Developing a Data Dashboard Framework for Population Health Surveillance: Widening Access to Clinical Trial Findings

Dashboards to Support Implementation of the Quebec Alzheimer Plan: Evaluation Study With Regional and Professional Considerations

BACKGROUND

Health organizations face the critical task of executing and overseeing comprehensive health care. To address the challenges associated with this task, evidence-based dashboards have emerged as valuable tools. Since 2016, the regional health organizations of Quebec, Canada, have been responsible for ensuring implementation of the Quebec Alzheimer Plan (QAP), a provincial plan that aims to reinforce the capacity of primary care services to detect, diagnose, and treat persons with dementia. Despite the provincial scope of the QAP, the diverse material and human resources across regions introduce variability in the interest, utility, and specific needs associated with these dashboards.

OBJECTIVE

The aim of this study was to assess the interest and utility of dashboards to support the QAP implementation, as well as to determine the needs for improving these aspects according to the perspectives of various types of professionals involved across regions.

METHODS

An evaluative study using qualitative methods was conducted within a collaborative research approach involving different stakeholders, including the ministerial advisor and the four project managers responsible for supporting the implementation of the QAP, as well as researchers/scientific advisors. To support these organizations, we developed tailored, 2-page paper dashboards, detailing quantitative data on the prevalence of dementia, the use of health services by persons with dementia, and achievements and challenges of the QAP implementation in each organization's jurisdiction. We then conducted 23 focus groups with the managers and leading clinicians involved in the implementation of the QAP of each regional health organization. Real-time notes were taken using a structured observation grid. Content analysis was conducted according to different regions (organizations with university mandates or nearby organizations, labeled "university/peripheral"; organizations for which only part of the territory is in rural areas, labeled "mixed"; and organizations in remote or isolated areas, labeled "remote/isolated") and according to different types of participants (managers, leading clinicians, and other participants).

RESULTS

Participants from organizations in all regions expressed interest in these dashboards and found them useful in several ways. However, they highlighted the need for indicators on orphan patients and other health care providers. Differences between regions were observed, particularly in the interest in continuity of care in university/peripheral regions and the need for diagnostic tools adapted to the culture in remote/isolated regions.

CONCLUSIONS

These dashboards support the implementation of an Alzheimer Plan and contribute to the emergence of a learning health care system culture. This project allows each region to increase its monitoring capacity for the implementation of the QAP and facilitates reflection among individuals locally carrying out the implementation. The perspectives expressed will guide the preparation of the next iteration of the dashboards.

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.

Developing public health surveillance dashboards: a scoping review on the design principles

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.

Integrating human-centered design in public health data dashboards: lessons from the development of a data dashboard of sexually transmitted infections in New York State

OBJECTIVE

The increased availability of public data and accessible visualization technologies enhanced the popularity of public health data dashboards and broadened their audience from professionals to the general public. However, many dashboards have not achieved their full potential due to design complexities that are not optimized to users' needs.

MATERIAL AND METHODS

We used a 4-step human-centered design approach to develop a data dashboard of sexually transmitted infections for the New York State Department of Health: (1) stakeholder requirements gathering, (2) an expert review of existing data dashboards, (3) a user evaluation of existing data dashboards, and (4) an usability evaluation of the prototype dashboard with an embedded experiment about visualizing missing race and ethnicity data.

RESULTS

Step 1 uncovered data limitations and software requirements that informed the platform choice and measures included. Step 2 yielded a checklist of general principles for dashboard design. Step 3 revealed user preferences that influenced the chart types and interactive features. Step 4 uncovered usability problems resulting in features such as prompts, data notes, and displaying imputed values for missing race and ethnicity data.

DISCUSSION

Our final design was accepted by program stakeholders. Our modifications to traditional human-centered design methodologies to minimize stakeholders' time burden and collect data virtually enabled project success despite barriers to meeting participants in-person and limited public health agency staff capacity during the COVID-19 pandemic.

CONCLUSION

Our human-centered design approach and the final data dashboard architecture could serve as a template for designing public health data dashboards elsewhere.

Community engagement in the development of health-related data visualizations: a scoping review

OBJECTIVE

This scoping review aims to address a gap in the literature on community engagement in developing data visualizations intended to improve population health. The review objectives are to: (1) synthesize literature on the types of community engagement activities conducted by researchers working with community partners and (2) characterize instances of "creative data literacy" within data visualizations developed in community-researcher partnerships.

METHODS

Using the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles from 2010 to 2022 in PubMed, Web of Science, and Google Scholar. A community engagement tool was applied to the studies by independent reviewers to classify levels of community engagement, social determinants, and vulnerable populations.

RESULTS

Twenty-seven articles were included in the scoping review. Twelve articles worked with vulnerable populations. Four articles attempted to alleviate barriers to representation in their respective studies, with addressing language barriers being the most prevalent approach. Thirteen articles considered social determinants of health. Sixteen studies engaged in iterative approaches with intended users when developing the visualization or tool.

DISCUSSION

Only a few significant examples of creative data literacy are incorporated in the studies. We recommend a specific focus on engaging intended users at every step of the development process, addressing language and cultural differences, and empowering intended users as data storytellers.

CONCLUSIONS

There is room for deeper and more meaningful community involvement in the development of health-related data visualizations geared towards them.

Grouping Public Health Skills to Facilitate Workforce Development: A Factor Analysis of PH WINS

OBJECTIVES

This study examined whether distinct factors exist among public health skills, measured through the Public Health Workforce Interests and Needs Survey (PH WINS). Understanding how workforce training needs group is important for developing targeted and appropriate public health workforce training sessions.

DESIGN

Exploratory factor analysis was used to examine public health skills among tier 1 staff (nonmanagers) and a combined group of tier 2 and 3 staff (managers and executives).

SETTING

Data for this study come from the 2017 PH WINS, which assessed public health workforce perceptions of training needs, workplace environment, job satisfaction, perceptions about national trends, and demographics. The analysis included 22 items.

PARTICIPANTS

All public health staff in participating agencies were eligible to complete the survey. The national data set included participants from 47 state health agencies, 26 large local health departments (LHDs), and 71 mid-sized LHDs across all 10 Health and Human Services regions in the United States (including LHDs from all states). The analytic sample was n = 9630 in tier 1, n = 4829 in tier 2, and n = 714 in tier 3 staff.

MAIN OUTCOME MEASURE

Three factors were identified within the skills portion of PH WINS, using exploratory factor analysis. To interpret retained factors, the following parameters were used: factor loadings greater than 0.4, factor cross-loadings less than 0.4 or higher than loadings on other factors, and communalities greater than 0.5.

RESULTS

Factors included (1) data and systems thinking, (2) planning and management, and (3) community collaboration, with slight variation in item loadings between tier 1 and tier 2 and 3 staff analyses.

CONCLUSION

This study was the first known factor analysis of the training needs and workforce skills portion of PH WINS in the published literature. This study advances our conceptualization of public health workforce skills and has the potential to shape future critical workforce training development.

Protocol for developing a dashboard for interactive cohort analysis of oral health-related data

INTRODUCTION

A working knowledge of data analytics is becoming increasingly important in the digital health era. Interactive dashboards are a useful, accessible format for presenting and disseminating health-related information to a wide audience. However, many oral health researchers receive minimal data visualisation and programming skills.

OBJECTIVES

The objective of this protocols paper is to demonstrate the development of an analytical, interactive dashboard, using oral health-related data from multiple national cohort surveys.

METHODS

The flexdashboard package was used within the R Studio framework to create the structure-elements of the dashboard and interactivity was added with the Shiny package. Data sources derived from the national longitudinal study of children in Ireland and the national children's food survey. Variables for input were selected based on their known associations with oral health. The data were aggregated using tidyverse packages such as dplyr and summarised using ggplot2 and kableExtra with specific functions created to generate bar-plots and tables.

RESULTS

The dashboard layout is structured by the YAML (YAML Ain't Markup Language) metadata in the R Markdown document and the syntax from Flexdashboard. Survey type, wave of survey and variable selector were set as filter options. Shiny's render functions were used to change input to automatically render code and update output. The deployed dashboard is openly accessible at https://dduh.shinyapps.io/dduh/ . Examples of how to interact with the dashboard for selected oral health variables are illustrated.

CONCLUSION

Visualisation of national child cohort data in an interactive dashboard allows viewers to dynamically explore oral health data without requiring multiple plots and tables and sharing of extensive documentation. Dashboard development requires minimal non-standard R coding and can be quickly created with open-source software.

The DASH model: Data for addressing social determinants of health in local health departments

Recent frameworks, models, and reports highlight the critical need to address social determinants of health for achieving health equity in the United States and around the globe. In the United States, data play an important role in better understanding community-level and population-level disparities particularly for local health departments. However, data-driven decision-making-the use of data for public health activities such as program implementation, policy development, and resource allocation-is often presented theoretically or through case studies in the literature. We sought to develop a preliminary model that identifies the factors that contribute to data-driven decision-making in US local health departments and describe relationships between them. Guided by implementation science literature, we examined organizational-level capacity and individual-level factors contributing to using data for decision-making related to social determinants of health and the reduction of county-level disparities. This model has the potential to improve implementation of public health interventions and programs aimed at upstream structural factors, by elucidating the factors critical to incorporating data in decision-making.

Digital dashboards visualizing public health data: a systematic review

Introduction

Public health is not only threatened by diseases, pandemics, or epidemics. It is also challenged by deficits in the communication of health information. The current COVID-19 pandemic demonstrates that impressively. One way to deliver scientific data such as epidemiological findings and forecasts on disease spread are dashboards. Considering the current relevance of dashboards for public risk and crisis communication, this systematic review examines the state of research on dashboards in the context of public health risks and diseases.

Method

Nine electronic databases where searched for peer-reviewed journal articles and conference proceedings. Included articles (n = 65) were screened and assessed by three independent reviewers. Through a methodological informed differentiation between descriptive studies and user studies, the review also assessed the quality of included user studies (n = 18) by use of the Mixed Methods Appraisal Tool (MMAT).

Results

65 articles were assessed in regards to the public health issues addressed by the respective dashboards, as well as the data sources, functions and information visualizations employed by the different dashboards. Furthermore, the literature review sheds light on public health challenges and objectives and analyzes the extent to which user needs play a role in the development and evaluation of a dashboard. Overall, the literature review shows that studies that do not only describe the construction of a specific dashboard, but also evaluate its content in terms of different risk communication models or constructs (e.g., risk perception or health literacy) are comparatively rare. Furthermore, while some of the studies evaluate usability and corresponding metrics from the perspective of potential users, many of the studies are limited to a purely functionalistic evaluation of the dashboard by the respective development teams.

Conclusion

The results suggest that applied research on public health intervention tools like dashboards would gain in complexity through a theory-based integration of user-specific risk information needs.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=200178, identifier: CRD42020200178.

Cross-platform mobile app development for disseminating public health information to travelers in Thailand: development and usability

Background

The risk of disease is a key factor that travelers have identified when planning to travel abroad, as many people are concerned about getting sick. Mobile devices can be an effective means for travelers to access information regarding disease prevalence in their planned destinations, potentially reducing the risk of exposure.

Methods

We developed a mobile app, ThaiEpidemics, using cross-platform technology to provide information about disease prevalence and status for travelers to Thailand. We aimed to assess the app’s usability in terms of engagement, search logs, and effectiveness among target users. The app was developed using the principle of mobile application development life cycle, for both iOS and Android. As its data source, the app used weekly data from national disease-surveillance reports. We conduced our study among visitors to the Travel Clinic in the Hospital for Tropical Diseases, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. The participants were informed that the app would collect usage and search logs related to their queries. After the second log-in, the app prompted participants to complete an e-survey regarding their opinions and preferences related to their awareness of disease prevalence and status.

Results

We based our prototype of ThaiEpidemics on a conceptualized framework for visualizing the distribution of 14 major diseases of concern to tourists in Southeast Asia. The app provided users with functions and features to search for and visualize disease prevalence and status in Thailand. The participants could access information for their current location and elsewhere in the country. In all, 83 people installed the app, and 52 responded to the e-survey. Regardless of age, education, and continent of origin, almost all e-survey respondents believed the app had raised their awareness of disease prevalence and status when travelling. Most participants searched for information for all 14 diseases; some searched for information specifically about dengue and malaria.

Conclusions

ThaiEpidemics is evidently potentially useful for travelers. Should the app be adopted for use by travelers to Thailand, it could have an impact on wider knowledge distribution, which might result in decreased exposure, increased prophylaxis, and therefore a potential decreased burden on the healthcare system. For app developers who are developing/implementing this kind of app, it is important to address standardization of the data source and users’ concerns about the confidentiality and safety of their mobile devices.

Using Implementation Mapping to Ensure the Success of PrEP Optimization Through Enhanced Continuum Tracking (PrOTECT) AL-A Structural Intervention to Track the Statewide PrEP Care Continuum in Alabama

INTRODUCTION

Ending the HIV Epidemic initiatives provide a unique opportunity to use implementation scientific methods to guide implementation of evidence-based practices and evaluate their effectiveness in real-word settings to improve HIV inequities. This report demonstrates our use of Implementation Mapping (IM) to engage participating county health departments, AIDS services organizations, and community-based organizations in the development of a data dashboard to track the PrEP care continuum for the state of Alabama, an Ending the HIV Epidemic hotspot.

METHODS

Our project is guided by an overarching Implementation Research Logic Model and by the tenets of IM, a 5-step approach to support researchers and community partners in the systematic selection, development, and/or tailoring of implementation strategies to increase program adoption, implementation, and sustainability.

RESULTS

Step 1, the needs assessment, established baseline data elements for a PrEP care continuum for participating community-based organizations, AIDS services organizations, and the state health department as well as investigated their desire for data visualization and willingness to share data to inform initiatives to improve PrEP access. Step 2 identified adaptability, relative advantage, and complexity as determinants of intervention adoption. Based on findings from steps 1 and 2, the investigators and community partners determined to move forward with development of a data dashboard. Step 3 identified the following implementation strategies to support a dashboard, including development of educational materials, synchronous and asynchronous training, technical assistance, and improved record systems.

DISCUSSION

Using IM supports community-engaged researchers in designing strategies to end the epidemic that are context-specific and more impactful in real-word settings.

A Framework for Evaluating Dashboards in Healthcare

In the era of 'information overload', effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse information sources, dashboards have become an indispensable tool, providing fast, effective, adaptable, and personalized access to information for professionals and the general public alike. However, these objectives place heavy requirements on dashboards as information systems in usability and effective design. Understanding these issues is challenging given the absence of consistent and comprehensive approaches to dashboard evaluation. In this article we systematically review literature on dashboard implementation in healthcare, where dashboards have been employed widely, and where there is widespread interest for improving the current state of the art, and subsequently analyse approaches taken towards evaluation. We draw upon consolidated dashboard literature and our own observations to introduce a general definition of dashboards which is more relevant to current trends, together with seven evaluation scenarios - task performance, behaviour change, interaction workflow, perceived engagement, potential utility, algorithm performance and system implementation. These scenarios distinguish different evaluation purposes which we illustrate through measurements, example studies, and common challenges in evaluation study design. We provide a breakdown of each evaluation scenario, and highlight some of the more subtle questions. We demonstrate the use of the proposed framework by a design study guided by this framework. We conclude by comparing this framework with existing literature, outlining a number of active discussion points and a set of dashboard evaluation best practices for the academic, clinical and software development communities alike.

Humane Visual AI: Telling the Stories Behind a Medical Condition

A biological understanding is key for managing medical conditions, yet psychological and social aspects matter too. The main problem is that these two aspects are hard to quantify and inherently difficult to communicate. To quantify psychological aspects, this work mined around half a million Reddit posts in the sub-communities specialised in 14 medical conditions, and it did so with a new deep-learning framework. In so doing, it was able to associate mentions of medical conditions with those of emotions. To then quantify social aspects, this work designed a probabilistic approach that mines open prescription data from the National Health Service in England to compute the prevalence of drug prescriptions, and to relate such a prevalence to census data. To finally visually communicate each medical condition's biological, psychological, and social aspects through storytelling, we designed a narrative-style layered Martini Glass visualization. In a user study involving 52 participants, after interacting with our visualization, a considerable number of them changed their mind on previously held opinions: 10% gave more importance to the psychological aspects of medical conditions, and 27% were more favourable to the use of social media data in healthcare, suggesting the importance of persuasive elements in interactive visualizations.

From the micro to the macro to improve health: microorganism ecology and society in teaching infectious disease epidemiology

Chronic and emerging infectious diseases and antimicrobial resistance remain a substantial global health threat. Microbiota are increasingly recognised to play an important role in health. Infections also have a profound effect beyond health, especially on global and local economies. To maximise health improvements, the field of infectious disease epidemiology needs to derive learning from ecology and traditional epidemiology. New methodologies and tools are transforming understanding of these systems, from a better understanding of socioeconomic, environmental, and cultural drivers of infection, to improved methods to detect microorganisms, describe the immunome, and understand the role of human microbiota. However, exploiting the potential of novel methods to improve global health remains elusive. We argue that to exploit these advances a shift is required in the teaching of infectious disease epidemiology to ensure that students are well versed in a breadth of disciplines, while maintaining core epidemiological skills. We discuss the following key points using a series of teaching vignettes: (1) integrated training in classic and novel techniques is needed to develop future scientists and professionals who can work from the micro (interactions between pathogens, their cohabiting microbiota, and the host at a molecular and cellular level), with the meso (the affected communities), and to the macro (wider contextual drivers of disease); (2) teach students to use a team-science multidisciplinary approach to effectively integrate biological, clinical, epidemiological, and social tools into public health; and (3) develop the intellectual skills to critically engage with emerging technologies and resolve evolving ethical dilemmas. Finally, students should appreciate that the voices of communities affected by infection need to be kept at the heart of their work.