Shared decision-making and disease management in advanced cancer and chronic kidney disease using patient-reported outcome dashboards.

OBJECTIVES: To assess the use of a co-designed patient-reported outcome (PRO) clinical dashboard and estimate its impact on shared decision-making (SDM) and symptomatology in adults with advanced cancer or chronic kidney disease (CKD). MATERIALS AND METHODS: We developed a clinical PRO dashboard within the Northwestern Medicine Patient-Reported Outcomes system, enhanced through co-design involving 20 diverse constituents. Using a single-group, pretest-posttest design, we evaluated the dashboard's use among patients with advanced cancer or CKD between June 2020 and January 2022. Eligible patients had a visit with a participating clinician, completed at least two dashboard-eligible visits, and consented to follow-up surveys. PROs were collected 72 h prior to visits, including measures for chronic condition management self-efficacy, health-related quality of life (PROMIS measures), and SDM (collaboRATE). Responses were integrated into the EHR dashboard and accessible to clinicians and patients. RESULTS: We recruited 157 participants: 66 with advanced cancer and 91 with CKD. There were significant improvements in SDM from baseline, as assessed by collaboRATE scores. The proportion of participants reporting the highest level of SDM on every collaboRATE item increased by 15 percentage points from baseline to 3 months, and 17 points between baseline and 6-month follow-up. Additionally, there was a clinically meaningful decrease in anxiety levels over study period (T-score baseline: 53; 3-month: 52; 6-month: 50; P < .001), with a standardized response mean (SRM) of -0.38 at 6 months. DISCUSSION: PRO clinical dashboards, developed and shared with patients, may enhance SDM and reduce anxiety among patients with advanced cancer and CKD.

More, better feedback please: are learning analytics dashboards (LAD) the solution to a wicked problem?

There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic Dashboard (LAD), which holds the promise of a comprehensive view of student performance via partial or fully automated feedback delivered to learners in real time. The possibility of displaying performance data visually, on a single platform, so users can access and process feedback efficiently and constantly, and use this to improve their performance, is very attractive to users, educators and institutions. However, the mainstream literature tends to take an atheoretical and instrumentalist view of LADs, a view that uncritically celebrates the promise of LAD's capacity to provide a 'technical fix' to the 'wicked problem' of feedback in health professions education. This paper seeks to recast the discussion of LADs as something other than a benign material technology using the lenses of Miller and Rose's technologies of government and Barry's theory of Technological Societies, where such technical devices are also inherently agentic and political. An examination of the purpose, design and deployment of LADs from these theoretical perspectives can reveal how these educational devices shape and govern the HPE learner body in different ways, which in turn, may produce a myriad of unintended- and ironic- effects on the feedback process. In this Reflections article we wish to encourage health professions education scholars to examine the practices and consequences thereof of the ever-expanding use of LADs more deeply and with a sense of urgency.

SARS-CoV-2 Genomic Epidemiology Dashboards: A Review of Functionality and Technological Frameworks for the Public Health Response.

During the coronavirus disease 2019 (COVID-19) pandemic, the number and types of dashboards produced increased to convey complex information using digestible visualizations. The pandemic saw a notable increase in genomic surveillance data, which genomic epidemiology dashboards presented in an easily interpretable manner. These dashboards have the potential to increase the transparency between the scientists producing pathogen genomic data and policymakers, public health stakeholders, and the public. This scoping review discusses the data presented, functional and visual features, and the computational architecture of six publicly available SARS-CoV-2 genomic epidemiology dashboards. We found three main types of genomic epidemiology dashboards: phylogenetic, genomic surveillance, and mutational. We found that data were sourced from different databases, such as GISAID, GenBank, and specific country databases, and these dashboards were produced for specific geographic locations. The key performance indicators and visualization used were specific to the type of genomic epidemiology dashboard. The computational architecture of the dashboards was created according to the needs of the end user. The genomic surveillance of pathogens is set to become a more common tool used to track ongoing and future outbreaks, and genomic epidemiology dashboards are powerful and adaptable resources that can be used in the public health response.

Overdose deaths before and during the COVID-19 pandemic in a US county.

Introduction: Globally, overdose deaths increased near the beginning of the COVID-19 pandemic, which created availability and access barriers to addiction and social services. Especially in times of a crisis like a pandemic, local exposures, service availability and access, and system responses have major influence on people who use drugs. For policy makers to be effective, an understanding at the local level is needed. Methods: This retrospective epidemiologic study from 2019 through 2021 compares immediate and 20-months changes in overdose deaths from the pandemic start to 16 months before its arrival in Pinellas County, FL We examine toxicologic death records of 1,701 overdoses to identify relations with interdiction, and service delivery. Results: There was an immediate 49% increase (95% CI 23-82%, p < 0.0001) in overdose deaths in the first month following the first COVID deaths. Immediate increases were found for deaths involving alcohol (171%), heroin (108%), fentanyl (78%), amphetamines (55%), and cocaine (45%). Overdose deaths remained 27% higher (CI 4-55%, p = 0.015) than before the pandemic through 2021.Abrupt service reductions occurred when the pandemic began: in-clinic methadone treatment dropped by two-thirds, counseling by 38%, opioid seizures by 29%, and drug arrests by 56%. Emergency transport for overdose and naloxone distributions increased at the pandemic onset (12%, 93%, respectively) and remained higher through 2021 (15%, 377%,). Regression results indicate that lower drug seizures predicted higher overdoses, and increased 911 transports predicted higher overdoses. The proportion of excess overdose deaths to excess non-COVID deaths after the pandemic relative to the year before was 0.28 in Pinellas County, larger than 75% of other US counties. Conclusions: Service and interdiction interruptions likely contributed to overdose death increases during the pandemic. Relaxing restrictions on medical treatment for opioid addiction and public health interventions could have immediate and long-lasting effects when a major disruption, such as a pandemic, occurs. County level data dashboards comprised of overdose toxicology, and interdiction and service data, can help explain changes in overdose deaths. As a next step in predicting which policies and practices will best reduce local overdoses, we propose using simulation modeling with agent-based models to examine complex interacting systems.

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach.

BACKGROUND: Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs. OBJECTIVE: This study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints-events that precede overdoses-to highlight prevention opportunities. METHODS: We conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents' past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations. RESULTS: The findings highlighted the importance of showing decedents' interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection. CONCLUSIONS: The Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.

Early development of local data dashboards to depict the substance use care cascade for youth involved in the legal system: qualitative findings from end users.

INTRODUCTION: Rates of substance use are high among youth involved in the legal system (YILS); however, YILS are less likely to initiate and complete substance use treatment compared to their non legally-involved peers. There are multiple steps involved in connecting youth to needed services, from screening and referral within the juvenile legal system to treatment initiation and completion within the behavioral health system. Understanding potential gaps in the care continuum requires data and decision-making from these two systems. The current study reports on the development of data dashboards that integrate these systems' data to help guide decisions to improve substance use screening and treatment for YILS, focusing on end-user feedback regarding dashboard utility. METHODS: Three focus groups were conducted with n = 21 end-users from juvenile legal systems and community mental health centers in front-line positions and in decision-making roles across 8 counties to gather feedback on an early version of the data dashboards; dashboards were then modified based on feedback. RESULTS: Qualitative analysis revealed topics related to (1) important aesthetic features of the dashboard, (2) user features such as filtering options and benchmarking to compare local data with other counties, and (3) the centrality of consistent terminology for data dashboard elements. Results also revealed the use of dashboards to facilitate collaboration between legal and behavioral health systems. CONCLUSIONS: Feedback from end-users highlight important design elements and dashboard utility as well as the challenges of working with cross-system and cross-jurisdiction data.

National Public Health Dashboards: Protocol for a Scoping Review.

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.

Advancing Newborn Screening Long-Term Follow-Up: Integration of Epic-Based Registries, Dashboards, and Efficient Workflows.

The Connecticut Newborn Screening (NBS) Network, in partnership with the Connecticut Department of Public Health, strategically utilized the Epic electronic health record (EHR) system to establish registries for tracking long-term follow-up (LTFU) of NBS patients. After launching the LTFU registry in 2019, the Network obtained funding from the Health Resources and Services Administration to address the slow adoption by specialty care teams. An LTFU model was implemented in the three highest-volume specialty care teams at Connecticut Children's, involving an early childhood cohort diagnosed with an NBS-identified disorder since the formation of the Network in March 2019. This cohort grew from 87 to 115 over the two-year project. Methods included optimizing registries, capturing external data from Health Information Exchanges, incorporating evidence-based guidelines, and conducting qualitative and quantitative evaluations. The early childhood cohort demonstrated significant and sustainable improvements in the percentage of visits up-to-date (%UTD) compared to the non-intervention legacy cohort of patients diagnosed with an NBS disorder before the formation of the Network. Positive trends in the early childhood cohort, including %UTD for visits and condition-specific performance metrics, were observed. The qualitative evaluation highlighted the achievability of practice behavior changes for specialty care teams through responsive support from the nurse analyst. The Network's model serves as a use case for applying and achieving the adoption of population health tools within an EHR system to track care delivery and quickly fill identified care gaps, with the aim of improving long-term health for NBS patients.

A Novel Electronic Record System for Documentation and Efficient Workflow for Community Health Workers: Development and Usability Study.

BACKGROUND: The COVID-19 pandemic added to the decades of evidence that public health institutions are routinely stretched beyond their capacity. Community health workers (CHWs) can be a crucial extension of public health resources to address health inequities, but systems to document CHW efforts are often fragmented and prone to unneeded redundancy, errors, and inefficiency. OBJECTIVE: We sought to develop a more efficient data collection system for recording the wide range of community-based efforts performed by CHWs. METHODS: The Communities Organizing to Promote Equity (COPE) project is an initiative to address health disparities across Kansas, in part, through the deployment of CHWs. Our team iteratively designed and refined the features of a novel data collection system for CHWs. Pilot tests with CHWs occurred over several months to ensure that the functionality supported their daily use. Following implementation of the database, procedures were set to sustain the collection of feedback from CHWs, community partners, and organizations with similar systems to continually modify the database to meet the needs of users. A continuous quality improvement process was conducted monthly to evaluate CHW performance; feedback was exchanged at team and individual levels regarding the continuous quality improvement results and opportunities for improvement. Further, a 15-item feedback survey was distributed to all 33 COPE CHWs and supervisors for assessing the feasibility of database features, accessibility, and overall satisfaction. RESULTS: At launch, the database had 60 active users in 20 counties. Documented client interactions begin with needs assessments (modified versions of the Arizona Self-sufficiency Matrix and PRAPARE [Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences]) and continue with the longitudinal tracking of progress toward goals. A user-specific automated alerts-based dashboard displays clients needing follow-up and upcoming events. The database contains over 55,000 documented encounters across more than 5079 clients. Available resources from over 2500 community organizations have been documented. Survey data indicated that 84% (27/32) of the respondents considered the overall navigation of the database as very easy. The majority of the respondents indicated they were overall very satisfied (14/32, 44%) or satisfied (15/32, 48%) with the database. Open-ended responses indicated the database features, documentation of community organizations and visual confirmation of consent form and data storage on a Health Insurance Portability and Accountability Act-compliant record system, improved client engagement, enrollment processes, and identification of resources. CONCLUSIONS: Our database extends beyond conventional electronic medical records and provides flexibility for ever-changing needs. The COPE database provides real-world data on CHW accomplishments, thereby improving the uniformity of data collection to enhance monitoring and evaluation. This database can serve as a model for community-based documentation systems and be adapted for use in other community settings.

Promoting a Patient-Centered Understanding of Safety in Acute Mental Health Wards: A User-Centered Design Approach to Develop a Real-Time Digital Monitoring Tool.

BACKGROUND: Acute mental health services report high levels of safety incidents that involve both patients and staff. The potential for patients to be involved in interventions to improve safety within a mental health setting is acknowledged, and there is a need for interventions that proactively seek the patient perspective of safety. Digital technologies may offer opportunities to address this need. OBJECTIVE: This research sought to design and develop a digital real-time monitoring tool (WardSonar) to collect and collate daily information from patients in acute mental health wards about their perceptions of safety. We present the design and development process and underpinning logic model and programme theory. METHODS: The first stage involved a synthesis of the findings from a systematic review and evidence scan, interviews with patients (n=8) and health professionals (n=17), and stakeholder engagement. Cycles of design activities and discussion followed with patients, staff, and stakeholder groups, to design and develop the prototype tool. RESULTS: We drew on patient safety theory and the concepts of contagion and milieu. The data synthesis, design, and development process resulted in three prototype components of the digital monitoring tool (WardSonar): (1) a patient recording interface that asks patients to input their perceptions into a tablet computer, to assess how the ward feels and whether the direction is changing, that is, "getting worse" or "getting better"; (2) a staff dashboard and functionality to interrogate the data at different levels; and (3) a public-facing ward interface. The technology is available as open-source code. CONCLUSIONS: Recent patient safety policy and research priorities encourage innovative approaches to measuring and monitoring safety. We developed a digital real-time monitoring tool to collect information from patients in acute mental health wards about perceived safety, to support staff to respond and intervene to changes in the clinical environment more proactively.

Trainee-supervisor collaboration, progress-visualisation, and coaching: a survey on challenges in assessment of ICU trainees.

BACKGROUND: Assessing trainees is crucial for development of their competence, yet it remains a challenging endeavour. Identifying contributing and influencing factors affecting this process is imperative for improvement. METHODS: We surveyed residents, fellows, and intensivists working in an intensive care unit (ICU) at a large non-university hospital in Switzerland to investigate the challenges in assessing ICU trainees. Thematic analysis revealed three major themes. RESULTS: Among 45 physicians, 37(82%) responded. The first theme identified is trainee-intensivist collaboration discontinuity. The limited duration of trainees' ICU rotations, large team size operating in a discordant three-shift system, and busy and unpredictable day-planning hinder sustained collaboration. Potential solutions include a concise pre-collaboration briefing, shared bedside care, and post-collaboration debriefing involving formative assessment and reflection on collaboration. The second theme is the lack of trainees' progress visualisation, which is caused by unsatisfactory familiarisation with the trainees' development. The lack of an overview of a trainee's previous achievements, activities, strengths, weaknesses, and goals may result in inappropriate assessments. Participants suggested implementing digital assessment tools, a competence committee, and dashboards to facilitate progress visualisation. The third theme we identified is insufficient coaching and feedback. Factors like personality traits, hierarchy, and competing interests can impede coaching, while high-quality feedback is essential for correct assessment. Skilled coaches can define short-term goals and may optimise trainee assessment by seeking feedback from multiple supervisors and assisting in both formative and summative assessment. Based on these three themes and the suggested solutions, we developed the acronym "ICU-STAR" representing a potentially powerful framework to enhance short-term trainee-supervisor collaboration in the workplace and to co-scaffold the principles of adequate assessment. CONCLUSIONS: According to ICU physicians, trainee-supervisor collaboration discontinuity, the lack of visualisation of trainee's development, and insufficient coaching and feedback skills of supervisors are the major factors hampering trainees' assessment in the workplace. Based on suggestions by the survey participants, we propose the acronym "ICU-STAR" as a framework including briefing, shared bedside care, and debriefing of the trainee-supervisor collaboration at the workplace as its core components. With the attending intensivists acting as coaches, progress visualisation can be enhanced by actively collecting more data points. TRIAL REGISTRATION: N/A.

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action.

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.

Health-system specialty pharmacist intervention types, acceptance, and associated actions for patients with multiple sclerosis.

PURPOSE: Health-system specialty pharmacy (HSSP) pharmacists play an integral role in the care of patients with multiple sclerosis (PwMS) by facilitating medication access, providing counseling, improving adherence, and decreasing provider workload. However, current literature detailing pharmacist interventions and their acceptance rates in this population is limited. The purpose of this study was to identify the types and acceptance rate of clinical interventions completed by pharmacists for PwMS. METHODS: To evaluate the acceptance rate of HSSP pharmacist interventions, we conducted a retrospective, multicenter, observational, descriptive study for the period from October 2019 to August 2022. Intervention types were categorized into reasons for intervention, recommendations from the pharmacists, and their acceptance rates. RESULTS: For 225 patients enrolled in HSSP services, 449 interventions were completed, with an average of 2.0 interventions per patient. Most interventions identified were associated with medication adherence (28.7%), medication regimen (27.6%), adverse drug reaction (ADR) (20.7%), and laboratory values (15.1%). The average adherence, defined by the proportion of days covered, was 94%. The most common recommendations were to continue therapy (14.9%), schedule laboratory tests (12.7%), and follow up with providers (11.8%). Recommendations had an acceptance rate of 85.3%, with 3.8% of recommendations declined and 10.9% requiring follow-up with providers. CONCLUSION: Pharmacists impact patient outcomes through the completion of clinical interventions that improve adherence, identify medication regimen problems, manage ADRs, and coordinate proper laboratory testing. Pharmacist recommendations were most often accepted for interventions related to medication regimen and ADRs. Proper identification and management of medication regimen concerns, as well as tolerability of medications, can positively impact adherence and improve overall patient outcomes.

End Users' Perceived Engagement with Clinical Dashboards: A Rapid Review.

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.

Getting More Out of Clinical Documentation: Can Clinical Dashboards Yield Clinically Useful Information?

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.

Operationalizing an open-source dashboard for communicating results of wastewater-based surveillance.

COVID-19 saw the expansion of public health tools to manage the pandemic. One tool that saw extensive use was the public health dashboard, web-based visualization tools that communicate information to users in easy-to-read graphics. Dashboards were widely used prior to the pandemic, but COVID-19 saw expanded use and development. To date, dashboards have become an important part of public health surveillance programs around the world helping decisionmakers use data to evaluate different public health metrics including caseloads, hospitalizations, and environmental surveillance results from testing wastewater. Wastewater surveillance provides community-based, spatially relevant data on disease trends within communities to assess the scale of infection in a region, which makes it an excellent candidate for dashboard development to improve public health. We developed a dashboard for New York State's wastewater surveillance program using open-source, reproducible web programming. The dashboard we developed has been used for the COVID-19 response in New York, and our methods can be adapted to other programs and pathogens. We provide:•descriptions of how the dashboard was developed and maintained•specific guidance for reproducing our dashboard in other areas and for other pathogens•fully reproducible code with step-by-step instructions for researchers and professionals to make their own data dashboards.

Participatory design of teacher dashboards: navigating the tension between teacher input and theories on teacher professional vision.

In the field of AI in education, there is a movement toward human-centered design in which the primary stakeholders are collaborators in establishing the design and functionality of the AI system (participatory design). Several authors have noted that there is a potential tension in participatory design between involving stakeholders and, thus, increasing uptake of the system on the one hand, and the use of educational theory on the other hand. The goal of the present perspective article is to unpack this tension in more detail, focusing on the example of teacher dashboards. Our contribution to theory is to show that insights from the research field of teacher professional vision can help explain why stakeholder involvement may lead to tension. In particular, we discuss that the sources of information that teachers use in their professional vision, and which data sources could be included on dashboards, might differ with respect to whether they actually relate to student learning or not. Using this difference as a starting point for participatory design could help navigate the aforementioned tension. Subsequently, we describe several implications for practice and research that could help move the field of human centered design further.

Digital Health Dashboards for Decision-Making to Enable Rapid Responses During Public Health Crises: Replicable and Scalable Methodology.

BACKGROUND: The COVID-19 pandemic has reiterated the need for cohesive, collective, and deliberate societal efforts to address inherent inefficiencies in our health systems and overcome decision-making gaps using real-time data analytics. To achieve this, decision makers need independent and secure digital health platforms that engage citizens ethically to obtain big data, analyze and convert big data into real-time evidence, and finally, visualize this evidence to inform rapid decision-making. OBJECTIVE: The objective of this study is to develop replicable and scalable jurisdiction-specific digital health dashboards for rapid decision-making to ethically monitor, mitigate, and manage public health crises via systems integration beyond health care. METHODS: The primary approach in the development of the digital health dashboard was the use of global digital citizen science to tackle pandemics like COVID-19. The first step in the development process was to establish an 8-member Citizen Scientist Advisory Council via Digital Epidemiology and Population Health Laboratory's community partnerships. Based on the consultation with the council, three critical needs of citizens were prioritized: (1) management of household risk of COVID-19, (2) facilitation of food security, and (3) understanding citizen accessibility of public services. Thereafter, a progressive web application (PWA) was developed to provide daily services that address these needs. The big data generated from citizen access to these PWA services are set up to be anonymized, aggregated, and linked to the digital health dashboard for decision-making, that is, the dashboard displays anonymized and aggregated data obtained from citizen devices via the PWA. The digital health dashboard and the PWA are hosted on the Amazon Elastic Compute Cloud server. The digital health dashboard's interactive statistical navigation was designed using the Microsoft Power Business Intelligence tool, which creates a secure connection with the Amazon Relational Database server to regularly update the visualization of jurisdiction-specific, anonymized, and aggregated data. RESULTS: The development process resulted in a replicable and scalable digital health dashboard for decision-making. The big data relayed to the dashboard in real time reflect usage of the PWA that provides households the ability to manage their risk of COVID-19, request food when in need, and report difficulties and issues in accessing public services. The dashboard also provides (1) delegated community alert system to manage risks in real time, (2) bidirectional engagement system that allows decision makers to respond to citizen queries, and (3) delegated access that provides enhanced dashboard security. CONCLUSIONS: Digital health dashboards for decision-making can transform public health policy by prioritizing the needs of citizens as well as decision makers to enable rapid decision-making. Digital health dashboards provide decision makers the ability to directly communicate with citizens to mitigate and manage existing and emerging public health crises, a paradigm-changing approach, that is, inverting innovation by prioritizing community needs, and advancing digital health for equity. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/46810.

Informatics progress of the Global Burden of Animal Diseases programme towards data for One Health.

The Global Burden of Animal Diseases (GBADs) programme will provide data-driven evidence that policy-makers can use to evaluate options, inform decisions, and measure the success of animal health and welfare interventions. The GBADs' Informatics team is developing a transparent process for identifying, analysing, visualising and sharing data to calculate livestock disease burdens and drive models and dashboards. These data can be combined with data on other global burdens (human health, crop loss, foodborne diseases) to provide a comprehensive range of information on One Health, required to address such issues as antimicrobial resistance and climate change. The programme began by gathering open data from international organisations (which are undergoing their own digital transformations). Efforts to achieve an accurate estimate of livestock numbers revealed problems in finding, accessing and reconciling data from different sources over time. Ontologies and graph databases are being developed to bridge data silos and improve the findability and interoperability of data. Dashboards, data stories, a documentation website and a Data Governance Handbook explain GBADs data, now available through an application programming interface. Sharing data quality assessments builds trust in such data, encouraging their application to livestock and One Health issues. Animal welfare data present a particular challenge, as much of this information is held privately and discussions continue regarding which data are the most relevant. Accurate livestock numbers are an essential input for calculating biomass, which subsequently feeds into calculations of antimicrobial use and climate change. The GBADs data are also essential to at least eight of the United Nations Sustainable Development Goals.

Le programme " Impact mondial des maladies animales " (GBADs) a pour but de réunir des éléments probants axés sur des données, qui soient exploitables par les décideurs politiques pour évaluer les solutions envisagées, fonder leurs décisions et mesurer le succès des interventions dans les domaines de la santé et du bien-être des animaux. L'équipe informatique du GBADs a conçu un processus transparent pour l'identification, l'analyse, la visualisation et le partage des données, grâce auquel il sera possible d'estimer l'impact des maladies du bétail et de réaliser des modèles et des tableaux de bord sur le sujet. Les données ainsi réunies peuvent être combinées avec celles couvrant d'autres problématiques ayant un impact mondial (santé humaine, pertes de récoltes, maladies d'origine alimentaire) afin de fournir l'éventail complet d'informations Une seule santé requis pour faire face à des enjeux tels que la résistance aux agents antimicrobiens ou le changement climatique. La première phase du programme a consisté à recueillir des données ouvertes auprès de diverses organisations internationales (qui procèdent également à leur propre transformation numérique). Les efforts déployés pour parvenir à une estimation précise des effectifs des cheptels ont mis en lumière les difficultés à trouver les données détenues par différentes sources, à y accéder et à les recouper au fil du temps. Des ontologies et des bases de données graphiques sont en cours d'élaboration pour résoudre le problème des silos de données et pour améliorer la facilité de recherche et l'interopérabilité des données. Les données du GBADs sont désormais expliquées sous forme de tableaux de bord, de récits construits à partir des données, ainsi que dans un site web documentaire et un Manuel de gouvernance des données, tous disponibles via une interface de programmation d'applications. Le partage des évaluations de la qualité des données renforce la confiance dans ces dernières et encourage à les appliquer pour traiter les problématiques affectant l'élevage ou relevant de l'approche Une seule santé. Les données relatives au bien-être animal présentent une difficulté particulière : elles sont, pour l'essentiel, détenues à titre privé et la question de savoir quelles sont les données les plus pertinentes est toujours en discussion. Les effectifs des cheptels doivent avoir été déterminés de manière précise afin de calculer la biomasse animale, élément qui entre par la suite dans le calcul des quantités d'agents antimicrobiens utilisés et des indicateurs du changement climatique. Les données du programme GBADs sont également essentielles au regard d'au moins huit des objectifs de développement durable des Nations Unies.

El programa sobre el Impacto Global de las Enfermedades Animales (GBADs) proporcionará información contrastada y basada en el uso de datos de la que luego puedan servirse los planificadores de políticas para valorar distintas opciones, decidir con conocimiento de causa y medir la eficacia de una u otra intervención en materia de sanidad y bienestar animales. El equipo informático encargado del GBADs está preparando un proceso transparente destinado a seleccionar, analizar, visualizar y poner en común datos que ayuden a calcular la carga de enfermedades del ganado y a guiar la elaboración de modelos y paneles de control. Estos datos pueden ser combinados con datos referidos a otros grandes problemas planetarios (salud humana, pérdida de cultivos, enfermedades de transmisión alimentaria) para obtener el repertorio completo de información en clave de Una sola salud que se necesita para abordar problemáticas como la resistencia a los antimicrobianos o el cambio climático. El programa empezó por reunir datos abiertos procedentes de organizaciones internacionales (inmersas, por otra parte, en su propio proceso de transformación digital). La labor emprendida para estimar con exactitud las cifras de ejemplares del mundo pecuario reveló ciertos problemas a la hora de encontrar, obtener y conciliar datos de distintas fuentes a lo largo del tiempo. Ahora se están elaborando ontologías y bases de datos gráficos para crear conexiones entre los "silos de datos" y lograr que los datos sean a la vez más compatibles entre sí y más fáciles de localizar. Paneles de control, interpretaciones narrativas de los datos ("data stories"), un sitio web de documentación y un manual de gestión de datos ayudan a explicar y aprehender los datos del GBADs, accesibles ahora por medio de una interfaz de programación de aplicaciones. El hecho de poner en común las evaluaciones de la calidad de los datos genera mayor confianza en esta información, promoviendo con ello su aplicación en temas de ganadería y de Una sola salud. Los datos de bienestar animal plantean una particular dificultad, pues gran parte de esta información está en manos privadas y todavía no está claro cuáles son los datos de mayor interés. Disponer de cifras exactas sobre el número de cabezas de ganado es fundamental para efectuar los cálculos de biomasa que después se utilizan para hacer otros cómputos referidos al uso de antimicrobianos y al cambio climático. Los datos del GBADs son asimismo esenciales para al menos ocho de los Objetivos de Desarrollo Sostenible de las Naciones Unidas.