PCCI’s Community Vulnerability Compass Delivers Actionable Data to Municipal, Community-Based Organizations and Healthcare Providers

PCCI’s Community Vulnerability Compass Delivers Actionable Data to Municipal, Community-Based Organizations and Healthcare Providers

By Lance Rather, Senior Director, Product & Strategic Partnerships, PCCI

My goal, as part of a healthcare innovation organization, has always been to find factual and data-backed understanding of the community I’m trying to serve. At PCCI, we focus on finding opportunities to support vulnerable populations through actionable data. With our Community Vulnerability Compass (CVC), we’ve been able to go beyond assumptions and deliver hard facts about the health of our community. Currently, hundreds of organizations around the state are either using or are set to receive access to the CVC where they can leverage powerful, data-driven insights.

Since its creation, we have been able to use the CVC in a variety of ways to reveal actionable insights about the health of communities around Texas. PCCI’s CVC provides an interactive dashboard that helps stakeholders—including community-based organizations (CBOs), safety-net hospitals, health systems, philanthropic organizations, governmental agencies, universities, and managed care organizations (MCOs)—to make informed decisions that enhance health outcomes and drive equity in service delivery. The CVC breaks through “what we think we know” to provide hard facts, including root causes of the overall state of any given area down to the block group.

Using Dallas County as a test case, we demonstrated how the CVC can surface community needs in relation to the area’s socioeconomic realities. For example, we examined the mental health state of Dallas County and the CVC found the areas of the county that have historically faced economic challenges were also the most vulnerable to mental health issues.

The CVC was also able to break through assumptions about communities experiencing high social or structural barriers. We found that in Dallas County, regardless of the economic condition, low vulnerable ZIP Codes had high vulnerability neighborhoods and high vulnerable ZIP codes had low vulnerability neighborhoods. In some areas you could see a high or low vulnerability area separated by a single street. This provides our community leaders an opportunity to reach all vulnerable areas, and it offers root cause insights into a neighborhood’s vulnerability. These insights allow us to appreciate the individual strengths of each area in our communities.

PCCI also conducted a full vulnerability assessment of the five largest counties in Texas (Bexar, Dallas, Harris, Tarrant and Travis counties) where we found more than 4.2 million residents live in high or very high vulnerability block groups. We learned that Bexar County had the most vulnerable block groups of the five counties where the most prominent root cause for its vulnerability is neighborhood safety, followed by chronic diabetes and households without vehicles.  Additionally, the largest county, Harris, had the second most vulnerable block groups, but also had the highest number of low vulnerable block groups, with the most vulnerable block groups indicators being Neighborhood Safety, followed by Health Insurance Coverage and Mental Health.

These assessments are powerful examples of how the CVC is helping us gain a better understanding of our communities and the variety of root causes that drive the vulnerabilities throughout the state. Beyond analysis, we are seeing the CVC used in practical daily uses that have a direct impact on our residents.

For example, PCCI’s CVC has been incorporated into a variety of solutions throughout Texas, including adoption across the Parkland Health system, by the Dallas County Department of Health & Human Services, the University Heath (San Antonio) Transplant Center. Beyond dashboard access, for larger organizations, we offer the ability to reverse geocode individual-level data and append block group–level CVC insights. These insights can be integrated directly into electronic health records or customer relationship management systems, allowing organizations to use localized non-medical drivers of health (NMDoH) as a meaningful proxy at the individual level—enhancing precision in population health efforts, risk stratification, and targeted interventions.

PCCI’s CVC also serves as the backbone for the United Way of Metropolitan Dallas’ Data Capacity Building Initiative (DCBI), which is helping hundreds of organizations in North Texas turn insights into impact. The DCBI initiative has shown how the CVC is scalable and usable outside traditional healthcare settings. For instance, one CBO is using the CVC’s block group data to understand more about residents’ situations and tailor services more prescriptively. One organization has become better positioned to help victims and their children get out of harm’s way using the CVC, while another CBO is using the data to confirm service overuse in certain neighborhoods and service deserts in others.

An underlying goal for PCCI is to leverage the CVC to create a standard language and shared understanding around how NMDoH is utilized in Dallas County and beyond. This shared understanding would allow CBOs, governmental and healthcare providers to collaborate around a shared language of data in a more efficient manner.  

Above all, the CVC fosters collaboration among diverse stakeholders by creating a shared understanding of community vulnerabilities and empowering organizations to advocate for and implement policy changes that address systemic issues. By addressing both health and overall equity, the CVC empowers safety-net hospitals and clinics serving vulnerable populations, funders, and CBOs to develop comprehensive strategies that enhance access to essential services, improve health outcomes, and ultimately promote social justice. In doing so, the CVC serves as a critical tool in advancing health equity, driving policy change to break cyclical inequity, and addressing systemic issues that impact the well-being of individuals and communities.

Learn more about the development of the CVC in PCCI’s recent publication in JAMIA which highlights how the CVC elevates insights and expands on the performance of existing tools that measure community socioeconomic variation.

Access the full research paper at: https://doi.org/10.1093/jamiaopen/ooaf059

About the Author

Lance Rather is the Senior Director of Product and Strategic Partnerships at PCCI. At PCCI he leverages his extensive expertise in technology and data analytics to develop and refine health-related products. Lance plays a crucial role in the creation and enhancement of tools like the Community Vulnerability Compass (CVC), focusing on making complex data accessible and actionable for healthcare providers and policymakers.

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How We Are Fighting HIV Infection Using AI  

How We Are Fighting HIV Infection Using AI  

By Jacqueline Naeem, MD, Vice President of Clinical and Social Health, PCCI

During the last decade, we have seen major breakthroughs in preventing HIV infection. However, even with these advances, the infection rate has not appreciably dropped1. Pre-exposure prophylaxis (PrEP) has emerged as a highly effective preventive strategy for HIV, reducing the risk of HIV infection by up to 99% when taken consistently. Due to its effectiveness, the CDC recommends2,3 that medical providers counsel and prescribe PrEP to all sexually active patients if they are at risk for HIV infection.  However, despite its efficacy, PrEP remains underutilized, in large part due to lack of awareness. This is where artificial intelligence (AI) has stepped in to significantly advance our HIV prevention efforts.

Despite improvements in morbidity and mortality associated with HIV due to antiretroviral therapy, and the availability of an effective preventative medication, the incidence of HIV has only modestly decreased, with a 9% decrease between 2015 and 2019 and total of 36,136 cases in 2021. In Dallas County4, we find a situation that is almost at crisis levels with the spread of sexually transmitted infections (STI), including HIV. For example, Dallas County ranks 2nd highest in HIV, 6th in Syphilis, 21st in Gonorrhea, and 26th in Chlamydia infection rates compared to the other 254 Texas counties. With its position as North Texas’s largest safety-net hospital system, Parkland Health (Parkland) serves an extensive population of at-risk patients, creating a vital opportunity to enhance HIV testing and facilitate connections to PrEP programs.

Although we knew the mission was clear, the challenge was also great. We have an effective preventive treatment— PrEP, and opportunities to reach PrEP candidates—through Parkland, but what we were lacking was a way to identify candidates for referral in a simple way that could be incorporated into Parkland’s workflows and be paired with provider tools to guide discussion and assessment of indications and eligibility criteria for PrEP. To address this critical gap, we developed and implemented a predictive model, PCCI’s HIV Detection AI/ML Model, informed by EHR data and paired with provider tools to guide discussions on PrEP eligibility criteria, to efficiently identify (and target for outreach) individuals who stand to benefit most from PrEP.

PCCI’s HIV Detection AI/ML Model project work began in the latter part of 2020. Once underway, we then worked with Parkland’s IT to integrate the developed model for provider alert-based, risk-stratified interventions, in silent mode. We then automated PrEP Model load to the Parkland test table for piloting and testing the workflow.  We also identified the patient population cohort eligible for HIV risk scoring.  In late 2022, the model went live, using information from the EHR to predict the individuals at increased likelihood of acquiring HIV and who may be candidates for HIV PrEP. Once identified, the patients can be offered HIV testing, and if negative can be offered PrEP.  So far, the HIV Detection AI/ML Model has risk stratified hundreds of thousands of patients, demonstrating that machine learning models can be used for predicting and classifying the risk of HIV using available EHR data.  

We see this as a breakthrough for identifying candidates who are at risk for HIV infection. PCCI’s HIV Detection AI/ML Model has been shown to effectively address the needs of vulnerable populations and can be implemented in hospital settings with limited resources. There are opportunities to expand this model to reach even more patients in Dallas County, through an additional project underway with Dallas County Health and Human Services.

We revealed the methods and results of PCCI’s HIV Detection AI/ML Model in three peer-reviewed papers released in the past year:

  • AJPM Focus      

Supporting Access to HIV Pre-Exposure Prophylaxis in a Shifting Financial and Insurance Landscape

https://www.ajpmfocus.org/article/S2773-0654(24)00129-9/fulltext

  • Journal of Acquired Immune Deficiency Syndrome (JAIDS)         

Using Machine Learning to Identify Patients at Risk of Acquiring HIV in an Urban Health System

https://journals.lww.com/jaids/fulltext/2024/09010/using_machine_learning_to_identify_patients_at.6.aspx

  • Applied Clinical Informatics

Association of an HIV-Prediction Model with Uptake of Preexposure Prophylaxis

https://www.thieme-connect.de/products/ejournals/abstract/10.1055/a-2524-4993

Leveraging predictive models within Parkland and Dallas County allows providers to identify individuals at high risk for HIV acquisition and those who are prime candidates for PrEP. By doing so, we can implement proactive interventions that can bridge critical gaps in the HIV prevention cascade, thereby contributing to the broader goal of reducing HIV incidence in Dallas County.

About the Author

Naeem, MD, is Vice President of Clinical and Social Health at PCCI. She is a graduate of the University of Manchester Medical School, Manchester, England, where she also obtained her post-graduate diploma in Psychiatry at the University of Manchester. She undertook postgraduate training in both psychiatry and general practice also in the UK, as well as working as a medical school examiner. Since joining PCCI, Dr. Naeem has used her clinical experience and unique insights in several projects, particularly those with an emphasis on Non-Medical Drivers of Health and also mental behavioral projects. Dr. Naeem was also the program leader for the U.S. Centers for Medicare & Medicaid Services (CMS) Accountable Health Communities (AHC) Model in Dallas County.

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1. Centers for Disease Control and Prevention. Diagnoses of HIV infection in the United States and dependent areas, 2021. HIV surveillance report 2023; 34. Published May 23, 2023. Accessed January 22, 2024.

2. US Preventive Services Task Force. Preexposure prophylaxis for the prevention of HIV infection: US preventive services Task Force recommendation statement. JAMA. 2019;321:2203–2213.

3, Centers for Disease Control and Prevention. Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 dependent areas, 2019. HIV Surveillance Supplemental Report 2021;26(No. 2). Available at: http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html. https://www.cdc.gov/hiv/library/reports/hiv-surveillance/vol-32/content/special-focus-profiles.html#Women

4. Dallas County Health and Human Services. 2017 profile of HIV in Dallas County. Published August 14, 2018. Available at: https://www.dallascounty.org/Assets/uploads/docs/hhs/epistats/HIVSTIProfiles2017.pdf. Accessed January 30, 2024.

How PCCI’s Innovative Community Vulnerability Compass Offers the Most Effective Way to Understand Our Community’s Health and Root Causes

How PCCI’s Innovative Community Vulnerability Compass Offers the Most Effective Way to Understand Our Community’s Health and Root Causes

Yolande Pengetnze, MD, MS, Senior Vice President, Clinical Leadership, PCCI

If you are leading efforts to improve and understand public health in your community, we’ve researched and validated that PCCI’s Community Vulnerability Compass (CVC) offers an improvement in advanced insights and performance compared to existing tools that measure community socioeconomic conditions in our neighborhoods. Although getting here took a lot of innovation and perseverance, through a recent publication, we are now able to share what factors differentiate the CVC and why it offers the gold-standard of social determinants of health (SDOH) measurement. 

In research published in JAMIA Open, through Oxford University Press’ platform, we detailed how the CVC can help lead the way in measuring community SDOH, while also offering deeper, hyper-localized insights unavailable anywhere else.

Access the full research paper at: https://doi.org/10.1093/jamiaopen/ooaf059

CVC provides a unique methodology embedded into an interactive dashboard that helps stakeholders—including community-based organizations (CBOs), safety-net hospitals, health systems, philanthropic organizations, governmental agencies, universities, and Managed Care Organizations (MCOs)—to make data-driven decisions that enhance health outcomes and drive equity in service delivery.

The CVC’s unique value proposition offers one-of-a-kind insights where it analyzes, at the ZIP Code, census tract, and block-group level, where a community’s most vulnerable residents live and the root cause factors limiting these residents’ ability to thrive. The CVC analyzes 26 clinical and socio-economic indicators that reveal the health, resiliency, and economic vibrancy of neighborhoods. CVC’s analyses provide true, holistic pictures of who needs the most assistance and where to find them, enabling proactive support of those in need.

Though the CVC offers an impressive set of features, as public health leaders, we have choices. There are many available tools we can use to better understand our communities and their social conditions. That is where CVC sets itself apart. It offers localized data to our partners or customers catchment area, not just generalized, large geographical regions. It shows— to the block group — what the social conditions are and the root causes of those conditions.  

For example, our research reflected the differences between CVC and the Area Deprivation Index [ADI], Social Vulnerability Index [SVI], and Environmental Justice Index [EJI]). As presented in the article, the CVC’s Community Vulnerability Index (CVI), and 4 sub indexes, were used to classify all 18,638 Texas census-block groups as Very-High, High, Moderate, Low, and Very-Low social vulnerability. Individual patients were then assigned the vulnerability classification of their home address census-block group, creating a bridge between neighborhood-level data and individual-level health insights. CVC’s classifications were compared against three existing community vulnerability tools and validated against individual-level SDOH screening tools or Z-code documentation, but where we clearly separate ourselves from the others is we localize data to our partners or customers catchment area. Spearman rank correlation was used for neighborhood-level comparisons and precision/recall, for individual-level comparisons.

Let’s look at what each of these different systems offer and how we differ in features and performance.

Area Deprivation Index (ADI)

What the ADI Provides: The ADI is a composite measure that uses U.S. Census data to assess socioeconomic disadvantage at a neighborhood level. It provides valuable insights for healthcare providers and policymakers to understand and address health disparities.

CVC Difference: While ADI focuses on socioeconomic disadvantage, CVC goes beyond this by integrating various medical and non-medical determinants of health (NMDoH) indicators to provide actionable insights at the block-group level. CVC provides key insights to strengthen local interventions, empowering both health systems and CBOs to implement strategies directly targeting specific vulnerabilities in their communities.

The Social Vulnerability Index (SVI)

What The SVI Provides: Developed by the CDC, the SVI measures community resilience to external stresses using various social factors. It is commonly used for disaster preparedness and resource allocation.

CVC Difference: While SVI provides valuable data at a census tract level, CVC offers block-group-level insights, allowing for more precise targeting of interventions. CVC focuses on actionable data for public health departments, health systems, and CBOs, empowering them to engage effectively with vulnerable populations.

Environmental Justice Index (EJI)

What The EJI Provides: The EJI assesses the environmental and health burdens faced by disadvantaged communities. It focuses on exposure to environmental hazards, considering factors like pollution and access to green spaces, to identify areas at risk.

CVC Difference: CVC complements the EJI by not only focusing on environmental factors but also incorporating social vulnerabilities that contribute to overall health disparities. This broader perspective allows CVC to provide a more comprehensive understanding of community needs, facilitating targeted interventions that address factors: health, environment, and NMDoH.

In the research presented in the JAMIA paper, we see that overall, the CVC was comparable to, or outperformed, existing neighborhood indexes in measuring key SDOH at both the neighborhood and individual level. CVC showed a strong correlation with existing SDOH indexes from the ADI, SVI, and EJI across multiple social risk domains, demonstrating its ability to identify a cross-cutting range of social vulnerabilities and community equity markers. Additionally, CVC had very good recall rates for individual-level SDOH, both when validated against Z-code documentation and against self-reported survey tools (>75%).

This table, developed for the JAMIA paper, tells the full comparison article1:

Community Vulnerability Index (CVI) and CVC Subindexes Recall and Precision Rates for Self-Reported Social Determinants of Health (SDOH) Using Surveys.

      SDOH Community Vulnerability Index  Empowered People Subindex  Equitable Communities Subindex  Good Health Subindex  Household Essentials Subindex 
Precision (%) Recall (%) Precision (%) Recall (%) Precision (%) Recall (%) Precision (%) Recall (%) Precision (%) Recall (%)
Food Need 75.1 77.5 75.1 73.4 74.6 55.3 75.1 72.9 75.4 74.4
Housing Need 36.9 78.6 36.4 73.4 39.1 59.8 37.3 74.7 36.3 73.9
Safety Need 1.2 79.6 1.0 66.0 1.2 56.3 1.3 81.6 1.1 70.9
Transportation Need 31.9 79.3 31.9 75.2 33.5 59.9 32.5 76.0 31.8 75.7
Utility Need 42.6 77.0 42.7 73.2 41.4 53.7 42.3 71.8 42.8 74.0

For each CVC Index/Sub-index, the highest values of precision/recall are highlighted in green and the lowest in blue; CVC: Community Vulnerability Compass. 

PCCI’s CVC has been incorporated into a variety of use cases and settings throughout Texas, including adoption by the Dallas County Department of Health & Human Services, the University Heath (San Antonio) Transplant Center and serves as the backbone for the United Way of Metropolitan Dallas’ Data Capacity Building Initiative, which is helping hundreds of organizations in North Texas turn insights into impact.

As a member of the public health community, I am excited to see how we can use the CVC to better understand the true health of our communities and the contributing root causes.  The research we presented in the JAMIA paper is so important to me as it shows clearly how the CVC can give me insights unavailable through any other means.

The thought-provoking results we are seeing gives our public health leaders a trusted new technology that will enable the delivery of more precise approaches to address the needs of those most at-risk in our communities.

About Yolande Pengetnze

Yolande Pengetnze, MD, MS, FAAP, is PCCI’s Senior Vice President of Clinical Leadership where she leads multiple projects including population health quality improvement projects focusing on preterm birth prevention and pediatric asthma at the individual and the population level. Dr. Pengetnze received her MD from the University of Yaounde in Cameroon and completed a Pediatric Residency at Maimonides Medical Center in New York. She was a faculty member at UTSW’s General Pediatric Hospitalist Division where she completed a General Pediatric/Health Services Research Fellowship training and earned a Master of Sciences in Clinical Sciences.

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1 Oxford Academic – JAMIA Open Journal, Published July 2025, The Community Vulnerability Compass: a novel, scalable approach for measuring and visualizing social determinants of health insights, https://doi.org/10.1093/jamiaopen/ooaf059

 

PCCI’s Sachs Summer Scholar Interns Set To Advance AI Innovations for Vulnerable Populations

PCCI’s Sachs Summer Scholar Interns Set To Advance AI Innovations for Vulnerable Populations

STEM focused program offers female students’ side-by-side experience with AI experts and clinicians

PCCI’s summer intern program, Sachs Summer Scholars, Advancing Women in Data Science and Technology Summer Internship is underway and is a demonstration of PCCI’s ongoing commitment to provide women opportunities to experience new, transformational concepts in the data science and technology industry. The Sachs Summer Scholars program aims to support PCCI’s core mission as an innovation leader that develops scalable solutions focusing on responsible applications of AI-in-Medical Care for vulnerable populations.

As one of the premier STEM-focused internships in North Texas, PCCI’s program immerses students in meaningful, real-world projects with actual impact through practical applications of analytics, computing, and data science, all while advancing the spirit of mentorship and advancement of female students. This program provides each intern direct experience with innovative healthcare, groundbreaking artificial intelligence programs, and non-medical drivers of health (NMDOH) projects.

The 2025 class of Sachs Summer Scholars includes seven women from a wide variety of backgrounds and hailing from four different universities and a North Texas high school. The interns will work side-by-side with PCCI clinical and data science experts to hone their programming and analytics skills while building lifelong memories of meaningful accomplishments. They will focus on core PCCI projects, such as preterm birth prevention, large language models, maternal health, and suicide risk modeling, to name a few.

The 2025 Sach Summer Scholar interns are:

  • Xiao (Rachel) Bai from University of Southern California
  • Anne Hulme from Southern Methodist University
  • Trinity Jones from the University of Texas at Dallas
  • Sandra Futwi from Southern Methodist University
  • Aditi Nethi from Prosper High School
  • Pooja Patil from State University of New York, Buffalo
  • Xin Yan from Southern Methodist University

This internship class will present findings based on their work on PCCI projects at a presentation on Friday, August 8 from 9 a.m. to 12 p.m., at Pegasus Park (MAP) in Room 101. To join virtually, use this link: https://events.teams.microsoft.com/event/23077c98-65ac-4b1e-904f-6fb60e49b7c1@9a2a9ade-704f-4416-b094-47b8a504ad39

Our full 2024 Sachs Summer Scholars End of Term program showcase can be viewed here: https://www.youtube.com/watch?v=GezENNicf78&t=12s

Five years after the chaos of COVID-19 comes a new era of AI innovation

Five years after the chaos of COVID-19 comes a new era of AI innovation

By Steve Miff, PhD, President & CEO of PCCI

Five years ago this week, the COVID-19 pandemic threw our world into chaos. But that chaos also sparked an opportunity and a drive to accelerate innovation, through leveraging artificial intelligence with clinical knowledge in unprecedented ways. The results of these Covid-driven efforts have led to a fuller understanding of our community’s health, enabling the initiation of care further upstream and enhancing management of resources and costs in ways benefiting both patients and providers.

I can still remember that week five years ago. I had my bags packed and flight booked to travel to one of the biggest healthcare technology conferences, HIMSS, in Orlando, Fla., when the word came down. The government declared a full lockdown of the country thanks to the pernicious COVID-19 outbreak that the World Health Organization had declared a full-blown pandemic.

Sadly, the cost of COVID-19 in lives— 1.2 million deaths in the U.S. alone— was devastating and the reverberations of the pandemic still affect our daily lives.

However, the chaos and heartache also stimulated a new mindset for collaboration. While the lockdown closed our office doors, it opened new windows to collaborate with other stakeholders across our community.  Our teams immediately partnered with Dallas County Health and Human Services (DCHHS), Parkland Health (Parkland) , and other local providers and governmental agencies to help support our North Texas public health leaders and families manage through the ever-changing nature of the COVID-19 pandemic.  We deployed a transparent, data-driven set of analytics to inform the dynamic allocation of resources, guide triage protocols in emergency rooms, identify COVID-19 community hotspots, and predict rising waves of hospitalizations and capacity challenges. These collaborations would evolve into support for testing, vaccination distribution, and measuring of community-wide immunity to the infection.

While many of the solutions developed during COVID-19 were industry firsts, we continue today to leverage and expand on many of these same novel applications in AI and non-medical drivers of health (NMDoH) analytics. 

Vulnerability Index

The development of the Covid Vulnerability Index and geo-mapped hotspotting created the dynamic dashboards that guided the local pandemic response, including the placement of the testing, and later vaccination sites.  This novel approach later expanded into what’s now the Community Vulnerability Index, an industry leading NMDoH analytics method modeling community and neighborhood barriers to health and wellness.

Proximity Index

The Covid Proximity Index was used to predict the risk of infection daily at the individual level using advanced geomapping and data science techniques to guide personal awareness and behaviors, county-wide contact tracing, healthcare provider virtual care scheduling, and ED triage.  We are so proud of the United States Patent for AI driven proximity index system and methods (US 12,087,449 B2) that was awarded to PCCI late last year.  We’re now leveraging these methods alongside mobility data to understand access to vital services and placement of new access points in the community. The Proximity Index was also featured in the highly respected peer-reviewed New England Journal of Medicine Catalyst in a paper authored by Parkland’s CEO Frederick Cerise, MD and others.

Community Protection Modeling

The national Covid Community Protection Dashboard was launched in collaboration with the Institute for Healthcare Improvement (IHI), Civitas Networks for Health, and Cincinnati Children’s Hospital to model local behaviors and immunity patterns and help communities manage through new Covid variants and waves. We learned that the dynamic nature of modeling factors and a community’s protection depends on the characteristics of the most prevalent current variant and the immunity from prior vaccination and infections, adjusting for the time elapsed from the most recent immunizing event. These innovations translated into the development and deployment of the Pediatric Asthma Surveillance System (PASS), the soon to be released Diabetes/Hypertension Surveillance System, and the development of a novel Maternal Health Surveillance System. Each of the programs are (or will be) in use in Dallas County and provide life-saving support to its residents.

Better Preparedness for Future Crises

The pandemic brought Parkland, our main public health system, closer to DCHHS and many other public health leaders, working together with PCCI to build new policies and procedures to manage the COVID-19 emergency and future public health crises. And have no doubt about it, it is only a matter of when, not if, we will have more COVID-19-like outbreaks.

In the big picture for public health innovation, COVID-19 created a necessity for us to be innovative and try new ways to solve extremely difficult problems. This same way of thinking is helping us today as we tackle ongoing health challenges through improved collaborations and tools. For example, our Community Vulnerability Compass (CVC) is a tool that can provide deeps insights into the complexities of societal challenges to health, access, and community well-being affecting our neighborhoods throughout Texas. It can tell you, for example, what local daily challenges our residents face down to the block level. The CVC has been adopted by a variety of organizations around the state, led by the United Way of Metropolitan Dallas through its Data Capacity Building Initiative that, within five years, aims to equip over 200 community-based partners with robust data insights from the CVC.

And as previously mentioned, the PASS system is celebrating its two-year anniversary of providing residents of Dallas County unprecedented understanding of their vulnerability to asthma-related risks. PASS is a community-wide effort between the county, PCCI, and Parkland and is publicly available at the DCHHS website. It has been visited by thousands of Dallas County residents and was honored by the Dallas County Commissioners for its service to asthma sufferers and was described by the Dallas Morning News as “a win for Dallas County.” PASS has also been featured in the New England Journal of Medicine Catalyst.

The pandemic did put a damper on at least one of our innovations.  The book, “Building Connected Communities of Care,” was due to drop via a major release at the Orlando HIMSS convention in March, 2020.  The celebration and release was changed and conducted virtually and digitally.  This guidebook helps communities and public health leaders create holistic community networks that support any number of health management issues. Thanks to its insights and easy-to-follow steps, “Building Connected Communities of Care” has become an invaluable resource for many public health leaders across the country. It was also featured in the New England Journal of Medicine Catalyst for its insights it offers in handling community healthcare crises.

The COVID-19 pandemic was not easy on anyone, but we are wise to remember what happened during those tough times and leverage the innovations and progress towards bigger and broader ongoing impact. We will continue to leverage the critical clinical and community health lessons COVID-19 taught us in innovative programs incorporating the newest AI technology. As a community, while we remember the terrible price COVID-19 cost our friends and families, we should feel some level of optimism that the next time we will be better prepared and stronger together.

Pre-pandemic Post pandemic

About Steve Miff

Dr. Steve Miff is the President and CEO of Parkland Center for Clinical Innovation (PCCI), a leading, research non-profit, artificial intelligence and cognitive computing organization affiliated with Parkland Health, one of the country’s largest and most progressive safety-net hospitals. Spurred by his passion to use next-generation analytics and technology to help serve the most vulnerable and underserved residents, Steve and his team focus on leveraging technology, data science, and clinical expertise to obtain unique non-medical-determinants-of-health data and incorporate those holistic, personal insights into point-of-care interventions.

Cracking the Nutritional Puzzle: A Path Out Of Dallas’ Food Desert

Cracking the Nutritional Puzzle: A Path Out Of Dallas’ Food Desert

By Olayide “Olay” Adejumobi, Project Manager, PCCI

Recently, I was shocked to hear that North Texas is one of the hardest hit areas of the country for food insecurity. Shocked, but not surprised. As a registered dietitian and a participant in PCCI’s management of the Dallas Accountable Health Community (DAHC)[1] program, I have seen the Dallas County’s food depravations firsthand, and while this food desert may seem trackless, I believe that by using data, we have ways to create oases.

It turns out that Dallas County has the highest rate of food insecurity among counties in North Texas, with a rate of 15.6%, which is approximately nearly 407,000 residents, per a new report from Feeding America released by the North Texas Food Bank.

I couldn’t agree more with the statement made by Trisha Cunningham, President and CEO of the North Texas Food Bank, “In North Texas, where hunger affects more people than the populations of cities like Seattle or San Francisco, the most alarming statistic is that nearly 40% of those in need are children—a situation that is simply unacceptable.”

As an expert in nutrition, public health, I can tell you that the effects of food insecurity are pernicious and corrosive to families, communities and entire populations. These effects include:

  • Overall poor health and increased likelihood of chronic illnesses such as diabetes, cancer, heart disease, and stroke
  • Mental and social stresses of food insecurity, can lead to social isolation and stigma, while leading to depression due to heightened stress and anxiety
  • Declining academic success: Children who have food insecurities may see an adverse effect on their mental and physical health, reducing their educational opportunities

Ending in 2022, PCCI managed the DAHC[1], a five-year initiative that tested whether identifying and addressing health related social needs of Medicare and Medicaid beneficiaries such as housing instability and quality, food insecurity, utility needs, interpersonal safety, and transportation, would reduce both in health costs and emergency department utilization – we found it did. As a part of the team, I was witness to the myriad of social, economic and health issues the most underserved residents of Dallas faced.

What I can tell you is that food insecurity isn’t just a statistic― it’s a lived reality for many in the southeastern areas of Dallas County.

What I can tell you is that food insecurity isn’t just a statistic― it’s a lived reality for many in the southeastern areas of Dallas County. I’ve seen how non-medical drivers of health can amplify health disparities and lead to adverse health outcomes when quality, nutritious, and affordable food isn’t within reach. The people in these areas grapple with food insecurity due to a complex interplay of non-medical factors. Which makes solving this issue more that just having grocery stores available in those areas, though that would definitely be a good start. The challenges these areas face include:

  • Economic Challenges: The neighborhoods in southeast Dallas have high poverty rates, making it a daily struggle for residents to afford nourishing food. Families often find themselves compelled to prioritize cheaper, less nutritious options due to limited financial resources.
  • Transportation Barriers: Full-service grocery stores, where fresh produce and essential items are readily available, are scarce in these areas, and the lack of reliable transportation compounds the problem, preventing residents from reaching distant grocery stores and compelling them to settle for less healthy options closer to home.
  • Educational Disparities: Low educational attainment in these areas leads to limited knowledge about nutrition and healthy eating, making it a daunting task for residents to make informed food choices.

My journey inside the community data PCCI collected has been an eye-opener. But it’s not just about the numbers we see; it’s about understanding the lives and stories behind those data points. Armed with this information, we have the potential to embark on a path to address food insecurity in these communities through:

  • Community Health Workers: These unsung heroes bridge the gap by providing education, resources, and emotional support to individuals and families in need. They connect people to local resources like food banks and assistance programs and help them develop coping strategies.
  • Community-Led Initiatives: Data-driven strategies can empower grassroots organizations and community leaders to tackle food insecurity head-on. With the PCCI’s data, we can pinpoint, at the block-level, areas of the greatest need and tailor interventions accordingly.
  • Local Government Support: Guided by data-driven insights, local government officials can allocate resources more effectively. Advocacy for policies promoting the establishment of grocery stores and farmers’ markets can be rooted in this specific data.
  • Transportation Solutions: PCCI’s data also identifies transportation deserts within the most underserved areas of Dallas, paving the way for improved public transportation options. This strategic approach can ensure residents can access grocery stores with greater ease.
  • Education and Outreach: Customized nutrition education programs and workshops, based on PCCI’s data, can empower residents to overcome educational disparities and make healthier food choices.

Since the conclusion of the DAHC program, PCCI has developed the Community Vulnerability Compass (CVC), which provides actionable data regarding social barriers to health, access, and well-being of a community’s most vulnerable populations at the block group level. This includes insights into the number of individuals who are eligible for Supplemental Nutrition Assistance Program (SNAP) benefits, which is a leading indicator of food insecurity.

With the CVC, PCCI has been able to learn more about the pressing issues at the block group level in the hardest hit areas of southeast Dallas. PCCI’s data has reinforced the importance of understanding the unique challenges faced by these communities. Through leveraging this data, we can develop new community-led initiatives to engage residents and foster healthier, more resilient communities. The ultimate goal is to ensure equitable access to resources that enable all Dallas residents―regardless of their neighborhood, to lead healthy and fulfilling lives.

About Olayide “Olay” Adejumobi

Olay is a seasoned healthcare professional with ten years of clinical experience and five years of medical nutrition therapy and disease management experience. As a clinical project manager, she collaborated with cross-functional key stakeholders primarily focused on patient outcomes. She earned a Bachelor of Science in Nutritional Science and Public Health plus a Master’s degree in Healthcare Administration and Information Analytics from Texas Tech University.

[1] This project was supported by the Centers for Medicare and Medicaid Services (CMS) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award totaling $4.5M with 100 percent funded by CMS/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement by, CMS/HHS or the U.S. Government. Although PCCI’s participation in the AHC Model is now over and CMS is no longer affiliated, we are continuing aspects of the program established during our participation in the Model. 

BLOG: Community Health Workers Are Key in Building a Connected Community of Care

Community Health Workers Are Key in Building a Connected Community of Care

By Estefania Salazar Contreras, Advisory Service Ops Manager

Community health workers (CHWs) were found to be one of the critical elements that supported the Parkland Center for Clinical Innovation’s (PCCI) successful five-year implementation of the U.S. Centers for Medicare & Medicaid Services (CMS) Accountable Health Communities (AHC) Model in Dallas County1.

PCCI and its provider partners and community-based organizations (CBOs) supporting the Dallas AHC model (DAHC) offered innovative and highly effective new technologies and methods to help address health-related social needs (HRSNs), i.e., food housing, transportation, utilities, and interpersonal safety, of Medicare and Medicaid beneficiaries in Dallas County. But the element that served as the glue to the entire process was the human touch delivered by the CHWs who worked with the program participants every day through a process called “navigation.”

The navigation work itself was not unique to the DAHC. CMS required AHC awardees to conduct an initial screening to identify high-risk beneficiaries with HRSNs and then provide them with active navigation services consisting of referrals to aligned CBOs, accompanied by monthly follow-up calls for up to 12 months or until the documented HRSNs  were successfully addressed. CMS provided specific methods, goals, and even scripts for this work. But what

 we didn’t count on was the impact of our CHWs in delivering compassionate support to those who were not expecting it, but were incredibly grateful to receive it.

The Ideal Beneficiary Screening Setting

One key factor for a successful outreach program such as this is to have the “Ideal Screening Setting.” When we first began implementing the AHC program, we thought we could conduct the screening for HRSNs as part of outpatient clinical site encounters. However, our CHWs and team quickly realized that screening in an outpatient clinic’s waiting areas was not ideal for the beneficiaries. Patients were preoccupied waiting to be called to see their physician or financial department advisor. In addition, because we did not have a private space allocated for conducting the screening, they were concerned that other people could see and hear their conversations with the CHWs. As a result, this process yielded a low rate of completed screenings, making it nearly impossible to meet our CMS navigation targets. 

Therefore, we decided to change our approach by next screening inside of Emergency Departments (EDs). While this approach yielded slight increases in the number of completed screenings, these numbers were still not sufficient to meet the CMS targets. It is no secret that EDs are extremely busy. Moreover, CHWs wanted to be respectful of the clinical staff who had pressing priorities, and completing a screening was not at the top of their lists. It was also difficult to get participation from individuals who were understandably focused on their immediate health needs or in pain.

Using these lessons learned, we then decided to shift to a telephonic post-clinical-visit screening intervention. With this approach, our CHWs could screen beneficiaries within five days of their inpatient, ER, or outpatient encounter. PCCI’s data scientists helped make this engagement possible by generating beneficiary eligibility call lists for the CHWs to utilize daily. Beneficiaries were not preoccupied with clinical staff, in urgent pain, and could request a call back if they did not feel comfortable answering the screening questions at the time of the initial call. The CHWs also communicated in the language of the beneficiary’s preference.  Due to these factors, the telephonic post clinical visit screening became the “Ideal Screening Setting,” which allowed PCCI to not only meet―but ultimately surpass―the CMS navigation targets.

What Successful Outreach Looks Like

Once an eligible beneficiary completed the AHC HRSN screening and personal interview, through the navigation process, the CHW provided a list of referrals to one of the many CBOs best suited to meet the beneficiary’s needs (e.g.,  help with food, rent, or transportation). Referrals for each beneficiary were determined based on the CHW’s personal knowledge of available local resources. The outreach didn’t end with one screening and one referral. Following an initial two-week referral follow-up, our CHWs continued the case-management/navigation process by contacting the beneficiary monthly to determine if additional referrals were needed, as well as to assess the status of the beneficiary’s experience with the current resource list and referrals. If a beneficiary was unsuccessful with a specific CBO, the CHW provided additional guidance or a new referral. We found another benefit to this process as beneficiaries often reported new needs not identified during the initial screening stage.

The CHWs had to overcome a number of obstacles, primarily including the COVID-19 pandemic. Many CBOs limited or changed their hours of operations or even closed  for spans of time that sometimes were undisclosed. Our CHWs found themselves driving by CBOs to check on their availability while updating the program’s network on the CBOs’ status. This speaks to the dedication and passion our team had in making sure the program participants were well cared for and received the most up-to-date and accurate information.

Additionally, with the help of PCCI’S data scientists, they were able to create a daily automated case management report that identified what beneficiaries needed to be prioritized in the CHW’s caseload and weekly workflow. This allowed each CHW to maintain a caseload of about 200-250 beneficiaries at any one time. Because CHWs were very consistent with monthly beneficiary follow-ups,, beneficiaries could rely on them and began to trust them and disclosed more information on their existing (or new) HRSNs with more honesty and openness. Some of the most prevalent HRSNs outside of the five CMS core HRSN were affordable child-care, baby supplies (e.g.,  formula and diapers), and medical equipment. These additional needs were then incorporated into our CBO directory so we could align the needs with  potential community resources. We were able to conclude that on average it takes about 93 days or 4 telephone contacts to be able to resolve a need. During the COVID-19 pandemic, we did note that CHW phone calls with beneficiaries lengthened, especially for those who did not have any family or friends to count on or had to isolate because they were high risk for infection..  

Human Touch is still the Best Human Service

The quantitative results of the program speak to the overall success of each facet of the DAHC in very meaningful ways. For example, results showed that actively navigated individuals experienced a greater decrease in ED visits than those in a comparable control cohort, with those navigated having a statistically significant reduction in average ED utilization, both while actively navigated and in the 12 months after navigation. Those navigated also demonstrated a greater likelihood to seek — and keep — outpatient visits compared with the control cohort2.. These results offer our community greater cost savings and lead to a healthier community, especially for those who are considered the most at-risk.

But in addition to these results, we surveyed our participants on their own perspectives and experiences. Here are a few of the respondent’s comments from the survey:

  • “It helped me out in so many ways with my first baby. As moms we think everything will be easy, but there was so much I didn’t know about that helped me.”
  • “It made a big difference for me both emotionally and with my physical needs like food and bills. To know Parkland cares about us means so much!”
  • “It was nice to hear that there was help. I didn’t feel alone.”

One of the key highlights from these surveys was the value the participants placed on the connection with their CHWs, underscoring the importance of the human touch in improving the health and well-being of those most at-risk. For our team of CHWs who regularly went above and beyond for the beneficiaries they served, the positive data and cost savings are great, but their pride comes from knowing they helped to provide meaningful compassion, care, and support to people who needed it the most.

For a deep dive into PCCI’s efforts supporting the Dallas AHC, please review this article in the New England Journal of Medicine Catalyst: https://pccinnovation.org/new-england-journal-of-medicine-the-dallas-accountable-health-community-its-impact-on-health-related-social-needs-care-and-costs/

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[1] This project was supported by the Centers for Medicare and Medicaid Services (CMS) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award totaling $4.5M with 100 percent funded by CMS/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by CMS/HHS, or the U.S. Government.

[2] Naeem J, Salazar-Contreras E, Sundaram V, Wainwright L, Kosel K, Miff S. The Dallas Accountable Health Community: its impact on health-related social needs, care, and costs. NEJM Catalyst. 2022 Aug 17.

PCCI Pediatrician: The U.S. preterm birth rate is troubling, but we have proven ways we can help bring pregnancies to term

By Yolande Pengetnze, MD, MS, FAAP, Vice President of Clinical Leadership, PCCI

Recently, the March of Dimes (MOD) released its report card (https://www.marchofdimes.org/peristats/reports/united-states/report-card) that highlights the latest key indicators describing the state of the nation’s maternal and infant health. The MOD gave the U.S. a near failing, D+ grade for its 10.5 percent preterm birthrate.

The rising U.S. preterm birth rate is partly explained by racial/ethnic disparities, with Black women having ~50% higher risk of preterm birth than White women. The single most important intervention to prevent preterm births is adequate prenatal care. Yet one in 5 pregnant Black women and 1 in 4 pregnant American Indian/Alaska Native women do not receive adequate prenatal care.

The high U.S. preterm birth rate, while concerning, can be reduced by closing racial/ethnic and socioeconomic gaps in care through programs that increase access to prenatal care and address non-medical determinants of health (NMDOH, also known as Non Medical Drivers of Health or NMDOH). Moreover, widening racial/ethnic disparities in maternal death are partially explained by the same factors that drive preterm birth risk. Therefore, addressing preterm birth risk in a holistic manner has the added benefit of potentially (and positively) impacting maternal mortality.

At PCCI, we’ve developed ways to identify and support at-risk pregnant women in bringing their pregnancies to term. Specifically, to better serve pregnant women in our community, PCCI, the Parkland Community Health Plan (PCHP) and Parkland Health developed and implemented, beginning in 2018,  a novel preterm birth prevention program  that uses a machine learning algorithm, healthcare data, and NMDOH to identify pregnant women who are at a higher risk of pre-term birth. The program engages these women through text messages designed to help them better manage their health and proactively seek care during pregnancy.

Our program consistently risk stratifies about 13,000 pregnant women per year by combining clinical, socioeconomic, and demographic indicators from diverse data sources to predict pregnant women who present a high risk for preterm delivery. By predicting preterm birth accurately and in a timely manner, we are able to target patient education and engagement, as well as clinical and population-level interventions to reduce preterm birth rates among low-income Medicaid patients.

As socioeconomic factors and psychosocial stress are increasingly recognized as important drivers of preterm birth risk, PCCI’s risk prediction model paves the way for novel approaches to preterm birth prevention, combining clinical and non-traditional preterm birth prevention interventions addressing NMDOH targeted to high-risk patients.

This ongoing program enables early interventions, including enrolling women in a text education and reminder program that has helped reduce preterm birth rates by 20 percent and has increased prenatal doctor visits by 8-15 percent.

The combination of technology― a predictive model that identifies the most at risk and a risk-driven text messaging program―efficiently reaches expectant mothers where they are in their pregnancy journey. Rather than simply throwing out a broad net for all pregnant women, through our examination of NMDOH elements, we gain a clearer picture of who we need to help and why. This makes interventions much more holistic, effective, and cost efficient.

Through trial and error, we found that simple texting was the best way to reach expectant mothers and provide positive and easy-to-understand messages and reminders to help them to reach term. Examples of texts include:

This innovative yet simple approach for participant management allows us to extend great resources and focus on those who need help the most. In fact, in our quarterly surveys of the program participants, an average of 73% of respondents have agreed this program made them better prepared to take care of themselves and their babies. These results are meaningful not just to the mother and her family, but to the entire community.

It is extremely important to emphasize that while the program itself is innovative, it can be scaled and utilized in just about any community. Preterm birth  is not an issue that we want to simply shrug our shoulders about. Each time we have a premature birth, the costs to the baby, parents, hospital, and ultimately the community can be enormous. The life of a premature baby can be one of hardship and challenge and create lifelong difficulties for the individual, their family, and the society at large. Our collaborative team behind our preterm birth prevention program passionately believes that any preterm birth that can be prevented is a chance for a life to flourish and make a difference in the world.

About Yolande Pengetnze

Yolande Pengetnze, MD, MS, FAAP, is PCCI’s Vice President of Clinical Leadership where she leads multiple projects including population health quality improvement projects focusing on preterm birth prevention and pediatric asthma at the individual and the population level. Dr. Pengetnze received her MD from the University of Yaounde in Cameroon and completed a Pediatric Residency at Maimonides Medical Center in New York. She was a faculty member at UTSW’s General Pediatric Hospitalist Division where she completed a General Pediatric/Health Services Research Fellowship training and earned a Master of Sciences in Clinical Sciences.

Inside the New England Journal of Medicine Catalyst Article on PCCI’s Successful Management of the Dallas Accountable Health Communities Model

Inside the New England Journal of Medicine Catalyst Article on PCCI’s Successful Management of the Dallas Accountable Health Communities Model

The globally recognized leader in healthcare publishing, the New England Journal of Medicine Catalyst (NEJM Catalyst), has distributed an in-depth article authored by PCCI detailing its successful journey managing the U.S. Centers for Medicare & Medicaid Services (CMS) Accountable Health Communities (AHC) Model in Dallas County1.

To view the NEJM Catalyst article, click here: https://catalyst.nejm.org/doi/full/10.1056/CAT.22.0149

The NEJM Catalyst article offers the results of this five-year initiative, which included partnerships with the region’s top healthcare providers and community-based organizations (CBOs), that demonstrates its positive impact on health care outcomes for some of the most vulnerable Dallas County residents.

The peer reviewed NEJM Catalyst article outlines the purpose of the AHC Model in testing whether systematically identifying and addressing Medicare and Medicaid beneficiaries’ health-related social needs (HRSN), i.e., food, housing, transportation, utilities, and interpersonal safety, through screening, referral, and community navigation services impacts total health care costs and reduces inpatient and outpatient utilization.

The article further describes how bridge organizations (such as PCCI) served as ‘hubs’ in their communities, forming partnerships with their state Medicaid Agencies, local clinical delivery sites, and CBOs. The Dallas AHC (DAHC) included five major healthcare systems (Parkland Health, Baylor Scott & White, Children’s Health, Methodist Health System, and Metrocare Services), Texas Health and Human Services Commission (TX HHSC), and more than 100 CBOs who provided critical social services to meet the needs of residents in Dallas County ZIP codes with high concentrations of unmet HRSN.

Written by PCCI clinical experts and leaders of all aspects of the DAHC, the NEJM Catalyst article offers a comprehensive look at the full five-year initiative in Dallas and its impact on HRSN, utilization, and costs. This analysis includes critical details (and lessons learned) in the DAHC’s planning and implementation as well as methodology, results, and a look forward.

“We are so proud of the opportunity to lead such a meaningful initiative in partnership with CMS, TX HHSC, our participating healthcare systems, and the hundreds of other North Texas organizations who participated. The innovations, learnings, and results are invaluable and can hopefully serve as a blueprint for expanding these efforts regionally and even to other markets in our collective journey to address the social and personal determinants of health of our most vulnerable families,” said Steve Miff, PCCI’s CEO and President. “The significant number of individuals screened and navigated could not have been possible without the amazing support of the hospital systems and many CBOs in Dallas that actually delivered services to the people who came through the DAHC. This article shows the true scope and community-wide effort that makes programs like this successful.”

The NEJM Catalyst article, co-authored by PCCI’s Jacqueline Naeem, MD, Estefania Salazar-Contreras, Venky Sundaram, PhD, Leslie Wainwright, PhD, Keith Kosel, PhD, and Miff, provided strong evidence of the benefit of addressing HRSNs in a comprehensive manner using active navigation within the framework of a connected community of care model that coordinates efforts between clinical and community services.

“The NEJM Catalyst article digs deep into what our challenges were and the steps we took to test how addressing HRSNs improves utilization and health of vulnerable populations,” said Leslie Wainwright, PhD, PCCI’s Chief Funding and Innovation Officer. “Because of the tremendous effort and success we had in identifying, screening, and navigating so many individuals, this article is able to show some clear, thought-provoking results that will give us a logical path forward as we seek ways to address the needs of those most at-risk in our communities.”

The article reports that during the initiative’s five-year course, PCCI and its partners screened 12,548 individuals and identified more than 19,000 distinct needs, with 61% of individuals having two or more concurrent needs. Through the referral process, CBOs provided a multitude of support services, including more than 200,000 pounds of food and $540,000 in utility and rent assistance.

Additionally, the article shows that actively navigated individuals experienced a greater decrease in per-person ED visits.

“This was a tremendous project that garnered some exciting results, which is why the NEJM Catalyst article is so important for sharing how communities can make this work,” said PCCI’s Jacqueline Naeem, MD, Senior Medical Director/Program Director AHC. “But while the article shows important results, this is about more than just data, this is about the people in need who benefited substantially from the screenings, navigations, and participation in the initiative. The stories we heard of the lives we touched during the five-year program is a lasting legacy of the work our entire community put forward.”

In addition to the DAHC work and with the goal to help other municipalities build their own connected communities of care, PCCI also published an in-depth guidebook, “Building Connected Communities of Care.” This is the definitive guide for taking action using Non Medical Drivers of Health, with practical actionable insights from PCCI’s experience building, deploying, and expanding a connected community of care in Dallas. For more information on “Building Connected Communities of Care,” click here: https://pcci1.wpengine.com/playbook/

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[1] This project was supported by the Centers for Medicare and Medicaid Services (CMS) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award totaling $4.5M with 100 percent funded by CMS/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by CMS/HHS, or the U.S. Government.