Culture of Data 2025

This session will spotlight how diverse fields—spanning environmental health, maternal and child health, education, and food security—converge to address the social determinants of health and advance equity.

Our 3 panelists, representing a range of sectors including community organizations, academia, public health, and state/local government, will share insights on:

The interconnected roles of education, food systems, environmental health, and maternal and child health in shaping community well-being.

How cross-sector collaboration can amplify efforts to address structural inequities and improve health outcomes.

Real-world examples of data integration and sharing across disciplines to create actionable solutions for health justice.

This session will provide attendees with a deeper understanding of how interdisciplinary partnerships can dismantle systemic barriers and leverage community assets to create a healthier, more equitable future. Be inspired by innovative strategies and frameworks that set the tone for meaningful action throughout the conference.

A first step to improving the way you communicate data and analysis is to have some basic understanding of best practices and strategies. In this talk, I lay out three principles for better data visualization: Show the Data, Reduce the Clutter, and Integrate Graphics and Text. I also lay out three principles for better presentations: Visualize, Unify, and Focus. Together, with the help of examples, both good and bad, I demonstrate how anyone can more effectively communicate their data and elicit insight.

Grab your lunch and join us for a dynamic and fun virtual networking event! Ditch the awkward small talk and connect with your Culture of Data peers in a relaxed and interactive setting. We'll be using breakout rooms to facilitate 3 rounds of intimate small group discussions, giving you the opportunity to connect with multiple professionals and enjoy your meal at the same time. And to help you return to the conference refreshed, we'll end this session with a re-energizing mindfulness exercise. Come expand your network and make valuable connections from the comfort of your own computer.

Wastewater-based epidemiology (WBE) offers a promising tool for monitoring infectious diseases and advancing health equity, but when working with Indigenous communities, challenges rooted in past and present exploitative research practices must be addressed to build trust and foster collaboration. Historical inequities have significantly impacted public health in these communities, which underscores the need for ethical and culturally aligned engagement strategies. This presentation will explore the benefits of integrating the principles of Indigenous Research Methodologies (IRM) into WBE projects to improve data collection and analysis practices when working with Tribal communities. 

Drawing on specific IRM principles – relationality, respect, responsibility, representation, relevance, and reciprocity – this presentation illuminates how WBE projects can adopt a collaborative approach that respects Tribal self-determination and promotes culturally appropriate practices. This approach cultivates effective engagement and empowers Tribal communities to lead in shaping public health strategies, resulting in tangible benefits in these communities. By integrating these principles, WBE initiatives can be tailored to reflect the unique needs of Tribal communities such as respecting Tribal sovereignty and data sovereignty. 

Key recommendations presented demonstrate the transformative impact of incorporating IRM principles into WBE initiatives. These recommendations include establishing Tribal liaisons and cultivating relationships with respect for history and culture to facilitate communication and Indigenous representation. Furthermore, by implementing reflexive evaluation, projects ensure that Tribal priorities and community-identified benefits align with a project’s initiatives, and that Tribal sovereignty and data sovereignty are respected. 

This presentation will showcase examples of Colorado’s innovative, strength-based approach in taking strides towards these recommendations as a framework for leveraging data to address health inequity within the state. By prioritizing Indigenous voices at the forefront, this work aims to respect Tribal sovereignty and data sovereignty, promote ethical, culturally responsive public health solutions, and provide valuable insights to public health professionals, policymakers, and Tribal leaders.

The Colorado Equity Compass (CEC) is a resource platform and capacity-building initiative that helps communities understand the social determinants of health and learn how to advocate for change. Its website is free, easy-to-use, and combines population statistics, data visualizations, community stories, and advocacy tools to bring local data to life. Users can access statistics about the social determinants of health for each neighborhood and county in Colorado. This includes data about economics, education, the environment, food, health services, housing, and social factors.

In 2024, CEC launched a data-use learning collaborative, providing a paid opportunity for community-based organizations with little to no internal data capacity to gain practical skills using data to promote equity. Organizations worked with social determinants of health data to learn about the needs of the communities they serve. The collaborative consisted of virtual meetings over five months with opportunities for individualized data help sessions. Each meeting focused on data skills, from the fundamentals of how to frame data, to beginner analysis approaches, to practice presenting information. Throughout the collaborative, each participant worked on a data project meant to practice skills and create a relevant, equity-focused data product for their organization to use. Organization received a stipend for participating.

In this presentation, we will provide an overview of the learning collaborative effort, including successes and lessons learned. We will also share solutions to common data problems that learning collaborative participants encountered, including what to do when data is not available because of small sample size or there's no disaggregation. We are pleased to co-present with a community partner from the learning collaborative who will share their data project and reflect on their experience working with social determinant of health data.

The CEC is supported by The Colorado Trust, the Colorado Health Institute, Change Matrix, and Consume & Create.

Firearms in Colorado are common; 45% of Coloradans report they live in a home with a firearm. The majority of firearm owners also state they own a firearm to protect their homes and families. However, access to a firearm is a risk factor for suicide lethality as 90% of all suicide attempts with a firearm are fatal, and research suggests the time between deciding to attempt suicide and then attempting suicide is often under 10 minutes. Thus, strategies to reduce access to lethal means are a promising strategy for suicide prevention. 

Since 2014, the Colorado Office of Suicide Prevention has supported the Colorado Gun Shop Project (GSP) as a strategy to promote lethal means safety in Colorado. The GSP coordinates outreach between local firearm community advocates and firearm retailers/owners to share effective safe storage strategies for Coloradans who own firearms. However, measuring outreach in the community has been a consistent challenge for GSP program evaluation efforts. This presentation provides an overview of the GSP, its implementation in the Office of Suicide Prevention, and efforts to improve data quality from GSP outreach efforts. 

In 2024, The Office of Suicide Prevention created a new data collection protocol for the GSP that emphasized timely reporting with local insights from GSP firearm community advocates. In this presentation we will present 1) lessons learned from previous iterations of the GSP implementation 2) the use of online survey tools (Qualtrics) to improve data collection from GSP  firearm community advocates and 3) how GSP automates data collection and analysis using Google Looker Studio to create reports that can inform program decisions for the Office of Suicide Prevention as well as local outreach teams, and improve reporting processes for GSP funding agencies.

Background: Texas’ 2021 SB8 was passed in September 2021, which effectively banned abortion after six weeks. We sought to investigate the association of this change in legal access with infant mortality.
Methods: Utilizing CDC Wonder mortality data from January 2018 to June 2024, an interrupted time series analysis assessed the association between changes in the law and monthly counts of deaths under the age of one year in Texas, adjusting for both long term time trends and seasonality, using abortion-rights protective jurisdictions including Colorado for comparison. The interruption point was set at 3 months after legal access changed. Aggregate mortality was assessed along with mortality disaggregated by race, ethnicity, and two groups of specific causes.
Results: Overall mortality was 18% higher after SB8 when compared to before. Rate Ratio (RR): 18%, (95% Confidence Interval (CI): 10%, 26%). In disaggregated race and ethnicity data, non-Hispanic Black mortality was 21% higher (95%CI: 6%, 39%), where non-Hispanic white mortality was 15% (95% CI: 2%, 30%). Cause-specific mortality was also higher after SB8. Grouped comparison states showed a 6% increase in the same timeframe, while separately analyzed Colorado infant mortality showed no evidence of change.
Discussion: Higher mortality after SB8 was identified both overall and in disaggregated racial and ethnic groups, with non-Hispanic Black infants having the highest increase. Increases in some cause-specific mortality associated with changes in abortion access were even more pronounced.
Conclusion: This study contributes evidence that infant mortality in Texas rose significantly after the implementation of a six-week abortion ban, and that impacts were differential by race and ethnicity, as well as among specific causes of death. Changes to population health in association with abortion bans may extend beyond pregnancy, providing further motivation for ensuring abortion access in states like Colorado.

Climate change is accelerating the frequency and intensity of wildfires, particularly in Colorado where drought and increased heat have led to significantly longer fire seasons and an average of over 5,000 reported wildfires yearly. Knowing that reduced air quality affects population health, Center for Improving Value in Health Care (CIVHC) set out to understand health impacts of wildfires and ozone pollutant events. The Wildfire and Ozone Impact on Health analysis uses data from the Environmental Protection Agency (EPA) and the Colorado All Payer Claims Database (CO APCD) to evaluate the impact of wildfires and ozone spike events on emergency department (ED) visits for respiratory and circulatory conditions. 

CIVHC’s analysis found that poor air quality impacts younger and older people, with the 0-17 and 65+ age groups consistently showing higher rates of ED visits across various environmental conditions, indicating a heightened vulnerability among these groups. In winter months above the ozone threshold, children and youth had a significantly higher ED visit rate compared to other age groups and months without poor air quality.

Seniors (65+) also experience heightened impact during these times. 

Findings from the analysis show that air quality events could trigger emergent health care events, and show which groups experience the most severe impacts of wildfire and ozone pollutants. This session will delve into potential policy response and discuss where communities can allocate resources and target interventions to protect populations most impacted by these events.

Data from the Healthy Kids Colorado Survey highlights the critical role of data in addressing youth mental health and suicide prevention. Suicide remains a leading cause of death among high school students, with disproportionately high rates among LGBTQ+ youth and racially diverse populations. Understanding these disparities is essential for designing culturally responsive interventions that address the unique social, cultural, and economic stressors faced by minority youth.

Our data, obtained from the Colorado School of Public Health’s research program, includes raw survey responses from 2015, 2017, 2019, 2021, and 2023. Through a detailed analysis of age, mental health indicators, school/district identifiers, and demographics, we identified key trends, assessed the impact of past interventions, and highlighted areas requiring further support.

Notably, the 2023 survey revealed a decline in persistent sadness, hopelessness, and suicidal ideation among Colorado youth compared to 2021. This positive shift follows a surge in mental health challenges during the pandemic, which prompted data-driven policy responses. In 2021, Colorado lawmakers launched a statewide initiative providing free counseling for children and adolescents, while school districts expanded access to mental health services by hiring more social workers, counselors, and psychologists.

These findings suggest that strategic investments in mental health and suicide prevention—guided by data—are making a measurable impact. Colorado’s approach demonstrates the power of collaborative data use in advancing health equity and improving youth well-being.

The Healthy Food for Denver’s Kids initiative (HFDK), created through a 2018 ballot measure, aspires to improve access to healthy food and food-based education for children and families throughout Denver. Administered by the Denver Department of Public Health and Environment, HFDK allocates grants to nonprofits and public entities in Denver. CAI, the external evaluator, utilizes cluster and multi-level evaluation strategies to measure and assess HFDK’s outcomes and impact. We will present two innovative ways CAI uses data systems and visual analytics to promote community collaboration to improve hunger and nutrition for families in Denver. 

As part of CAI’s HFDK evaluation, grantees submit quarterly and annual-level data on their programmatic activities through Quickbase (QB), a cloud-based project management platform. Data consists of process and outcomes metrics, as well as client-level feedback, on food access and distribution; food and nutrition assistance; food and nutrition education; food production; reach; community engagement; and partnerships. Using QB, we compile and analyze grantee data to produce reports, showcasing key trends and insights to share with stakeholders, commission members, and the funder. These reports support strategic decision-making and provide transparency on program performance. Grantees can also access their data in real-time, visualize outputs and outcomes via data dashboards, and utilize data to enhance their programming, services, and reach. 

The evaluation includes a thorough review of secondary data, utilizing grantee-submitted information and publicly available food and nutrition data from city sources to benchmark HFDK's contributions to improvements. This also includes geospatial analysis and detailed maps, visualizations highlighting the geographic distribution of services across Denver’s 61 high-priority neighborhoods where food insecurity remains prevalent.

The presentation will showcase our evaluation approaches and how grantee and citywide data, accessible through real-time and highly visual platforms, equips HFDK stakeholders with actionable insights for advocacy, education, partnership-building, and informed strategic planning.

This presentation explores the accessibility of obstetric providers in Adams County, Colorado, a rural region facing unique challenges in healthcare delivery. Access to obstetric care is a critical issue affecting maternal and child health outcomes, with disparities often exacerbated by geographic and socioeconomic factors. We analyze the spatial distribution of obstetrics services, identify barriers to care, and examine how social determinants of health, such as income, transportation, and education, influence access to prenatal and postnatal care in Adams County. Specifically, in our analysis we looked at the distribution of live births, women of reproductive age, and birth rates across Adams County, identifying where there was the most need for obstetric care. Additionally, we looked at birth outcomes, including low birth weight, prenatal care, forms of payment, and maternal morbidity conditions among births from 2021 to 2023. We also conducted a drive-time analysis at 15-, 30-, and 60-minute intervals, identifying areas of Adams County with decreased obstetric care access.

By leveraging geographic information systems (GIS), patient demographics, birth outcomes, and service availability data, this presentation highlights significant gaps in obstetric care access and its impact on maternal and child health outcomes. These findings identify disparities in access to care among rural populations in Adams County, underscoring the need for data-driven strategies to be integrated into policy and healthcare planning.

This presentation demonstrates how data can be utilized to address the social determinants of health that affect maternal and child care. Attendees will gain valuable insights into the intersection of rural healthcare, social determinants, and data science, empowering them to apply these findings in their own communities to foster more just and accessible healthcare systems.

This presentation delves into applying the Indigenous Social Determinants of Health when discussing the SDoH within Colorado. It will provide a high-level overview of CDPHE-specific examples of collaborative partnerships that respect Tribal sovereignty and Tribal data sovereignty rights and utilize best practices for engaging American Indian and Alaska Native communities. For example, we will highlight work with CDPHE's Baby & You program to provide strategic guidance and support with outreach. Outreach which has resulted in an increase in Native American and Alaska Native participation in comparison to previous survey participation.

"Through these collaborations, we will demonstrate how incorporating practices that are sovereignty-affirming and mindful of Indigenous Determinants of Health can improve public health data systems. Our goal is to focus on how entities should have parameters set in place for Tribal data collection.

We will examine strategies that prioritize community involvement in every step of the process, ensuring that American Indian/Alaska Native voices remain at the center of health equity initiatives. Furthermore, we will explain the importance of braiding Indigenous determinants with SDoH when focusing on AIAN communities, which is currently not being considered in data collection. Moreover, we will touch on how data pertaining to the Indigenous determinants, which can transcend SDoH and reflect the holistic health perspectives valued by American Indian/Alaska Native populations. Throughout these discussions, our presentation addresses the importance of Tribal data sovereignty and the ethical considerations necessary for equitable partnerships along the way.

Ultimately, this presentation aims to foster an understanding of Indigenous social determinants of health and inspire action among attendees by emphasizing the importance of partnerships rooted in respect, trust, inclusion, and shared goals. By advancing innovative practices and promoting collaboration, it seeks to build a stronger foundation for Indigenous health equity initiatives grounded in cultural identity and Tribal sovereignty."

The future of public health is now. This high-energy Lightning Round session brings together visionary leaders exploring cutting-edge trends—AI-driven health solutions, emerging technologies, and next-generation data strategies—to dismantle systemic inequities. Discover how data science is reshaping access to care, housing, employment, and environmental conditions. Walk away with actionable insights that will help you harness data for health justice and drive lasting change in your field. Don't miss this rapid-fire, thought-provoking session packed with bold ideas and real-world solutions.

Featuring these presentations:
Engaging Youth to Reshape Health : The Power of Youth Councils by Chanelle Jones Ahmed, Stacey Adimou, Vivian Thompson and Stephanie De Jesus Ayala
Artificial Intelligence (AI) in healthcare delivery – a systematic review by Garvita Thareja

This presentation highlights the development of a streamlined data collection and sharing system for Adams County Health Department’s (ACHD) Harm Reduction Program, in partnership with the Colorado Department of Public Health and Environment (CDPHE). Supporting multiple programs, the Harm Reduction Program faced complex reporting requirements and relied on a time-intensive, error-prone process: collecting client data on paper and manually entering it into both an internal Excel document and CDPHE’s REDCap database. Seeking to improve efficiency and accuracy, the Harm Reduction team collaborated with ACHD’s Health Data and GIS (HDGIS) team to create the ACHD Harm Reduction Data Ecosystem.

Methods
   The HDGIS team designed the Harm Reduction Data Ecosystem using ESRI software to streamline data workflows and facilitate accurate reporting. To safeguard sensitive client data, the HDGIS team created a temporary data collection database on ArcGIS Online and a permanent secure database on ArcGIS Enterprise. An automated process then securely transferred data to the internal database, reducing manual entry. The team also built two client lookup dashboards for easy record access and updates, enhancing client care continuity. Finally, a monthly data export feature automated ACHD-to-CDPHE data uploads, improving data accuracy and timely reporting.

Results
The Harm Reduction team’s transition to the ACHD Harm Reduction Data Ecosystem has resulted in higher data quality, improved client tracking, enhanced resource referrals, and greater program efficiency. Staff spend less time on data entry, allowing more focus on client services. The team has also expanded their use of program data for insights and informed decision-making.

Recommendations/Practical Applications/Future Goals
   The Harm Reduction Data Ecosystem has strengthened ACHD’s partnership with CDPHE and enhanced data management for the Harm Reduction team. This project serves as a model for similar data solutions across ACHD programs, demonstrating the impact of an integrated, client-centered data approach."

Behavioral health disparities in rural areas are significantly influenced by social determinants of health (SDOH), such as economic stability, access to care, and social support networks. Northeast Colorado, like many rural regions, faces unique challenges, including provider shortages, geographic isolation, and systemic barriers that exacerbate mental health inequities. This presentation explores how data science can be a powerful tool for addressing these disparities, offering actionable insights into the complex relationships between SDOH and behavioral health outcomes. By leveraging data-driven approaches, stakeholders can identify at-risk populations, design targeted interventions, and advocate for policy changes that prioritize health equity.

Through a combination of case studies, local data analysis, and community engagement strategies, participants will gain a comprehensive understanding of how to integrate data science into behavioral health planning. The presentation will highlight practical tools for mapping SDOH, employing predictive analytics, and fostering collaborative partnerships to implement tailored solutions. Attendees will leave equipped with actionable strategies to harness data for advancing health justice and improving behavioral health outcomes in Northeast Colorado’s rural communities.

Explore groundbreaking research and real-world applications of data in tackling social determinants of health. This interactive poster session showcases innovative projects that use data to expose inequities and drive actionable change in public health. From housing disparities to environmental justice, presenters will share key insights and engage in live discussions. Drop in to discover cutting-edge strategies, connect with experts, and uncover new ways data can be leveraged to advance health equity in your community.

Poster Session 1: 10-year Evaluation Report of the Integrated Health Care Model at Colorado Coalition for the Homeless by Madison Stiglich

Poster Session 2: Early-life exposure to black carbon and childhood lung function in the Healthy Start study by Christopher Hollander

Poster Session 3: Meeting LGBTQ+ Youth in the Moment: Exploring the impact of protective factors on LGBTQ+ suicidality through the Healthy Kids Colorado Survey by Christine Mulitauopele and  Tate Steidley

Poster Session 4: Vaccine confidence among Afghan, Ukrainian, and Somali Communities: A Qualitative Approach by Annika Jones, Graham Hardt and Tara Trujillo

Poster Session 5: Driving Health Equity Through Inclusive Demographic Data: Best Practices and Benefits by Devanshi Tripathi, Atmaja Aswadhati, Callie Lambert and Jordan Massa

The American Telemedicine Association launched a Disparities Toolkit, which includes an online data system that generates a Digital Infrastructure Score (DIS) available via an interactive map. The composite DIS was derived through multiple regression analysis that integrates diverse datasets encompassing telehealth accessibility factors (including affordability and internet speeds) and social drivers of health (such as the social vulnerability index), along with health outcomes. The DIS provides a place-based snapshot of technology and social factors and their relation to health outcomes. The data's hierarchical geographic structure, ranging from micro-level units (zip codes) to macro-level regions (states), facilitates comparative analyses both within Colorado and across other states. The tool allows users to conduct analysis and create visualizations within the system, and the data can be exported in a variety of formats.

Digital inclusion has emerged as a “super social driver of health” that intersects with multiple health-related social needs. An expanding ecosystem of technology-enabled health platforms and tools, including patient portals, health apps, and remote monitoring devices, supports diverse aspects of health information access and healthcare delivery. The future of public health and the achievement of reducing inequities lies, to a great degree, in the use of technology. 

This session will explain the tool's data sources and development methodology, offering practical examples of its visualization features and analytical capabilities. The DIS analytical framework serves diverse stakeholders including policymakers, program directors, evaluators, educators, and community organizations. These partners can utilize the tool for identifying areas of access barriers and health disparities, implementing evidence-based programs, monitoring and evaluating intervention outcomes, developing educational resources, and guiding community health improvement initiatives.

This presentation will feature Family Connects; an evidence-based postpartum nurse home visiting program that has been implemented in several counties across Colorado. During the visit, nurses conduct an assessment of families’ strengths and needs and connect them to appropriate community-based resources. Because the program is universal rather than targeted, and aims to serve 60% of the eligible population, we have a unique opportunity to gather data around the support needs of our perinatal community and their ability to successfully connect to community-based resources to meet those needs. Specifically, participant data collected includes demographic data such as caregiver and infant race and ethnicity, caregiver education level, primary language spoken, and caregiver and infant insurance type. Additionally, participants’ strengths and needs are assessed in 12 domains and assigned a matrix score of 1-4 depending on risk-level. Participants are referred to community-based resources and supports for any matrix ratings of 3 or 4, signifying high need or risk for the family. Participants receive a follow-up call 30 days after their visit, and data is collected on whether or not the participant successfully connected to community resources. This data is being used to identify systems-level gaps in services and improve community alignment efforts across systems of service. Specifically, this presentation will present data from Denver and Jefferson counties. Denver county launched their program in late 2024 and Jefferson County launched their program in 2023. As both programs move through the implantation phase, they are serving approximately 17% and 11% of the eligible birthing population, respectively.
Through this presentation, the audience will better understand the current needs of families with young children in Denver and Jefferson counties and how well the counties’ systems are supporting families through available resources. It will also provide an example of how to use programmatic data to identify areas that need system level improvement. The presentation will feature intentional strategies for engaging community voice in program implementation and data interpretation in order to reduce disparities among marginalized communities and improve health equity.

The fight against food insecurity is led by diverse distribution agencies, often with limited
coordination and intentional design across providers. Data science can be used to guide
decisions and make the system more effective at tackling inequities. In New Jersey a
cross-sector partnership has employed an innovative methodology powered by data to address
food insecurity. Trenton Health Team (THT), in partnership with local stakeholders, constructed
a food insecurity index to highlight the intensity of food need across the county. Using publicly
available data, geospatial methodologies, and cluster analysis, the Index assigned a relative
food insecurity score to each census block group. Stakeholder feedback was centered
throughout the process, resulting in an interactive map which transformed fifteen variables into
an accessible, visual tool.
The Food Insecurity Index has been utilized for both short and long term change. THT
worked with the regional food bank to deploy mobile pantries to areas with higher need but
limited resources, and plans are being finalized for a new brick and mortar food hub located in
the center of the most under-resourced neighborhood. Emphasizing the project as a
collaborative process not only allowed THT to incorporate valuable local insight in the tool, but
also established trust and increased buy-in from community partners. This framework of
participatory data-based decision making to build consensus will continue to be used by THT as
the Index expands to cover the entire state of New Jersey, and is applicable to an array of
projects across public health and nationwide.
Attendees of this presentation will learn how to apply the Index methodology to their
local geography, as its backbone of census data allows it to be utilized anywhere in the USA.
Attendees will also learn how they can translate data projects into actions via participatory
processes with diverse stakeholders.