic sites.

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Real‐time analysis and display of quantitative measures to track and improve clinical workflow

Munbodh

Roth

Leonard

et al. 2022

J Applied Clin Med Phys

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Purpose: Radiotherapy treatment planning is a complex process with multiple, dependent steps involving an interdisciplinary patient care team. Effective communication and real-time tracking of resources and care path activities are key for clinical efficiency and patient safety. Materials and Methods:We designed and implemented a secure, interactive web-based dashboard for patient care path, clinical workflow, and resource utilization management. The dashboard enables visualization of resource utilization and tracks progress in a patient's care path from the time of acquisition of the planning CT to the time of treatment in real-time. It integrates with the departmental electronic medical records (EMR) system without the creation and maintenance of a separate database or duplication of work by clinical staff. Performance measures of workflow were calculated. Results:The dashboard implements a standardized clinical workflow and dynamically consolidates real-time information queried from multiple tables in the EMR database over the following views: (1) CT Sims summarizes patient appointment information on the CT simulator and patient load; (2) Linac Sims summarizes patient appointment times, setup history, and notes, and patient load; (3) Task Status lists the clinical tasks associated with a treatment plan, their due date, status and ownership, and patient appointment details; (4) Documents provides the status of all documents in the patients' charts; and (5) Diagnoses and Interventions summarizes prescription information, imaging instructions and whether the plan was approved for treatment. Real-time assessment and quantification of progress and delays in a patient's treatment start were achieved. Conclusions: This study indicates it is feasible to develop and implement a dashboard, tailored to the needs of an interdisciplinary team, which derives and integrates information from the EMR database for real-time analysis and display of resource utilization and clinical workflow in radiation oncology.The framework developed facilitates informed, data-driven decisions on clinical workflow management as we seek to optimize clinical efficiency and patient safety.

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Clinical dashboard: use in older adult mental health wards

Cited by 56 publications

References 4 publications

Dashboards for improving patient care: Review of the literature

Dashboards for improving patient care: Review of the literature

Changes in Primary Care Quality Associated With Implementation of the Veterans Health Administration Preventive Health Inventory

Real‐time analysis and display of quantitative measures to track and improve clinical workflow

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