Displaying 61-80 of 154 results for

Project ECHO: Overdose Fatality Investigation Techniques (OD-FIT) Project ECHO: Overdose Fatality Investigation Techniques (OD-FIT) provides coroners, medical examiners, toxicologists, forensic pathologists, and public health personnel opportunities to learn and share their overdose investigation expertise with peers across the United States and territories. Coroners and medical examiners are called after a fatal overdose to investigate the cause and manner of death. Public health agencies and practitioners use this mortality data to better understand trends in fatal overdoses and to inform the allocation of resources, such as fentanyl test strips and naloxone in states with high rates of overdose deaths.  Project ECHO: Overdose Fatality Investigation Techniques (OD-FIT) is a collaboration between ASTHO and the Centers for Disease Control and Prevention (CDC) to provide coroners, medical examiners, toxicologists, forensic pathologists, and public health personnel with an opportunity to learn and share their overdose investigation expertise with peers across the United States and territories. By strengthening the medicolegal death investigation system, state and territorial health agencies can improve the accuracy and reliability of overdose death data to benefit public health and safety programs, law enforcement investigations, and upstream prevention strategies.  Project ECHO OD-FIT consists of live online sessions featuring didactic presentations followed by case study discussions. Didactic recordings and accompanying resources from the most recent series can be found below. website no False

Social determinants of healthcare are the conditions in which people are born, live, work, play, worship, and age. Read how these issues affect population health.

This report analyzes the results from a survey of state and territorial health agency staff to collect information regarding health agency efforts to address climate change and extreme weather.

What I Wish I Knew Before Linking Data ASTHO, Association of State and Territorial Health Officials, linking data, data linkage, family and child health, public health, data linkage research, public health agencies, north Carolina, children's data network, child welfare indicators, california health and human services, child welfare, child welfare policy, maternal and child health, alaska division of public health, analytics and epidemiology, data analysis, applied surveillance, data systems, child protection, birth data, vital records, medicaid data, record registries, child advocacy, data pieces, connecting records, data sources, medical histories 45:57 Data linkage experts share insights and recommendations for leveraging data linkage projects to explore and make an impact on public health issues. PH Conversations Series - What I Wish I Knew Before Linking Data This episode features a conversation between two data linkage experts—Jared Parrish, PhD, MS, and Emily Putnam-Hornstein, PhD—highlighting their lessons learned and sharing recommendations for those seeking to use data linkage projects to examine key public health issues, such as: The thought process behind choosing which datasets to link, which linkage tools and methods to use, and how to bring intentionality to these choices when considering a research question. The benefits of using data linkage to enhance datasets and build a comprehensive and robust collection of information for new insights. Lessons learned for navigating data linkages with important considerations for preparation, analysis, and the uses of data linkage. Show Notes Interviewer Stephany Strahle, MPH, Maternal and Child Health Contractor, ASTHO Guests Jared Parrish, PhD, Senior Epidemiologist, State of Alaska, DHSS, Division of Public Health Emily Putnam-Hornstein, PhD, Distinguished Professor for Children in Need, University of North Carolina at Chapel Hill <!-- Resources Braiding and Layering Funding to Address the Social Determinants of Health --> PHC Podcast Transcript - What I Wish I Knew Before Linking Data website yes

This report shares Puerto Rico’s strategy and recommendations for developing a social determinants of health dashboard.

Learn step by step how to modernize data infrastructure at your health agency to improve public health outcomes, with helpful examples and resources.

Olmsted County Pilots a Regional Population Health Data Hub to Improve Data Accessibility Gelila Tamrat, Sara Black, Reema Mistry, Christina Severin Olmsted County, Minnesota, pilots a regional population health data hub to improve data accessibility, which supports improved decision-making and interventions. Historically, Olmsted County and other local counties in southeast Minnesota have faced barriers to accessing timely and actionable public health data, including limited data analytics workforce capacity, lack of data-sharing agreements (DSAs), and misaligned data suppression standards. To address these challenges, Olmsted County Public Health Services (OCPHS) piloted a regional population data hub, in partnership with the Minnesota Department of Health (MDH) and 10 local health departments (LHDs). OCPHS procured resources to develop a regional data-sharing platform, expanded their epidemiology team, and pursued DSAs. As a result, they gained access to critical data that supports informed decision-making and tailored interventions at the local level. Tina Jordahl - Brief - Olmsted County MN DMI Hub Developing a Regional Population Health Data Hub With financial support from the Minnesota legislature in 2021, OCPHS collaborated with MDH and its regional counterparts to develop a regional population health data hub for smaller LHDs to access community-level public health data. OCPHS maintains the hub by managing data from the state, regional partners, and 10 LHDs, and creating data dashboards to support southeast Minnesota counties’ population health data needs. This effort involved building and expanding relationships with MDH unit-specific epidemiologists, working closely with public health system consultants at MDH, and raising awareness of the need for sustained data analytics workforce support. Following the initiative’s success, OCPHS plans to engage with state and local leaders to identify funding sources that can sustain the hub beyond the pilot funding cycle. Promoting Data Accessibility through Strategic Partnerships and Agreements MDH’s Center for Public Health Practice supports public health system consultants, who offer technical assistance and consultation services to strengthen public health infrastructure across Minnesota. The consultant for the southeast region of the state was crucial in linking state and local staff to advance the development of the regional population health data hub. They helped triage and expedite requests from OCPHS by identifying the right points of contact for datasets and legal counsel within MDH. The collaboration of MDH, OCPHS, and participating LHDs facilitated the development of DSAs, which allowed for proper data flow and enabled OCPHS to request data from MDH on behalf of participating counties, reducing the need for each county to request data. It also helped OCPHS to become the first county in the state to adopt CDC’s ESSENCE tool to monitor hospital visits for syndromic surveillance across Minnesota and neighboring states, better enabling LHDs to address the needs of communities residing along state borders. Hiring Strategies for the Data Analytics Workforce OCPHS focused on hiring staff to support the regional population health data hub with data expertise, strong communication skills, and a particular interest in population health and social determinants of health. OCPHS created two permanent epidemiologist positions to promote sustainability for that position in the future. To expand their hiring pool, OCPHS relied on Olmsted County’s updated remote work policies following the COVID-19 pandemic when many shifted to remote or hybrid work. They also invited leaders from partner counties to help vet candidates who could support other LHDs’ needs. Meaghan Sherden - Brief - Olmsted County MN DMI Hub Advancing Equity Through Data Accessibility Due to data suppression rules, counties in southeast Minnesota had limited access to county-level data for certain statewide datasets. OCPHS worked with MDH to identify appropriate data suppression standards that supported access to community-level public health data and preserved privacy and security, and collaborated with the county IT department to develop the regional data hub with public-facing and internal dashboards, aligned with the required privacy and security standards. The public-facing dashboards show aggregate data with appropriate suppression standards at county, regional, and state levels. The internal dashboards provide complete data summaries and are protected with appropriate permissions and multi-factor authentication for LHD staff to perform population-level analysis. Providing timely, granular data to participating counties allows LHD staff to develop tailored strategies to address emerging health issues promptly, bridging health equity gaps. OCPHS also integrates standard demographic data on race, sex, gender, and age into its dashboards, enabling regional LHDs to gain deeper insights into their communities and fine-tune equity-centered public health initiatives and interventions. Jenny Passer - Brief - Olmsted County MN DMI Hub Implementation Considerations Foster collaborative relationships across state and local health departments to identify opportunities to share resources when advancing data-sharing efforts. Models in which larger LHDs support key data infrastructure needs on behalf of smaller LHDs may bolster data analytics/epidemiology capacity across multiple LHDs and streamline coordination with key partners at the state health department. Consider how state health department consultant or liaison roles charged with providing technical assistance to state or local partners may help facilitate key connections between state and local health department staff pursuing cross-jurisdictional data-sharing efforts. Invest in data analytics/epidemiology workforce strategies that help address specific needs related to population health and relationship building, along with technical skills. Cross-jurisdictional data-sharing efforts require staff with strong data analytics and communication skills, as they work with multidisciplinary leaders and across jurisdictions to inform community-based interventions. Collaborate proactively with legal and IT departments to identify data governance solutions and technical approaches to adhere to required privacy and security standards. Establishing DSAs is important, as it allows sharing of data within required legal guardrails. Similarly, IT leaders can identify technological solutions that support effective access to data. OT18-1802 website yes

Arizona Department of Health Services Pursues Policies to Advance Data Sharing with Tribal Nations Erik Skinner, Christina Severin, Reema Mistry The Arizona Department of Health Services is pursuing policies to advance data sharing with tribal nations, centered around partnerships, education, and more. With leadership support and funding to modernize its public health infrastructure, the Arizona Department of Health Services (ADHS) is pursuing policies to advance data sharing with tribal nations. This includes investing in partnerships with tribal leaders, educating the public health workforce about tribal governments and tribal health care, and working to improve data identification processes to support effective data sharing between the state and tribal nations. Data sovereignty is an important consideration for ADHS, as there are 22 federally recognized tribal nations in Arizona. ADHS recognizes the inherent right of tribal nations to access their citizens’ public health data and is developing a tribal data sovereignty policy that both acknowledges their unique data needs and aligns with state requirements around tribal engagement. Leadership Support and Effective Tribal Engagement ADHS leadership understands the importance of making strong connections with tribal nations and recognizing each nation’s public health priorities while meeting its statutory requirement to develop tribal consultation policies. To that end, ADHS developed the tribal liaison position to serve as a resource, advocate, and communication link between ADHS and Arizona’s Native American health care community partners, including tribal community leaders, health and epidemiology directors, Indian Health Service (IHS), and Tribal Epidemiology Centers (TECs). Understanding cultural norms is essential to building trust with tribal partners; the tribal liaison role has been vital to ADHS engagement with tribal nations on data sovereignty topics. People and processes are important to establishing data sharing policies, and a well-informed workforce is essential for effective collaboration with sovereign tribal nations. ADHS is working with the Native Nation Institute to provide training on tribal sovereignty and cultural humility for staff. It has also developed a tribal handbook for public health staff on sovereignty, cultural trauma, and the roles of IHS and TECs. Identifying Tribal Affiliation within Datasets and Tribal Public Health Priorities ADHS conducted a data assessment to identify instances in which data sharing was active and ongoing between ADHS and tribal nations, and instances in which it had expired. A notable technical challenge was identifying tribal members within existing datasets, as many public health datasets are incomplete (e.g., do not include tribal affiliation) or rely on IT systems that are unable to aggregate data appropriately—making it difficult to ensure tribal authorities receive relevant, comprehensive public health data for their communities. In addition, because each tribal nation’s public health priority areas and data needs could differ from the data that state health information systems collect, sharing relevant data with tribal nations can be challenging. ADHS is working with each nation to identify tribal public health priority areas, find solutions to identify tribal data within state collected datasets, and share it with the respective nations. Ken Komatsu - Brief - AZ DHS Pursues Policies to Advance Data Sharing with Tribal Nations Honoring Sovereignty in Data Sharing Relationships Data sharing agreements with public health agencies often establish that the state agency controls the disposition and use of the data, and that each party benefits. Acknowledging that tribal partners are entitled to their citizens’ data without conditions differs from how ADHS has historically approached data-sharing relationships with others. ADHS plans to formally establish a non-transactional data sharing policy with tribal public health partners, and establish data sharing agreements that align with this approach going forward. Implementation Considerations Considerations for state health agencies in fostering strong relationships and effective engagement with tribal partners around data-sharing efforts include: Center tribal sovereignty when framing data sharing agreements with tribal nations. Engage tribal liaisons in data-sharing efforts with tribal nations. They maintain close relationships with tribes and can help develop mutual cultural understanding, which is essential to engaging tribal partners. Assess datasets to determine data completeness with regards to tribal affiliation and identify opportunities to improve comprehensive data sharing with tribal authorities. Invest in state health agency staff training on tribal sovereignty and cultural humility, so staff can be well-prepared when engaging in data sharing conversations with tribal partners. Gerilene Haskon - Brief - AZ DHS Pursues Policies to Advance Data Sharing with Tribal Nations OT18-1802 website yes

Disease Forecasting and Modeling Data for Public Health Action Disease Forecasting Benefits Public Health Planning Disease forecasting and modeling help prepare public health departments for future infectious disease outbreaks and epidemics. Disease forecasting and modeling data can be powerful tools for state and local health agencies (S/THAs) that respond to outbreaks, develop appropriate policies, and ensure interventions have maximum impact. Actions for which decision-makers can leverage such data include: Surveillance. Forecasts and modeling help public health agencies anticipate the spread of disease or outbreaks. This advance warning allows public health officials to inform public health recommendations, preparation, and response. Communication. Disease forecasts help relate the risk of disease outbreaks to various audiences accurately and quickly, which, in turn, can inform messages on important preventive measures and encourages compliance with recommended interventions. Resource allocation. Modeling data can help decision-makers better allocate resources by predicting where and when disease outbreaks are likely to intensify and create the greatest need. Evaluation. Forecasts and modeling can help make evaluating the effectiveness of public health policies and interventions more efficient by comparing predicted outcomes with observed data and adjusting as needed. Considerations Informed by S/THA Forecasting Jurisdictions with forecasting experience identified key indicators to monitor as part of outbreak forecasting, which fall into three main categories: Epidemic spread indicators (e.g., symptom monitoring, morbidity and mortality data, percent positivity, regional pictures of transmission). Health care system capacity (e.g., essential and/or surge personnel, available beds, ventilator usage, and supply of personal protective equipment. Public health capacity for testing capacity and contact tracing. Further considerations for S/THAs: Know your strengths. Identify the unique skillsets among partners in public health, academia, and the private sector and consider how they foster reciprocal relationships. Recognize capacity/expertise gaps. Consider leveraging partnerships for specific types of analytics expertise while exploring internal capacity building opportunities (e.g., job shadowing and resource-sharing programs on workflows and methodologies). Engage legal and compliance teams. Ensure policy and practice are aligned among partners. Explore data access/sharing pipelines. Connect public, private, academic partners, and their audiences. Start small. Identify discrete forecasting and modeling projects to demonstrate success. Identify decision-makers’ needs. Provide quick access to analyses, metrics, dashboards. Michigan Used Models and Forecasting for Hep C Cases In response to Hepatitis C virus (HCV) in young adults from 2010-2018, the Michigan Department of Health and Human Services (MDHHS) simulated how HCV treatment could significantly reduce HCV prevalence among young people who inject drugs, especially for those both previously or currently injecting drugs. MDHHS used several novel predictors to paint a local picture of probable HCV diagnoses among residents up to age 40. These predictors included measures related to a variety of population characteristics (e.g., access to transportation, college education, presence of non-family households) and public health indicators (e.g., heroin treatment admissions, newborns with neonatal abstinence syndrome, and sexually-transmitted infections). MDHHS also leveraged county-level assessments of HCV vulnerability to identify locations for new syringe services programs in the state. MDHHS has recognized several modeling and analytics use cases that benefitted their work during responses to HCV and COVID-19: Short-term forecasts (i.e., weeks) helped predict likely transmission patterns and potential ranges of projections. Longer-term forecasts (i.e., months) explored scenarios based on new recommendations and policy changes. Retrospective counterfactuals evaluated the impact of policies or other changes by examining “what-if” situations. MDHHS is considering using forecasts and models for COVID-19, influenza epidemics, tuberculosis vulnerability, and C. auris spread. Resource constraints require decision-makers and public health practitioners to consider how they are using available resources for the highest return on investment. Models generated momentum to respond to threats and evaluate whether interventions were successful. CDC-RFA-OT18-1802 2018-2024 article yes

Policy Approaches to Improve State and Local Data Sharing Health officials can pursue organizational policies across key priority areas to advance state and local data sharing. Learn about these policy approaches. Several factors impact effective data sharing between state and local health departments—which is vital to public health decision-making—such as legislation and regulations, limited funding, IT and workforce resources, departmental processes, leadership buy-in, and data governance. Health officials can pursue organizational policies across these key priority areas to advance data sharing practices. Get the Infographic (PDF) website yes

This article in the Journal of Public Health Management and Practice assesses the impact of COVID-19 on health service utilization of adults with intellectual and developmental disabilities through an analysis of Medicaid claims data..

TEFCA Overview and Perspectives From the Field TEFCA Overview and Perspectives From the Field aims to introduce the Trusted Exchange Framework and Common Agreement (TEFCA) in the context of public health participation in TEFCA-based data exchange. This session features panelists, including ASTHO President Steven Stack (SHO-KY), who discuss how they envision their health agency benefiting from TEFCA and how they are preparing to participate. You will also learn more about the legal and policy considerations around TEFCA. Speakers Alexandra Woodward, DrPH, MPH: Senior Advisor, Public Health Data Modernization & Informatics, ASTHO Steven Stack, MD, MBA: ASTHO President and Commissioner for Public Health for the Commonwealth of Kentucky Kate Goodin, MPH, MS: Director, Surveillance Systems and Informatics Program, Tennessee Department of Health Andy Baker-White, JD, MPH: Senior Director of State Health Policy, ASTHO Susan Bsharah: Associate Director, Health Sector, Guidehouse Resources TEFCA Overview and Perspectives From the Field: Presentation Slides TEFCA Frequently Asked Questions website yes

Following disruptions to daily life caused by the COVID-19 pandemic, emergency departments saw an increase of mental health-related visits. A June 2021 study showed a significant increase of mental health-related visits among 12–17-year-olds compared to the previous year. States and territories that implement a comprehensive public health approach to suicide prevention across all domains of life—an approach known as the socio-ecological model—can reduce contributing risk factors.

Linking Datasets to Address Racial Equity in Maternal and Child Health Outcomes astho, association of state and territorial health officials, data sources, people of color, centers for disease control, racial inequities, advance racial equity, maternal morbidity, maternal death, maternal health, child health, participate in prams, risk assessment monitoring system, disease control and prevention, maternal and child, morbidity and mortality, pregnancy risk assessment monitoring, pregnancy related death, racial justice, linked data, achieve health equity, advancing health equity, racial equity, maternal and child health, maternal mortality and morbidity, racial disparities, health equity, data linkages, vital records, pregnancy risk assessment monitoring system Stephany Strahle ASTHO | Strategies for promoting racial equity in maternal and infant health through data linkages. Racial disparities in maternal and child health outcomes impact populations across the United States. Having robust data to understand these disparities may inform more comprehensive initiatives and policies that address the impacts and root causes of inequities. Looking at administrative datasets, such as hospital discharges and vital records, allows health professionals to monitor inequities by racial and ethnic communities. Often not captured in these data, however, is the complex interaction of social determinants—such as access to social support, racial discrimination, insurance coverage throughout pregnancy and postpartum, and access to paid family and medical leave—and their impact on health outcomes. Public health surveillance systems monitor these outcomes and aim to answer questions on a broad range of contextual experiences. These systems can be combined with administrative data through data linkage, “a process that matches records representing the same person or entity derived from different data sources in order to generate new and more comprehensive datasets.” These linkages can help identify areas for patient-centered outcomes research and inform policy recommendation and programs that address maternal and child health disparities across racial and ethnic groups. State Approaches to Data Linkages Linking Vital Records with Income Data California In a recent working paper on maternal and infant health inequities in California, researchers linked administrative vital records with parental income data. This research found that “infant and maternal health in Black families at the top of the income distribution is markedly worse than that of White families at the bottom of the income distribution.” Linking vital records, a source that typically does not capture income information, with data sources that do, provided a novel and robust dataset illuminating the exacerbated disparities experienced by racial and ethnic minorities at all income levels. Using PRAMS to Monitor Health Outcomes The Pregnancy Risk Assessment Monitoring System (PRAMS) allows jurisdictions to monitor various maternal and infant health indicators before, during, and after pregnancy. As one of the few public health surveillance systems collecting data on race-related experiences and discrimination, it also provides a better understanding of disparities among racial and ethnic groups. As part of ASTHO’s Linking PRAMS and Clinical Outcomes Data Multi-Jurisdiction Learning Community, two state teams from Massachusetts and Georgia used data linkage of PRAMS to explore racial disparities in maternal and child health outcomes. Massachusetts The Division of Maternal and Child Health Research and Analysis at the Massachusetts Department of Public Health linked PRAMS data with the Pregnancy to Early Life Longitudinal Data System (PELL), a data system linking birth files to hospital discharge records that can be later used to link hospital-based service records, data on early intervention services, and other data documenting maternal and infant health experiences beyond birth. Previously, both PRAMS and PELL data informed Massachusetts’s 2022 report from the Special Commission on Racial Inequities in Maternal Health, which provided policy-related recommendations on doula workforce development and equitable implementation of paid family and medical leave within the state. Sarah Stone, PhD, MPH, the director of the Massachusetts Office of Data Translation, notes that linking PRAMS, which provides insights into the social determinants shaping people’s experiences during pregnancy, with the more administrative data included in PELL can further inform additional evidence-based initiatives to address inequities in maternal mortality and severe maternal morbidity. Georgia At the Maternal and Child Health Section of the Division of Epidemiology in the Georgia Department of Public Health, linkages between PRAMS and Georgia Vital Record data can provide insight into the observed differences in health outcomes among the state’s diverse population. Jenna Self, MPH, Georgia’s PRAMS project director and health surveys team lead, explains that “the linkages will help explore the association between maternal postpartum behaviors and negative infant health outcomes (e.g., mortality, hospitalization, emergency department visits) with the goal of understanding the health disparities” to inform future equity-focused initiatives. The development of a linked data environment will allow the Georgia Department of Public Health to ask and answer previously time and resource prohibitive questions. Recommendations Data linkage can be a powerful tool to create enhanced datasets that better inform state initiatives to improve racial equity in maternal and infant health outcomes. To use data linkages that identify areas needing equitable public health efforts, states should: Build and strengthen cross-collaborative relationships within and between various state agencies owning the datasets to facilitate data sharing. Consider the racial equity impacts of performing data linkages by exploring research questions that lead to more evidence-based decision-making. Understanding the linked data using a racial equity lens can better inform equitable policy recommendations and programmatic planning. Examine which data sources, when linked, could fill in gaps of understanding and provide a wealth of information to identify disparities and point to specific gaps in quality health care. Brief - Linking Datasets to Address Racial Equity in Maternal and Child Health Outcomes - Special Thanks website yes

A mid-session legislative update on five of ASTHO's top 10 public health state policy issues to watch in 2023: data privacy and modernization, reproductive health, health equity, strengthening public health agencies, and immunization.

Vaccines are one of the greatest public health achievements of the last century, as well as some of the most powerful and cost-effective tools to prevent disease, disparities, disability, and death among children and adults. The COVID-19 pandemic and the unprecedented development and distribution of the vaccines against the novel coronavirus have generated much focus on state laws related to vaccinations. As state and territorial legislatures prepare to convene in the coming weeks, we can already identify several topics within vaccine law that policymakers across the country will consider.

Learn about the Vermont Department of Health's efforts to prioritize data modernization initiatives through its Data Modernization Advisory Committee.

Fairfax County Health Department Modernizes Infrastructure to Optimize Public Health Data Sharing Susan Fluerant, Reema Mistry, Christina Severin Learn how the Fairfax County Health Department in Virginia is working to modernize its data infrastructure & optimize public health data sharing. Using lessons learned from the COVID-19 pandemic, the Fairfax County Health Department (FCHD) is coordinating with county agencies, the Virginia Department of Health (VDH), and nonprofit public health organizations to modernize its data infrastructure and optimize public health data sharing functions. FCHD’s Informatics and IT team engaged in a strategic process to develop a multiyear IT roadmap, which outlines solutions and systems required to support this modernization, including clinical services, communicable disease surveillance, laboratory information systems, communication systems, and solutions for community engagement and administrative needs. As a result, FCHD is well-positioned to leverage its robust IT and data infrastructure to align with VDH for better data sharing. Advancing IT and Informatics Infrastructure Challenges associated with manual data-sharing processes (e.g., the use of CSV files to ingest data and produce analyses) during the COVID-19 pandemic prompted FCHD to reassess its informatics capacity. It conducted department-wide needs assessments and identified the need for improved technology, increased workforce capacity, and better data governance policies. It then ascertained IT functions that could be outsourced (e.g., cloud-hosted solutions and managed services for FHIR HL7 implementation) versus core public health functions (e.g., manipulating and managing data for epidemiologic use) that needed to remain internal, allowing FCHD to preserve internal staff capacity for key public health activities. Public health staff found working with CSV files to be inefficient for large or frequently updated datasets. To address this challenge, FCHD worked closely with VDH and the Fairfax County Informatics and IT team to adopt automated processes and develop a data warehouse solution—allowing FCHD to manage and transform data from multiple sources as well as control the frequency and timing of data retrieval, enhancing their ability to respond promptly to public health needs while keeping data secure on cloud-host servers. VDH hosted an API for FCHD to retrieve death data, significantly increasing flexibility and reducing the need for manual intervention. As FCHD increases the use of new data sources and technology, it continues to develop data governance policies, roles/responsibilities for data users, and data safeguarding guidance. Noel Clarin - Brief - Fairfax VA DMI to Optimize Public Health Data Sharing Engaging State and Local Partners FCHD recognizes that data sharing agreements are vital to support data exchange and, until recently, relied on informal data sharing agreements among other jurisdictions in Virginia. It partnered with attorneys at the state and local levels to work toward a universal data sharing agreement, which can expedite the data sharing process when public health programs have new use cases for local data. As a result, FCHD executed a Memorandum of Understanding with VDH in less than six months—a notable improvement from past data sharing agreements, which historically could take over a year to execute. They worked collaboratively through complex technical and bureaucratic challenges, highlighting the iterative nature of establishing effective data sharing protocols. FCHD also supported relationship-building between programs and divisions within the Fairfax County government, allowing for greater strategic alignment around emerging technologies. Interdepartmental relationship-building between public health program staff and the Fairfax County IT team has been equally important to foster effective collaboration and identify data modernization champions within FCHD. Alida Laney - Brief - Fairfax VA DMI to Optimize Public Health Data Sharing Planning for Sustainable and Diverse Funding Sources FCHD received an initial grant from the Public Health FHIR Implementation Collaborative through NACCHO, which helped launch the IT infrastructure improvement work; however, one-time funding is not a long-term solution. Now, FCHD is developing a long-term funding strategy to support the costs of IT systems licensing, operations and maintenance, and research and development. FCHD recognizes as public health changes, so must the technology that supports it, and modernization will require sustainable funding from government, associations, and other sources. Centering Health Equity in Informatics Solutions FCHD is developing processes to collect and standardize data disaggregated by sexual orientation and gender identity, race and ethnicity, language, and the social determinants of health to better identify and address health disparities. By incorporating additional data into its systems, program staff can now make informed decisions to strengthen health literacy by disseminating information in preferred languages and easy-to-read formats, and ensuring materials are accessible to persons with colorblindness. Ben Klekamp - Brief - Fairfax VA DMI to Optimize Public Health Data Sharing(2) Implementation Considerations Foster relationships within and across local and state government to get buy-in for the modernization of public health informatics infrastructure and the improvement of data-sharing practices. Define clear goals for implementing new technology, and build a strategy for infrastructure improvement, partner engagement, and long-term sustainability that’s grounded in a shared understanding of the goals. Align workforce responsibilities, process improvement efforts, and technological advancements. Develop universal data sharing agreement templates between state and local health departments to expedite future data-sharing efforts. OT18-1802 website yes

Communicating About Disease Forecasting Effectively Communicating About Disease Forecasting Clearly communicating about disease forecasting helps policymakers, the media, and the public make informed decisions in public health emergencies. Communicating effectively about disease forecasting data is essential for the public to understand the associated risks, implications, and recommended actions. It’s also critical for policymakers who can use the data to determine effective, equitable strategies for outbreak response. In turn, the public can make informed decisions to keep safe. Each audience, including the media, will likely need tailored messages about the indications and limitations of a given forecast. Approaches for communicating about disease forecasts/models with policymakers and the public align with many of the key tenets of public health communications more broadly. Public health practitioners should consider integrating Crisis and Emergency Risk Communication (CERC) principles, which suggest that communications be first, right, credible, empathetic, actionable, and respectful to help the public make informed decisions during challenging circumstances. Communicating with Policymakers Policymakers—public health or elected—have important decision-making and rule-making authority; additional considerations may be needed when communicating with them about disease forecasting. Interactions frequently occur through staffers, who may have limited knowledge and/or time. In addition to CERC principles, communications should also be: Relevant. Tailor communications to policymakers’ priorities to emphasize potential impacts on resource allocation, public health outcomes, local or regional policies, and public sentiment. Collaborative. Foster relationships with policymakers and offer subject matter expertise on forecasting to inform policy decisions. Timely. Provide frequent updates, allowing for proactive collaboration, decision-making, and communication with the public. Concise. Develop briefs that summarize forecasts and their implications for constituents. Consistent. Build trust with policymakers and their staff between emergencies to highlight disease forecasting as a useful tool whose methodologies, data sources, and limitations are clear. Communicating with the Public In addition to CERC principles and in collaboration with media partners, communication about disease forecasts/models with the public should be: Accessible. Provide easily accessed information about methodology, data sources, and limitations in the forecasts. Clear. Use jargon-free, non-technical language to convey critical messages. Contextualized. Frame forecasts within the broader public health context, emphasizing how individual and community actions can mitigate risk, and reinforce the effects of collective actions as part of an outbreak response. Empowering. Give the public reasonable, actionable steps to protect themselves and their communities. Local. Use social media, news releases, listening sessions, and other relevant means to reach as broad an audience as possible. Collaborate with community leaders and health care providers to amplify messaging and reduce misinformation. Frequent. Keep the public informed with regular updates on forecast products including changes in local risk levels, new trends, guidance, and recommendations. Utah’s Best Practices for Communicating Forecasts During the COVID-19 response, the Utah Department of Health and Human Services (DHHS) modeled potential disease transmission and shared how to effectively communicate with the media and public. DO Create diverse forecasting and communications teams that include public health, universities, and ‘bonus’ team members (e.g., political representatives, laboratories, and health economists). Clarify the purpose for which a given model was developed. Discuss the limitations of the disease model. Communicate about future outcomes (i.e., what would happen without further intervention). Provide language on how to alter the current path (e.g., ‘With this intervention, we could potentially avoid…’) Remind audiences that models can affect the future, not only predict it. Share information and data that are digestible for the public. DON’T Sound definitive when outcomes aren’t clear or make predictions using absolute terms. Omit a variety of scenarios or tools when presenting a forecast. Disregard inherent uncertainties in forecasts. Show models with conflicting results. Utah DHHS also recognized that members of the media are key partners in communicating public health messages; closely coordinating and contextualizing forecasts helps communicate accurate conclusions and/or recommendations. Communicators and staff should be prepared and have information ready to share for more complex questions as needed. Storytelling with forecasts and models helps the reader internalize them and make informed decisions. CDC-RFA-OT18-1802 2018-2024 article yes

Learn how to build a business case for data modernization efforts to translate technical needs into impact-driven narratives.