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Heart failure (HF) is a common disease with increasing prevalence around the world. There is high morbidity and mortality associated with poorly controlled HF along with increasing costs and strain on healthcare systems due to a high rate of rehospitalization and resource utilization. Despite the establishment of clear evidence-based guideline directed medical therapies (GDMT) proven to improve HF morbidity and mortality, there remains significant clinical inertia to optimizing HF patients on GDMT. Only a minority of HF patients are prescribed on all four classes of GDMT. To bridge the gap between the vulnerable population of HF patients and lifesaving GDMT, HF implementation is of increasing importance. HF implementation involves strategies and techniques to improve GDMT optimization along with other modalities to improve HF management. HF implementation meets patients where they are, including at the time of acute decompensation in the inpatient setting, at the vulnerable discharge stage, and at the chronic management stage in the outpatient setting. Inpatient HF implementation strategies include protocolized rapid titration of GDMT, site-level audit-and-feedback, virtual GDMT optimization teams, and electronic health record notifications and alerts. Discharge HF implementation strategies include education at patient and provider levels, discharge summaries, and HF transitional programs. Outpatient HF implementation strategies include digital innovations such as electronic health record utilization and mobile applications, population level strategies such as registries and clinical dashboards), changes in HF team structure and member roles, remote monitoring with implanted devices and telemonitoring, and hospital at home care model. With a growing population of HF patients, there is an increasing need for novel and creative HF implementation and monitoring methods.

Background: A clinical dashboard is a data-driven clinical decision support tool visualizing multiple key performance indicators in a single report while minimizing time and effort for data gathering. Studies have shown that including patient-reported outcome measures (PROMs) in clinical dashboards supports the clinician's understanding of how treatments impact patients' health status, helps identify changes in health-related quality of life at an early stage, and strengthens patient-physician communication., Objective: This study aims to determine design components for clinical dashboards incorporating PROMs to inform software producers and users (ie, physicians)., Methods: We conducted interviews with software producers and users to test preselected design components. Furthermore, the interviews allowed us to derive additional components that are not outlined in existing literature. Finally, we used inductive and deductive coding to derive a guide on which design components need to be considered when building a clinical dashboard incorporating PROMs., Results: A total of 25 design components were identified, of which 16 were already surfaced during the literature search. Furthermore, 9 additional components were derived inductively during our interviews. The design components are clustered in a generic dashboard, PROM-related, adjacent information, and requirements for adoption components. Both software producers and users agreed on the primary purpose of a clinical dashboard incorporating PROMs to enhance patient communication in outpatient settings. Dashboard benefits include enhanced data visualization and improved workflow efficiency, while interoperability and data collection were named as adoption challenges. Consistency in dashboard design components is preferred across different episodes of care, with adaptations only for disease-specific PROMs., Conclusions: Clinical dashboards have the potential to facilitate informed treatment decisions if certain design components are followed. This study establishes a comprehensive framework of design components to guide the development of effective clinical dashboards incorporating PROMs in health care practice., (©Anja Yvonne Bischof, David Kuklinski, Irene Salvi, Carla Walker, Justus Vogel, Alexander Geissler. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 02.10.2024.)

Background: Obstetric Bleeding Study UK (OBS UK) (award ID: 152057) is a National Institute for Health and Care Research (NIHR)-funded stepped wedge cluster randomised controlled trial of a complex intervention for postpartum haemorrhage. This was developed in Wales and evaluated in a feasibility study, with improvements in maternal outcomes observed. Generalisability of the findings is limited by lack of control data and limited ethnic diversity in the Welsh obstetric patient population compared to the United Kingdom (UK): 94% of the Welsh population identifies as White, versus 82% in the UK. Non-White ethnicity and socioeconomic deprivation are linked to increased risk of adverse maternal outcomes. Traditionally, decisions regarding site selection are based on desire to complete trials on target in 'tried and tested' research active institutions. To ensure widespread applicability of the results and investigate the impact of ethnicity and social deprivation on trial outcomes, maternity units were recruited that represent the ethnic diversity and social deprivation profiles of the UK., Method: Using routinely collected, publicly available data, an interactive dashboard was developed that demonstrates the demographics of the population served by each maternity unit in the UK, to inform site recruitment. Data on births per year, ethnic and socioeconomic group of the population for each maternity unit, across the UK, were integrated into the dashboard., Results: The dashboard demonstrates that OBS UK trial sites reflect the ethnic and socioeconomic diversity of the UK (study vs UK population ethnicity: White 79.2% vs 81.7%, Asian 10.5% vs 9.3%, Black 4.7% vs 4.0%, Mixed 2.5% vs 2.9%, Other 3.0% vs 2.1%) with variation in site demography, size and location. Missing data varied across sites and nations and is presented., Conclusion: The NIHR equality, diversity and inclusion strategy states studies must widen participation, facilitating individuals from all backgrounds to engage. The development of this novel interactive dashboard demonstrates an innovative way of achieving this. National Health Service (NHS) maternity researchers should consider using this tool to enhance diversity in research, address health disparities and improve generalisability of findings. This approach could be applied to healthcare settings beyond maternity care and across different global populations., Trial Registration: ISRCTN 17679951. Registered on August 30, 2023., (© 2024. The Author(s).)

Background/aim: In the past decades, there has been an increasing focus on defining, identifying and reducing unwarranted variation in clinical practice. There have been several attempts to monitor and reduce unwarranted variation, but the experience so far is that these initiatives have failed to reach their goals. In this article, we present the initial process of developing a safety, quality and utilisation rate dashboard ('clinical dashboard') based on a selection of data routinely reported to executive boards and top-level leaders in Norwegian specialist healthcare., Methods: We used a modified version of Wennberg's categorisation of healthcare delivery to develop the dashboard, focusing on variation in (1) effective care and patient safety and (2) preference-sensitive and supply-sensitive care., Results: Effective care and patient safety are monitored with outcome measures such as 30-day mortality after hospital admission and 5-year cancer survival, whereas utilisation rates for procedures selected on cost and volume are used to follow variations in preference-sensitive and supply-sensitive care., Conclusion: We argue that selecting quality indicators of patient safety, quality and utilisation rates and presenting them in a dashboard may help executive hospital boards and top-level leaders to focus on unwarranted variation., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Data dashboards have become more widely used for the public communication of health-related data, including in maternal health., Objective: We aimed to evaluate the content and features of existing publicly available maternal health dashboards in the United States., Methods: Through systematic searches, we identified 80 publicly available, interactive dashboards presenting US maternal health data. We abstracted and descriptively analyzed the technical features and content of identified dashboards across four areas: (1) scope and origins, (2) technical capabilities, (3) data sources and indicators, and (4) disaggregation capabilities. Where present, we abstracted and qualitatively analyzed dashboard text describing the purpose and intended audience., Results: Most reviewed dashboards reported state-level data (58/80, 72%) and were hosted on a state health department website (48/80, 60%). Most dashboards reported data from only 1 (33/80, 41%) or 2 (23/80, 29%) data sources. Key indicators, such as the maternal mortality rate (10/80, 12%) and severe maternal morbidity rate (12/80, 15%), were absent from most dashboards. Included dashboards used a range of data visualizations, and most allowed some disaggregation by time (65/80, 81%), geography (65/80, 81%), and race or ethnicity (55/80, 69%). Among dashboards that identified their audience (30/80, 38%), legislators or policy makers and public health agencies or organizations were the most common audiences., Conclusions: While maternal health dashboards have proliferated, their designs and features are not standard. This assessment of maternal health dashboards in the United States found substantial variation among dashboards, including inconsistent data sources, health indicators, and disaggregation capabilities. Opportunities to strengthen dashboards include integrating a greater number of data sources, increasing disaggregation capabilities, and considering end-user needs in dashboard design., (©Jennifer A Callaghan-Koru, Paige Newman Chargois, Tanvangi Tiwari, Clare C Brown, William Greenfield, Güneş Koru. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.09.2024.)

Background and Objectives: Incidence of type 1 diabetes mellitus (T1DM) is increasing, and these patients often have poor glycemic control. Electronic dashboards summating patient data have been shown to improve patient outcomes in other conditions. In addition, educating patients on T1DM has shown to improve glycated hemoglobin (A1C) levels. We hypothesized that using data from the electronic dashboard to monitor defined diabetes management activities to implement population-based interventions would improve patient outcomes., Methods: Inclusion criteria included patients aged 0 to 18 years at Phoenix Children's Hospital with T1DM. Patient data were collected via the electronic dashboard, and both diabetes management activities (A1C, patient admissions, and visits to the emergency department) and patient outcomes (patient education, appointment compliance, follow-up after hospital admission) were analyzed., Results: This study revealed that following implementation of the electronic dashboard, the percentage of patients receiving appropriate education increased from 48% to 80% (Z-score = 23.55, P < .0001), the percentage of patients attending the appropriate number of appointments increased from 50% to 68.2%, and the percentage of patients receiving follow-up care within 40 days after a hospital admission increased from 43% to 70%. The median A1C level decreased from 9.1% to 8.2% (Z-score = -6.74, P < .0001), and patient admissions and visits to the emergency department decreased by 20%., Conclusions: This study shows, with the implementation of an electronic dashboard, we were able to improve outcomes for our pediatric patients with T1DM. This tool can be used at other institutions to improve care and outcomes for pediatric patients with T1DM and other chronic conditions., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

India launched the Ayushman Bharat Digital Mission (ABDM) in 2021 to strengthen the digital health ecosystem by developing and integrating health data records and registries. We apply the health system control knob framework to assess the progress of ABDM by analyzing five indicators. Data from the ABDM dashboard reveal notable progress in beneficiary registration (400 million, as of June 3, 2023) and health records linkage (273 million). The registrations of over 208,000 health facilities and 190,000 health care professionals have been verified by ABDM. However, inter-state variation in progress is significant, particularly in health facility and health professional registration. Going forward, ABDM should expand its strategic framework to ensure that more health facilities and health professionals are registered, as registration is important to influence the payment, organization, and regulation control knobs. These actions are related to the achievement of final health system goals: improved health status, financial risk protection, and beneficiary satisfaction.

Telehealth has the potential to improve access to health care by mitigating barriers related to geography, time, and finances. However, the increased adoption of ambulatory telehealth has inadvertently widened access gaps for socially disadvantaged and marginalized populations. Quality improvement approaches are a valuable strategy to address health care access inequities and disparities, involving data-driven implementation, assessment, and adaptation of tests of change over time. Because these iterative changes and interventions are data-driven, a critical element of quality improvement requires ongoing data collection and monitoring. This perspective describes the development and validation processes of a telehealth equity dashboard. This dashboard is currently available for use by our health system leaders, providers, and clinic staff. The overall objective of this dashboard is to identify and track inequities and to improve equitable ambulatory telehealth access across diverse patient groups. Lessons learned from creating this dashboard can inform other health care systems of how to develop and validate telehealth data feedback systems to promote quality improvement efforts to advance telehealth equity and accessibility., (© The Author(s) 2024. Published by Mary Ann Liebert, Inc.)

The existing surgery timetable is very simple, not user-friendly, and has very limited information. This article outlines the creation of a surgical dynamic dashboard for users, using Microsoft Power BI. The dashboard was developed based on in-depth interviews with the surgical team members to determine their requirements. The outcome of dashboard was evaluated by 5-likert scale questionnaire to measure satisfaction of all surgical team members. All team members were very satisfied with the dashboard compared to the existing surgery timetable. In addition, with the function of auto-generated analytic reports through data criteria selection on the dashboard saved time on manually generating reports. This study supports to replace the existing surgery timetable by the user-centric and real time surgical dashboard.

Purpose: To describe the development and implementation of clinical dashboards to standardize data capturing and reporting across multiple partner health systems., Summary: Between July and September 2020, clinical dashboards were developed and implemented across multiple partner health-system specialty pharmacies (HSSPs) located throughout the United States. The dashboards were developed via collaboration between personnel involved in clinical subcommittees, clinical outcomes, data analytics, information technology, and clinical and central operations. Utilizing a cloud-scale business intelligence service, patient clinical data documented in a shared patient management system was utilized to create customizable dashboards that displayed patient-reported outcome measures, collected laboratory or test results, and completed pharmacist interventions. Separate dashboards were developed for several disease states and/or medication classes. Based on specialty pharmacy recommendations, medical literature, and clinical guidelines, internally developed disease-specific protocols defined data included in the dashboards and ensured consistent data collection amongst partner health systems. Having access to real-time clinical information allows health systems to closely monitor performance metrics, track patient outcomes, and identify operational gaps., Conclusion: Accurately capturing and reporting clinical metrics using clinical dashboards can assist HSSPs in delivering high-quality care. Having access to clinical outcome measures allows HSSPs to better understand the impact of their services on patients' health and quality of life. Health systems can utilize this data to analyze trends and recognize areas of opportunity so that measures can be taken to improve patient care., (© American Society of Health-System Pharmacists 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: The COVID-19 pandemic highlighted the importance of robust public health data systems and the potential utility of data dashboards for ensuring access to critical public health data for diverse groups of stakeholders and decision makers. As dashboards are becoming ubiquitous, it is imperative to consider how they may be best integrated with public health data systems and the decision-making routines of diverse audiences. However, additional progress on the continued development, improvement, and sustainability of these tools requires the integration and synthesis of a largely fragmented scholarship regarding the purpose, design principles and features, successful implementation, and decision-making supports provided by effective public health data dashboards across diverse users and applications., Objective: This scoping review aims to provide a descriptive and thematic overview of national public health data dashboards including their purpose, intended audiences, health topics, design elements, impact, and underlying mechanisms of use and usefulness of these tools in decision-making processes. It seeks to identify gaps in the current literature on the topic and provide the first-of-its-kind systematic treatment of actionability as a critical design element of public health data dashboards., Methods: The scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The review considers English-language, peer-reviewed journal papers, conference proceedings, book chapters, and reports that describe the design, implementation, and evaluation of a public health dashboard published between 2000 and 2023. The search strategy covers scholarly databases (CINAHL, PubMed, Medline, and Web of Science) and gray literature sources and uses snowballing techniques. An iterative process of testing for and improving intercoder reliability was implemented to ensure that coders are properly trained to screen documents according to the inclusion criteria prior to beginning the full review of relevant papers., Results: The search process initially identified 2544 documents, including papers located via databases, gray literature searching, and snowballing. Following the removal of duplicate documents (n=1416), nonrelevant items (n=839), and items classified as literature reviews and background information (n=73), 216 documents met the inclusion criteria: US case studies (n=90) and non-US case studies (n=126). Data extraction will focus on key variables, including public health data characteristics; dashboard design elements and functionalities; intended users, usability, logistics, and operation; and indicators of usefulness and impact reported., Conclusions: The scoping review will analyze the goals, design, use, usefulness, and impact of public health data dashboards. The review will also inform the continued development and improvement of these tools by analyzing and synthesizing current practices and lessons emerging from the literature on the topic and proposing a theory-grounded and evidence-informed framework for designing, implementing, and evaluating public health data dashboards., International Registered Report Identifier (irrid): DERR1-10.2196/52843., (©Itzhak Yanovitzky, Gretchen Stahlman, Justine Quow, Matthew Ackerman, Yehuda Perry, Miriam Kim. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 16.05.2024.)

Background:  Intensive care unit (ICU) clinicians encounter frequent challenges with managing vast amounts of fragmented data while caring for multiple critically ill patients simultaneously. This may lead to increased provider cognitive load that may jeopardize patient safety., Objectives:  This systematic review assesses the impact of centralized multipatient dashboards on ICU clinician performance, perceptions regarding the use of these tools, and patient outcomes., Methods:  A literature search was conducted on February 9, 2023, using the EBSCO CINAHL, Cochrane Central Register of Controlled Trials, Embase, IEEE Xplore, MEDLINE, Scopus, and Web of Science Core Collection databases. Eligible studies that included ICU clinicians as participants and tested the effect of dashboards designed for use by multiple users to manage multiple patients on user performance and/or satisfaction compared with the standard practice. We narratively synthesized eligible studies following the SWiM (Synthesis Without Meta-analysis) guidelines. Studies were grouped based on dashboard type and outcomes assessed., Results:  The search yielded a total of 2,407 studies. Five studies met inclusion criteria and were included. Among these, three studies evaluated interactive displays in the ICU, one study assessed two dashboards in the pediatric ICU (PICU), and one study examined centralized monitor in the PICU. Most studies reported several positive outcomes, including reductions in data gathering time before rounds, a decrease in misrepresentations during multidisciplinary rounds, improved daily documentation compliance, faster decision-making, and user satisfaction. One study did not report any significant association., Conclusion:  The multipatient dashboards were associated with improved ICU clinician performance and were positively perceived in most of the included studies. The risk of bias was high, and the certainty of evidence was very low, due to inconsistencies, imprecision, indirectness in the outcome measure, and methodological limitations. Designing and evaluating multipatient tools using robust research methodologies is an important focus for future research., Competing Interests: None declared., (Thieme. All rights reserved.)

This study investigated coded data retrieved from clinical dashboards, which are decision-support tools that include a graphical display of clinical progress and clinical activities. Data were extracted from clinical dashboards representing 256 youth (M age = 11.9) from 128 practitioners who were trained in the Managing and Adapting Practice (MAP) system (Chorpita & Daleiden in BF Chorpita EL Daleiden 2014 Structuring the collaboration of science and service in pursuit of a shared vision. 43(2):323 338. 2014, Chorpita & Daleiden in BF Chorpita EL Daleiden 2018 Coordinated strategic action: Aspiring to wisdom in mental health service systems. 25(4):e12264. 2018) in 55 agencies across 5 regional mental health systems. Practitioners labeled up to 35 fields (i.e., descriptions of clinical activities), with the options of drawing from a controlled vocabulary or writing in a client-specific activity. Practitioners then noted when certain activities occurred during the episode of care. Fields from the extracted data were coded and reliability was assessed for Field Type, Practice Element Type, Target Area, and Audience (e.g., Caregiver Psychoeducation: Anxiety would be coded as Field Type = Practice Element; Practice Element Type = Psychoeducation; Target Area = Anxiety; Audience = Caregiver). Coders demonstrated moderate to almost perfect interrater reliability. On average, practitioners recorded two activities per session, and clients had 10 unique activities across all their sessions. Results from multilevel models showed that clinical activity characteristics and sessions accounted for the most variance in the occurrence, recurrence, and co-occurrence of clinical activities, with relatively less variance accounted for by practitioners, clients, and regional systems. Findings are consistent with patterns of practice reported in other studies and suggest that clinical dashboards may be a useful source of clinical information. More generally, the use of a controlled vocabulary for clinical activities appears to increase the retrievability and actionability of healthcare information and thus sets the stage for advancing the utility of clinical documentation., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

As the field of public health rises to the demands of real-time surveillance and rapid data-sharing needs in a postpandemic world, it is time to examine our approaches to the dissemination and accessibility of such data. Distinct challenges exist when working to develop a shared public health language and narratives based on data. It requires that we assess our understanding of public health data literacy, revisit our approach to communication and engagement, and continuously evaluate our impact and relevance. Key stakeholders and cocreators are critical to this process and include people with lived experience, community organizations, governmental partners, and research institutions. In this viewpoint paper, we offer an instructive approach to the tools we used, assessed, and adapted across 3 unique overdose data dashboard projects in Rhode Island, United States. We are calling this model the "Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action." This approach reflects the iterative lessons learned about the improvement of data dashboards through collaboration and strong partnerships across community members, state agencies, and an academic research team. We will highlight key tools and approaches that are accessible and engaging and allow developers and stakeholders to self-assess their goals for their data dashboards and evaluate engagement with these tools by their desired audiences and users., (©Jesse Yedinak, Maxwell S Krieger, Raynald Joseph, Stacey Levin, Sarah Edwards, Dennis A Bailer, Jonathan Goyer, Colleen Daley Ndoye, Cathy Schultz, Jennifer Koziol, Rachael Elmaleh, Benjamin D Hallowell, Todd Hampson, Ellen Duong, Abdullah Shihipar, William C Goedel, Brandon DL Marshall. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.02.2024.)

Background: Public Health Dashboards (PHDs) facilitate the monitoring and prediction of disease outbreaks by continuously monitoring the health status of the community. This study aimed to identify design principles and determinants for developing public health surveillance dashboards., Methodology: This scoping review is based on Arksey and O'Malley's framework as included in JBI guidance. Four databases were used to review and present the proposed principles of designing PHDs: IEEE, PubMed, Web of Science, and Scopus. We considered articles published between January 1, 2010 and November 30, 2022. The final search of articles was done on November 30, 2022. Only articles in the English language were included. Qualitative synthesis and trend analysis were conducted., Results: Findings from sixty-seven articles out of 543 retrieved articles, which were eligible for analysis, indicate that most of the dashboards designed from 2020 onwards were at the national level for managing and monitoring COVID-19. Design principles for the public health dashboard were presented in five groups, i.e., considering aim and target users, appropriate content, interface, data analysis and presentation types, and infrastructure., Conclusion: Effective and efficient use of dashboards in public health surveillance requires implementing design principles to improve the functionality of these systems in monitoring and decision-making. Considering user requirements, developing a robust infrastructure for improving data accessibility, developing, and applying Key Performance Indicators (KPIs) for data processing and reporting purposes, and designing interactive and intuitive interfaces are key for successful design and development., (© 2024. The Author(s).)

Objective: Describe the development, implementation, and utilization of dashboards for epidemiological analysis through open data research during the COVID-19 pandemic., Methods: The dashboards were designed to analyze COVID-19 related public data from various sources, including official government data and social media, at world level. Data processing and cleaning techniques were used to join datasets. We calculated Spearman correlation coefficient between the COVID-like symptoms data of the University of Maryland and Facebook Health research, called COVID Trends and Impacts Survey (CTIS) and the official data of notified COVID-19 cases by the Brazilian Health Ministry., Results: The dashboards were successful in predicting the onset of new waves of COVID-19 in Brazil. The data analysis revealed a correlation between the CTIS and the official number of cases the country. This article shows the potential of interactive dashboards as a decision-making tool in the context of public health emergencies, as it was used by the official communication of the Rio Grande do Sul state government., Conclusion: The use of dashboards for predicting the spread of COVID-19 in Brazil was a useful tool for decision-making. To anticipate waves of the disease gives time so that these decisions can be potentially more assertive. This drafts the need of more interdisciplinary actions of this nature, with visualization tools on epidemiologic research.

Background: Per- and polyfluoroalkyl substances (PFAS) encompass a class of chemically and structurally diverse compounds that are extensively used in industry and detected in the environment. The US Environmental Protection Agency (US EPA) 2021 PFAS Strategic Roadmap describes national research plans to address the challenge of PFAS., Objectives: Systematic Evidence Map (SEM) methods were used to survey and summarize available epidemiological and mammalian bioassay evidence that could inform human health hazard identification for a set of 345 PFAS that were identified by the US EPA's Center for Computational Toxicology and Exposure (CCTE) for in vitro toxicity and toxicokinetic assay testing and through interagency discussions on PFAS of interest. This work builds from the 2022 evidence map that collated evidence on a separate set of ∼ 150 PFAS. Like our previous work, this SEM does not include PFAS that are the subject of ongoing or completed assessments at the US EPA., Methods: SEM methods were used to search, screen, and inventory mammalian bioassay and epidemiological literature from peer-reviewed and gray literature sources using manual review and machine-learning software. For each included study, study design details and health end points examined were summarized in interactive web-based literature inventories. Some included studies also underwent study evaluation and detailed extraction of health end point data. All underlying data is publicly available online as interactive visuals with downloadable metadata., Results: More than 13,000 studies were identified from scientific databases. Screening processes identified 121 mammalian bioassay and 111 epidemiological studies that met screening criteria. Epidemiological evidence (available for 12 PFAS) mostly assessed the reproductive, endocrine, developmental, metabolic, cardiovascular, and immune systems. Mammalian bioassay evidence (available for 30 PFAS) commonly assessed effects in the reproductive, whole-body, nervous, and hepatic systems. Overall, 41 PFAS had evidence across mammalian bioassay and epidemiology data streams (roughly 11% of searched chemicals)., Discussion: No epidemiological and/or mammalian bioassay evidence were identified for most of the PFAS included in our search. Results from this SEM, our 2022 SEM on ∼ 150 PFAS, and other PFAS assessment products from the US EPA are compiled into a comprehensive PFAS dashboard that provides researchers and regulators an overview of the current PFAS human health landscape including data gaps and can serve as a scoping tool to facilitate prioritization of PFAS-related research and/or risk assessment activities. https://doi.org/10.1289/EHP13423.

Traditionally, Electronic Medical Records (EMR) have been designed to mimic paper records. Organizing and presenting medical information along the lines that evolved for non-digital records over the decades, reduced change management for medical users, but failed to make use of the potential of organizing digital data. We proposed a method to create clinical dashboards to increase the usability of information in the medical records. Official clinical guidelines were studied by a working group, including dashboard target users. Necessary clinical concepts contained in the medical records were identified according to the clinical context and finally, dedicated technical tools with standard terminologies were used to represent categories of information. We used this method to generate and implement a dashboard for sepsis. The dashboard was found to be appropriate and easy to use by the target users.

Clinical dashboards are an emerging and fast-evolving technology used to support frontline clinicians' practice. Understanding end users' perceived engagement with clinical dashboards is essential to co-design, implementation, and adoption. There is a lack of literature exploring the integration of dashboards into clinical workflow. This rapid review explores clinical end users' perceived engagement with dashboards that support workflow. We conducted a literature search in PubMed and CINAHL. Four articles met our eligibility criteria. Findings reveal variations in taxonomy and measures used to evaluate clinicians' perceived engagement. There are also a variety of reported barriers and facilitators to adoption. Standardized frameworks and vocabulary are needed to facilitate a common understanding of clinical end users' perceived engagement with dashboards.

We developed a standardized framework named RHEA to represent longitudinal status of patient with cancer. RHEA generates a dashboard to visualize patients' data in the Observational Medical Outcomes Partnership-Common Data Model format. The generated dashboard consists of three main parts for providing the macroscopic characteristics of the patient: 1) cohort-level visualization, 2) individual-level visualization and 3) cohort generation.

In support of the Improving Primary Care Understanding of Resources and Screening for Urinary Incontinence to Enhance Treatment initiative with the Veterans Health Administration, we developed a clinical dashboard to support primary care providers in identifying underdiagnosed, undertreated women Veterans with urinary incontinence. This paper describes our dashboard development and evaluation. We employed a user-centered design in determining dashboard requirements, interface design, and functionality. We invited early users at three pilot sites to formal usability reviews. We quantified the dashboard usability using the System Usability Scale and administered surveys and interviews for insights on performance. We employed process maps to uncover processes of end-users' dashboard engagements within local environments. User evaluations demonstrated the dashboard as a helpful instrument in identifying women Veterans with good to excellent usability performance. User feedback offers a user-driven pathway to develop our dashboard that supports clinicians to better care for women Veterans with urinary incontinence., (©2023 AMIA - All rights reserved.)

Heart failure (HF) is a common disease with increasing prevalence around the world. There is high morbidity and mortality associated with poorly controlled HF along with increasing costs and strain on healthcare systems due to a high rate of rehospitalization and resource utilization. Despite the establishment of clear evidence-based guideline directed medical therapies (GDMT) proven to improve HF morbidity and mortality, there remains significant clinical inertia to optimizing HF patients on GDMT. Only a minority of HF patients are prescribed on all four classes of GDMT. To bridge the gap between the vulnerable population of HF patients and lifesaving GDMT, HF implementation is of increasing importance. HF implementation involves strategies and techniques to improve GDMT optimization along with other modalities to improve HF management. HF implementation meets patients where they are, including at the time of acute decompensation in the inpatient setting, at the vulnerable discharge stage, and at the chronic management stage in the outpatient setting. Inpatient HF implementation strategies include protocolized rapid titration of GDMT, site-level audit-and-feedback, virtual GDMT optimization teams, and electronic health record notifications and alerts. Discharge HF implementation strategies include education at patient and provider levels, discharge summaries, and HF transitional programs. Outpatient HF implementation strategies include digital innovations such as electronic health record utilization and mobile applications, population level strategies such as registries and clinical dashboards), changes in HF team structure and member roles, remote monitoring with implanted devices and telemonitoring, and hospital at home care model. With a growing population of HF patients, there is an increasing need for novel and creative HF implementation and monitoring methods., Competing Interests: Declaration of competing interest JX has no disclosures; NKB has no disclosures; GCF has consulted for Abbott, Amgen, AstraZeneca, Bayer, Boehinger Ingelheim, Cytokinetics, Eli Lilly, Johnson & Johnson, Medtronic, Merck, Novartis, and Pfizer; BZ has no disclosures., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Little is known so far about the actual benefits of digital platforms that mediate volunteer helpers with households facing care responsibilities., Objective: This article presents the initial results of a survey conducted among placement agencies as part of a multistage organized interview study. The key question is what benefits do agencies ascribe to the services in their own organization for the users and on a societal or sociospatial level., Material and Methods: For the purpose of conducting explorative guideline-based interviews, four placement agencies were selected. Of these, two use a matching platform and two do not. The data were analyzed using content analysis methods., Results: The providers perceive advantages in efficiency, improvements in quality but also new possibilities for harnessing new helper clientele as important beneficial aspects of using digital placement platforms for their own organization. In terms of nurturing users' trust and acceptance, hybrid matching models appear to be particularly advantageous by deploying digital technologies and also enabling personal support in developing helping relationships. The findings also suggest that public welfare-oriented, quality-assured matching platforms can unfurl additional benefits at sociospatial and societal levels., Conclusion: Besides beneficial aspects for organizations and users it was also possible to reconstruct potential benefits in relation to local care networks., (© 2023. The Author(s).)