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.

VIDEO: PCCI Unveils Community Vulnerability Compass, Giving Deep Insights Into the Health of Texas Communities

VIDEO: PCCI Unveils Community Vulnerability Compass, Giving Deep Insights Into the Health of Texas Communities

PCCI’s CEO, Steve Miff, PhD, and Chief Funding and Innovation Officer, Leslie Wainwright, PhD, reveal the details of PCCI’s newest innovation, the PCCI Community Vulnerability Compass. The CVC can help virtually any Texas-based organization (hospital system/health plan, care provider, CBO, public health entity, philanthropic funder, etc.) seeking to understand not only where its community’s most vulnerable residents live but also many of the underlying, multi-dimensional root cause factors driving these residents’ poor health and healthcare access and ability to thrive. Through a fuller understanding of these root causes, organizations can develop better programs, resources, and interventions to eliminate disparities, achieve health equity, and improve the health and well-being of vulnerable residents.

Click on the link below to view the video on PCCI’s LinkedIn page:

https://www.linkedin.com/feed/update/urn:li:activity:7066805134663548928

PCCI’s Community Vulnerability Compass Shows Mental Health Vulnerability Highest In Economically Challenged Areas of Dallas County

PCCI’s Community Vulnerability Compass Shows Mental Health Vulnerability Highest In Economically Challenged Areas of Dallas County

The Parkland Center for Clinical Innovation (PCCI) has released an analysis of Dallas County using its cutting-edge Community Vulnerability Compass (CVC) tool that shows how economically disadvantaged areas of Dallas County are also the most vulnerable to mental health concerns.

Sections in the south and southeast areas of Dallas County, which historically have had socio-economic disadvantaged populations, are revealed to have the highest mental health vulnerability rating (“Very High”) by the CVC. The “Very High” designation indicates that these areas are in the top 20 percent of vulnerability, when compared to the rest of Dallas County.

“In addition to poor mental health, these areas also have some of the lowest life expectancies and highest density of chronically ill populations in the County,” said Steve Miff, PhD, CEO and President of PCCI. “Just like our bodies need preventative care to optimize our physical health, our minds need the same attention to improve our mental health. There is also a strong correlation between your environment and both mental and physical health. In fact, these are tightly interwoven, where poor physical health can negatively impact mental health, and poor mental health can adversely impact physical health. We at PCCI believe that efforts to improve health must address the whole person. To lift the health of our community, you can’t focus solely on chronic diseases, but must also concurrently tackle mental health and address life barriers to access resources, especially in the most at-risk neighborhoods.”

The CVC is designed to help Texas-based organizations seeking to understand (at a county, ZIP code, census tract, or block-group level) not only where its community’s most vulnerable residents live but also many of the underlying, multi-dimensional root cause factors driving these residents’ poor mental and physical health and ability to thrive. The CVC tool includes 26 clinical and socio-economic indicators that reveal the health, resiliency, and economic vibrancy of neighborhoods.

PCCI’s CVC measures mental health by analyzing CDC data on the number of adults 18 years and older who stated that their mental health, which includes stress, depression, and problems with emotions, was not good for 14 or more of the last 30 days. The CVC also analyzes economic, education, safety, environmental, and other diverse health and social indicators to create a full picture of the County’s community health, as well as community health across the entire State.  

“As a start, these data can be extremely useful for community action groups, charities, or healthcare organizations to target education/information about mental health to these high vulnerability block groups. Although this map only highlights those 18 and older, we know caregivers’ mental health affects the children they are caring for, so organizations can also consider supporting schools in these areas. Sharing resources, teaching people about how to recognize when someone around them is struggling and promoting activities that encourage improving mental health are things that each of us can do,” said Jacqueline Naeem, MD, Senior Medical Director at PCCI.

Dr. Naeem added that the CVC’s analysis includes a wide range of data points, providing a true, holistic picture of who needs the most help and where to find them. The data PCCI provides is based on the best, most currently available information, which serves as a powerful tool to allow for proactive support of those in need.

“There is still stigma that exists around mental health, and mental illness that we need to work together to overcome,” said Dr. Naeem. “This data allows us to focus on the whole person by concurrently addressing the physical and mental needs of our neighbors and identifying their local barriers to access services. In doing so, the location and type of services can be tailored in ways that are more convenient for the recipients and education can be hyper-localized and tailored to those recipients in a more culturally empowered way.”

For more information about PCCI’s Community Vulnerability Compass, go to: https://pcciprod.wpengine.com/pccis-community-vulnerability-compass/

About Parkland Center for Clinical Innovation

Parkland Center for Clinical Innovation (PCCI), founded in 2012, is celebrating a decade as a not-for-profit, healthcare innovation organization affiliated with Parkland Health. PCCI leverages clinical expertise, data science and social determinants of health to address the needs of vulnerable populations. 

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GALLERY: PCCI Experts Make Important Impact At HIMSS Events

This Spring, HIMSS (Healthcare Information and Management Systems Society), a global thought leader and member-based society committed to reforming the global health ecosystem with information and technology, offered several platforms for PCCI’s experts to share their innovative programs with thousands of healthcare IT professionals.

PCCI in collaboration with leaders from Parkland Health, Parkland Community Health Plan and Dallas County, have delivered eight presentations, four at the national HIMSS conference in Chicago and four at the Texas HIMSS regional conference in Dallas. These eight presentations highlight the impactful and diverse applications of artificial intelligence and social determinants of health in clinical and populations health programs.

These presentations include:

HIMSS Annual National Convention:

“ML-AI-Driven Community Coalition, Digital Outreach Improves Asthma Among Low-Income Children”

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

Teresita Oaks, MPH, Director of Community Health Programs, Parkland Health

Description: PCCI partnered with Parkland Health to develop a Machine Learning/Artificial Intelligence asthma risk prediction model, using diverse social and clinical data sources to identify rising risk for asthma-related ED visits/hospitalizations among low-income children with asthma. Monthly risk-reports were leveraged to develop a multidisciplinary coalition across six high-asthma-morbidity Dallas County zip codes, for communitywide interventions.

“Using Data-Driven Insights to Prioritize Programs Addressing Social Vulnerabilities”

Natasha Goburdhun, MS, MPH, Vice President, Connected Communities of Care, PCCI

Paula Turicchi, FACHE, Chief Strategy Officer at Parkland Community Health Plan

Description: Despite the increasing awareness of the importance of social determinants of health (SDoH) and their influence on health outcomes, few organizations have adequate, contextualized insights to better address interrelated, social needs across a community. This presentation demonstrated how the Parkland Community Health Plan leveraged a three-tiered strategic analysis of SDoH and patient-level data to identify and prioritize programs to meet their members’ social needs.

“Integrating Universal Suicide Screening in EMR Improving Detection of Risk”

Jacqueline Naeem, MD, Senior Medical Director/Program Director AHC, PCCI

Kim Roaten, PhD., UT Southwestern Medical Center

Description:

In 2015, a universal suicide screening program was implemented at Parkland Health in which all patients 10 and older are screened for suicide risk during every provider encounter. Analysis was completed on over 3 million unique patients to understand the distribution of levels of risk in the population, as well as insights around the impact of the pandemic on patients identified with suicidal ideation.

“Patient Segmentation and Clustering Using ML to Develop Holistic, Patient Programs and Treatment Plans”

Yusuf Tamer, PhD, Senior Data and Applied Scientist, PCCI

Albert Karam, MS, MBA, Vice President, Data Strategy Analytics, PCCI

Brett Moran, MD, Chief Medical Informatics Officer, Parkland Health

Description:

In close collaboration with Parkland, PCCI developed a novel, advanced analytics process called Know-Thy-Patient (KTP) to group patients other than by their primary disease or diagnoses (e.g., diabetes, hypertension). By integrating and analyzing metrics associated with barriers to health care access — social vulnerabilities, transportation barriers, lack of insurance coverage — into the clinical context, health strategies adopting these cohort-similarity approaches can more readily incorporate a wider variety of patient-centered, whole-person approaches to care, such as integrated practice units, targeted digital programs, virtual and in-person support groups, and focused outreach and communication.

HIMSS Texas Regional Conference

“AI-Driven Interventions Improve Preterm-Birth Among Medicaid Pregnant Members”
PCCI’s Yolande Pengetnze, MD, VP Clinical Leadership joins Amrita Waingankar, MD, MBA, Senior Medical Director at Parkland Community Health Plan to share how they successfully implemented preterm birth prevention program in Dallas.


“Predicting Mortality of Trauma Patients”
PCCI’s Albert Karam, Vice President of Data Strategy and Analytics presents with Parkland’s Adam J. Starr, MD, will discuss this innovative predictive trauma model.


“Data Driven Approach to Addressing Health Related Social Needs (HRSN)”
PCCI’s Jacqueline Naeem, MD, Medical Director will present with Vidya Ayyr, MPH, CHW, Director Social Impact at Parkland about the Accountable Health Community model recently and successfully completed in Dallas.

“Implementing Inpatient Sepsis Early Prediction Model”
PCCI’s Yusuf Talha Tamer, PhD, Principal Data and Applied Scientist, will present with Parkland’s Nainesh Shah, Hospital Physician, DMIO, will share how their predictive sepsis model is changing how sepsis can be addressed.

PCCI’s Community Vulnerability Compass

PCCI’s Community Vulnerability Compass

An interactive tool to navigate SDOH-based needs of vulnerable populations

The CVC is a web-based tool enabling its users to visualize and more fully understand the context and complexities of the social barriers to health, access, and well-being of a community’s most vulnerable populations.

Based on the Healthy People 2030 framework seeking to achieve health equity, eliminate disparities, and promote good health for all, the CVC includes 26 clinical and socio-economic indicators clustered into four thematic domains denoting the health, resiliency, and economic vibrancy of neighborhoods.

Through a user-friendly dashboard, individuals can view which indexes, subindexes, and indicators are impacting vulnerability. They can utilize the dashboard’s dynamic online mapping feature, tabulated scores of indicators, and detailed analytics around other attributes that may affect vulnerability scores (e.g., race/ethnicity and demographics).

Key Features of the CVC

• Information can be visualized at the county, ZIP code, census tract, and block-group levels, giving users both a “forest and trees” view of a community. Intended to serve as a more detailed complement to other research studies (e.g., Community Health Needs Assessments) and field-based community voice initiatives, the CVC provides a comparable, data-driven summary of insights about community vulnerabilities.

• Users can also drill down to ask a series of follow-up “why” questions to really understand the root causes of inequities–a capability that is absent from other available tools.

• Insights provided by the CVC enable users to more effectively and efficiently prioritize, plan, and deploy–in a hyper localized way–supportive resources and interventions targeted to individuals or populations to advance whole-person health.

Vulnerable populations are groups of individuals (e.g., racial and ethnic minorities, the economically disadvantaged, those with chronic health conditions) who are at greater risk of poor health and well-being due to significant health and healthcare disparities (i.e., physical, economic, and social inequities). Their health and healthcare needs are most heavily driven by socio-economic, or social determinants of health (SDOH), factors such as lack of education, language barriers, and difficulty in accessing care (e.g., transportation barriers, absence of internet connectivity, deficiency in insurance coverage). However, assessing, understanding, and addressing these SDOH issues is not a simple or straightforward process for any organization seeking to improve the health of these residents. Specific unmet needs include:

• The need to look across SDOH factors to gain a holistic picture. For individuals facing high vulnerability, rarely is there only one issue they are facing; they often have multiple, complex needs. In addition, language and cultural barriers, issues with health literacy, and the organization’s own lack of resources all work against obtaining this understanding (e.g., through individual interviews) for the required number of individuals and frequency needed for impact.

• The need for a shared language across communities. In addition, evidence continues to mount that an upstream, cross-sector approach to health can result in more positive, sustainable health outcomes. A broad, community-based approach focusing on societal conditions, disruption of structural barriers (e.g., cross-sector silos), and targeted risk-driven interventions for collective impact can more effectively and sustainably remove health inequities and transform a person’s quality of life and health outcomes. However, organizations across communities use disparate data sources and different measure sets, meaning there is a lack of standardization needed to efficiently build needed cross-sector networks, create a common starting point, and effectively evaluate progress over time.

• The need to have the means to conduct root cause analyses. While there are a number of publicly available indexes that measure vulnerability, there are few that enable the root cause analyses needed to effect lasting change (i.e., showing the specific SDOH factors that are most impacting vulnerability in any given block group at any given time).

CVC addresses all of these needs and is rapidly becoming the go-to resource for teams addressing the needs of vulnerable populations.

CVC Is Built for both Clinical and Community-Based Organizations

Diagram

Description automatically generatedThe CVC can help virtually any organization (hospital system/health plan, care provider, CBO, public health entity, philanthropic funder, etc.) seeking to understand not only where its Community’s most vulnerable residents live but also many of the underlying, multi-dimensional root cause factors driving these residents’ poor health and healthcare access and ability to thrive. Through a fuller understanding of these root causes, organizations can develop better programs, resources, and interventions to eliminate disparities, achieve health equity, and improve the health and well-being of vulnerable residents.

CVC is an extremely useful tool for health systems and health plans who have made a commitment to community-based programming and need data-driven insights to support contemplated strategic objectives (e.g., new clinic locations). CVC insights can provide critical, contextualized information to guide these organizations and help them prioritize strategic imperatives.

CVC is especially useful for providers who have made commitments around addressing SDOH. Given the Health Systems/Health Plans with increased focus on SDOH difficulty in capturing this information directly from patients, the CVC can serve as a proxy to understand the block level of factors affecting individuals and their families. This information can also help providers design holistic programs to more effectively address the complex needs of their patients, particularly with respect to barriers to healthcare access. For example, grouping diabetic patients into diabetes program cohorts with other patients who have high degrees of similarity across clinical, personal, and behavioral characteristics can facilitate stronger provider-to-patient and patient-to-patient connections and support.

Delivering Impact

Organizations are successfully and innovatively leveraging the CVC to improve health and well-being across communities. Examples of current uses of CVC delivering impact include:

• In addition to a CBO’s use of CVC to identify areas of high vulnerability and root causes of needs across a community, the CBO is integrating its own outcome measures/goals (e.g., greater health insurance coverage across its region of service) into the CVC and tracking progress (through KPIs) over a multi-year timeframe.

• As part of an upstream, community-wide program to improve pediatric asthma in high-risk neighborhoods, organizational stakeholders are leveraging the CVC to identify rising risk for asthma-related Emergency Department (ED) visits/hospitalizations among low-income children with asthma.

CVC is also integrated into the design of a single, community-wide, data-driven surveillance system to track and monitor pediatric asthma at the community, neighborhood, and individual levels. This will improve the capacity of community stakeholders (including providers) to incorporate upstream, contextual SDOH factors and other important data into local policies, programs, and interventions to prevent ED visits and hospitalizations, close the asthma disparity gap, and meaningfully evaluate the impact of these efforts on the long-term health outcomes, quality of life, and care experience of children with asthma (and their families).

• Through use of patient-specific data via electronic health records (EHR) and SDOH data via the CVC (as a proxy for individual data), a health system is grouping patients by their access and utilization of healthcare resources rather than by disease group in order to more fully understand access barriers of patient cohorts and their utilization patterns. The goal is to improve patient healthcare access by supporting and informing better design of clinical programs that enable new community partnerships and enhanced models for patient engagement, such as expansion of virtual engagement options.

• A provider is using CVC SDOH insights (e.g., transportation challenges, internet connectivity, access to vital services) to determine, among other things, optimal locations for new community clinics serving vulnerable populations with advanced healthcare access issues.

• A health system and health department are analyzing (via side-by-side dashboards) CVC SDOH data and chronic disease data to better understand the specific SDOH factors impacting disease prevalence and then design and drive improved care programs to that cohort.

Methods

The CVC Leverages Curated SDOH Data to Create Normalized, Comparable Insights

While the ideal state is to hear about SDOH challenges directly from the affected individuals, it isn’t feasible to obtain this information at scale across communities. However, through research we know that SDOH factors are personalized to neighborhoods and this information can serve as a reasonable proxy for individual specifics, as characteristics of a resident’s block (e.g., transportation challenges, lack of green space) closely represent the challenges that resident likely faces.

The CVC groups levels of vulnerability for each of its four subindexes and 26 indicators into quintiles from lowest to highest vulnerability (i.e., very high, high, moderate, low, very low). Users can identify and create a visual map of where targeted individuals reside, study the characteristics of their neighborhoods and underlying barriers to health (ranked highest to lowest) based on location, and then prioritize individual or community-based service support. At the geographic level, the CVC captures data with increasing granularity from the county, ZIP code, census tract, to the block-group level. Users can view the 26 specific clinical and SDOH factors clustered by theme across the four subindexes aligning with the Healthy People 2030 framework. The subindexes include Household Essentials (e.g., food insecurity, paycheck predictability, health insurance coverage), Empowered People (e.g., mobility, internet connectivity, education), Equitable Communities (e.g., employment, housing, green space), and Good Health (e.g., chronic diseases, life expectancy, mental health). The CVC provides a score (Community Vulnerability Index/CVI) based on vulnerability for each individual indicator, aggregated factors across each of the four CVC subindexes, and a “rolled-up” single score across the targeted geographic area.

For its users, the CVC also provides a standard, single source of accurate, in-depth, real-time data that they can access, understand, disseminate, and act upon to ensure the most effective, coordinated, evidence-driven programs and the best possible health outcomes. Through the CVC’s four subindexes and 26 clustered indicators, provider and community-support networks can have a common starting point from which to incorporate SDOH factors and other important data into programs (e.g., reduction in pediatric asthma) that operate further upstream to close disparities gaps and advance health equity. And through a common evaluation framework, these networks can quantify the impact of interventions against the changing SDOH dynamics across a community in both the short-term (e.g., reduction in readmissions) and in the longer-term improvements in health outcomes.

Depending on their specific use cases and programming, organizations need access to different levels of geographic specificity. The CVC allows users to view its subindexes (and the composite indicators) at the county, ZIP code, census tract, and block-group levels. This flexibility to zoom up or down, depending on the use cases, allows users to more effectively address their unique challenges, especially given their finite resources.

In collecting the data from multiple data sources for the CVC, PCCI goes through a rigorous cleansing and quality assurance (QA) process to ensure the input data is complete and more robust than what users would obtain from publicly available websites. For example, PCCI uses data-science approaches to fill in missing values (e.g., computing a score based on averaging the values of the three closest neighborhoods). We also make needed QA adjustments, such as excluding those of retirement age when calculating unemployment or including both rental- and mortgage-related expenses when calculating costs associated with housing. PCCI has also validated the CVC against the gold standard Area Deprivation Index (ADI) and the CDC’s Social Vulnerability Index (SVI) to ensure the CVC is directionally aligned with other commonly used sources. Although the ADI is a well-known, powerful tool in capturing community need across a number of factors, it does so in the aggregate and does not enable users to drill down to the level of specificity needed across individual factors to more effectively inform the best, most holistic program or intervention design. Conversely, other tools such as the SVI do allow users to drill down for specificity across included factors but those factors don’t encompass the broader CVC range of risk factors impacting a community’s health. For example, the SVI factors focus on the attributes relevant to its purpose in planning for public health emergencies. While the CVC and SVI include some common indicators, the CVC is specifically designed, through its alignment with the Healthy People 2030 framework, to focus on the wider range of specific, actionable neighborhood risk factors known to influence the health of vulnerable populations.

Finally, the CVC allows for integration—using the existing CVC dashboard—of a user’s existing data to create new, custom indexes or models. For example, if an organization is tracking particular metrics for readmissions reduction, those metrics can be integrated into the CVC and tracked over time along with the existing CVC subindexes/indicators.

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To download a PDF of the CVC Information Sheet, use the following: