community
health needs
assessment(CHNA)

2021 REPORTContents
1.

Acknowledgements........................................................................................................................... 42.

Introduction ...................................................................................................................................... 6
Alignment to the State Health Improvement Plan of Ohio ...............................................................6
The Regional CHNA Geographic Region ...........................................................................................7

3.

An Inclusive Approach..................................................................................................................... 10
Comprehensive Data Collection ....................................................................................................10
Co-Created Research Questions ....................................................................................................11
Equity-Centered Framework .........................................................................................................12Comprehensive Drivers of Health Outcomes .................................................................................12

4.

Summary Of Regional CHNA Results............................................................................................... 14

5.

Most Prevalent Health Conditions in the Region............................................................................ 15
Greatest Unmet Needs .................................................................................................................18
Underserved Populations ................................................................................................................... 21
Places With Unmet Needs .................................................................................................................. 25

6.

SDOH Driving Health in the Region ................................................................................................. 26
6.1 Economic Stability ..................................................................................................................29
Health Conditions Impacted by Low Economic Stability .................................................................... 29
People Impacted by Low Economic Stability in the Region ................................................................ 30
Places with Low Economic Stability in the Region .............................................................................. 32
6.2 Neighborhood and Built Environment .....................................................................................37
Health Conditions Impacted by Low Perceptions of the Neighborhood and Built Environment ....... 37
People with Low Neighborhood and Built Environment Stability ...................................................... 37
Places with Low Perceptions of their Neighborhood and Built Environment .................................... 38
6.3 Education Access and Quality ..................................................................................................43
Health Conditions Impacted by Low Education Access and Quality ................................................... 43
People with Low Education Access and Quality ................................................................................. 43
Places with Low Education Access and Quality .................................................................................. 44
6.4 Social and Community Connectiveness ....................................................................................45
Health Conditions Impacted by Low Social and Community Connectiveness .................................... 45
People with Low Social and Community Connectiveness................................................................... 45

Additional Social Factors ..................................................................................................................... 47
6.5 Access to Quality Health Care..................................................................................................49
Health Conditions Impacted by Low Health Care Access and Quality ................................................ 49
People with Low Healthcare Access and Quality ................................................................................ 50
Places with Low Access to Quality Health Care .................................................................................. 51
Barriers to Accessing Quality Health Care According to Region’s Community Members .................. 52
7.

Societal Systemic Barriers to Improving Overall Health of Community Members ......................... 58
Structural Racism .........................................................................................................................58
America’s High-Cost Healthcare System ........................................................................................59
The Structural Divide of Holistic Health Care .................................................................................59
Demographics and Geographic Areas Uniquely Impacted by Structural Barriers .............................60

8.

Healthcare System’s Structural Barriers to Improving Quality of Health Care ............................... 62
Community Perspective on Opportunities to Improve Quality of Health Care.................................62
Region’s Systemic Barriers Faced by Healthcare Professionals to Improving Quality Care ............... 63
Increasing the Quality of Healthcare Encounters Can Help Meet Community Needs ....................... 65

9.

Community Assets and Considerations for Addressing Prioritized Needs ..................................... 68
Regional Assets and Concrete Opportunities to Address Prioritized Needs .....................................68
Gaps in Assets for Addressing Prioritized Needs ............................................................................69
Organizations Identified by Peers as Implementing Best Practices to Address Barriers to Health Care....................................................................................................................................................72

10.

Conclusion ....................................................................................................................................... 76

11.

Prioritization of Health Needs for Regional CHNA .......................................................................... 77

12.

Appendix A: Methods ..................................................................................................................... 81

Comprehensive Data Collection ....................................................................................................81
Secondary Data ................................................................................................................................... 81
Provider Survey ................................................................................................................................... 81
Population Survey ............................................................................................................................... 84
Focus Groups....................................................................................................................................... 88
Interviews............................................................................................................................................ 89
Collaborative Data Collection ............................................................................................................. 90
Data Considerations (Limitations) .................................................................................................91
13.

Appendix B: Supplemental Data for Health Conditions .................................................................. 92

14.

Appendix C: Supplemental Data for Social Determinants of Health .............................................. 982

Barriers Rooted in Limited Accessibility to Healthcare Information and Service Availability .......... 101
Barriers Rooted in High Healthcare Costs and Convoluted Insurance Policies ................................ 106
Barriers Rooted in Negative Past Experiences and Negative Perceptions of the Healthcare System.......................................................................................................................................................... 108
15.
Appendix D: Service Model, Policy and Practice Initiatives Identified by Region’s Healthcare
Professionals and Community Members .................................................................................................. 114
Recommendations from Community and Providers: Service Model, Policy, and Practice Initiative 114
16.

Appendix E: Local Implementation of Best Practices to Overcome Barriers to Health Care........ 122

17.

Appendix F: Original Data-Driven Recommendations .................................................................. 129

18.

Endnotes ....................................................................................................................................... 130

31. Acknowledgements
This Regional Community Health Needs Assessment (Regional CHNA) process and report would not
be possible without a collaborative approach from a variety of stakeholders across the community.
Specifically, this collaboration was built on the Mobilizing Action through Planning and Partnerships(MAPP) Circle of Involvement Framework, including the Core Circle (The Health Collaborative,
Greater Dayton Area Hospital Association (GDAHA), and consulting organizations) and the Circle ofEngagement (our Advisory Committee).
The Core Circle met regularly, hosted, and facilitated meetings, were responsible for deliverables,and managed day-to-day operations of the project. The Circle of Engagement (Advisory Committee)
kept the Core Circle accountable, provided expertise on each step of the Regional CHNA including
quantitative instrument development, qualitative questions, data collection efforts, reviewing
results and report drafts, finalizing the Regional CHNA report, and committing to implementation
efforts for their organization to address top needs.

ADVISORY COMMITTEE
Denisha Porter
Kiana Trabue
Lauren Brinkman
Monica Mitchell
Jeanne Bowman

All In Cincinnati
bi3
Cincinnati Children’s
Cincinnati Children’sChampaign Health District

Allison Luntz
Gina Hemenway
Carolyn Young
Geralyn Litzinger
Barbara Marsh

Maryse Amin

Cincinnati HD

Dawn Ebron

Susan Tilgner
Anna Jean Sauter

Cincinnati HD
Clark County Combined
Health District
Clark County Combined
Health District/Public
Health Dayton
Montgomery County
CoHearBrian Williamson
Sarah Moore

Mercy Health/Bon Secours
Mercy Health
Mercy Health Springfield
Margaret Mary HealthMontgomery/Dayton County
Public HealthMontgomery/Dayton County
Public Health
Norwood Health Department
Norwood Health Department

Roopsi Narayan

Premier Health

Erik Balster

Crossroads Center
Greater Dayton Area
Hospital Association(GDAHA)
Hamilton County Public
HealthHamilton County Public
HealthHealthCare Access Now(HCAN)

Ashley Clos
Jessica Coyle

Southwest Association of Ohio
Health Commissioners(AOHC)/Preble County Public
HealthThe Christ Hospital
The Christ Hospital

Shelley Spencer

The Christ HospitalFrank Nation

TriHealthSusan Murray

TriHealthEmma Smales

Dani Isaacsohn

Jamahal Boyd
Lisa Henderson
Becca Stowe
Greg Kesterman
Sarah Mills

4

ADVISORY COMMITTEE
Jolene Joseph
Colleen Desmond
Kelly Adcock
Jonathan Duffy
Molly Hallock

Healthcare Connection
Interact for HealthInteract for Health
Kettering Health Network
Kettering Health Network

Regan Johnson
Dan Maxwell
Lindsey Cencula
Laura Nabors
Gabe Jones

Jayda Carlton

Mercy Health/Bon Secours

Bruce Jeffery

University of Cincinnati
UC Health
UC Health
University of Cincinnati
West Central Association of
Ohio Health Commissioners(AOHC)/Champaign County
Public Health
YMCA Cradle to Career

CORE CIRCLE
Lisa Henderson

GDAHA

Erik Balster

Preble County Public
HealthThe Health Collaborative

Lauren Bartoszek
EricsonImarenezor
Elizabeth Pafford

Sheri Chaney
Jones
Eliza Gardiner
Alyssa Petty

The Health Collaborative

Harley Vossler

Measurement Resources
Company

Calista Smith

Measurement Resources
Company
Measurement Resources
Company
Measurement Resources
Company
Measurement Resources
Company
Scale Strategic Solutions

Additionally, the three circles in this framework were critical to success, breadth, and diversity of datacollection. Our Circle of Engagement participants were instrumental in survey distribution and focus
group recruitment through their Circle(s) of Champions, within counties and cities, hospital networks
and community-based organizations.
Also, the Circle of Information and Awareness provided high-level review and oversight of the work onbehalf of their organizations. This was represented by leadership of organizations participating in our
Circle of Engagement.
Finally, the Circle of Possibility represents all the community organizations and community members
who can and should be included in actionable strategies for implementation of the Community Health
Improvement Plan.

5

2. Introduction
We envision a region where everyone has the opportunity to be healthy. To achieve this vision, ourregion is working on eliminating health disparities by embracing community voice, investing in trusted
partnerships, and implementing evidence-based strategies and best practices to achieve equitable healthoutcomes for all.
To move this vision forward with data-driven action, The Health Collaborative (THC), in partnership with
the Greater Dayton Area Hospital Association (GDAHA), facilitated the 2021 Regional Community Health
Needs Assessment (CHNA). This Regional CHNA includes 36 hospitals, 22 health departments, across 26
counties in southwest Ohio and the Greater Dayton Area, southeast Indiana, and northern Kentucky.
Data collection, analysis, and synthesis was conducted by Measurement Resources Company (MRC) andsubcontractor Scale Strategic Solutions. A comprehensive, inclusive, and balanced mixed-method
approach, and best practices in community engagement, were used in data collection to ensure a
representative sample of community members, specifically the voices of marginalized populations andthe inclusion of providers across health and social services sectors.
In this Regional CHNA, health encompasses physical, mental, and social conditions. Health care isinclusive of hospitals and emergency rooms, primary care, behavioral health, specialty care (i.e., vision,
dental, chiropractic, etc.) and social services that support health or link community members to healthcare.
The Regional CHNA was guided by the Advisory Committee. A total of 42 individuals are part of theadvisory committee representing hospitals, health departments, and community partners in southwest
Ohio and the Greater Dayton Area, southeast Indiana, and northern Kentucky. The advisory committee
met monthly with THC, GDAHA, MRC and Scale Strategic Solutions to oversee the work and keep THC
accountable to the inclusive process.
The success of the Regional CHNA is a result of the collaboration from THC, local community champions,and strategic partners throughout the region to help with community engagement and data collection
efforts.
THC will use the Regional CHNA to inform how they direct energy and resources to equitably meet thehealthcare needs of the community. The results will encourage innovative healthcare delivery models
designed to unite region-wide efforts in providing high-quality care, increasing access to care, andachieving improved health outcomes for all.

Alignment to the State Health Improvement Plan of Ohio
This Regional CHNA includes a comprehensive data-driven approach to define the current state ofhealth and health equity with the goal of informing a collective, prioritize an actionable agenda for
improving health outcomes across the region over the next three years. Like the Statewide Health
Improvement Plan (SHIP) for Ohio, this Regional CHNA explores the priority factors that influence healthincluding perceptions of healthcare quality and access, health behaviors and community conditions (i.e.,social determinants of health). Guided by the SHIP, the Regional CHNA focuses on the priority healthoutcomes related to chronic disease, mental health and addiction, and maternal and infant health. The
recommendations put forth in this Needs Assessment support the priorities of the SHIP and provide aframework for working collaboratively in addressing disparities and barriers to a healthier community.
6

The Regional CHNA Geographic Region72021 CHNA Geographic Area
and Participating Organizations
HOSPITALS/HEALTH SYSTEMSBon Secours Mercy Health
Bon Secours Mercy Health Anderson Hospital
Bon Secours Mercy Health Clermont Hospital
Bon Secours Mercy Health Fairfield Hospital
Bon Secours Mercy Health Jewish Hospital
Bon Secours Mercy Health West Hospital
Cincinnati Children’s Hospital
Cincinnati Children’s Burnet Campus
Cincinnati Children’s Liberty Campus
Cincinnati Children’s College Hill Campus
The C&F Lindner Center of HOPE
The Christ Hospital, Mt. Auburn
TriHealth
TriHealth Good Samaritan Hospital
TriHealth Good Samaritan Evendale Hospital
TriHealth Bethesda North Hospital
TriHealth Bethesda Butler Hospital
TriHealth McCullough Hyde Memorial Hospital
UC Health
UC Health University of Cincinnati Medical Center
UC Health West Chester Hospital
UC Health Drake Center for Post-Acute CareGreater Dayton Area Hospital Association (GDAHA):
Kettering• Kettering Medical Center• Sycamore Medical Center• Kettering Behavioral Medical Center• Grandview Medical Center• Southview Medical Center• Soin Medical Center• Greene Memorial Hospital• Fort Hamilton Hospital8

Premier• Miami Valley Hospital• Atrium Medical Center• Upper Valley Medical Center• Miami Valley Hospital South• Miami Valley Hospital North
Wilson Memorial HealthWayne Healthcare
Mercy Health Springfield Regional Medical Center
Mercy Health Urbana Hospital
Adams County Regional Medical Center
Margaret Mary Health

LOCAL HEALTH DEPARTMENTS
City: Cincinnati, Hamilton (City), Norwood, Piqua, SpringdaleCounty: Adams, Auglaize, Brown, Butler, Champaign, Clark, Clermont, Clinton, Darke, Fayette,
Greene, Hamilton, Highland, Miami, Montgomery, Preble, Shelby, Warren

COUNTIES
Indiana: Franklin, Dearborn, Ohio, Ripley, Union
Kentucky: Campbell, Boone, Grant, Kenton
Ohio: Adams, Auglaize, Brown, Butler, Champaign, Clark, Clermont, Clinton, Darke, Greene,
Hamilton, Highland, Miami, Montgomery, Preble, Shelby, Warren
Notes/Limitations:• 4 Kentucky counties are managed by 1 NKY Health Department and did not officially participate.
These counties are however in the services areas of participating hospitals (Christ, CCHMC) andtherefore are included in the county number.
• 5 Indiana counties do have their own health department/county but did not officially participate.
They are included in multiple hospital service areas (GDAHA, MMH, CCHMC) and therefore were
included in the county number.
• 5 additional city health departments were engaged, all located within participating counties in
Ohio

93. An Inclusive Approach
The Regional CHNA methodology and results were generated through an inclusive, comprehensive, andbalanced data collection strategy for answering the research questions.

Comprehensive Data Collection
The needs assessment utilized a mixed-method approach to data collection including secondary
quantitative data and primary quantitative (Regional CHNA community and provider surveys) andqualitative (focus groups and interviews) data.
Secondary data collection, beginning in January of 2021, sought to understand the greatest healthconditions of the region, including prevalence and impact on community members. These results
informed the creation of survey items that were organized around a set of co-created researchquestions.
Each data collection strategy adhered to a recruitment plan to ensure a representative sample ofcommunity members, voices of marginalized populations, and providers across the health and social
services sectors were captured. All results are summarized for the region which includes the Cincinnati
Metropolitan Statistical Area (MSA), 1 Dayton-Kettering MSA (to include Clark County which is not part of
the Dayton MSA but is similar in that it borders the Dayton MSA and is not a rural county), 2 and otherrural counties in the geographic service area that are predominately rural and not included in other
MSAs. 3Overall, the scope of data collection was robust and informed the results of this Regional CHNA. This
includes:8,321 community surveys available in five languages. Within this sample,
representation was seen across 26 counties, males, females, ages 18-65+,
Black/African American, Multiracial, Asian, American Indian, Alaskan Native, White,and Hispanic/Latino populations.
859 provider surveys inclusive of behavioral health, education, emergency
medical services, faith-based organizations, federally qualified health centers,
justice/corrections, medical care (adult, geriatric, pediatric) oral health, organizations
addressing health related social needs and social determinants of health,pharmaceutical, and public health departments.
o Providers also represented administration, direct patient care, academic, support
staff, and supervisors/management.
o Providers reported serving a variety of populations including children/youth,
people with disabilities, ethnic minorities, people experiencing homelessness,
people in the justice system, veterans, young adults, low-income populations,and LGBTQ+ populations.

Includes the following counties: Grant, Butler, Clermont, Hamilton, Warren, Dearborn, Kenton, Boone, Campbell,
Brown, Ohio, Union, and Franklin.
2
Includes the following counties: Clark, Montgomery, Miami, and Greene.
3
Includes the following counties: Clinton, Highland, Adams, Preble, Shelby, Darke, Auglaize, and Champaign.
1

10

51 focus groups with 234 people were held, representing all three MSAs.

Specifically, recruitment for these focus groups were based on advisory committee
identification of populations who are traditionally underrepresented, marginalized, or
experience greatest health disparities.
o Populations represented in these focus groups include adult men, thoseexperiencing foster care or foster parenting, youth and adults with disabilities,
ethnic, cultural and language minorities, first and second-generation immigrants,
people experiencing homelessness, those involved in the justice system, lowincome families and individuals, parents, veterans, older adults, community
members with lived experience of mental health and/or addiction, and first
responders.
38 stakeholder interviews were held across health and social service
providers, specifically with the following being represented: mental health andsubstance use disorder (SUD), public health, hospital systems, Federally QualifiedHealth Centers (FQHCs), transportation, housing, food access, healthcare access andpolicy, school-based health and children’s health care, maternal and infant care,
LGBTQ+ health care, pharmacy access, and healthcare workforce development.
Appendix A contains a detailed description of each data collection strategy including the sampling or
recruitment strategy, and analysis.
Data collection was also comprehensive in that community members, social service providers andhealthcare professionals were not only asked “what could be better,” but also “whatis working.” As a result, this Regional CHNA includes a collection of assets andrecommended policy and practice initiatives identified by the community that
directly tie to system barriers. The symbol (to the left) can be found throughout thisreport. This symbol identifies a policy or practice that addresses the health needdiscussed in that section, corresponding to a more detailed description of therecommendation in Appendix D.

Co-Created Research Questions
To create the guiding research questions, the advisory committee participated in a group process,facilitated by MRC, to identify the emerging curiosities related to community health. The exercise
focused on moving beyond what is known through secondary data and asking questions that can lead toaction. The following five research questions were co-created by the advisory committee.
1. How do the greatest health needs differ across communities and community members?
2. What SDOH drive these greatest health needs among different communities and community
members?
3. What are the systemic barriers of these greatest health needs among different communities andcommunity members?
4. What are the structural barriers providers face in meeting the needs of the community?
5. What specific action steps can be taken by various partners to address the root causes andachieve more equitable health outcomes?
a. What community-based expertise should be leveraged?
b. What best practices are being implemented?
11

To answer these research questions, a framework was developed for centering equity and acomprehensive understanding of the drivers of health conditions. From this framework, MRC and theAdvisory Committee co-created a mixed-method data collection strategy including targeted recruitment.

Equity-Centered Framework
Health equity means everyone has a fair and just opportunity to be as healthy as possible. i To achieve an
understanding of health equity, each data collection strategy included mechanisms to:

1. Gathering the
Voices

2. Asking theQuestions

2. Ask questions about health experiences,outcomes, barriers, and solutions.

Understanding
Health Equity
4. Articulating theDifferences

1. Hear the voices of community members
and be intentional about engaging community
members who are historicallyunderrepresented in community data.

3. Disaggregating
the Data

3. Disaggregate the data by region, age, race,and gender and other characteristics with
sufficient sample sizes.
4. Using the data to clearly identify the uniqueexperiences of community members.

Comprehensive Drivers of Health Outcomes
The following framework helps us understand the drivers of health outcomes and provides the basis fororganizing the health needs assessment. In summary, community members experience healthconditions because of the risk and protective factors that are present in their life. Those factors are
driven by the programs and policies that govern society.

PROGRAMS & POLICIES• Systemic Barriers•••

FACTORS
Health Behaviors
Adverse Childhood
Experiences
Social Determinantsof Health•

OUTCOMES
Health Conditions

12

Programs and Policies
Systemic Barriers
Finally, the governing policies rooted in structural bias perpetuate health disparity and unhealthy
behaviors (i.e., not seeking services, self-medicating, etc.). In this Needs Assessment, systemic barriers
were assessed from the gender and race lens, perceptions related to stigma, and barriers specific tohealth care (i.e., workforce shortage, cost reimbursement, etc.).
Factors
Health Behaviors
Health behaviors are actions of community members that impact health. Health behaviors can improvehealth or put health at risk. Behaviors include diet and nutrition, exercise, sleep, substance use, etc. In
this Needs Assessment, the literature around each of the health behaviors are explored to determine
their impact on health outcomes and disparities in health conditions.
Adverse Childhood Experiences Framework
Adverse childhood experiences (ACEs) are also a significant risk factor that can lead to poor health,chronic disease and early death. ACEs are traumatic events experienced as a child including abuse,neglect, violence, incarceration of relatives, parental divorce, etc. Exposure to trauma from an early age
can disrupt the development of a young person’s brain, ultimately leading to higher rates of chronic risk
behavior, disease, mental illness, and early death if appropriate interventions and protective factors are
not present. As a child’s ACEs increase, so does their likelihood of chronic disease and early death. ii
Secondary data and literature were used to inform the discussion of ACEs and ACEs-related disparities.
Social Determinants of Health Framework
Social Determinants of Health (SDOH) are the structural and social conditions in the environment that
affect a wide range of health, functioning, and quality-of-life outcomes and risks. iii The Healthy People
2030 SDOH iv framework provided guidance for this Regional CHNA in identifying the community
conditions that impact the health of community members. These community conditions include (not inrank order):•Economic stability•
Neighborhood and built environment•
Education access and quality•
Social and community context•
Healthcare access and quality
SDOH are explored in all data collection strategies to understand their relationship to the region’s
greatest health needs and disparities in health conditions.
Outcomes
Health Conditions
The health conditions of our communities are driven by factors within and outside an individual’scontrol. A study from the University of Wisconsin Population Health Institute showed that about 80% of
people’s health is the result of physical, environmental and behavioral factors. v In this Regional CHNA,
health factors were explored to understand what impacts the most prevalent health conditions in theregion.
13

4. Summary Of Regional CHNA Results
To summarize the results of the Regional CHNA, the lists below highlight main takeaways to consider inthe prioritization process.
Most Prevalent Health Conditions(Ranked)1. Cardiovascular Conditions(Hypertension)
2. Mental Health (Depression
and Anxiety)3. Arthritis
4. Lung/Respiratory Health
5. Dental
6. Maternal health concerns
7. Prevention- related healthneeds

Health Condition Most Untreated(Ranked)1. Vision
2. Dental
3. Allergy
4. Mental Health (Depression
and Anxiety)5. Arthritis
6. Cardiovascular Conditions(Hypertension)
7. Maternal health concerns

Health Conditions Most Impacted
By SDOH• Cardiovascular Conditions(Hypertension)• Mental Health (Depression andAnxiety)• Vision• Lung/Respiratory Health• Diabetes

SDOH Factors Impacting Health in the Region
•
•
•
•
•

Economic stability (Stable housing, food security, paying bills)
Neighborhood and Built Environment (Access to reasonable transportation, parks/outdoor activities,
stable phone, and internet)
Education Access and Quality (Perception of quality of schools and childcare that are available)
Social and Community Connectedness (Having someone to talk to and feeling connected to thecommunity)
Healthcare Access and Quality (Perception of quality of health care available, cultural relevancy ofhealth care, ease of finding desired health care, ease of navigating healthcare costs)
Structural Barriers in the Region’s Healthcare System

•
•
•
•
•
•
•
•
•
•
•

Competition across healthcare organizations/systems
Workloads and caseloads are highLack of effective clinical-community linkages
Language barriers and cultural differences
High cost of services
Limited workforce
Inflexible and restricted funding structures and/or investment in community
Lack of culturally relevant communication strategies and services across providers
Limited implementation of DEI practices within organizations
Community member distrust in the healthcare ecosystem (providers, insurers, pharmacies, etc.)
Limited implementation of best practices of trauma-informed care
Systemic Barriers•••

Structural racism
High-Cost healthcare system
Structural divide between healthcare system, holistic wellness providers, and social service providers
Prioritized Health Needs•••

Increase access to services in order to improve equitable outcomes for the region’s top health needs:
behavioral health, cardiovascular disease, dental, and vision.
Address access to and use of resources for food security and housing with a focus on the development
and strengthening of partnerships between providers and community-based organizations.
Strengthen workforce pipeline and diversity, including cultural competence, within the healthcare
ecosystem.

14

Regional CHNA Results
5. Most Prevalent Health Conditions in the Region
Greatest health needs across the region were identified utilizing multiple data sources, including selfreport Regional CHNA community survey results (see Figure 1), hospitals’ utilization data (see Appendix
A for details), and county-level Center for Disease Control (CDC) leading cause of death data. In reviewof these varying data sources, the most prevalent health conditions across the region include:
1. Cardiovascular-related conditions (i.e., high blood pressure and/or high cholesterol)
As shown in Figure 1, approximately three in ten residents from the Regional CHNA community
survey report needing treatment for high blood pressure and/or high cholesterol. As
cardiovascular-related conditions, including high blood pressure/high cholesterol are the leading
health needs among residents and are major risk factors for heart disease, 4 it is of no surprisethat Diseases of the Heart, particularly Major Cardiovascular Disease, was the leading cause ofdeath in 2019, with an average age-adjusted rate of 251 per 100,000 individuals. 5 Nationally,
heart disease is the leading cause of death. vi Further, among emergency room and inpatient
hospital visits in the region from January 2019 through June 2020, seven percent (or 72,889) of
the visits were due to primary diagnoses of the circulatory system (after removing visits due tosymptoms, signs, and abnormal clinical and laboratory findings).
2.

Mental health-related conditions (i.e., depression and anxiety disorders)Across the region, approximately two in ten residents from the Regional CHNA community
survey report needing treatment to support their mental health (i.e., depression, anxiety, etc.;
Figure 1). This is consistent with national rates. vii Further, among emergency room and inpatient
hospital visits in the region from January 2019 through June 2020, three percent (or 22,112) ofthe visits were due to primary diagnoses of mood/affective and anxiety/stress-related disorders(after removing visits due to symptoms, signs, and abnormal clinical and laboratory findings).

3. Arthritis or osteoporosis
Across the region, approximately one in ten residents from the Regional CHNA community
survey report needing treatment for arthritis or osteoporosis (Figure 1). This is slightly lower
than national trends with an estimated two in ten U.S. residents having been diagnosed witharthritis. viii Further, among emergency room and inpatient hospital visits in the region fromJanuary 2019 through June 2020, one percent (or 10,498) of the visits were due to primaryhttps://www.cdc.gov/heartdisease/risk_factors.htm
Age-adjusted rates were obtained from CDC Wonder, Underlying Cause of Death(https://wonder.cdc.gov/wonder/help/DataExport.html#Excel) and averaged across all counties within the region(with exception of Ohio and Union Counties due to limited data), ranging from 189.8 in Ripley County to 325.4 in
Adams County.
4
515

diagnoses of osteoarthritis and osteoporosis (after removing visits due to symptoms, signs, andabnormal clinical and laboratory findings).
4. Lung/respiratory-related conditions, including asthma
Across the region, approximately one in ten residents from the Regional CHNA community
survey report they needed treatment for lung health conditions (including asthma, COPD,
emphysema, chronic bronchitis) and, similarly, for COVID-19 (Figure 1). This is higher thannational trends. Across the U.S., approximately 8% of adults have asthma and 4.6% have chronic
obstructive pulmonary disease (COPD). In terms of the Regional CHNA community survey, needfor treatment prevalence for lung-related conditions ranked fifth in terms of the conditions
surveyed, however, hospital data reveals that it is among the leading reasons (among thepriority health conditions) why people visit the ER or are hospitalized as inpatient. From January
2019 through June 2020, 11 percent (or 111,301) of the visits were due to primary diagnoses of
diseases of the respiratory system 6 (after removing visits due to symptoms, signs, and abnormal
clinical and laboratory findings).
5. Oral/Dental disease
Across all communities, there is a need for access to dental services. Because dental services are
not under the system’s ‘healthcare’ umbrella, dental care often requires supplemental
insurance. In focus groups, dental services were identified as a need across many community
members.
6. Maternal health complications
Maternal health complications were a priority health area for women. Across the region, lessthan one in ten residents reported they needed treatment for maternal health complications (alower rate relative to other conditions is to be expected given this can only apply to pregnant
women; Figure 1). Further, among emergency room and inpatient hospital visits in the region
from January 2019 through June 2020, three percent (or 30,363) of the visits were due toprimary diagnoses of pregnancy, childbirth, and the and certain conditions originating in theperinatal period.
7. Prevention services
While community members reported needing treatment for the above specific conditions, when
asked in focus groups and interviews, community members and providers alike identified theneed for prevention services in the region. Prevention services are needed across the life span,with community members highlighting the need for more mental health and addiction
prevention programs for youth, adults, and older adults (e.g., mindfulness); preventative
reproductive health care for youth and adults; nutritional education; programs that promotesocial connectivity; and programs that promote exercise and coping with stress.

6

Based on ICD10 codes provided in the hospital data, we were unable to determine if this accounts for COVID-19.

16

Additional health conditions were assessed in this Regional CHNA based on interests and priorities of
local health improvement plans across all three states. All conditions are summarized in Figures 1 and 2
as well as in Tables 1 and 2. However, only the most prevalent are discussed and further analyzed in thisRegional CHNA.

Figure 1. Overall Need for Treatment for Health Conditions% of individuals who self-reported needing treatment for this condition in the pastyear
Cardiovascular Conditions, including High Blood
Pressure, High Cholesterol
Mental Health
Arthritis or Osteoporosis
Diabetes (Type 1 or 2)
Lung Health Conditions
Injury from Accidents
COVID-19
Neurological Disorders
CancerBlood Disorders
Psychiatric Disorders
Pregnancy/Prenatal Care
Maternal Health Complications
Suicidal Ideation
Alcohol or Drug Addiction
STI/STD
HIV/AIDS
Alzheimer's
0%

10%

20%

30%

40%

Data Source: REGIONAL CHNA Community Survey
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

17

Greatest Unmet Needs
In the Regional CHNA community survey, community members were asked to identify their unmet
health needs, i.e., the health conditions for which they needed health care but did not receive
care/treatment in the past year (Figure 2). To investigate health needs further, community members
were also asked what other conditions they had and needed treatment for but did not get treatment in
the past year. These other conditions were not identified in the original list of health conditions but
were included in the survey based on the understanding that these conditions were also prevalent in thecommunity. Together, there are seven leading unmet healthcare needs reported in the Regional CHNA
community survey by community members throughout the region. Systemic barriers driving these
unmet needs are further discussed in the following sections of this report.
1. Vision Concerns
When asked what other health conditions (i.e., other than the priority health conditions shownin Table 1) community members needed treatment for but did not get, the most common
condition was vision concerns, with approximately two in ten community members indicating
this (Table 1).
2. Oral/Dental disease
Similar to unmet vision needs, community members are presented with barriers that lead to
unmet dental needs. Approximately two in ten community members reported needing
treatment for dental concerns but not receiving it within the past year (Table 1).
3. Allergies
Unmet health needs for allergies are also fairly prevalent throughout the region withapproximately two in ten residents reporting needing but not receiving care for this healthcondition (Table 1).
4. Mental health-related conditions (i.e., depression and anxiety disorders)Among the priority health conditions surveyed, mental health treatment was the leading unmet
need across the region. Specifically, among residents who reported needing treatment formental health, nearly one in three indicated that they did not receive it (Figure 2).
5. Arthritis or osteoporosis
Among the priority health conditions surveyed, treatment for arthritis or osteoporosis was thesecond highest unmet need across the region. Specifically, among residents who reported
needing treatment for arthritis or osteoporosis (Figure 2), one in three or more (in Cincinnati
MSA and rural counties) indicated that they did not receive it (Figure 2).

18

6. Cardiovascular-related conditions (i.e., high blood pressure and/or high cholesterol)
Not only are high blood pressure/high cholesterol the leading health needs in the region, butthese conditions are also a leading unmet health need among the priority health conditions
surveyed. Specifically, among residents who reported needing treatment for high bloodpressure/high cholesterol, approximately one in ten did not receive it (Figure 2).
7. Maternal health complications
Maternal health is a priority for the region. Among pregnant women who need/needed
treatment for maternal health complications, more than half report an unmet need in the
Regional CHNA community survey results. Further, across Dayton and Cincinnati MSAs in 2019,
approximately six percent of pregnant women received late (care started in the third trimester)or no prenatal care during their pregnancy. 7
Table 1. Percent of individuals with other unmet health needs.
What other health conditions did you have and need treatment for but did not get in the past 12
months?
Other Health Condition
Cincinnati
DaytonRural
MSA
KetteringCounties(n = 4,415)
MSA(n = 1,363)(n = 2,543)
Vision concerns
23%
22%
23%
Dental concerns
20%
17%
17%
Allergies
20%
16%
15%
Migraines
9%7%8%Autoimmune disease
6%
5%
5%
Men’s reproductive health concerns (not cancer)
2%
3%
2%
Women’s reproductive health concerns (not cancer)
3%4%3%
Another3%2%3%
Data Source: Regional CHNA community survey

https://wonder.cdc.gov/wonder/help/DataExport.html#Excel; estimates are limited to counties with sufficient
data needed for CDC to calculate reliable estimates. These counties include: Boone, Kenton, Butler, Clermont,
Hamilton, Warren, Clark, Greene, Miami, and Montgomery.
7

19

Figure 2. Unmet Need for Health Conditions% of individuals who self-reported needing treatment for this condition but did notreceive it in the past year
Mental Health
Arthritis or Osteoporosis
Cardiovascular Conditions, including High Blood
Pressure, High Cholesterol
Neurological Disorders
Lung Health Conditions
Injury from Accidents
COVID-19
Cancer
Psychiatric Disorders
Blood Disorders
Alcohol or Drug Addiction
Suicidal Ideation
Maternal Health Complications
Diabetes (Type 1 or 2)
Pregnancy/Prenatal Care
STI/STD
HIV/AIDS
Alzheimer's
0%
Cincinnati MSA

1%

2%

3%

4%

5%

6%

7%

8%

Data Source: REGIONAL CHNA Community Survey

Dayton-Kettering MSA

Rural Counties

When asked in focus groups what healthcare services they need most in their communities,
community members across the region said, “dental, mental health, and prevention.”20

Underserved Populations
There is a myriad of factors that can explain why individuals have unmet health needs (defined as
needing treatment for a condition and not receiving it), ranging from individual factors (e.g., choosing
not to seek out health care due to the assumption symptoms will improve on their own),
family/personal responsibilities (e.g., prioritizing caregiving responsibilities over one’s own healthneeds), and system-level factors (e.g., lack of availability or accessibility to care). Regardless of thereason why individuals have unmet needs, understanding for whom unmet health needs are mostprevalent are critical to inform targeted interventions and/or outreach efforts to ensure residents
throughout the region understand when, where, and how to get treatment. The following lists for whom
unmet needs are most common and the following sections will provide greater context behind thereasons why treatment is not sought.
•••

Males. Among the greatest unmet needs across the regions, males, relative to females, aresignificantly more likely to have unmet health needs for vision concerns (1.2 times as likely), 8
dental concerns (1.3 times as likely), 9 and mental health (2.2 times as likely). 10
Black, Multiracial, Asian, and American Indian/Alaskan Native. Among the greatest unmet
needs across the regions, Black/African American individuals, relative to White individuals, aresignificantly more likely to have unmet health needs for dental (1.3 times as likely) 11 and allergyrelated concerns (1.6 times as likely), 12 as well as mental health (1.6 times as likely). 13
Multiracial individuals were also significantly more likely to have unmet dental needs (1.5 times
as likely) relative to White individuals. 14 Finally, individuals identifying as Asian, American
Indian/Alaskan Native, Native Hawaiian or Pacific Islander or another race (that is not Black,
White or multiracial) relative to those identifying as White, are significantly more likely to haveunmet mental health (1.8 times as likely) 15 and allergy needs (1.7 times as likely). 16
Younger Individuals. Among the greatest unmet health needs throughout the region, younger
individuals 17 are significantly more likely to experience unmet needs among nearly all the

8 The odds of having an unmet vision need for males is 1.2 times as large as it is for females (b = .15, p < .05).

9 The odds of having an unmet dental need for males is 1.3 times as large as it is for females (b = .24, p < .05).

10 The odds of having an unmet mental health need for males is 2.2 times as large as it is for females (b = .80, p < .05).

11 The odds of having an unmet dental need for Black/African American individuals is 1.3 times as large as it is for White

individuals (b = .29, p < .05)

12 The odds of having an unmet allergy need for Black/African American individuals is 1.6 times as large as it is for White

individuals (b = .45, p < .001)

13 Greater unmet mental health needs for Black/African American individuals mainly derived from qualitative data collection.

The logistic regression results were not statistically significant at p < .05, though the effect size, odds ratio, for having an unmet
mental health need was rather sizeable for Black individuals relative to White individuals (odds were 1.6 times as large; b = .47,
p =.059).
14 The odds of having an unmet dental need for Multiracial individuals is 1.5 times as large as it is for White individuals (b = .43,
p < .05)
15 The odds of having an unmet mental health need for individuals identifying as Asian, American Indian/Alaskan Native, Native
Hawaiian or Pacific Islander, or identified as another race that is not Black, White or multiracial is 1.8 times as large as it is for
White individuals (b = .57, p < .05)
16 The odds of having an unmet allergy need for individuals identifying as Asian, American Indian/Alaskan Native, Native
Hawaiian or Pacific Islander, or identified as another race that is not Black, White or multiracial is 1.7 times as large as it is for
White individuals (b = .51, p < .001)
17 Age is treated as a continuous variable and thus differences in unmet need based on age is interpreted as each additional
year younger.

21

•

•

•

conditions, including dental, 18 allergy, 19 mental health, 20 arthritis/osteoporosis, 21 andcardiovascular-related conditions. 22 Thus, though younger individuals are less likely to needtreatment for these conditions, when they do need treatment, they are also less likely to get it.
(See footnotes for effect sizes.)
LGBTQ+ Individuals. The exposure to chronic and pervasive stress, in line with the minority
stress model, ix creates results in health disparities among LGBTQ+ individuals when comparedto heterosexual, cisgender individuals (Caceres 2020). x The health disparity among LGBTQ+
individuals has primarily been studied in relationship to cardiovascular disease and mental
health, with research concluding that rates of occurrence are higher in both cases (Gonzales
2017; Merschel 2020). xi Certain health conditions are found to be more prevalent among
LGBTQ+ adults including high blood pressure and obesity. xii Because LGBTQ+ individuals reporthigh levels of discrimination when accessing health care (between 50-70% depending on sexual
orientation and gender identity), they are more apt to “delay primary or preventative care” anddisplay mistrust in health care. xiii
Maternal Age Women. Unmet needs for maternal age women highlight racial and ethnic
discrepancies in health care. In Dayton and Cincinnati MSAs, individuals who are Hispanic as wellas individuals who are Black have lower rates of receiving prenatal care during the firsttrimester, with first trimester prenatal care rates up to 19% lower for these individuals relative
to other populations in these regions. 23 Overall, rates of pre-pregnancy obesity, as well as
chronic illness during pregnancy including diabetes and hypertension, have all increased by anaverage of two percent (Cradle Cincinnati 2020). Other conditions such as drug exposure,
postpartum depression, unintentional pregnancies, and those with an underweight prepregnancy body mass index have all decreased in recent years (Cradle Cincinnati 2020).
Veterans and Active Military. Active military, relative to non-active military, are significantly
more likely to have unmet mental health (2.5 times as likely), 24 arthritis/osteoporosis (2.8 times
as likely), 25 and cardiovascular-related needs (2.7 times as likely). 26 Further, veterans, relative to
non-veterans, are significantly more likely to have unmet mental health needs (2.3 times as
likely). 27

18 For each additional year increase in age, the odds of having an unmet dental need are .7% less (b = -.007, p < .05). Thus, theodds of having an unmet need for an individual aged 55 are .7% less relative to an individual aged 54; the odds of having an
unmet need for an individual aged 55 are 6.4% less than an individual aged 45.
19 For each additional year increase in age, the odds of having an unmet allergy need are 1.6% less (b = -.02, p < .001).
20 For each additional year increase in age, the odds of having an unmet mental health need are 3.0% less (b = -.03, p < .001).
21 For each additional year increase in age, the odds of having an unmet arthritis/osteoporosis need are 4.5% less (b = -.05, p <.001).
22 For each additional year increase in age, the odds of having an unmet cardiovascular need are 7.4% less (b = -.08, p < .001).
23
https://wonder.cdc.gov/wonder/help/DataExport.html#Excel; estimates are limited to counties with sufficient data needed
for CDC to calculate reliable estimates. These counties include: Boone, Kenton, Butler, Clermont, Hamilton, Warren, Clark,
Greene, Miami, and Montgomery.
24 The odds of having an unmet mental health need for active military is 2.5 times as large as it is for non-active military (b = .90,
p < .01)
25 The odds of having an unmet arthritis/osteoporosis need for active military is 2.8 times as large as it is for non-active military(b = 1.01, p < .05)
26 The odds of having an unmet cardiovascular need for active military is 2.7 times as large as it is for non-active military (b =.98, p < .01)
27 The odds of having an unmet mental health need for veterans is 2.3 times as large as it is for non-veterans (b = .82, p < .001)

22

•

•

•

•
•

Individuals with Disabilities. Individuals with disabilities, relative to those without disabilities,
are significantly more likely to have unmet vision (1.7 times as likely), 28 dental (1.7 times as
likely), 29 and allergy needs (1.4 times as likely). 30
Caregivers of Individuals with Disabilities. Individuals caring for others with a disability are
significantly more likely to have unmet needs for nearly all of the greatest unmet needs in theregion (except cardiovascular-related), including mental health (1.5 times as likely), 31 dental (1.7
times as likely), 32 vision (1.5 times as likely), 33 allergy (1.2 times as likely), 34 andarthritis/osteoporosis (2.1 times as likely). 35
Individuals without Private Insurance. Individuals without private insurance (those not insured
and those publicly insured) are significantly more likely to have unmet mental health (.6 times as
likely), 36 dental (.7 times as likely), 37 and cardiovascular-related needs (.6 times as likely), 38
relative to privately insured individuals.
Individuals with Lower Educational Attainment. Individuals with lower educational attainment
are significantly more likely to have unmet vision, 39 dental, 40 and cardiovascular needs. 41
Women with past traumas of physical abuse and/or sex trafficking identified a need forchiropractic care but the cost can be too high, the care is not often covered by insurance, and/or
the service is not accessible from shelters or group homes.

28 The odds of having an unmet vision need for individuals with disabilities is 1.7 times as large as it is for those without

disabilities (b = .52, p < .001)

29 The odds of having an unmet dental need for individuals with disabilities is 1.7 times as large as it is for those without

disabilities (b = .53, p < .001)

30 The odds of having an unmet allergy need for individuals with disabilities is 1.4 times as large as it is for those without

disabilities (b = .30, p < .001)
The odds of having an unmet mental health need for caregivers of individuals with disabilities is 1.5 times as large as it is for
those who are not caregivers (b = .40, p < .01)
32
The odds of having an unmet dental need for caregivers of individuals with disabilities is 1.7 times as large as it is for those
who are not caregivers (b = .53, p < .001)
33
The odds of having an unmet vision need for caregivers of individuals with disabilities is 1.5 times as large as it is for those
who are not caregivers (b = .44, p < .001)
34
The odds of having an unmet allergy need for caregivers of individuals with disabilities is 1.2 times as large as it is for those
who are not caregivers (b = .18, p < .05)
35
The odds of having an unmet arthritis/osteoporosis need for caregivers of individuals with disabilities is 2.1 times as large as
it is for those who are not caregivers (b = .74, p < .001)
36
The odds of having an unmet mental health need for privately insured is .6 times as large (i.e., less likely) as it is for those
who are not privately insured (b = -.51, p < .001)
37
The odds of having an unmet dental need for privately insured is .7 times as large (i.e., less likely) as it is for those who are
not privately insured (b = -.34, p < .001)
38
The odds of having an unmet cardiovascular need for privately insured is .6 times as large (i.e., less likely) as it is for those
who are not privately insured (b = -.51, p < .01)
39
The odds of having an unmet vision need for those with a college degree and those with a graduate degree are .81, and .76
times as large (i.e., less likely), respectively, as it is for those with only a high school degree (b = -.22, p < .05; b = -.28, p < .05,
respectively).
40
The odds of having an unmet dental need for those with a college degree and those with a graduate degree are .71, and .59
times as large (i.e., less likely), respectively, as it is for those with only a high school degree (b = -.33, p < .05; b = -.53, p < .05,
respectively).
41
The odds of having an unmet cardiovascular need for those with a graduate degree are .46 times as large (i.e., less likely) as it
is for those with only a high school degree (b = -.77, p < .05).
31

23

•

•
•

Incarcerated community members and community members transitioning back into thecommunity identified a need for greater access to longer term mental health services,
particularly coordination of services.
Community members in addiction recovery reported needing dental repair and/or dentures.
Older adults and youth need prevention services in both mental health and addiction.

Themes from qualitative, secondary, and survey data highlight specific populations within the region
most likely to have unmet needs. All differences reported below (except for qualitative data summaries)
are after accounting for all other demographic variables listed in Table 2.

Males
Younger
individuals
Older
individualsBlack
individuals
Multiracial
individuals
Asian,
AmericanIndian/Alaskan
Native, Native
Hawaiian orPacific Islanderor anotherrace that is not
White or Blackor Multiracial
Active military
Military
veterans
Individuals
without private
insurance
Individuals
withdisabilities
Individuals
with lower
education

Table 2. Populations most likely to have unmet needs among the largest unmet
health conditions in the regions.
AllergyMental Arthritis/
CardioMaternal
Vision Dental
Related
HealthOsteoporosis vascularComplications
X
X
X
X

X

X

X

X

*

X

X

X

X

X
*

X

X

X

X

X
X
X

X

X

X

X

X

X
X

24

Individuals
caring for adisabled
individual
LGBTQ+
individuals
Cincinnati MSA
Dayton MSA

Table 2. Populations most likely to have unmet needs among the largest unmet
health conditions in the regions.
AllergyMental Arthritis/
CardioMaternal
Vision Dental
Related
HealthOsteoporosis vascularComplications
X

X

X

X

*
X

X

*
X

Data source: Regional CHNA community survey
Note. “X” indicates significant, negative effects (i.e., greater likelihood of having an unmet need relative to the reference,such as males compared to females or Black/African American compared to White) from logistic regression analyses. Eachunmet health condition was a separate analysis with the same predictors across all models: gender, age, race, ethnicity,
education, military/veteran status, disability status, private insurance, sexual orientation, and caregiver of an individual witha disability. Thus, all negative effects are after controlling for all other variables in the model. “*” indicates an additional
theme gathered from interviews/focus groups or secondary data, not effects from regression analyses.

Places With Unmet Needs
Differences between subregions were not very common with respect to unmet health needs (i.e., after
accounting for individual demographic differences, there were often not meaningful differences bysubregion). However, two themes emerged.
••

Relative to Dayton MSA, individuals in Cincinnati MSA are significantly more likely to haveunmet allergy needs. 42
Relative to individuals living in Cincinnati MSA, individuals living in Dayton MSA are significantly
more likely to have unmet cardiovascular-related needs. 43

42

The odds of having an unmet allergy need for individuals living in Cincinnati MSA are 1.7 times as large as it is for those living
in Dayton MSA, adjusting for age, sex, race, ethnicity, education level, military status, disability status, and caring for a disabled
person. (b = .29, p < .001).
43
The odds of having an unmet cardiovascular need for individuals living in Cincinnati MSA are .66 times as large (i.e., lesslikely) as it is for those living in Dayton MSA, adjusting for age, sex, race, ethnicity, education level, military status, private
insurance or lack thereof, caring for a disabled person, and sexual orientation. (b = -.42, p < .05).

25

6. SDOH Driving Health in the Region
Only a part of an individual’s health status depends on their genetics and behaviors. Social Determinantsof Health (SDOH) are the structural and social conditions that affect a wide range of health, functioning,and quality-of-life outcomes and risks. xiv In line with Healthy People 2030 SDOH framework, fivecategories of Social Determinants of Health were identified as key drivers of health in this Region (not ina rank order):
•
•
•
•
•

Economic stability
Neighborhood and built environment
Education access and quality
Social and community connectiveness
Healthcare access and quality

As a driving factor of health, strategies to improve health at the community level will need to address
all SDOH.
Different SDOH impact different health conditions (Table 3a) and SDOH are experienced differently
depending on specific people groups (Table 3b) and places (Table 3c) as identified through thecommunity survey (“X”) and the Healthy People 2030 Framework (“+”).
Methods utilized to assess these themes are further explained in the respective SDOH sections below. It
should be noted that the lack of statistical significance in survey analysis does not mean there is not aneed for a particular population group; rather such a need was not detected after accounting for allother demographic variables in the models in the context of the survey sample.
Key Takeaways:• Healthcare access and quality as a SDOH is associated with the largest number of healthconditions, using national Healthy People 2030 data. Using Regional CHNA community survey
data, economic stability factors are associated with the largest number of health conditions,(Table 3a).
• Regional CHNA community survey data shows that Black community members in the region are
significantly more impacted (negatively) in every SDOH when compared to White community
members, followed by community members who identify as Asian, American Indian/Alaskan
Native, Native Hawaiian or Pacific Islander, or identified as another race and community
members with lower levels of education, (Table 3b).
• Regional CHNA community survey data shows that community members in rural counties
reported significantly lower perceptions of their neighborhood and built environment. (Table
3c).

26

Table 3a. Health Conditions Associated with SDOH
Economic
Stability

Allergy
Arthritis
AsthmaDentalDepression
Diabetes
Disability
Heart Disease
Lung Conditions
Maternal
Complications
Mental Health
Obesity
Physical Safety
VisionNeighborhoodand Built
Environment

Education
Access andQualitySocial andCommunity
Connectedness

X
X

+

X

+
+

+
+
+/X
X

+

X
X

X
+

+

+ Data Source: Healthy People 2030
X Data Source: Regional CHNA Community Survey

X

X

X

X

X

X

Table 3b. People Impacted Most by SDOH
Economic
Stability

Sex

Males
Females
Age
Younger Individuals
Older Adults
Race and Ethnicity
Asian, American
Indian/Alaskan Native,
Native Hawaiian orPacific Islander oranother race that is not
White or Black orMultiracial
Black Individuals
Multiracial Individuals
White
Hispanic
Not Hispanic

Healthcare
Access andQuality

Neighborhoodand Built
Environment

X

Education
Access andQuality

X

X
X

X

X

X

X

X
X

X

X

X

Social andCommunity
Connectedness

Healthcare
Access andQuality

X

X
X
X

X
X

X

X
27

Table 3b. People Impacted Most by SDOH

Military Status
Active Military
Military Veterans
Not in Military
Employment Status
Unemployed and Not
Looking for Work
Disabled and Not Able
to Work
Working Part Time
Working Full Time
Specific Populations
Individuals withoutchildren in home
LGBTQ+ individuals
Individuals withdisabilities
Individuals with lower
education
Individuals without
private insurance
Individuals not fluent inEnglishEconomic
Stability

Neighborhoodand Built
Environment

X
X

X
X

Education
Access andQualityX

Social andCommunity
Connectedness

Healthcare
Access andQuality

X
X

X
X
X

X

X
X

X

X

X

X
X

X

X

X
X

X

X

Social andCommunity
Connectedness

Healthcare
Access andQualityX

X Data Source: Regional CHNA Community Survey

Table 3c. Places Impacted Most by SDOH
Economic
Stability

Cincinnati MSA
Dayton MSA
Rural Counties

X

Neighborhoodand Built
Environment

X

Education
Access andQuality

XX

X Data Source: Regional CHNA Community Survey

To provide data-driven guidance on prioritizing populations and interventions to improve health in theregion, primary and secondary data from this Regional CHNA identifies:
1. the health conditions most associated with each SDOH,
2. the people most negatively impacted by each SDOH,
3. and the places in which each SDOH factors are more prevalent.

28

6.1 Economic Stability

According to the research conducted for The Healthy People 2030 framework, economic stability lowers
health risks and can be a protective factor that lowers the impact of other social determinants of healththat one might experience. Poverty, on the other hand, is linked to harsh conditions that puts health atsignificant risk. In this report, economic stability is measured by a scale score of how frequently (on ascale of 1 to 5, 1 being “never” and 5 being “always or almost always”) individuals have had enoughfood, enough money to pay bills, and safe housing in the past year utilizing Regional CHNA community
survey data. Additional survey and secondary data are also used to provide additional context.

Health Conditions Impacted by Low Economic Stability
Nationally, individuals living in poverty are at greater risk of chronic disease and early death. Specifically,studies show that individuals with the lowest income and education levels are at greater risk of heartdisease, diabetes, and obesity. Disability is higher among poor older adults. To assess the impact of
economic stability on health in the region, community members were asked the extent to which theyagreed that they have:
1. Enough money to pay bills
2. Enough food to eat
3. Safe and stable housing
These three variables were turned into a scale score. 44 A higher scale score reflects greater economic
stability; a lower scale score reflects lower economic stability.
Data from the Regional CHNA community survey revealed that people in the region with lower
economic stability are more likely to need treatment for heart conditions, 45 which is consistent with theliterature. Additionally, people in the region with lower economic stability are more likely to reportneeding treatment for lung conditions, (i.e., Asthma, Chronic Obstructive Pulmonary Disease [COPD],
Emphysema, Chronic Bronchitis, or other similar conditions). 46 This may be somewhat explained by the
COVID-19 pandemic and the higher health risk people with low economic stability face with COVID-19 xv
and lung conditions in general. xvi Additionally, individuals with lower economic stability were more likely
to need treatment for maternal complications than community members with higher economic
stability.

Scale internal consistency (Cronbach’s Alpha = .95)
As economic mean scale score increases by one point, the odds of needing treatment for a heart condition
decrease by 5%, adjusting for sex, age, race, ethnicity, frequency of preventive care, healthcare quality scale score,and MSA. (b = -0.05, p < 0.05)
46
As economic mean scale score increases by one point, the odds of needing treatment for a lung condition
decrease by 6%, adjusting for sex, age, race, ethnicity, MSA, frequency of preventive care, healthcare quality scalescore, and education mean scale score. (b = -0.06, p < 0.05)
44
45

29

People Impacted by Low Economic Stability in the Region
To achieve health equity, the region needs to consider the communities and populations within thosecommunities who are most disadvantaged and design strategies to eliminate that disparity. In doing so,
the entire community can attain the highest level of health for all people.
To assess for differences in perceptions of economic stability using a demographic lens, multiple linear
regression analyses were used to determine which members of the community were reporting
significantly lower perceptions of economic stability compared to other community members 47 (see list
below).

Populations Reporting Significantly Lower Economic Stability than their Counterparts

•
•
•
•
•
•
•
•
•

Active-duty military and Veterans relative to non-military people
Black relative to White individuals
Cincinnati MSA relative to Dayton MSA community members
Disabled and not able to work, and those not employed and also not looking
for work relative to full-time employment
Individuals without private insurance relative to those with it
Individuals who do not speak English relative to those who are fluent in it
Individuals with a disability relative to those without a disability
Males relative to Females
Asian, American Indian/Alaskan Native, Native Hawaiian or Pacific Islander or
identified as another race relative to White individuals

Develop strategies to eliminate disparities so that the entire community can attain the highest
level of health for all people.

47

On average, males have an expected economic stability SDOH mean scale score 0.11 less than females, adjusting for all otherpredictors. (b = -0.11, p < 0.05); On average, Black individuals have an expected economic stability SDOH mean scale score 0.30
lower than White individuals, adjusting for all other predictors. (b = -0.30, p < 0.05); On average, individuals who identify as

Asian, American Indian/Alaskan Native, Native Hawaiian or Pacific Islander or another race that is not Black, Whiteor multiracial) have an expected economic stability SDOH mean scale score 0.23 points lower than White individuals, adjusting
for all other predictors. (b = -0.23, p < 0.05); On average, those living in Cincinnati MSA have expected economic stability SDOH
mean scale scores 0.12 lower than those in Dayton MSA, adjusting for all other predictors. (b = -0.12, p < 0.05); On average,
active military and veterans have expected economic stability SDOH mean scale scores 0.68 and 0.35 points lower than those
not in the military, respectively, adjusting for all other predictors. (b = -0.68, p < 0.05), Military veteran (b = -0.35, p < 0.05); On
average, those without private insurance have expected economic stability SDOH mean scale scores 0.20 points lower thanthose with private insurance, adjusting for all other predictors. (b = -0.20, p < 0.05); On average, those who speak no English
have expected economic stability SDOH mean scale scores 0.54 points lower than those who speak English fluently, adjusting
for all other predictors. (b = -.54, p < 0.05); On average, those who are disabled have expected economic stability mean scalescores 0.14 lower than those who are not disabled, adjusting for all other predictors. (b = -.14, p < 0.05).

30

From this list of population groups reporting lower economic stability, the community can begin
prioritizing strategies that will disrupt or overcome the disparities these community members face. In
doing so, collective efforts will have the biggest impact on overall economic stability and improved
health.
Food Security with Specific Community Members
As stated above, food security is part of the economic stability equation. In the primary analysis for thisRegional CHNA, food security was specifically defined as having enough money to buy food and data
were collected from the Regional CHNA community survey. A more complete definition of food security
is having access to enough nutritionally adequate food for an active, healthy life for all household
members. Adequate nutrition is not only needed to be healthy, but it is also critical to the success oftreatment plans. In focus groups and interviews, community members spoke about food in several
different ways. When asked what it means to be healthy, young adults, older adults, parents and Blackand Hispanic youth were the community members that most often identified having enough healthy
food as a key part of being healthy. Youth and young adults in particular spoke to the challenges ofovercoming habits of eating junk food or meals of lower nutritional quality they learned throughout
childhood. According to community members, primary barriers to overcoming unhealthy eating habits
include perceptions that unhealthy foods/foods with less nutritional value are commonly the mostaffordable to buy, available to find, and convenient to prepare; challenges associated with overcoming
taste preferences of high fat/high sugar foods formed as a child/adolescent; and community members’
limited cooking skills and knowledge.
“For some people [poor nutrition and health] is a choice and for others it’s barriers. In some communities
there are food deserts or people who can’t take a long lunch to walk or know that they even should. You
have to think how you are delivering information on healthy eating and living because people won’t hearit the same way. My friend group is super healthy and we influence each other.” - Black Young Adult
Parents in focus groups are concerned that students are not eating healthy food even in school,sometimes due to access to healthy foods and sometimes due to students’ taste preferences. Teachersand school-based healthcare providers also spoke about children being the most impacted by foodinsecurity and to the challenges their schools can have getting food to children in need due to stigma ofreceiving food assistance: “We try to provide meals over the weekends and food is sent home in a big
brown bag but the kids would rather not be labeled and go hungry than walk home with a bag. We
started taking food to the houses so the kids would get the food they need.” Another school-based
provider explained, “We started a food pantry at our school and we delivered groceries to 80 different
families. When we stopped delivering and told them they could come to the school to pick up the food
we only had two families show up to pick up food; the others didn’t want to come.”
Community members identified a need for improving the quality of food provided in
hospitals. In particular, opportunities were identified to improve hospital meals fordiabetic patients, children, older adults, and new mothers. Asian and African
community members recommend looking at postnatal food traditions of their cultures
for ideas of how new mothers can be better supported with nutrition as they wait toreturn home from the hospital.

31

Healthy eating habits are an important element of food security. Community members expressed asentiment that while they know making nutritional/diet changes require self-discipline of their own,
they also identified a need for providers to provide more strategies or supports for community members
to be successful with making diet changes. Community members identified a desire to make dietchanges before turning to medications, when possible, but that they needed help to break negative
eating habits.

Places with Low Economic Stability in the Region
Economic instability is present in communities across the region. Approximately 3 out of 10 community
members in the Regional CHNA community survey self-reported having low economic stability. From theRegional CHNA community survey, low economic stability is most prevalent in Rural Counties and theCincinnati MSA (Figure 3). 48 However, Montgomery County in the Dayton MSA was among the top
three counties in the region for food insecurity in 2018 data from Feeding America. Within each region,
there may be trends in economic stability factors that can help tailor strategies in specific parts of theregion.

Figure 3. Economic Stability

How often do you experience these factors?
% Never or Almost Never to Sometimes
30%
24%
29%

Have safe and stable housing?

34%
29%
34%

Have enough money to pay your bills?

31%
26%
31%

Have enough food to eat?
0%

20%

40%

60%

Data Source: Regional CHNA Community Survey

Rural Counties

Dayton-Kettering MSA

80%

100%

Cincinnati MSA

Places with High Rates of Food Insecurity
Secondary data was used to identify specific counties that may benefit fromprioritized intervention. Figure 4 shows food insecurity by the percent of the
population that lacked access to enough food or had limited or uncertain availabilityof nutritionally adequate foods for all household members in 2018-2019. The data
show that Adams and Highland counties in Ohio have the largest percentage of the
population who are food insecure, both of which are rural counties. Boone County,
KY and Warren County, OH have the lowest percentage of food insecure households which are both in
Figure 3 uses weighted survey data to best estimate what the results would look like at a population level ineach of the three areas of interest.
48

32

the Cincinnati MSA. Child food insecurity is particularly high in Adams County, OH with more than 1 in 4
children living in households that experienced food insecurity (Figure 5). 49 In the United States, anestimated 10.5% of households were food insecure in 2019 which is a decrease from 2018 when an
estimated 11.1% of households were food insecure. xvii

Figure 4. Percent of County Population That is Food Insecure
19%

17%

16%

15%15%15%

14%14%

13%

12%12%12%12%12%12%12%12%12%

11%11%11%11%11%11%

10%

9% 9%

Data Source: Feeding America's Map the Meal Gap 2021 (County Data Table 2019)Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

Figure 5. Percent of Child Population in the County That is Food
Insecure26%

22% 21%

20% 19%19%

18%18%

16%16% 15%15%15%15%15%15%

14% 13%13%13%13%13%

12%12%12%

10% 9%

Data Source: Feeding America's Map the Meal Gap 2021 (County Data Table 2019)Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

Gundersen, C., Strayer, M., Dewey, A., Hake, M., & Engelhard, E. (2021). Map the Meal Gap 2021: An Analysis ofCounty and Congressional District Food Insecurity and County Food Cost in the United States in 2019. Feeding
America.
49

33

County Health Rankings and Roadmaps also provides county-level data on the percent of the populationthat has limited access to healthy foods by estimating the percentage of the population that is low
income and does not live close to a grocery store. 50 Figure 6 shows the region’s access to healthy food,with Clark, OH and Montgomery, OH having 11% and 10%, respectively, of their population experiencing
limited access to healthy food.

Figure 6. Percent of County Population That Have Limited Accessto Healthy Foods
11%

10%

9% 9% 9%8% 8% 8%7% 7%

6% 6% 6%

5% 5%

4% 4%

3%

2% 2% 2%

1% 1%

0%

Data Source: County Health Rankings Food Environment Index, 2015
Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

When it comes to food security, the Supplemental Nutrition Assistance Program (SNAP), provides somerelief for many families. However, according to Feeding America’s “Map the Meal Gap,” in each countyof the region there are significant percentages of the population who are food insecure but do not
qualify for SNAP. Warren County has the highest percentage of the population that is food insecure, but
not eligible for SNAP at 75%, compared to Grant County, the lowest percentage in the region, at 20%(Figure 7). It is important to note that SNAP gross income eligibility threshold in Ohio and Indiana is130% of the poverty line and is 200% in Kentucky. 51

50
As a factor of the Food Environment Index (https://www.countyhealthrankings.org/app/ohio/2019/measure/factors/
133/data) Low Income is defined as having an annual family income of less than or equal to 200% of the federal poverty
threshold for the family size. Living close to a grocery store is defined differently in rural and nonrural areas; in rural areas, itmeans living less than 10 miles from a grocery store whereas in nonrural areas, it means less than 1 mile.
51 Ohio and Indiana offer some nutrition programs for persons earning between 130% and 185% of the poverty line, such as
reduced-price National School Lunch Program and/or Special Supplemental Nutrition Program for Women, Infants, andChildren (WIC).

34

Figure 7. Percent of County Population That is Food Insecure But
Not Eligible for SNAP
75%
62%60%59%59%
58%57%57%56%56%56%
54%52%52%52%
50%48%47%
46%45%44%43%
42%42%41%
35%
20%

Data Source: Map the Meal Gap, 2019Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

In comparing counties in Figures 4, 5, 6, and 7, each MSA in the region has counties that show high andlow food security across measures. This highlights an opportunity for a regional approach to addressing
food insecurity. However, Adams OH, Highland OH, Brown OH, and Clinton OH all rank above theaverage (see Table C1 in Appendix C) in the food security figures. This may suggest a unique opportunity
in these counties for economic stability interventions to improve health outcomes. Further, counties inCincinnati MSA fall on both the high and low ends of economic stability suggesting a wider economic
gap and a need to target interventions based on micro conditions.
Places with High Rates of Housing Instability
Being housing cost burdened is paying more than 30% of income on housing costs. In Census data,
economic instability, as defined by the percent of total households who are housing cost burdened, ismost prevalent in Hamilton, Campbell, Grant, and Butler Counties in Cincinnati MSA and least prevalent
in Ohio County, IN (also within Cincinnati MSA) and Auglaize County, OH which is a rural county (Figure
8).

35Figure 8. Percent of Households that are Housing Cost Burdened
30%

28%28%

27%26%26%26%

25%25%25%25%

24%24%24%23%

22%22%21%

21%21%20%

19%19%19%19%18%

16%

Data Source: American Community Survey, 5-Year Estimates, 2019.
Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

36

6.2 Neighborhood and Built Environment

Health Conditions Impacted by Low Perceptions of the Neighborhood and Built Environment
Environmental conditions include unclean water and healthy air, exposure to toxins including lead andsecondhand smoke; safety including neighborhood violence; unsafe roadways, limited access to spacing
for physical activity, and limited access to broadband or transportation. These conditions are shown to
impact health and safety including asthma, and physical safety (The Healthy People 2030 Framework).
To assess the impact of the neighborhood and built environment on health in the region, community
members were asked the extent to which they agreed that they have:
•
•
•
•
•
•

Stable internet
Stable phone
Clean water
Clean airAccess to parks
Reliable transportation

These six variables were turned into a scale score (while violence in the neighborhood is part of thisSDOH the item was not included in the scale because it did not reflect internal consistency with otheritems). 52 A higher scale score reflects higher perceptions of the neighborhood and built environment; alower scale score reflects lower perceptions of the neighborhood and built environment.

People with Low Neighborhood and Built Environment Stability
To understand which communities are most disadvantaged in the area ofneighborhood and built environment stability, regression analyses, as described in the
Economic Stability section above, were conducted. The Regional CHNA data show thatthe following individuals are significantly more likely to report low neighborhood andbuilt environment stability. 53 Strategies designed to eliminate the disparity for these groups will be
more effective at improving health equity.

Scale internal consistency (Cronbach’s Alpha = .93)
On average, Black individuals have an environment SDOH mean scale score 0.30 points lower than White
individuals. (b = -0.30, p < 0.001); On average, Asian, American Indian/Alaskan Native, Native Hawaiian or Pacific Islander,
or identified as another race that is not Black, White or multiracial individuals have an environment SDOH mean scalescore 0.17 points lower than White individuals. (b = -0.17, p < 0.05); On average, those who are not Hispanic havean environment SDOH mean scale score 0.19 lower than those who are Hispanic. (b = -0.19, p < 0.05); On average,
those with higher education have higher expected environment SDOH mean scale scores than high school
graduates. Some college (b = 0.13, p < 0.001), Bachelor’s degree (b = 0.41, p < 0.001), Graduate degree or higher (b= 0.64, p < 0.001); On average, active military and veterans have environment SDOH mean scale scores 0.49
(active) and 0.20 (veteran) points lower than those not involved in the military. (b = -0.49, p < 0.001), (b = -0.20, p <0.05).
52
53

37

Populations Reporting Significantly Lower Neighborhood and Built Environment
Stability than their Counterparts• Black relative to White individuals• Asian, American Indian/Alaskan Native, Native Hawaiian or Pacific Islander or
identified as another race relative to White individuals• Those who are not Hispanic relative to Hispanic individuals• Older individuals relative to younger individuals• Individuals with a high school degree relative to those with more than a highschool degree• Individuals living in Cincinnati MSA relative to Dayton MSA• Individuals living in Rural counties relative to Cincinnati MSA• Active military and veterans relative to those with no military involvement
The importance of phone and internet access was brought to the forefront of daily life during the
COVID-19 pandemic. Not only was internet access important for education and employment, but also
for telehealth. Access to technology is so important that legislation has been passed in the digital
infrastructure bill to expand access and availability. According to recent Pew Research Center, eventhough more people at lower income levels have adopted technology into their daily lives, the disparity
in digital access persists among low-income households. xviii
Transportation was also identified as a significant barrier in focus groups and interviews. Transportation
is a long-standing barrier. Based on qualitative data, it is specifically a barrier for older adults, families
with children, people with disabilities and anyone needing to access care from multiple locations. The
transportation barrier causes people to be late or miss appointments. In interviews, it was identified
that many clinics have policies related to missed appointments to offset costs to the provider. However,the unintended effect is that families “bounce” between providers, thus undermining any opportunity
for consistent care. Without consistent medical care, issues go undetected and opportunities to address
them are missed. The burden to identify concerns falls to other professionals like teachers and daycare
professionals. However, when these individuals report issues, it can frighten parents and push themfurther away. Transportation barriers can also limit people’s ability to get affordable medications or to
see the provider of their choice. A provider of choice or a pharmacy with the most affordable
medication may be outside of a community member’s ability to travel.

Places with Low Perceptions of their Neighborhood and Built Environment
The quality of neighborhoods is a product of structural racism and impacts
individuals’ health and access to health care. From the Regional CHNA community
survey, low perceptions of the neighborhood and built environment is most prevalentin Rural Counties and the Cincinnati MSA (Figure 9) where about 5 or 6 in 10
community members have low perceptions. About 3 in 10 community members
report never to almost never or sometimes having reliable transportation (Figure 10).
Counties within each region have their own trends, highlighting the need to tailor regional strategies.
38

Figure 9. Neighborhood and Built Environment

To what extent do you experience the following in your household or community?
% Very little to Some
Parks within walking distance

51%
55%

Clean air

38%

48%
44%

Access to clean drinking water

36%
40%

Stable phone connection

38%
41%

Stable internet connection

38%
42%
0%

20%

40%

64%

47%
51%
53%
60%

80%

100%

80%

100%

Data Source: Regional CHNA Community Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

Figure 10. Neighborhood and Built Environment
How often do you experience these factors?
% Never or Almost Never to Sometimes
38%
Have reliable transportation?

25%
34%

0%

20%

40%

60%

Data Source: Regional CHNA Community Survey

Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

Places with Low Internet Connection
Using data from the American Community Survey 5-Year Estimates for 2015-2019, data shows thepercentage of households with broadband internet connection. As shown in Figure 11, the range ofinternet access is from 92% of households in Warren, OH to 64% of households in Adams, OH. On the
low end of the spectrum, we see a quarter or more of the community members living in Ohio, Brown,
Ripley, Highland, and Grant, Union and Adams counties do not have access to the internet.

39

Figure 11. Percent of Households with Broadband Access
92%90%
87%87%86%86%86%85%
84%84%83%83%83%83%82%82%81%
79%79%
76%75%75%75%
71%70%70%
64%

Data Source: American Community Survey, 5-Year Estimates 2015-2019
Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

Places with Daily Exposure to Particulate Matter (Unhealthy Air Quality)
In regard to clean air, the Community Health Rankings also shows average daily density of fineparticulate matter in micrograms per cubic meter (PM2.5) published by the Environmental Public Health
Tracking Network. PM2.5 refers to tiny particles in the air that contribute to haziness. Because they areso small, they can bypass protective factors in your skin and face and lodge deep in the respiratory tract.
Daily exposure to PM2.5 particles is associated with poor lung function (asthma, bronchitis, cancer),heart disease, and allergy-like irritation to the eyes, nose, throat, etc. This is particularly problematic for
those with pre-existing conditions and vulnerable populations like children and older adults. As shown in
Figure 12, 11.6% of community members are exposed daily to unhealthy air in Butler County. This
supports the trend that air quality tends to be better in rural areas and worse in population dense areas
such as Butler County and Hamilton County and communities with a larger presence of manufacturing.

40

Figure 12. Average Daily Exposure to Harmful Particulate Matter(PM2.5)12%
10% 10%

10% 10% 10% 10% 10% 9% 9% 9%

9% 9% 9% 9% 9% 9% 9% 9% 9% 9%

9% 8%

8% 8%

8%

Data Source: Environmental Public Health Tracking Network 2016
Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

Places with Low Access to Parks
Access to parks within walking distance is a challenge in many communities. As shown in Figure 13, inthe region’s most populous cities, about 8 in 10 households live within a 10-minute walk to a park basedon 2020 data. At the other end of the spectrum, not even 1 in 10 households live within a 10-minute
walk to a park (in Boone and Campbell KY). This measure does not factor in perspectives of safety andquality of the park.

“In China and for older people, if you walk every night after dinner you will live to be
99. With the urban lifestyle in USA and modern technology we have excessive
nutrition. We need to exercise more, be more socially active, and more relationallyconnected after dinner. But, if there are not many walkways or older adults don’t feelsafe walking in their neighborhood, then that’s a problem.” - Chinese-American
Community Member

41

Figure 13. Percent of Households Within 10-Minute Walk to Parkby County and Largest City
87%

78%

74%
56%

55%
37%

30%

28%
7%

3%

Data Source: The Trust for Public Land (2020)
Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

Places with Higher Rates of Violence
Community violence is an important part of the discussion when talking about the impact of theneighborhood and built environment on health. Cincinnati and Dayton MSAs have violent crime rates of
312.3 and 282.1 respectively, much higher than that of rural counties at 88.1 (per 100,000; Figure C1 in
Appendix C). In addition to these trends, counties with higher populations, such as Montgomery County
and Hamilton County, often have more segregation (Figure C2 in Appendix C) and higher rates of violent
crime. Hamilton County had a violent crime rate of 468.5, much higher than the state average of 292.6.
On the other hand, counties with smaller populations such as Ripley County and Franklin County, IN
have very low violent crime rates of 29.8 and 36.3, respectively. Nationally, the total violent crime rate is366.7.

42

6.3 Education Access and Quality

Health Conditions Impacted by Low Education Access and Quality
Getting a good education is crucial for gaining employment and a decent paying job. Education alsosignificantly predicts one’s ability to earn a wage that is above poverty levels. Children from underperforming schools and those who are bullied or experiencing other social difficulties are more likely to
struggle in school and less likely to go to college. The risk for depression, heart disease, and diabetes ishigher among individuals without safe, high paying jobs (The Healthy People 2030 Framework).
To assess the impact of education access and quality on health in the region, community members wereasked the extent to which they:
1. Had access to quality childcare
2. Were in close distance to quality schools
These two variables were turned into a scale score. 54 A higher scale score reflects greater education
access and quality; a lower scale score reflects lower education access and quality.
Data from the Regional CHNA community survey showed that people in the region with lower education
access and quality are more likely to need treatment for mental health, 55 which is consistent with theliterature. Additionally, people in the region with lower education access and quality are more likely toreport needing treatment for vision. 56 This is also consistent with other literature in that vision care may
not be prioritized due to barriers such as cost, trust, accessibility, and poor patient-provider relationship.
All of these barriers are barriers to health care in general. xix

People with Low Education Access and Quality
As discussed in the SDOH section above, the Regional CHNA community survey provides data tounderstand who is most negatively impacted by education access and quality in the region. To use ademographic lens for differences in perceptions of education access and quality, regression analyses as
describe in the Economic Stability section above, were conducted. The box below shows the populations
who reported significantly lower education access and quality when compared to other community
members. 57 Note that these effects are significant after adjusting for all other significant predictors in
54 Scale internal consistency (Cronbach’s Alpha = .88)

55 As education mean scale score increases by one point, the odds of needing treatment for a mental health need decreases by

5%, adjusting for sex, age, race, ethnicity, healthcare quality scale score, MSA, environment mean scale score, economic mean
scale score, and social connectivity mean scale score. (b = -0.05, p < 0.05)
56 As education mean scale score increases by one point, the odds of needing treatment for a vision need decreases by 5%,adjusting for sex, age, race, ethnicity, MSA, frequency of preventive care, healthcare quality scale score, environment mean
scale score, and social connectivity mean scale score. (b = -0.05, p < 0.05)
57 On average, females have an expected education SDOH mean scale score 0.12 points lower than males (b = -0.12, p < 0.05);
On average, as age increases by one year, the expected education SDOH mean scale score decreases by 0.02 (b = -0.02, p <0.001); On average, those not involved in the military have an expected education SDOH mean scale score 0.32 points lower
than military veterans (b = -0.32, p < 0.001); On average, those with children in the household have an expected education
SDOH mean scale score 1.02 points higher than those with no children (b = 1.02, p < 0.001); On average, those with a graduate
degree or higher are expected to have an education SDOH mean scale score 0.29 points higher than those with a high school
education (b = 0.29, p < 0.001); On average, those with a disability are expected to have an education SDOH mean scale score0.19 points lower than those who are not disabled (b = -0.19, p < 0.001).

43

the model, as well as age, race, ethnicity, sex, and MSA. Strategies designed to eliminate the education
access and quality disparity for these groups will be more effective at improving health equity.

Populations Reporting Significantly Lower Education Access and Quality than theirCounterparts

Females relative to males
Individuals with lower education relative to those with higher education
Those not working full time relative to those working full time
Individuals not in the military relative to veterans
Families without children in the home relative to families with children in thehome• Individuals with disabilities relative to those without disabilities

•
•
•
•
•

From this list of population groups reporting lower education access and quality, the community canprioritize strategies that address the disparities these community members face. In doing so, collective
efforts will have the biggest impact on overall education access and quality and improved health for all.

Places with Low Education Access and Quality
As shown in Figure 14, over half of the region’s community members who completed the survey
reported low access to quality childcare and about half reported low access to quality schools. Without
access to quality childcare, families not only struggle with maintaining employment and assuring childsafety, they may also struggle to prioritize health care. Nationally, 51% of Americans live inneighborhoods classified as childcare deserts (more than 3:1 children under age 5 provider ratio). xx
Additionally, families who are not close to quality schools are at greater risk of long-term economic
instability which perpetuates health disparity. In addition, schools and daycares are natural places forchildren and families to receive health education, prevention, and intervention. Without access todaycares and schools, the community lacks opportunities to reach children.

Figure 14. Education Access and Quality

To what extent do you experience the following in your household or community?
% Very little to Some
Access to quality childcare

51%
51%

Close distance to quality schools

43%
46%
0%

20%

40%

63%

53%

60%

Data Source: Regional CHNA Community Survey

Rural Counties

Dayton-Kettering MSA

80%

100%

Cincinnati MSA

44

6.4 Social and Community Connectiveness

Health Conditions Impacted by Low Social and Community ConnectivenessAccording to Healthy People 2030 research, there is a need to help people get the support they need to
improve overall health and well-being. This support comes through relationships and having people who
can be depended on to help and to listen. Though the research does not link this SDOH to any specificcondition, it is understood that helpful relationships can reduce the negative impacts of factors that areoutside of a community member’s control, (i.e., discrimination, bullying, having parents who are in jail,etc.)
To assess the impact of social and community connectiveness on health in the region, community
members were asked in the survey how often they:
1. Have family or friends to talk to about health concerns
2. Have someone to talk to about other serious problems
3. Feel connected to their community
These three variables were turned into a scale score. 58 A higher scale score reflects greater social andcommunity connectiveness; a lower scale score reflects lower social and community connectiveness.
In the Regional CHNA community survey data, regression analyses showed that individuals who hadgreater social and community connectiveness were less likely to report needing treatment for mental
health 59 and vision concerns. 60 These results are consistent with other literature demonstrating that
relationships are an important factor of mental health and finding solutions for a range of healthconcerns, including vision.

People with Low Social and Community Connectiveness
The Healthy People 2030 Framework suggests children whose parents are in jail and students who arebullied do not get the support that they need. Similarly, people who are caretakers of a disabled or
chronically ill family member also do not get the support they need. Individuals with disabilities andLGBTQ+ community members face heightened risk of being bullied and not have many people in theirlife that they can depend on for comfort and support.
Across all focus groups and interviews, community members spoke to the loss of social connectivenessdue to the COVID-19 pandemic. In particular, youth and older adults spoke to the negative impact social
distancing and fear of the pandemic has had on their overall well-being. Black community members,
Scale internal consistency (Cronbach’s Alpha = .86)
A one-unit improvement in mean social connectivity scale score is associated with a 14% decrease in the odds ofneeding treatment for mental health, adjusting for sex, age, race, ethnicity, MSA, social built environment mean
scale score, education mean scale score, economic mean scale score, and healthcare quality scale score.
(b = -0.15, p < 0.05)
60
A one-unit improvement in social connectivity mean scale score is associated with a 9% decrease in the odds of
having unmet vision treatment needs, adjusting for sex, age, race, ethnicity, MSA, social built environment mean
scale score, education mean scale score, frequency of preventive care, and healthcare quality scale score.
(b = -0.09, p < 0.05)
58
59

45

both youth and adults, expressed a need for building stronger community connectiveness in order toprotect against the additional stresses of racism, social justice media coverages and campaigns, and thesocial impacts of COVID-19. Additionally, Asian community members spoke to the challenges of being
geographically dispersed throughout the region, making it difficult to build cultural community
connectiveness, especially for older adults in the community.
Again, regression analyses show differences in community members’ perceptions of social andcommunity connectiveness. The box below shows the populations who report significantly lower socialand community connectiveness when compared to other community members. 61 Note that thesesignificant effects are after adjusting for all other significant predictors in the model, as well as age, race,
ethnicity, and MSA.

Populations Reporting Significantly Lower Social and Community Connectiveness thantheir Counterparts

•
•
•
•
•
•
•
•

Non-Hispanic individuals relative to Hispanic individuals
Males relative to Females
Black or Multiracial individuals relative to White individuals
Individuals in active duty or veterans relative to those who are not engaged in
the armed forces
Individuals without private insurance relative to those with private insurance
Individuals with disabilities relative to those without disabilities
Individuals other than heterosexual relative to those who are heterosexual
Individuals living in Cincinnati MSA relative to those in Dayton MSA

Strategies that include addressing SDOH to improve the health of the community should prioritize
populations shown to be experiencing the greatest disadvantage. This analysis identifies community

Hispanic individuals have an expected social connectivity mean scale score 0.32 higher than those who are not
Hispanic (b = -0.32, p < 0.001); Males have an expected social connectivity mean scale score 0.08 lower thanfemales. (b = -0.08, p < 0.05); Those who have a bachelor’s degree have an expected social connectivity mean scalescore 0.25 points higher than high school graduates. (b = 0.25, p < 0.001); Those who have a graduate degree orhigher have an expected social connectivity mean scale score 0.47 points higher than high school graduates.
(b = 0.47, p < 0.001); Black individuals have an expected social connectivity mean scale score 0.26 points lower
than White individuals. (b = -0.26, p < 0.001); Multiracial individuals have an expected social connectivity mean
scale score 0.19 points lower than White individuals. (b = -0.19, p < 0.05); Individuals living in Dayton MSA have an
expected social connectivity mean scale score 0.09 points higher than those in Cincinnati MSA. (b = 0.09, p < 0.05);
Active military members have an expected social connectivity mean scale score 0.39 points lower than those not
involved in military. (b = -0.39, p < 0.001); Military veterans have an expected social connectivity mean scale score0.15 points lower than those not involved in military. (b = -0.15, p < 0.05); Those with a disability have expectedsocial connectivity mean scale scores 0.09 points lower than those without a disability. (b = -0.09, p < 0.03); Those
without private insurance have an expected social connectivity mean scale score 0.16 points lower than those withprivate insurance. (b = -0.19, p < 0.001); Those who are not heterosexual have an expected social connectivity
mean scale score 0.13 points lower than those who are heterosexual. (b = -0.13, p < 0.05).
61

46

groups who are at a greater social and community connectiveness disadvantage when it comes to healthoutcomes.
Places with Low Social and Community Connectiveness
From Regional CHNA community survey data, we see that about half of the community members livingin the region “never or almost never” or “sometimes” feel connected to their community. About 3 in 10
community members report “never or almost never” or “sometimes” having someone to talk to aboutproblems or health concerns (Figure 15). Social connectivity seems to be an opportunity across theregion with the largest proportions feeling never or almost never connected to their community. This isalso the case nationally. In national studies, about 4 in 10 U.S. community members reported feelings ofisolation and lack of meaningful connectedness to their community. xxi

Figure 15. Social and Community ConnectivenessHow often do you experience these factors?
% Never or Almost Never to Sometimes
47%
51%
51%

Feel connected to your community?
Have someone to talk to about other serious
problems?

37%
31%
38%

Have family or friends to talk to about healthconcerns?

28%
0%

20%

35%
37%

40%

60%

80%

100%

Data Source: Regional CHNA Community Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

Additional Social Factors
Adverse Childhood Experiences
Additionally, adverse childhood experiences (ACEs) are also a determinant of health. Exposure to trauma
from an early age disrupts the development of a young person’s brain, ultimately leading to higher rates
of chronic disease, mental illness and early death if appropriate interventions and protective factors
are not present. Preventing ACEs is a health strategy to improve health outcomes xxii but requires
collective impact strategies with other systems of health and human services within communities.
Looking at state-level data from 2018-2019, Ohio, Kentucky, and Indiana all fall under the nationwide
estimated percentage of children with zero ACEs (CAHMI 2019). Kentucky is furthest from thenationwide average of 60.2%, with an estimated 54% of children having experienced zero ACEs. Thereare clear disparities when breaking down these numbers by race in each state. Generally, White (nonHispanic) children experience the fewest ACEs in each state, compared to those who are Black (nonHispanic), Hispanic, and other (non-Hispanic). The proportion of Black and Hispanic children
experiencing two or more ACEs is considerably higher in Ohio compared to Indiana and Kentucky, with35.0% of Black children in Ohio experiencing two or more ACEs and 33.5% of Hispanic children
experiencing two or more ACEs. Kentucky has a noticeably higher proportion of children identifying as
47

another race, other than White, Hispanic, or Black, experiencing two or more ACEs with 41.8%. Rates of
exposure to ACEs also differ based on income, disability, and other demographic factors; for example, ina 2020 study of LGTBQ+ individuals, 43% reported four or more ACEs and patterns of ACEs were higher
in nine of ten categories when compared to national samples. xxiii The top three ACEs reported from state
Behavioral Risk Factor Surveillance System data are indicated below (Table 4); these indicators are, ineach state, elements to note in addressing poor health outcomes related to ACEs.
Table 4. Top Three Reported ACEs Among Adults, by State
Ohio xxiv
Indiana xxv
First
Emotional Abuse (57%) Divorce or Separationof Parents (32%)
SecondHousehold SubstanceEmotional Abuse (30%)
Abuse (41%)
Third
Divorce or Separation
Household Substanceof Parents (36%)
Abuse (28%)

Kentucky xxvi
Divorce or Separationof Parents (32%)
Household Alcohol
Abuse (27%)
Verbal Abuse (26%)

Without addressing SDOH, community members will continue to experience healthcare
access and quality barriers, perpetuating disparity in health outcomes.

48

6.5 Access to Quality Health Care

Health Conditions Impacted by Low Health Care Access and Quality
Getting timely, high-quality healthcare services is key to improving the health of our communities but
not everyone has this kind of access. Not having insurance, a primary care physician, reliable/goodcommunication with healthcare providers or living too far away from a healthcare center can lead tolack of preventive care and greater risk of chronic disease.
To determine if access to quality health care was driving any specific health conditions in the region,
health quality was assessed based on the response to the question, Overall, how would you describe thequality of health care you typically receive? Community members rated the quality of health care as
poor, fair, good, very good, or excellent.
In several different logistic regression analyses looking at treatment need for disease, an increase(improvement) in quality of health care was associated with a decrease in odds of needing treatment formental health, 62 heart conditions, 63 arthritis, 64 and lung disease. 65 Analysis also showed that for an
increase of one unit in perception of quality health care, the odds of having unmet needs related tovision, 66 dental, 67 and allergy 68 concerns also decreased.

A one-unit improvement in quality of health care scale score is associated with a 9% decrease in the odds ofneeding treatment for mental health, adjusting for sex, age, race, ethnicity, MSA, social built environment mean
scale score, education mean scale score, economic mean scale score, and social connectivity scale score.
(b = -0.09, p < 0.05)
63
A one-unit improvement in quality of health care scale score is associated with a 15% decrease in the odds ofneeding treatment for heart conditions, adjusting for sex, age, race, ethnicity, MSA, economic mean scale score,and frequency of preventive care. (b = -0.15, p < 0.05)
64
A one-unit improvement in quality of health care scale score is associated with a 29% decrease in the odds ofneeding treatment for arthritis, adjusting for sex, age, race, ethnicity, MSA, economic mean scale score, andfrequency of preventive care. (b = -0.35, p < 0.001)
65
A one-unit improvement in quality of health care scale score is associated with a 19% decrease in the odds ofneeding treatment for lung disease, adjusting for sex, age, race, ethnicity, MSA, education mean scale score,economic mean scale score, and frequency of preventive care. (b = -0.21, p < 0.05)
66
A one-unit improvement in quality of health care scale score is associated with a 14% decrease in the odds of
having unmet vision treatment needs, adjusting for sex, age, race, ethnicity, MSA, social built environment mean
scale score, education mean scale score, social connectivity scale score, and preventive care frequency.
(b = -0.16, p < 0.001)
67
A one-unit improvement in quality of health care scale score is associated with a 24% decrease in the odds of
having unmet dental treatment needs, adjusting for sex, age, race, ethnicity, MSA, social connectivity scale score,and preventive care frequency. (b = -0.28, p < 0.001)
68
A one-unit improvement in quality of health care scale score is associated with a 16% decrease in the odds of
having unmet allergy treatment needs, adjusting for sex, age, race, ethnicity, MSA, and social connectivity scalescore. (b = -0.18, p < 0.001)
62

49

People with Low Healthcare Access and Quality
To determine who is impacted by low healthcare access and quality, the Regional CHNA looked at thedifferences in quality perceptions based on demographic characteristics using a logistic regression. The
box below shows the populations who are significantly more likely to report lower health care accessand quality compared to other community members. 69 Significant predictors seen
below are adjusting for all other significant predictors as well as age, sex, ethnicity,
race, and MSA. This analysis identified the specific populations within the communitythat are experiencing greater disadvantages in the area of healthcare access andquality.

Populations Reporting Significantly Lower Quality Health Care Experiences than theirCounterparts• Black or Asian, American Indian/Alaskan Native, Native Hawaiian or PacificIslander or identified as another race individuals relative to White individuals• Individuals with disabilities relative to those without disabilities• Individuals with lower education relative to those with higher education• Individuals who are younger relative to those who are older• Individuals without private insurance relative to those with private insurance• Individuals who care for a disabled individual relative to those who do not

As age increases by one year, the odds of rating one’s healthcare experience as good to excellent increases by
4%. (b = -0.04, p < 0.05); The odds of rating one’s healthcare experience as fair or poor for those with less than ahigh school education and those with some high school education are 2.15 (no high school) and 1.58 (some highschool) times that of high school graduates. (b = 0.77, p < 0.05), (b = 0.46, p < 0.05); Black individuals have 61%
higher odds of rating their healthcare experience fair/poor relative to White individuals. (b = 0.48, p < 0.05);
Individuals who identify as Asian, American Indian/Alaskan Native, Native Hawaiian or Pacific Islander or anotherrace that is not Black, White or multiracial have 62% higher odds of rating their healthcare quality fair/poor thanWhite people. (b = 0.48, p < 0.05); Individuals with a disability have 51% higher odds of rating their healthcare
fair/poor than those without a disability. (b = 0.42, p < 0.001); Those with private insurance have 28% lower odds
of rating their healthcare fair/poor compared to those without private insurance. (b = -0.32, p < 0.05); Those caring
for a disabled person have 81% higher odds of rating their healthcare quality as fair/poor compared to those notcaring for a disabled person. (b = 0.59, p < 0.001).
69

50

Places with Low Access to Quality Health Care
The majority of community members in the rural counties and MSAs perceive the quality of health care
to be “very good” or “excellent,” (Figure 16).

Figure 16. Quality of Health CareHow would you describe the quality of health care you typically receive?
Rural Counties (m = 3.9)

7%

Dayton-Kettering MSA (m = 4.0)

6%

Cincinnati MSA (m = 3.9)9%0%Poor/Fair

25%

67%

24%

71%

25%
20%
Good

67%
40%

60%

80%

Data Source: Regional CHNA Community Survey

100%

Very Good/Excellent

Having access to quality health care is a protective factor for preventing or minimizing chronic and lifethreatening conditions and preventing hospitalizations. When quality health care is readily available,community members can get the help they need before the health concern becomes an acute problem.
The County Health Rankings published the preventable hospital stays data using the Mapping Medicare
Disparities Tool for 2018. Preventable hospitalization are admissions for acute or worsening conditions
that could be managed successfully in an outpatient setting. As shown in Figure 17, Adams County, OH
has the highest rate of preventable hospitalizations and Darke County, OH has thelowest. Additionally, in interviews, it was noted that geographic location andavailability of services from healthcare systems is highly influential to preventable
hospitalizations. However, despite the density of health care in the region,community members are still going to the hospital for reasons that are preventable.
This lends itself to the need for prevention services outside of the hospital.

51

Figure 17. Preventable Hospitalizations(per 100,000 Medicare Enrollees, 2018)
7,070
5,877

5,151

4,595

4,456
3,504

Data Source: Medicare Disparities Tool: Rate of Hospital Stays for Ambulatory-Care
Sensitive Conditions per 100,000 Medicare Enrollees, 2018
Blue = Cincinnati MSA, Yellow = Dayton MSA, Gray = Rural Counties

Barriers to Accessing Quality Health Care According to Region’s Community Members
Many barriers to a healthy life and to health care that were identified by community members (outlined
below) align with SDOH-related barriers discussed above. While the following barriers to health care arewidely known by providers throughout this region, the list of barriers below were identified bycommunity members who participated in this Regional CHNA. Significantly, community members
identified SDOH-related barriers without being prompted to discuss SDOH.
Community members identified experiences related to information accessibility and service
availability; affordability and health insurance; and feeling unsafe and having negative pastexperiences as barriers to accessing quality health care when they need it. Exemplary quotes and survey
results from community members are shared below to provide insights into experiences related to eachbarrier. For a more detailed discussion of each barrier, please see Appendix C.

According to community members, to have accessible health care is to have confidence that,when needed, community members will know what services are available, where to findthem, will not have cause to fear seeking them, and will not suffer social stigmatization or
economic debt for using them. To have accessible health care is to be able to receive physical,
mental, and spiritual support in order to live a holistically healthy life.

52

Information Accessibility and Service Availability•

A Lack of Centralized, Up-to-Date Information on Healthcare Services and Providers.
Community members reported that the lack of a centralized resource for healthcare service
information also means there is a lack of a centralized resource for local public healthinformation that is trusted.

“People don’t know what is available, what their options are. I don’t know how tofind a good family doctor that will listen. I don’t know where I need to go or where I
need to point myself.” - Adult Community Member, Social Service Provider“We have a list of providers who are supposed to help us, but when we call it’s adifferent story- especially dental. Either they don’t give services to us anymore or they
don’t take my insurance anymore. The resources we get are not up-to-date.”- Woman in Recovery Housing•

A Limited or Lack of Access to Culturally and/or LGBTQ+ Competent
Healthcare Professionals. Black community members in focus groups
expressed feelings that “my doctor doesn’t listen to me.” Asian and Hispanic
community members expressed feelings of not being understood in regard toculture and language. Community members across all focus groups expresseda feeling that healthcare professionals do not know about or understand theimpact of community members’ past experiences or traumas. In focus groups, Black and Muslim
adults expressed a feeling of disempowerment at hospitals during delivery of their baby, feeling
little power to advocate for their needs [for a female doctor to deliver the baby] or fearing abacklash when they do advocate for themselves or a loved one. Misgendering and obtaining
gender-affirming prescriptions and treatments are priority issues for health care among the
LGBTQ+ community. When community members do not feel heard theyreported being more hesitant to trust a diagnosis, to follow treatment plans,
and/or to attend future healthcare appointments, according to focus groups.
This also extends to a lack of mental health care providers that share lived
experiences with community members, like first responders, veterans,
military family members, survivors of human trafficking, etc.

“Another thing I’ve noticed is many providers simply look at the skill sets of the interpreter… It’s very
important to have interpretation that does not just interpret the language but who also has the ability
to understand the cultural context of the patient.” - Asian Community Member, Medical Physician“There needs to be more women counselors. I’ve been waiting… Most civilians don’t have a clue what
it’s like to be in the military. I would choose a female non-veteran over a male veteran psychologist,
though.” - Woman Veteran Community Member53•A Limited Number of Service Appointments and Appointment Times. About 1 in 3 Regional
CHNA community survey respondents across the region report having to wait a long time in a
waiting or exam room and/or not being able to make an appointment for health care because
appointments were not available after work hours or during weekends (Figure C3). The limited
open appointments is even greater for transgender specialists, LGBTQ+ specialists, and minority
providers in general.

“When a person needs mental [healthcare] they don’t need help 9 to 5. Crises happen
at night a lot. So, like when you go to the ER and are having a heart problem, theygive you help right there. We need the same thing with mental health. Treatment isneeded right now. [Healthcare professionals] also need to meet people where they
are at, not requiring them to get to an office. I had to send someone to Columbus[from Dayton] so they could get services right away. We didn’t have anything in ourcommunity that could help them right away.” - Peer Supporter“I used Google and found a dentist who took my insurance, [but] it was schedulingmonths in advance.” - Woman Community Member Experiencing Homelessness

Affordability and Health Insurance•

Limited or Lack of Financial Resources to Pay for Healthcare Service.
Upwards of one in five Regional CHNA community survey respondents acrossthe region reported not being able to afford their medications and/or toafford to go to the doctor (Figure C7). In focus groups, community members
reported the unknown cost of a healthcare service (e.g., a “surprise medicalbill”) made them avoid seeking health care even when they knew theyneeded care.

“The healthcare worker said she made a few dollars too much to qualify for thepoverty discount but she didn't make enough money to pay for the surgery out of
pocket. She has the same problem for paying for prescriptions…” - Hispanic
Community Member speaking about experiences of women in her community“There are places where they will get your teeth pulled but you can’t find anyone
anywhere to help pay for dentures.” - Community Member in Addiction Recovery

54•

Limited or Lack of Transportation. This also includes commutes being too long (in distance, intime, or both), even when individuals have access to a personal vehicle or public transportation.

“I am legally blind. Having access to providers and even going to the store requires
access to home aides who can provide transportation. Even being able to use atelephone is hard… A month ago, I saw a specialist and I was disappointed because it
was rushed. I didn’t get what I needed and now I’ll need to go back.” - Community
Member with a Disability“I don't like to drive to where my family doctor is... If you use the county transit, they
will only take you in the county, and then when you're done with your appointment,
you have to sit there and wait on their discretion to come back and get you.” - Older
Adult Community Member•

Limited Experience Navigating Healthcare and Insurance Systems. Community members infocus groups explained they only learned how to navigate the healthcare system only after
negative and/or expensive experiences. Healthcare and insurance systems need to provide
more accessible information and tools for community members (young adults to older adults) tofind health care they need and to make the costs of health care transparent.
There is a need for healthcare systems to empower community memberswith the tools and skills to be informed of what insurance plans cover, how to
anticipate costs, what Medicare options exist for those who do not qualify for
Medicaid, and what financial assistance is available directly through theprovider.

“I would like to have a little more education about how the health system works here.
I thought I was a healthy young person and didn’t think I needed a doctor then I got
shingles and had to go to the ER doctor...” - Asian Community Member“What can be done to help get health care to the community? Hire a liaison that thecommunity trusts. Help them navigate insurance.” - Male Community Member“If there was a guide – as a starting point – you need to ask your doctor about thisand this. Most people don’t know what they don’t know…” - Caretaker for Veteran55

Feeling Unsafe and Having Negative Past Experiences•

Perceptions that Healthcare Providers Care More About Money. Community members in eachregion of this Regional CHNA perceive that the healthcare system does not have the bestinterest of community members in mind (Figure C8). Across focus groups, community members
spoke about healthcare providers, hospitals, clinics, pharmacies, insurance companies, healthdepartments, etc. as a single system that generally favors profit over what is best for patients.

“[Healthcare professionals] can’t treat it as just a job. They need to treat people aspeople. This is not just a job... Some operate like “I need a check” vs. “I want to helpyou.”- Male Community Member•

Feeling Unsafe in Receiving Care. In Regional CHNA community survey data, 7%-15% of
respondents across the region reported feeling unsafe in the location of a healthcare facility(Figure C9). Community members have also avoided health care due to fear of contracting
COVID-19; 18%-32% of survey respondents felt unsafe receiving health care due to COVID-19(Figure C9).

“Volumes remain high in emergency departments. Not due to COVID patients, but its
fallout of not managing health over the past year…. We need more effort to tell the
public that it is safe to seek health care in the ER.” - Emergency Room Physician.

•Experiences of Discrimination when Receiving Care. In Regional CHNA community survey data,
7%-14% of respondents across the region reported experiences of discrimination in health caredue to their race, culture, gender, and/or sexual orientation (Figure C11). As community
members generally perceive all healthcare institutions as a single system, a single experience of
discrimination or personal experience of someone they know, perpetuates a negative
perception of all healthcare institutions and healthcare professionals.

“Recently I took my son to get a checkup and the doctor was kind of rushing. I don’tknow if he was just busy or was uncomfortable with people who don’t look like him. I
was concerned about the result- he said my son was okay and we went home and myson continued to have a hard time so we went back and another person who tooktime with us saw that my son had an ear infection… you can’t help but feel like thedoctor rushed out because of how we looked.” - Muslim Community Member

56

•Fear of Judgement In general, when community members spoke about feeling judged, it went
hand in hand with healthcare professionals “talking down” to community members. In Regional
CHNA community survey data, 11%-16% of respondents across the region reported avoiding
health care for fear that the healthcare professional will judge them (Figure C8). In focus groups,
community members in recovery, homeless community members, and incarcerated/justiceinvolved community members specifically reported feeling judged bymental healthcare providers. Community members who are caretakers offamily members also describe experiences of being undermined byphysicians, with caretakers’ intimate knowledge of their family members’
symptoms being dismissed by treatment teams of healthcare professionals.

“When [people of color] go to the hospital and see the wall portraits of White, oldermen [former hospital presidents/CEOs] it sends the message that ‘this place is not forme’.” - Community Health Advocate

57

7. Societal Systemic Barriers to Improving Overall Health ofCommunity Members
Without interventions, community members experiencing health-related risk factors like economic
instability, social isolation, low healthcare access, and/or ACEs (e.g., SDOH-related risk factors) are at
greater risk of poor health and limited to no access to the quality of health care they need. SDOHrelated risk factors discussed in Section 4 of this report are rooted in various social, political, andeconomic structures. Analyzing survey, interview, and focus group data, three such structures stand out
as key barriers to addressing the region’s health disparities and overall health outcomes according to theregion’s stakeholders.
These structures include systemic racism; profit-driven design of America’s healthcare system; and thestructural division of medical care, healthcare providers who share patient’s/client’s cultural backgroundor gender, and social services that work to mitigate the negative impact of SDOH-related risk factors.
These structural barriers are driving disparity in access to health care, quality of health care, healthrelated behaviors (such as not seeking care) and disparities in health conditions (see above sections) andSDOH.
The following sections summarize these three structural barriers to improve health and quality healthcare in the region. In turn, these sections highlight structural barriers that require change in order topromote sustainable improvements to the health disparities of the region, to the overall health ofcommunity members, and to the quality of health care in the region.

Structural Racism
Based on the thematic analysis of focus group, interview, and survey data, it could be determined thatstructural racism drives barriers related to lack of culturally relevant health care, diversity in theworkforce, and a divided healthcare system.
Community members and providers identified a lack of culturally relevant health care and a lack ofdiversity in the workforce among healthcare professionals. These shortages are rooted in structural
racism that drives K-12 education disparities in Black and Hispanic communities, lowering the number ofminorities prepared to pursue higher level healthcare professions. In turn, there is a shortage ofhealthcare professionals who themselves are Black and/or Hispanic and/or female. The lack of diversity
going into healthcare professions further perpetuates a medical/clinical education curriculum that lackan equity lens and insufficient training in culturally relevant health care and cultural sensitivity. Even
more, leadership in healthcare institutions in the region are lacking in the implementation of Diversity,
Equity and Inclusion (DEI) best practices.
Structural racism is also a cause for distrust in the healthcare system among Black
community members. Lived experiences of racism can also influence a community
member’s perception of the health care they receive. For example, the data showsthat the “15-minute appointment” medical professionals’ schedule drives
perceptions of low healthcare quality across community groups. However, for Black
community members with lived experiences of racism, these short appointments canbe internalized as a disregard for their health and leading to demotivation to continue to seek healthcare. A community member explained, “My wife and I are Black. We are Muslim. When she was58

pregnant we went to the doctor. He spent maybe 15 minutes with us. I don’t know if he was
uncomfortable with us being Muslim or my wife’s headscarf, or what. But he rushed in and out of ourappointment.”“Health systems don’t make disaggregated data public and there is no public facing
dashboard showing data of quality when it comes to care for diverse andmarginalized populations. NOT moving towards a system that is more transparent isa barrier.” - Hospital Administration Expert

America’s High-Cost Healthcare System
America has the highest cost of healthcare per capita among developed countries. xxvii Community
members in focus groups agree that the high cost, in particular the unknown cost, of health care is amajor reason why they do not seek health care even if they think they need it. The fear of “surprise”
medical bills and medical debt is not unfounded, with an average of 19% of community members in theregion reporting medical debt in collections in 2020. Of total medical debts in collections in Hamilton
County, 25% is in communities of color, compared to 14% in majority White communities of the county.
Similar trends are also measured in Montgomery County, where 30% of medical debt collections is incommunities of color, compared to 18% in majority White communities. 70
The cost of health care not only limits access to health care, but it also drives what treatment or healthcare is provided. Many community members in focus groups agree that healthcare professionals are
more likely to prescribe a treatment plan that is most profitable over a treatment plan that is mostbeneficial to the health of the patient. On the other hand, healthcare professionals feel limited too, attimes feeling the treatment plan is restricted by what a patient can afford, rather than research-based
best practices. Health professionals are forced to ask what is the best action for care within the range ofaffordability? At the same time, community members must ask what financial crisis will going to adoctor to check on a symptom spark?

The Structural Divide of Holistic Health Care
Overall, community members need physicians, clinicians, hospitals, etc. to be in better coordination withholistic wellness programs and social services. Social services and culturally based holistic wellness
programs can help community members overcome barriers to accessing quality health care anddecrease risk factors. Few healthcare professionals reported having caseworkers on-site to directly
connect patients to social services. Social workers are increasingly being made available in emergency
departments and some emergency response units. However, social workers are not in healthcare offices
and clinics.

https://apps.urban.org/features/debt-interactivemap/?type=overall&variable=pct_w_medical_debt_in_collections
70

59

The barrier providers face is the historical division between the healthcare system, holistic wellness
providers, and social service providers. Between social, holistic, and healthcare systems, providers do
not know what services are provided, the benefits of those services, or how to advise community
members to access services outside their own system. Furthermore, healthcare
providers are reporting limited coordination with social service agencies, as well as
limited screening of patients for needed social services. Overall, public transportationand social service providers identified the opportunity for healthcare
providers/professionals to be a better partner in the coordination of care by initiating
contact with community-based and social service organizations that address barriers
to healthcare access.

Demographics and Geographic Areas Uniquely Impacted by Structural Barriers
Though structural barriers permeate every community, the needs assessment results show that specificcommunities are more likely to agree that structural barriers are impacting their healthcare access andquality. Table 5 below summarizes specific focus group populations who discussed being negatively
impacted by these structural barriers.
Table 5. Demographic Groups and Subregions Negatively Impacted by Structural Barriers
Distrust

Low income
Older Adults
Community
members witha disability
Incarcerated
ortransitioning
back into
communityBlackcommunity
members
Immigrant
community
members
AcrosscommunitygroupsCincinnati
MSA
Dayton MSA*

High Cost
Lack of(including
Diversity inservice,
workforcetreatment,
transportation)

Lack of
Culturally
Relevant
Health Care**

Lack of
Coordinationof Health andSocial Services

*
*
*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*

*
60

Table 5. Demographic Groups and Subregions Negatively Impacted by Structural Barriers
Distrust

Rural Counties

High Cost
Lack of(including
Diversity inservice,
workforcetreatment,
transportation)*

Lack of
Culturally
Relevant
Health Care

Lack of
Coordinationof Health andSocial Services**

Data Source: Focus Groups
The absence of an * does not mean that the community does not face the specific barrier. The

absence of an * means the barrier was not specifically discussed by that population in focus groups.

61

8. Healthcare System’s Structural Barriers to Improving Quality of
Health Care
Some governing policies within the region’s healthcare system diminish community members’ access toneeded services and decrease the quality of care provided. According to qualitative data, when acommunity member perceives a healthcare encounter/service to be of high quality, they are:• More likely to trust the opinion of the healthcare professional and follow through on treatment
plans• Less likely to put off seeking health care in the future• More likely to recommend healthcare services to family/friends.
In focus groups and interviews, community members were asked to describe a quality healthcare
experience they have had and to describe what could have made a poor health care more effective,
relevant and of higher quality. From their responses, seven types of community needs emerged that
range from a need for more time with healthcare professionals to a need for greater transparency of thecost of care (see Table 6 below).
Additionally, healthcare professionals were interviewed and surveyed in order to assess the barriers
providers face in meeting community needs and in improving the quality of care. Table 6 links
community needs to the barriers most commonly identified by healthcare professionals. Furthermore,
Appendix D provides a summary of policies and practices recommended by social service providers andhealthcare professionals in order to overcome the identified barriers.

Community Perspective on Opportunities to Improve Quality of Health Care
According to community members, a quality healthcare encounter ensures that a patient/community
member:•Is provided enough time (30+ minutes) to speak with their physician/clinician. “My doctors arealways rushed. It’s only 15 minutes to get to know me. They don’t know my life,” explains a
community member. Repeatedly, when asked to describe a quality experience with a healthcare
professional, community members were brought to tears as they described the amount of timea physician spent with them talking about a diagnosis, a treatment plan relevant to their everyday circumstances, or just getting to know them better. Increasing time talking about diagnoses
with community members was also associated with lowering individuals’ fears about returning
for follow-up care, even if community members know there might be a health condition
identified.

•Feels “heard” by their physician/clinician. Community members feel heard
by their healthcare professionals when health care is culturally relevant and istrauma informed.

•

Is provided the range of treatment options by their physician/clinician, including both medical
and non-medical options and the pros/cons of options in terms of overall health. Community
members want to trust their healthcare provider is presenting all the options, even if some62

options require the patient to go to a different provider or service, such as yoga, mindfulnessclasses, etc. Across focus groups, community members identified a need for more information
on how the healthcare system works in order to be able to advocate for themselves, particularly
among low-income community members and individuals new to having health insurance.
•

Is not sent a “surprise” medical bill. Community members were satisfied with healthcare
services when they knew the cost upfront, even when it was a more expensive service.
Community members are more satisfied when financial assistance policies are also provided
upfront. When these policies are not made known to community members, their trust in thehealthcare system declines and the perception that healthcare professionals are more concerned
about making money than patient health increases.

•

Is immediately connected to a follow-up service before leaving the site of service. This includes
coordination of prescribed medical services and social services needed to improve access tohealth care. Community members in focus groups who had met with social workers at thedoctor’s office/hospital, or a healthcare staff member that helped to arrange transportation,
were most satisfied with their healthcare service overall. In general, when social services toovercome access barriers to health care are coordinated in/through physician offices/hospitals,
community members perceived those healthcare professionals as ones whocare about putting the health of patients before profit. Overall, community
members need physicians, clinicians, hospitals, etc. to be in better
coordination with social services and community-based providers of holistic
health programming (i.e., yoga studios, outdoor recreation, community
connectedness activities, cultural events).

•

Is informed of prescription medication options (i.e., pros, cons, and side effects) at the time ofa healthcare service, not at the pharmacy. Community members want to trust that healthcare
professionals are offering non-medicated options before going to medication. Community
members find health care to be of higher quality when they are able to consider other aspects of
their lives when determining what medication might be the best option for them.

•Has the ability to make an informed choice on who their healthcare professional is, including
having access to gender-, race-, and skill level- specific physicians/clinicians. When community
members feel as if they cannot relate to their healthcare provider, and vice versa, they have apoor healthcare experience that impacts how community members perceive other healthcare
professionals. Being able to relate to a healthcare professional’s gender, race or lived experience
was also identified as key to community members’ sense of feeling safe.

Region’s Systemic Barriers Faced by Healthcare Professionals to Improving Quality Care
While the region’s healthcare professionals may not have singular power to change structural barriers,
there are governing policies within the region’s healthcare system that hinder healthcare professionals’
capacity to meet the needs of their communities. Through interviews, focus groups and surveys,
healthcare professionals were asked to identify the policy and other barriers they face to meeting63

community needs and to improving the quality of care. Theming for barriers rooted in the region’s
healthcare system (e.g., barriers that result from policies or circumstances in which the region’s
healthcare stakeholders control or have influence over), as opposed to structural barriers (see Section8), healthcare professionals identified four types of barriers to improving quality of health care to meet
community needs.
•

High caseloads and the increasing number of administrative tasks required of healthcare
providers are producing knowledge gaps in medical best practices, cultural needs of patients,and lack of time to practice continuous learning. Rural healthcare providers face limited accessto specialists and “beds” in emergency departments and some hospitals. Workloads are limitingtime spent with patients, decreasing the capacity to provide care coordination or screening ofother environmental conditions, basic needs, or social needs that promote positive healthoutcomes. Workloads are limiting time for continuous education and the implementation ofbest practices. They are also increasing stress among providers and decreasing providers’ jobsatisfaction.

•

The region’s healthcare institutions are competitors from a business perspective. Competitionis also driven by competitive grant structures. Each organization has its own funding structuresand service priorities that cause competition, not collaboration, with other providers.
Healthcare-providing organizations are competing for a relatively small pool of skilledemployees, struggling to fill staff vacancies at all levels and to diversify professional staff. This isrooted in a lack of pipeline infrastructure to expose community members to the variety ofhealthcare career tracks and the delay in availability of training programs (staffing/specialty
needs not known before they are needed, takes time to develop certification curriculum andstandards). Providers in Dayton are more likely than providers in other regions to report a
shortage of nurses as a barrier (69% relative to 56% in Cincinnati and 57% in rural counties) andhaving limited time to visit/follow-up with patients due to heavy caseloads (65% relative to 56%
in Cincinnati and 53% in rural counties). According to healthcare professionals, competition for
attracting community members and new staff stymie the capacity for organizations to
implement emerging best practices.

•

Healthcare providers’ lack of knowledge of, and investment in coordinated efforts with,
SDOH-related social services. Successes in coordinating care are the result of “star” staff going
above and beyond, or have high inter-agency social networks, not the result of the system itself.
Healthcare organizations do not share data, which ultimately harms community members as
there are not coordinated efforts to address SDOH or outcomes of services provided forcontinuous improvement purposes. There is a lack of effective linkages between health care,mental health care and community-based service providers that lead to poor health outcomeseven when health care is accessed. An overall lack of coordinated regional approaches to healthcare is rooted in competition for funds or organizational-specific policies. Healthcare
professionals identified a lack of knowledge of what social services exist and even a limited
understanding of the role different healthcare institutions play in the community (e.g., what is
the role of a health department).

64

“We never know the longevity of [hospitals’ or health departments’] commitments…
We see them make investments in a specific community project or grants orparticipate in certain meetings. But, that participation is limited to a short-term
project…. Hospitals would be better partners if [community-based organizations]
could rely on more long-term commitments.”- Community Expert in Food Security•

Language barriers and cultural differences are barriers to effectively communicating withpatients. Even when translating services are available, interpretive services
require technological knowledge, as well as cultural knowledge to be effective(not just language skills). Language barriers are also a challenge for providers
in that it is difficult to also be confident that treatment or medication plans
will be followed correctly and safely. Even when providers and community
members share a language, healthcare professionals reported that culturaldifferences (e.g., differences in attitudes towards health care, political ideologies, belief
systems, or lived experiences) make it difficult to effectively communicate and to build trusting
provider-patient relationships.

Increasing the Quality of Healthcare Encounters Can Help Meet Community Needs
Community members also identified a need for quality healthcare encounters. However, there arebarriers within the healthcare system that negatively impact the quality of the interaction. The tablebelow outlines the needs identified by community members and the region’s healthcare system barriers
that providers report (either in qualitative [Q] or survey [S] data) in meeting community needs related toquality healthcare delivery.
Table 6. Linking Community Member Need for Quality Health Care to Barriers Providers Face
What community members needwhen it comes to receiving healthcare?
According to community members,
a quality healthcare service meansa patient…
1. … is provided enough time (30+minutes) to speak with their
physician/clinician.

Barriers providers face to meeting this need

•
•
•
•

High caseloads and the increasing number of administrative
tasks required of healthcare providers. (Q/S)
Reimbursement structures and hospital/provider
productivity policies. (Q/S)
Shortage of staff/applicant pool. (Q/S)
Providers also indicate that they perceive a lack of time tovisit or follow up with patients as a major barrier driven byheavy caseloads. (S)65

Table 6. Linking Community Member Need for Quality Health Care to Barriers Providers Face
What community members needwhen it comes to receiving healthcare?
According to community members,
a quality healthcare service meansa patient…
2. … “feels heard” by their
physician/clinician.

Barriers providers face to meeting this need

•

•
•
•
3. … is provided the range oftreatment options by their
physician/clinician, including
both medical and non-medical
options and the pros/cons ofoptions in terms of overall
health.

•4. … is verbally informed upfront
by the physician/clinician of thecost of care and of financial
assistance policies.
5. … is immediately connected toa follow-up service before
leaving the site of service. This
includes coordination ofprescribed medical services andsocial services needed to
improve access to health care.

•

•
•

•
•
•
•
•
•
•
•

Not paid for “soft skills”; Increasing stress among
healthcare professionals due to caseloads and decreasing
job satisfaction makes it difficult to be constantly
empathetic. (Q)Increasingly less or no time for continuous education on
cultural relevancy. (Q)Some best practices simply require more time with patient.
(Q)
Providers report limited implementation of best practices
surrounding cultural competency and trauma-informedcare. (S)Medical services are siloed from other services, including
non-medical services that ultimately increase health andwell-being (even the success of a medical treatment). (Q)Language barriers and cultural differences make it difficult
to have confidence that patient/physician arecommunicating effectively. (Q)Providers report limited implementation of best practices
surrounding integration of cultural preferences for disease
management. (S)Informing on cost (and cost upfront) is historically outside
the role of physician/clinician. (Q)Healthcare providers work within their own network, canisolate from specialists or other providers. (Q)Profit-driven healthcare models drive competition. (Q)Overall shortage of specialty service providers. (Q/S)
Healthcare professionals generally lack knowledge of typesof available social services, the organizations offering
services, and eligibilities. (Q)Healthcare and social services are provided in separate,
sometimes distant, spaces. (Q)Interpretations of HIPAA/institutional competition prevent
important data sharing that could inform the better
coordination of health care and social services. (Q)Insurance policy can limit service options. (Q/S)
Medical providers reporting limited implementation of
screening for social service needs andcoordination/collaboration with social service providers. (S)66

Table 6. Linking Community Member Need for Quality Health Care to Barriers Providers Face
What community members needwhen it comes to receiving healthcare?
According to community members,
a quality healthcare service meansa patient…
6. … is informed of prescription
medication options (i.e., pros,cons, and side effects),
potential that medication may
change based on
supply/generic/etc., and costsby physician/clinician.
7. … has ability to make an
informed choice on who theirprovider is.

Barriers providers face to meeting this need•••

Providers perceive patient barriers to access medications as
a barrier for them in providing quality care. (S)Supply driven by insurance policies and prescription
medication corporations. (Q)Informing on cost is historically outside the role ofphysician. (Q)Competitive health institutions do not lend to a central
resource where all providers in area are presented as an
option. (Q)• Changing staff and insurance networks. (Q)(Q) Qualitative data from focus groups or interviews(S) Survey data•67

9. Community Assets and Considerations for Addressing Prioritized
Needs
Regional Assets and Concrete Opportunities to Address Prioritized Needs
The Regional CHNA provider survey, community focus groups, and interviews with system leaders
highlighted existing assets (i.e., models and strategies) in the community and concrete strategies toaddress health and social service care delivery challenges identified in this Reginal CHNA. Assets
included established agencies and organizations with expertise in a priority area to be engaged as apartners in addressing needs, and models or best practices that community members agree would
address prioritized needs if implemented. The list is limited to the perceptions and ideas of those who
were interviewed, engaged in a focus group, and/or completed the provider survey. While the list of
specific organizations and initiatives throughout the region who are addressing these prioritized needs isvast, the goal of this CHNA was to clearly identify the successful models and best practices thatcurrently exist in the region, and through capacity building, can be applied as strategies to address the
final prioritized needs.
Below are the organizations, programs, and strategies identified as Regional assets (i.e., models and bestpractices) specific to the health needs identified throughout the report and link the CHNA to concrete
action steps to address prioritized needs.

Prioritized Need

FOOD SECURITY*
Models and Best Practices to Inform Strategies:
Good Food Purchasing Program
Mobile Food and Basic Needs Truck model
Greater Cincinnati Regional Food Policy Council, an initiative of Green Umbrella Regional
Sustainability Alliance*Housing security is also a prioritized health-related social need. However, the models andstrategies discussed around housing security related more to successful models in accessing healthcare in communities who are housing insecure. Therefore, no housing security models were
specifically identified by community stakeholders.
**It should be noted that a collaborative effort of broad coalition stakeholders across Cincinnati
and Hamilton County have developed a strategy guide – Housing our Future – that focuses on theneed to preserve and produce affordable housing, protect existing residents, and make systemchanges that increase access to home ownership, production of housing units, preservation ofexisting affordable housing, equitable zoning policies, and resources and financing to meet goals.
Led by the Local Initiatives Support Corporation (LISC) of Greater Cincinnati, this report leveraged
comprehensive data collection and local expertise to show the full scope of housing needs within
Greater Cincinnati.
•
•
•

68

Prioritized NeedACCESS TO CARE
Models and Best Practices to Inform Strategies:
•
•
•
•
•
•
•
•
•
•
•
•
•
•

City planning agencies to support bringing health centers to communities
Public transportation agencies/transit authorities, both in urban and rural communities
Health and Cultural Fairs
School-based Healthcare Model
LGBTQ+ affirming care practices based on Human Rights Campaign’s Healthcare Equality Index
Peer Supporter Model
Charitable pharmacy model and effective communication strategies between healthcare
providers and pharmacies
Increasingly accessible technologies to leverage for a centralized resource for community
members to find services, providers that meet needs/preferences, and healthcare costtransparency across the region
Coordinated advocacy efforts
Best practices (and failed practices to avoid) learned from regional collaboration during COVID19 pandemic and in Opioid epidemic.
Doula Model
Community Health Worker Model and On-site Social Workers
Models for a regional approach to screening for health and SDOH-related needs/supports
Models for safety and prevention interventions across lifespanPrioritized Need

WORKFORCE DIVERSITY/CULTURAL COMPETENCY
Models and Best Practices to Inform Strategies:•••

Best practices in culturally competent design of healthcare spaces
Investment in future healthcare workforce through partnering with schools and Career Stat
Network Hospitals
National Fund for Workforce Solutions

Appendix D contains more information about these community assets.

Gaps in Assets for Addressing Prioritized Needs
Though the region as a whole may be resource rich and have many different organizations andinitiatives addressing the prioritized needs, the following list highlights gaps in assets for addressing
prioritized needs in the region in the existing ecosystem of health and social services. Some of the gaps
in assets listed below are also discussed in more detail throughout the Regional CHNA. Whenconsidering strategies to address the prioritized health needs, these gaps will need to be addressed or
taken into consideration for the strategy to be successful.

69

Prioritized Need

FOOD SECURITY*
Gaps in Regional Assets:•••

Food deserts in the region.
Perceptions of food being served to patients in hospitals is unhealthy.
There is a need for more long-term commitments to partnerships with food-security related
community organizations to provide better strategies/tools for community members to be
successful in developing healthier eating habits and to increase access to healthier foods that areculturally relevant. Partnerships between hospital or other health care system and a communitybased organization, for example, have historically been based on a short-term initiative.

Prioritized NeedACCESS TO CARE
Gaps in Regional Assets:
•
•
•
•

•

•
•
•
•

•

Limited partnerships with transportation providers.
Relative to Dayton MSA, individuals in Cincinnati MSA are significantly more likely to have unmet
allergy needs.
Relative to individuals living in Cincinnati MSA, individuals living in Dayton MSA are significantly
more likely to have unmet cardiovascular-related needs.
The region is missing a centralized information resource that can help community members finddoctors to meet needs related to specialties, gender, or cultural preferences; estimate health carecosts; and navigate insurance benefits, rights, and/or questions. Community members reported
that the lack of a centralized resource for healthcare service information also means there is alack of a centralized resource for local public health information that is trusted.
Limited number of service appointments and appointment times (i.e. longer waits for an
appointment, particularly new patients, and limited appointment times available outside regular
work hours).
Community members in each region of this Regional CHNA perceive that the healthcare systemdoes not have the best interest of community members in mind.
America’s high-cost healthcare system.
Limited time available for health care professionals to spend with each patient, including highcaseloads and increasing administrative tasks.
Community members need physicians, clinicians, hospitals, etc. to be in better coordination withsocial services and community-based providers of holistic health programming (i.e., yoga studios,
outdoor recreation, community connectedness activities, cultural events).
Lack of effective linkages between health care, mental health care, and community-based service
providers. Healthcare professionals generally lack knowledge of types of available social services,70Prioritized NeedACCESS TO CARE
Gaps in Regional Assets:••••

the organizations offering services, and eligibilities. Healthcare and social services are provided inseparate, sometimes distant, spaces.
Insurance policy can limit service options.
Lack of regional approach for screening for SDOH and considering SDOH when developing care ortreatment plans.
Outdated technology and lack of shared interpretation of HIPPA policies that makes it challenging
to have up-to-date data and to share data.
Lack of regional protocol for how crisis, addiction, and mental health cases should be treated inemergency departments and among emergency services.

Prioritized Need

WORKFORCE DIVERSITY/CULTURAL COMPETENCY
Gaps in Regional Assets:
•
•

•
•
•

Limited or lack of access to culturally and/or LGBTQ+ competent healthcare professionals
Translating services are available, but interpretive services require technological knowledge, as
well as cultural knowledge to be effective (not just language skills). Language barriers are also achallenge for providers in that it is difficult to also be confident that treatment or medication plans
will be followed correctly and safely.
Increasingly less or no time for health care professionals to pursue continuous education on
cultural relevancy.
Providers report limited implementation of best practices surrounding cultural competency andtrauma-informed care.
Regional staffing shortages from medical specialists to nurses to entry-level administrative andother support staff.

71

Organizations Identified by Peers as Implementing Best Practices to Address Barriers to
Health CareWith a research-informed understanding of the barriers providers face in delivering health and social
services, the Regional CHNA focused on identifying the best practices to overcome those barriers. The
Regional CHNA provider survey asked health and social service providers about the implementation ofbest practices that address the barriers providers face in serving the health needs of the community.
These best practices are categorized as:
•
•
•
•
•
•

Workforce development in social services
Ensuring cultural relevance of services
Screening and care coordination
Collaboration
Data sharing
Client-responsive services.

The main takeaway in the best practices analysis is that there is great opportunity to increase theimplementation of best practices across the region. Appendix E summarizes the results of best practice
implementation across the health and social service providers who completed the Regional CHNA
provider survey.
The following lists highlight the organizations who were specifically named by one or more of their peers
as successfully implementing best practices. Strategies to address barriers providers face in serving thehealth needs of the community could be informed by the successes of these listed organizations. These
organizations are recorded in the Regional Assets data file and is managed by THC.

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES INWORKFORCE DEVELOPMENT IN SOCIAL SERVICESBon Secour Mercy Health
Caracole, Inc.
Central Clinic Behavioral Health
Cincinnati Children's Hospital
Cincinnati Health Department
Cincinnati Health Department – Dental
Cincinnati Youth Collaborative
Community Health AssistantCompuNet Clinical Laboratories
Crossroad Health Center
Cypress
Dayton VA Medical Center
Dental Success Today
Department of Family and Community
Medicine
Equitas HealthGreater Cincinnati Behavioral Health
Health Source of Ohio
Kettering Health
Kettering Health Dayton / Grandview Medical Center
Kettering Health Franklin Emergency Department
Kettering Health Piqua
Lincoln Heights Health Center
Lindner Center of Hope
Margaret Mary Health Center
Maternal and Child Health Center
Medical Aid Station
Medical Comprehensive Authority Hospital
Mental Health and Recovery Board of Clark,
Champaign, and Madison Counties
Mercy Health
Mercy Health (Springfield and Urbana)72

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES INWORKFORCE DEVELOPMENT IN SOCIAL SERVICES
Goodwill Easter Seals Miami Valley
Greater Cincinnati Behavioral Health Services
Krause’s Sofa Factory
Mercy Health
Mercy Urbana SBU
Miami Valley Hospital
Premier HealthSamaritan Behavioral Health
Springfield Regional Medical Center
The Change Agency
The Christ Hospital Mt. Auburn FMC
TriHealthFive Rivers Health Center

Mt Lookout Dentistry
Restoration Ranch of Ohio
Rocking Horse Community Health Center
Samaritan Behavioral HealthSoin Medical Center
Temple University
The Christ Hospital
UC Health
University of Cincinnati, Department of Family andCommunity Medicine
University of Cincinnati, Department of Psychiatry
Vanguard Eldercare
Wright State Physicians OB/GYN

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES IN
ENSURING CULTURAL RELEVANCE OF SERVICESBon Secour Mercy HealthBrown and Gettings, DDS
Caracole, Inc.
Central Clinical Behavioral Health
Cincinnati Children’s Hospital
Cincinnati Health Department
Cincinnati Health Department – Dental
Cincinnati Health Network
Cincinnati Youth Collaborative
Clean Slate Sober Living
Community Health AssistantCompuNet Clinical Laboratories
Cradle Cincinnati
Crossroad Health Center
Cypress
Dayton VA Medical Center
Dental Success Today
Department of Family and Community
Medicine
Dole Foods
Equitas Health

Margaret Mary Health Center
Maternal and Child Health Center
Medical Aid Station
Medical Comprehensive Authority Hospital
Mental Health and Recovery Board of Clark,
Champaign, and Madison Counties
Mercy Health
Mercy Health (Springfield and Urbana)
Mercy Urbana SBU
Miami Valley Hospital
Mt Lookout Dentistry
Premier HealthPremier Health – Miami Valley Hospital
Premier Health – Upper Valley Medical Center
Purity Supreme
Restoration Ranch of Ohio
Rocking Horse Community Health Center
Samaritan Behavioral HealthSanta Maria Community Services
Soin Family Medicine Residency
Soin Medical Center
73

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES IN
ENSURING CULTURAL RELEVANCE OF SERVICES
Five Rivers Health Center
Good Samaritan Free Clinic
Goodwill Easter Seals
Grandview Medical Center
Greater Cincinnati Behavioral Health Services
Health Source of Ohio
Kettering Health Dayton / Grandview Medical
CenterKettering Health Franklin Emergency
Department
Kettering Health Main
Kettering Health Piqua
Kettering Network Breast Evaluation Center
Lincoln Heights Health Center
Lindner Center of HopeSouth Community
Springfield Regional Medical Center
Temple University
The Change Agency
The Christ Hospital
The Christ Hospital Mt. Auburn FMC
The HealthCare Connection
TriHealth
UC Health
UC Health – Primary Care Montgomery
University of Cincinnati Medical Center
University of Cincinnati Department of Psychiatry

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES INSCREENING AND CARE COORDINATIONBon Secour Mercy HealthBrown and Gettings, DDS
Cincinnati Children’s Hospital
Cincinnati Health Department
Cincinnati Health Network
Crossroad Health Center
Department of Family and Community
Medicine
Five Rivers Health Center
Goodwill Easter Seals
Grandview Medical Center
Greater Cincinnati Behavioral Health Services
Health Source of Ohio
Kettering Health
Kettering Health Dayton / Grandview Medical
CenterKettering Network KBEC

Maternal and Child Health Center
Mercy Health
Mercy Health (Springfield and Urbana)
Mercy Urbana SBU
Miami Valley Hospital
Premier HealthPremier Health – Upper Valley Medical Center
Samaritan Behavioral HealthSouth Community
The Change Agency
The Christ Hospital Mt. Auburn FMC
The HealthCare Connection
TriHealth
University of Cincinnati, Department of Psychiatry
University of Cincinnati/Cincinnati Children’s
Hospital

74

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES IN
DATA-SHARING
Anaheim Medical
Andrews University
CareSource
Cincinnati Health Department
Cleveland Clinic
Country Club Markets
Education and Training Institution
Perfect Plastic Body
Rocking Horse Community Health Center

ORGANIZATIONS SUCCESSFULLY IMPLEMENTING BEST PRACTICES IN
CLIENT-RESPONSIVE SERVICES
Anaheim Medical
CareSource
Cincinnati Health Department
Cleveland Clinic
Country Club Markets
Education and Training Institution
Kettering HealthRocking Horse Community Health Center
United Senior Services

7510. Conclusion
The region of providers desire to take a regional approach to ensuring everyone has the opportunity to
be healthy. Most of these health conditions align to the priorities set in the Ohio, Indiana, and Kentucky
Health Improvement Plans (HIPs) and conditions already prioritized in the community.
Community members have communicated a desire for a regional health system that is more supportiveof prevention and wellness. The research conducted in this Community Health Needs Assessmentshows the interconnectedness of structural barriers (policies and programs that govern thecommunity) and community factors (SDOH) that put community members at greater risk for healthconditions.
To advance health equity, the region should consider the communities who are most disadvantaged anddesign strategies to eliminate that disparity in healthcare access and outcomes. According to Regional
CHNA community survey data, Non-White community members, individuals with lower levels of
education, individuals with disabilities, those without health insurance, and veteran or active-duty
community members experience significant disparity related to multiple SDOH. As a result, initiatives toadvance health equity so that all community members have the opportunity to be healthy will require
strategies that address these disparities.
Further, these health disparities are also driven by the structural barriers that govern health care;
namely the profit-driven healthcare system and the structural division of the continuum of care. Thesesystemic barriers can be addressed in a collective impact strategy that includes policy and practicechange. Additionally, the barriers created uniquely by the healthcare system can also be addressed at
the policy and practice levels. At the policy level, the region can align internal organizational policies andleverage collective lobbying and political will. At the practice level, providers from every sector can focus
on improving the quality of interactions between providers and community members.
The region has come together around a common goal to use a regional approach to improving thehealth of the community. Data from this Regional CHNA clearly supports comprehensive strategies
including addressing SDOH that are driving health needs, a health equity lens that considers how
strategies will remove disparities, and mutually reinforcing action at the practice and policy levels.

76

11. Prioritization of Health Needs for Regional CHNA
The health needs of this region were identified (Table 7) through a series of robust quantitative andqualitative data collection methods across community members, healthcare and social service providers,subject matter experts in hospitals, health departments, community-based organizations, and throughreview of secondary data and an extensive literature review.
Table 7. Significant Health Needs for the Greater Cincinnati/Greater Dayton Regional CHNA

•
•
•
•
•
•
•

Most Prevalent Health
Conditions (Ranked)
Cardiovascular Conditions(Hypertension)
Mental Health (Depression
and Anxiety)
Arthritis
Lung/Respiratory Health
DentalMaternal health concerns
Prevention-related needs

•
•
•
•
•
•
•

Health Condition Most
Untreated (Ranked)
VisionDentalAllergy
Mental Health (Depression
and Anxiety)
Arthritis
Cardiovascular Conditions(Hypertension)Maternal health concerns

•
•
•
•
•

Health Conditions Most
Impacted By SDOH
Cardiovascular Conditions(Hypertension)
Mental Health (Depression
and Anxiety)
VisionLung/Respiratory HealthDiabetes

SDOH Factors Impacting Health in the Region
Economic stability (Stable housing, food security, paying bills)
Neighborhood and Built Environment (Access to reasonable transportation, parks/outdoor
activities, stable phone, and internet)• Education Access and Quality (Perception of quality of schools and childcare that are available)• Social and Community Connectedness (Having someone to talk to and feeling connected to thecommunity)• Healthcare Access and Quality (Perception of quality of health care available, cultural relevancy
of health care, ease of finding desired health care, ease of navigating healthcare costs)
Structural Barriers in the Region’s Healthcare System• Competition across healthcare organizations/systems• Workloads and caseloads are high• Lack of effective clinical-community linkages• Language barriers and cultural differences• High cost of services• Limited workforce• Inflexible and restricted funding structures and/or investment in community• Lack of culturally relevant communication strategies and services across providers• Limited implementation of DEI practices within organizations• Community member distrust in the healthcare ecosystem (i.e., providers, insurers,
pharmacies, etc.)• Limited implementation of best practices of trauma-informed care
Systemic Barriers• Structural racism, including workforce diversity and cultural competence of healthcare delivery• High-Cost healthcare system• Structural divide between healthcare system, holistic wellness providers, and social service
providers••77

A total of 25 one-on-one stakeholder meetings were conducted from September 27, 2021 to October
31, 2021 by The Health Collaborative to review results of the robust data collection process, andprioritize the significant health needs using a list of data-driven, actionable recommended priorities. 71
Prioritization of these needs began with a list of recommended priorities that were data driven andaction focused. Using a set of five criteria, the top priorities were finalized.
The criteria for prioritization included:
1. Burden and Severity: Are the health conditions the greatest burden for our region, acrossprevalence, those most often gone untreated, and those that were most impacted by social
determinants of health? Would addressing this have an impact on the greatest number ofcommunity members?
2. Equity: Does the health condition/social determinants of health have extreme health disparities
across prevalence and qualitative data for our community members? Would addressing thispriority significantly address health disparities?
3. Value to Stakeholders: Is the health conditions, social determinants of health, and/or systemicroot causes important to address across stakeholders? Would addressing this be a high priority
for stakeholders/organizations for the community members they serve?
4. Capacity and Feasibility: Does our region have the ability to address the need, throughpartnerships, resources, community will, and funding opportunities?
5. Alignment: The level of alignment of the recommended priority. Does the priority align with:a. internal strategic plans at stakeholder organizations?
b. the Ohio State Health Assessment (SHA) and Ohio State Health Improvement Plan
(SHIP)?
c. national goals through Healthy People 2030?
Each meeting was documented with qualitative data of comments, feedback, concerns, and ideas forprioritizing needs for the region. Additionally, quantitative data was collected on the recommended
priorities list by asking each stakeholder to name their top three priorities using a series of strategic
questions from the list below in Table 8.
Strategic Questions:
1. Based on your subject matter expertise, what should the top three priorities be for the region?
2. Based on your expertise within your organization, and as a representative of yourorganization, what should the top three priorities be for the region?
3. To move the needle on advancing health and reducing health disparities for our community,
what should the top three priorities be for the region?

THC and the CHNA Advisory Team reviewed the Regional CHNA Report and data-driven recommendations(Appendix F) drafted by MRC. From the report and data-driven recommendations, THC and the Advisory
Committee completed the prioritization methodology outlined in the chapter.
71

78

The list of data-driven, actionable recommended priorities discussed at each stakeholder meeting
includes:Table 8: Recommended Priorities and Quantitative Data
Recommended Priority
Address access to and use of resources for the most critical health related social needs, particularly
housing and food insecurity, through the development and strengthening of relationships between
providers and community-based organizations.
Increase access to services for the region’s greatest unmet needs, including dental, vision health, andmental health services.
Strengthen access to and the quality of health care for the region’s top health conditions, specificallymental health, and cardiovascular disease, particularly among populations of highest need.
Increase diversity in workforce across all levels, entry to executive (including trauma-informed carepractices and cultural competence).
Invest in upstream approaches for identified health equity zones (place-based, community-led
collaboratives, in specific geographic areas of highest need – those with the lowest lifespan or otheragreed upon metrics).
Increase training and availability of community health workers in clinical delivery sites andcommunity-based organizations.
Increase access to and use of telehealth services, particularly for addressing mental health needs.
Develop data-sharing processes for increasing access to clinical data for local health departments
and community-based organizations.

79As a result of the stakeholder meetings, Table 9 lists the three regional priorities with supporting datasummary:
Table 9. Prioritized Health Needs for the Greater Cincinnati/Greater Dayton Regional CHNA•

Increase access to services in order to improve equitable outcomes for the region’s top healthneeds: behavioral health, cardiovascular disease, dental, and vision.
o Across the region, cardiovascular conditions and mental health have the highest
prevalence and among the highest rate of unmet needs as compared to the otherpriority conditions. Among other health conditions, dental and vision concerns havethe highest rate of unmet needs and that rate is more than double the rate of unmet
needs for other conditions. (Figures 1 and 2 and Tables 1 and 2 in the beginning of
the report).

•

Address access to and use of resources for food security and housing with a focus on thedevelopment and strengthening of partnerships between providers and community-basedorganizations.
o In regression analysis, economic stability was the SDOH most commonly associatedwith prevalence of health conditions and rates of unmet health needs. Though
average economic stability indicators were relatively more positive compared toother factors in the survey data, the disparity in economic stability is driving thesignificant results. It is generally understood that food and housing are largely outsideof the healthcare system. However, they are a key driver of health. In interviews andfocus groups, the community identified many ways for health systems to partner with
community providers in delivering collaborative interventions.

•

Strengthen workforce pipeline and diversity, including cultural competence, within thehealthcare ecosystem.
o Survey data from health and social service providers as well as qualitative data frominterviews and focus groups highlight a lack of diversity in the healthcare provider
and management workforce. According to the community, lack of workforce
diversity negatively impacts the cultural relevancy of health care and healthcare accessibility. Additionally, healthcare system experts and community members
attribute the lack of diversity among healthcare professionals to be an outcome ofstructural racism, unwelcoming workplace cultures, and disparity in pursuinghealthcare careers across community groups.

8012. Appendix A: Methods
Comprehensive Data Collection
The needs assessment utilized a mixed-method approach to data collection including secondary
quantitative data and primary quantitative and qualitative data. Each data collection strategy adhered toa recruitment plan to ensure a representative sample of community members, voices ofunderrepresented populations and providers across the health and social services sectors were
captured. Below, each data collection strategy is outlined include the sampling or recruitment strategy,
and analysis.

Secondary Data
Secondary data sources were used to capture community-level data on health conditions, healthcare
access, and risk factors. Data sources are cited throughout the report. Large secondary data sources
include the American Community Survey (ACS), National Center for Health Statistics, CDC’s Behavioral
Risk Factor Surveillance System, and Ohio Hospital Association (OHA) and Health Information Exchange(HIE) hospital and emergency department utilization data. Other secondary data regarding social
determinants of health were pulled from 2021 County Health Rankings National Data (CHR).

Provider Survey
The primary goal of the provider survey was to assess the current state of system barriers to providing
health care and to addressing the greatest health needs of the community, and to identify solutions to
overcoming system and SDOH-related barriers. The online survey was open from April 2021 to May
2021. Below outlines the sampling and analysis strategy for the provider survey.
Sampling
A total of 859 provider surveys were included in the analysis. 72 Across the three regions, therepresentation of providers from different fields were relatively equal (Table A1) with the exception of
Dayton-Kettering MSA where there was much higher representation from Medical Health professionals(general population; 29%) compared to Cincinnati MSA (10%) and Rural Counties (14%). As shown in
Table A2, among healthcare professionals, more than half in each region provide direct patient care.
Among social service professionals, the most common roles among respondents were in
Administration/Senior Management. Providers also reported serving the Regional CHNA target
populations with 50% or more serving children/youth, disabled, ethnic minority, homeless, low-income,parent/caretaker and older adult populations (Table A3).
Table A1. Percent of Survey Respondents from Each Region by Provider Type
Provider Type
Cincinnati
Dayton-Kettering
MSA
MSA and Clark(n = 596)
County (n = 300)
Behavioral Health, Non-School-Based7%
8%
Behavioral Health, School-Based10%
5%
Education: College/University
9%
6%

Rural
Counties(n = 335)
10%
7%
7%

974 individuals began and/or completed the provider survey, with 113 responses removed due toincompleteness (i.e., did not provide answers to questions beyond the counties they serve and their role). Anothertwo responses were removed because the individuals did not work within the region.

72

81

Table A1. Percent of Survey Respondents from Each Region by Provider Type
Provider Type
Cincinnati
Dayton-Kettering
MSA
MSA and Clark(n = 596)
County (n = 300)
Education: Early Childhood
6%2%
Education: K-12
3%
2%
Emergency Medical Services/First Responder
5%6%
Faith-Based Organization
4%
3%
Federally Qualified Health Center
3%
1%
Justice or Corrections
2%
4%
Medical Health -Adult8%12%Medical Health -General Population
10%
29%
Medical Health -Geriatric2%2%
Medical Health -Pediatric3%
2%
Oral Health7%
5%Other organizations addressing social
5%6%determinants of healthPharmaceutical4%
2%
Public Health Department
7%
3%
Other
5%
4%
Table A2. Percent of Survey Respondents from Each Region by Provider Role
Provider Roles
Cincinnati
Dayton-Kettering
MSA
MSA and Clark(n = 596)
County (n = 300)
Health-Related
Administration
33%
23%
Provide direct patient care
59%
68%
Academic
7%
4%
Other Role
2%
4%
Social Service-Related
Administrative Support Staff
14%
9%Administrator/Senior Management
52%
47%
Direct Service Provider
21%
28%
Manager or Supervisor
10%
14%
Other Role
3%
1%
Table A3. Percent of Survey Respondents from Each Region by Populations Served
Populations Served
Cincinnati MSA
Dayton-Kettering(n = 594)
MSA and Clark
County (n = 300)
All Residents
43%
56%
Children/Youth28%
22%
Disabled
20%
22%
Ethnic Minorities
22%
25%

Rural
Counties(n = 335)
4%
4%
6%
5%
2%
3%
8%
14%
2%
2%
6%
5%
5%
6%
4%

Rural
Counties(n = 334)
37%
54%
6%
3%
11%
64%
17%
5%
3%

Rural Counties(n = 335)
48%
24%
19%
21%
82

Table A3. Percent of Survey Respondents from Each Region by Populations Served
Populations Served
Cincinnati MSA
Dayton-Kettering(n = 594)
MSA and Clark
County (n = 300)
Homeless
19%
22%
Justice-Involved Individuals
9%13%
Language Minorities
10%
13%
LGBTQ+
11%
18%
Low-Income Populations
22%
25%
Older Adults
26%
32%
Parents/Caretakers
16%
19%
Veterans
8%15%
Young Adults
13%
17%
Another Population
2%
4%

Rural Counties(n = 335)
20%
11%
7%
11%
19%
30%
17%
10%
10%
2%

Analysis
The provider survey analysis assessed overall perceptions among providers in THC’s region, as well as
differences in perceptions and experiences among different types of providers. For overall perceptions
and experiences, frequency and descriptive analyses were conducted.
To assess for differences in perceptions and experiences by provider characteristics, descriptive andfrequency statistics were compared by provider types (e.g., behavioral healthcare providers compared
to medical providers) and regions served. Multiple regression analysis was conducted to assess theextent to which best practice utilization impacts providers’ perceptions of barriers. Table A4 outlines theresearch questions and subsequent analysis types including the outcome and predictor variables thatwere used in analysis.
Table A4. Population Survey Planned Analysis and Research Questions
Research Question
Analysis
OutcomeHow do barriers providers face
Frequencies andBarriers scale scoresin addressing the needs of thedescriptive
community differ by provider
statistics
characteristics?
How do best practices toFrequencies and
Has Successfully
overcome these barriers to
descriptive
implemented
addressing the needs of thestatistics
this/Has notcommunity differ by provider
characteristics?
Does best practice utilization
significantly predict the extent
to which providers experiencebarriers to providing care?

Multiple
Regression

Barriers scale scores

Predictors
Provider region andtype of provider
Provider region andtype of provider

Sum score of bestpractices successfully
implemented,
Provider region, andtype of provider

83

Population Survey
The primary goal of the population survey was to gather a wide range of voices to share theirexperiences and insights with health conditions, risk factors, and structural barriers. The electronic
survey was open from April 2021 to June 2021 and available in Arabic, English, French, Nepali, andSpanish. Paper surveys were provided when requested. To improve response rates, there were two
drawings for a $100 Amazon gift card. An overview of the sampling and analysis strategies for the
population survey are provided below.
Sampling
To ensure a representative sample of THC’s geographic service area, three separate stratified samplingstrategies were developed to reflect the age, race, and gender of Cincinnati Metropolitan Statistical Area
(MSA), 73 Dayton-Kettering MSA (to include Clark County which is not part of the Dayton MSA but issimilar in that it borders the Dayton MSA and is not a rural county), 74 and other rural counties in thegeographic service area that are predominately rural and not included in other MSAs. 75 Over 11,000
individuals responded to an online survey with 8,321 valid responses. 76 Table A5 provides a descriptionof the valid sample represented in the results. A full description can be found in Appendix B.
Table A5. Percent of Population Survey Respondents by Region
Demographic
Cincinnati
Dayton-Kettering
MSA
SampleMSA
Samplen=1,646,873
n=4,415n=729,904 n=2,543
%
%
%
%
Age
18-24
12%
8%
12%
6%
25-34
18%
30%
17%
20%
35-44
16%
16%
15%
22%
45-64
35%
29%
34%
44%
65+
19%
17%
22%
9%
Race
Black or African
12%
8%
14%
8%
AmericanMultiracial
1%
4%
2%
3%
Asian, American
5%
12%
4%
7%
Indian/Alaskan
Native, Native

Other Rural Counties
MSA
Samplen=257,910
n=1,363
%
%
11%
14%
15%
37%
23%

7%
30%
16%
33%
13%

1%

2%

1%
2%

2%
10%

Includes the following counties: Grant, Butler, Clermont, Hamilton, Warren, Dearborn, Kenton, Boone, Campbell,
Brown, Ohio, Union, and Franklin.
74
Includes the following counties: Clark, Montgomery, Miami, and Greene.
75
Includes the following counties: Clinton, Highland, Adams, Preble, Shelby, Darke, Auglaize, and Champaign.
76
11,615 total responses were gathered from our survey results. From here, 2,343 respondents were dropped
from analysis due to listing their zip code as one clearly outside of our regions of interest. An additional 38
respondents were dropped based on unreliable reporting of needing treatment for five major diseases in the past
year. 198 individuals were dropped due to their written selection for race being uninformative or unreliable. An
additional 333 respondents were dropped for low question response rate (15 or less answered questions). 139
respondents were dropped for likely duplicate entries. Finally, those who did not have complete responses for
MSA, age, sex, and race were dropped from analysis, resulting in 8,321 valid responses.
73

84

Table A5. Percent of Population Survey Respondents by Region
Demographic
Cincinnati
Dayton-Kettering
Hawaiian or PacificIslander or anotherrace that is not
White or Black orMultiracial
White or
82%
76%
80%
83%
Caucasian
Ethnicity
Hispanic or Latino
2%
4%
2%
3%
Not Hispanic or
98%
96%
98%
97%
LatinoGender
Male
48%
34%
48%
20%
Female
52%
66%
52%
80%

Other Rural Counties

96%

85%

1%
99%

5%
95%

49%
51%

30%
70%

As shown in Table A5, as is often the case, the sample characteristics do not perfectly align to the
population within the Health Collaborative’s region. In order to make population-level conclusions andobservations from our data, a survey data weighting method was applied to ensure the sample
distribution of demographics align with the population distribution. The method of survey weightingused in this analysis is called raking. This method is also used by Pew Research Center, and the CDC alsouses raking in their Behavioral Risk Factor Surveillance System (BRFSS) data. For more details related to
the raking methodology, please refer to Appendix B.
Analysis
For overall perceptions and experiences, frequency and descriptive analyses were conducted using
survey response weighting described above. To assess for differences in perceptions and experiences
related to health, logistic and multiple regression analyses were conducted. Table A6 outlines theresearch questions and subsequent analysis types including the outcome, predictor, and control
variables that were used. Because much of the needs assessment was focused on determining which
individuals and in which regions individuals are experiencing the greatest health needs or gaps,
reference groups were selected based on the literature and previous research which inform groups ofindividuals who are most likely to be negatively impacted relative to majority or historically notunderrepresented groups (e.g., White individuals, individuals from higher socioeconomic statuses,
individuals without disabilities); choice of reference group does not change the reliability or validity ofthe statistics or model, but rather provides targeted insights into group differences.

85

Table A6. Population Survey Planned Analysis and Research Questions
Research Question
Analysis
OutcomePredictors
How does
Logistic
NeededGender identity,
need/prevalence ofRegression(received or
sexual orientation,
health conditionsnot) for each age, race/ethnicity,
differ acrossof the health income or education,communities andconditions of disability status,
members?
interest
employment status,
region, insurance,children inhousehold, military
statusHow do barriers toMultiple
Each of the
Gender identity,care differ acrossRegression
Barriersexual orientation,communities andsubscales asage, race/ethnicity,members?
separate
income or education,
outcomes
disability status,
employment status,
region, insurance,children inhousehold, military
statusHow does receipt ofpreventive care differ
across communities
and members?

Multiple
Regression

PreventiveCarefrequency

ControlsThebehavioral/healthrisk factors
correlated with eachhealth condition(options: alcohol,
healthy diet, highblood pressure, highcholesterol, tobacco,
exercise, BMI)

Gender identity, sexorientation, age,race/ethnicity,
income or education,
disability status,
employment status,
region, insurance,children inhousehold, military
status86

Which SDOH are most
predictive ofneed/prevalence of
health conditions?

Logistic
Regression

Needed(received ornot) for eachof the healthconditions ofinterest

Each of the SDOH
construct scalescoresHow does access tocare (needing and notreceiving relative toneeding and receivingcare) differ acrosscommunities andmembers?

Logistic
Regression

Needed and
Not Received
vs. Needed
and Received

gender identity, sexorientation, age,race/ethnicity,
income or education,
Disability status,
Employment status,
Region, Insurance,
Children inhousehold, Military
StatusHow do experiencesof SDOH differ acrosscommunities andcommunity members?

Multiple
Regression

Each of the
SDOH
subscales

gender identity, sexorientation, age,race/ethnicity,
income or education,
Disability status,
Employment status,
Region, Insurance,
Children inhousehold, Military
StatusThebehavioral/healthrisk factors
correlated with eachhealth condition(options: alcohol,
healthy diet, highblood pressure, highcholesterol, tobacco,
exercise, BMI)

87

How does the effectof COVID-19 on accessto care (delaying or
going without) differ
across communities
and members?

Multiple
Regression

Post COVID19 accessgender identity, sexorientation, age,race/ethnicity,
income or education,
Disability status,
Employment status,
Region, Insurance,
Children inhousehold, Military
StatusPre COVID-19 access

Focus Groups
The goal of focus groups was to document the unique health needs and experiences of community
members known to experience health disparities or that do not tend to participate in online surveys.
Focus group discussions centered around the following three broad questions:•••

How do health needs differ across communities and community members?
What are the personal experiences, local contexts, and social conditions (e.g., SDOH and root
causes) driving the greatest health needs in and across community groups?
How can healthcare providers better reach community members?

Focus groups were conducted, virtually, by researchers from MRC, Scale Strategic Solutions, and a teamof University of Cincinnati (UC) faculty and students, with MRC facilitating the collaborative effort.
Researchers collaborated with community champions in order to identify community members toparticipate. Focus groups lasted one hour, were conducted in person or via Zoom, and each participant
received a $25 grocery gift card (Amazon, Walmart, or Kroger) for their expertise in the focus group. An
overview of the recruiting and analysis strategies for the focus groups are provided below.
Recruiting
Based on the population groups the advisory committee identified as experiencing health disparities orbeing underrepresented in community data, MRC designed a recruitment strategy to ensure all the
population groups were included. A total of 51 focus groups were conducted, with a total of 234
community members (65% female, 31% male). Table A7 identifies some of the unique populations
represented in the focus groups.
Table A7. Population Representation in Focus Groups by Region
Population Category
Cincinnati
MSA
Adult Men
Experience in Foster Care, or Foster Care Parent
Disabled Youth and Adults
Ethnic, Cultural and Language Minorities

DaytonKettering MSAOther Rural
Counties






88

Table A7. Population Representation in Focus Groups by Region
Population Category
Cincinnati
MSA
First- and Second- Generation ImmigrantsHomeless Community Members
Justice-involved Individuals

Low-income Families/IndividualsOlder AdultsParents

VeteransYoung Adults (18-30 years)
Youth (high school)Community Members with lived experience ofmental health and/or addiction (including Peer
Supporters)

DaytonKettering MSA










Other Rural
Counties








Analysis
Focus group discussions were transcribed, and content analyzed for common clusters of similarstatements, organized by categories of clusters, and then analyzed for larger themes that summarize theglobal and unique perspectives of focus group participants.

Interviews
The goal of interviews was to assess the current state of system barriers to providing health care and toaddressing the greatest health needs of the community, and to identify solutions to overcoming system
and SDOH-related barriers. Interviews were designed around the following broad questions:••••

What are the system barriers providers face in addressing the needs of community groups?
What recommendations or best practices can be recommended to overcome system barriers toaddressing the health needs of the community?
What are the historical traumas, local contexts, and social conditions (e.g., SDOH and root
causes) driving the greatest health needs of your communities?
What specific action steps can be taken by various providers to address root causes to healthdisparities and achieve more equitable health outcomes?

Interviews were conducted via phone or virtually. MRC, Scale Strategic Solutions, and the UC researchteams conducted interviews, each lasting approximately 45 minutes. An overview of the sampling andanalysis strategies for the interviews are provided below.
Recruiting
MRC and UC worked with the Advisory Team to identify system experts and organizational-level
stakeholders representing governmental, Regional CHNA partners, healthcare providers andcommunity-based leaders. A total of 38 interviews were conducted, representing experience from thefollowing health and social service sectors shown in Table A8.

89Table A8. System Representation in Interviews by Region
Provider Category
Cincinnati
MSA
Community Health Centers and Federally QualifiedHealth Centers
Public Health and County Health Departments
Hospital Systems
Mental and SUD Health Care
Medical Health -Geriatric
SDOH -Housing
SDOH -Economic Disparity
SDOH -Transportation
LGBTQ+ Health Care
Emergency Health Care
Healthcare Access and Policy Experts
SDOH -Food Access
Pharmacy Access Experts
Healthcare Workforce Development Experts
Correctional Facility-based Health Care
School-based and Children’s Health Care

DaytonKettering
MSA


































Rural
Counties














Analysis
All individual stakeholder responses are confidential. Interviews were transcribed and content analyzed
for common clusters of similar statements, organized by categories of clusters, and then analyzed forlarger themes that summarize the global and unique perspectives of interview participants.
This comprehensive and inclusive data collection strategy resulted in a balanced representation acrossall three regions of the Regional CHNA. The success of the data collection is due largely to the advisorycommittee, community partners, and community champions.

Collaborative Data Collection
The University of Cincinnati (UC) received an applied research grant to conduct field research related tochild and youth health. This grant allowed the Regional CHNA to expand data collection to include
children and youth with wider representation. It is critical to uncover how to help youth, college
students and families in our region, and to understand their perceptions.
The UC Team for the Regional CHNA utilized interviews and focus groups to understand perceptions ofwhat it is to be healthy, needs of interest groups (focusing on youth and college students as well asfamilies), barriers to health, ideas for overcoming barriers, perceptions of telehealth, needs foradvocacy, healthcare access, healthcare successes in the region, and ideas for improving care and waysof interacting with patients. Twelve focus groups and 14 interviews were conducted by the UC team andthe results were analyzed using deductive coding methods. The results were integrated into the final
qualitative dataset for analysis. (Samples are included in Tables A7 and A8 above).

90

Data Considerations (Limitations)
When using the Regional CHNA community survey data to make generalizations of the population atlarge, it should be noted that a targeted snowball sampling methodology was utilized. Based on theimportance and, often, largely differing perceptions of health by age, race, and gender, the samplingstrategy prioritized oversampling numerically underrepresented populations to ensure a sufficient
sample to conduct statistical analyses by key demographic variables. As a result, the Regional CHNA
community survey has an overrepresentation of females, individuals ages 25 to 34 years, individuals
classified as a race other than White, Black, or Multiracial, and Hispanic individuals. Because of thisoverrepresentation, MRC conducted a weighted analysis as previously described to show frequency anddescriptive statistics for the three regions overall. Using the unweighted survey data, regression
analyses were performed to understand differing perceptions by demographics.

9113. Appendix B: Supplemental Data for Health Conditions
Survey Weighting Methods: Raking
The first step of the raking procedure is to choose our set of variables that we would use for theweighting procedure, and that have known values at the population level. In this analysis, thesevariables include sex assigned at birth, age category, race, and ethnicity (Hispanic or Non-Hispanic). The
categories for age and race were matched to the population level data from the U.S. Census Bureau’s
American Community Survey (ACS Tables B01001 A-I, 2019, 5-year estimates).
Raking is unique in the sense that only the marginal proportions (proportion of data by level in a single
variable) are needed for weighting our data. This weighting method iteratively adjusts the weights forindividuals based off the differences in the survey sample and population proportions. In other words,
first the weights are adjusted for the variable sex assigned at birth, then age, race, and finally ethnicity.
When the weights are adjusted for race, for example, the distribution of weights for other variables may
then be altered. To fix this alteration, another iteration of weighting is done, bringing the distribution ofweights for each variable closer to what is necessary to match our distribution of data to the true
population. The process continues until the distribution of variable weights in the sample most closely
matches that of the population. xxviii
In our raking procedure, the maximum weight value was set to five, and weights greater than five werethen truncated. This is an arbitrarily chosen value consistent with literature, which in our case translates
to five times the mean (mean of 1). The purpose of setting a limit on weights is to try and reduce theadded sampling variability our data gains by adding weights. xxix Additionally, the threshold for variable
inclusion was set to 5% (0.05), and the method for variable selection was total discrepancies acrossvariable levels. That is, for a variable to be selected in the raking procedure, the sum of discrepancies
between sample proportions and population proportions must be greater than 5% or 0.05. xxx The values
selected for maximum weight and percent limit are common practice, and the default used in the“anesrake” function used in r. xxxi All three MSA datasets reached convergence and have minimal
residual differences between the sample and population distribution of values after raking.
Behavioral Factors
Decades of data have linked behavioral factors to health conditions and this data has been used to
inform health promotions and interventions in communities throughout the region. The Regional CHNA
community survey asked community members about common behavioral factors most associated withthe priority health conditions. To summarize the behavioral factors results of the survey across theregion:•••••7 in 10 community members get a medical checkup or physical exam at least once a year (Figure
B1).
2 in 10 community members get 30 minutes of physical activity 5 or more days a week (Figure
B2).
3 to 4 in 10 community members reported very good to excellent healthy eating habits (Figure
B3).
4 in 10 community members reported being normal weight (Figure B4).
9 in 10 community members reported not smoking/vaping (Figure B5).
92

•
•

About half of community members reported never consuming 4 (for women) to 5 (for men) or
more alcoholic drinks in one sitting, in the past month (Figure B6).
Overall, Dayton MSA community members reported slightly higher rates of healthy behaviors
than community members in Cincinnati MSA or the rural counties.

Because these factors are well integrated into the knowledge base of the field and the researchquestions do not directly ask about behavioral risk factors, further analysis on these were not conductedin this Regional CHNA. Risk factors were included as control variables as appropriate for this Regional
CHNA.

Figure B1. Frequency of Preventive Care

About how often do you get medical checkups or physical exams?
Rural Counties (n = 1,326)

7% 4% 10%

Dayton-Kettering MSA (n = 2,487)

7% 2% 9%Cincinnati MSA (n = 4,270) 4% 3% 7%

12%

10%

15%

0%

20%

40%

51%

16%

58%

14%

58%

13%

60%

80%

100%

Data Source: Regional CHNA Community Survey

Never/Almost NeverLonger than every 5 years

Once every 3-5 years

Once every 2 years

Once a year

More than once a year

Figure B2. Physical Activity

Most weeks, how often do you do physical activity lasting 30 minutes or longer?

Rural Counties (n = 1,648; m = 3.7)

14%

10%

20%

24%

12%

21%

Dayton-Kettering MSA (n = 2,571; m = 3.8)

14%

10%

18%

25%

12%

21%

Cincinnati MSA (n = 3,981; m = 3.7)

13%

12%

19%

24%

11%

20%

0%

20%

40%

60%

80%

100%

Data Source: Regional CHNA Community Survey< 1 day

1 day

2 days3 days4 days5 or more days

93Figure B3. Healthy Eating Habits

How would you rate your overall habits of eating healthy foods (fruits, vegetables,
grains, dairy, lean meats like poultry, fish, and eggs)?
Rural Counties (n = 1,251; m = 3.1)

26%

41%

32%

Dayton-Kettering MSA (n = 2,332; m = 3.1)

28%

40%

32%

Cincinnati MSA (n = 3,985; m = 3.3)

22%
0%

38%
20%

40%

40%

60%

80%

100%

Data Source: Regional CHNA Community Survey
Poor/Fair

Good

Very Good/Excellent

Figure B4. Body Weight

Which of the following best describes your body weight?

Rural Counties (n = 1,250; m = 2.6) 3%

Dayton-Kettering MSA (n = 2,333; m = 2.7) 2%

42%

37%

Cincinnati MSA (n = 3,983; m = 2.6) 3%
0%

42%

45%

46%
20%

13%

16%

39%
40%

60%

12%
80%

100%

Data Source: Regional CHNA Community Survey
Underweight

Normal Weight

Overweight

Obese

94

Figure B5. Tobacco and Vapor Product Use
Do you currently smoke tobacco/vapor products?
% "Yes"

100%
80%
60%
40%
20%
0%

16%

10%

8%

Cincinnati MSA (n = 3,953)

14%

6%

Dayton-Kettering MSA (n = 2,316)

7%

Rural Counties (n = 1,236)

Data Source: Regional CHNA Community Survey% Smoke Tobacco% Use Vapor Products

Figure B6. Alcohol Use

How often would you consume 5 (or 4 for a woman) or more drinks during a single
occasion in the past month?
1%
Rural Counties (n = 1,646)
Dayton-Kettering MSA (n = 2,574)
Cincinnati MSA (n = 4,871)

16%

20%

47%
0%

20%

9%

19%

61%

40%

60%

1%

8%

7%

14%

18%

52%

2%
0%
4% 5%

8%

6%

2%

80%

1%

100%

Data Source: Regional CHNA Community Survey
Never< Once a Month

1-2 Times a Month< Once a Week

Once or Twice a Week

3-6 Days a Week

Daily or Almost Daily

Other Community Conditions
Weighted Average

Indianapolis
MSA

Cincinnati
MSA

DaytonMSA

RuralCounties

Ohio
Avg.

Indiana
Avg.

Kentucky
Avg.

U.S.
Overall

Preventable hosp.
(rate per 100,000)

4,319

4,748

4,591

4,834

4,901

4,795

5,615

4,236

Life expectancy(rate per 100,000)

77.7

77.2

75.9

76.6

77.0

77.1

75.6

79.2

Drug OD mortality(rate per 100,000)

28.3

46.9

55.5

39.4

38

26

32

21

95

Weighted Average

Indianapolis
MSA

Cincinnati
MSA

DaytonMSA

RuralCounties

Ohio
Avg.

Indiana
Avg.

Kentucky
Avg.

U.S.
Overall

Suicide (rate per
100,000) (ageadjusted)

15.1

13.8

15.6

15.9

15

15

17

14

Homicide (rate per
100,000)

9.5

5.6

7.8

9.6

6

6

6

6

Firearm fatality(rate per 100,000)

16.5

12.3

15.1

10.8

13

14

16

12

Frequent Mental
Distress

14.2%

14.7%

15.7%

16.4%

16%

15%

17%

13%

Infant mortality
rate (per 1,000 live
births)

6.7

7.6

6.8

7.0

7

7

6

6

Child mortality (rateper 100,000 underage 18)

56.5

58.8

60.7

57.0

60

60

60

50

High school
graduation %(Defined as“Percentage ofninth-grade cohortthat graduates infour years”)
Some college
education %

83.5%

87.4%

82.3%

90.1%

83%

88%

91%

85%

68.0%

69.2%

68.0%

54.8%

66%

63%

62%

66%

Median householdincome$67,954$68,125$57,846$57,598$58,700$57,600$52,300$65,700

Children in poverty
%

13.4%

15.3%

19.4%

16.1%

18%

15%

21%

10%

Uninsured %

9.4%

6.5%

8.0%

8.0%

8%

10%

7%

6%

Primary care
physician (rate per
100,000)

88.3

83.7

81.5

36.5

76.9

66.7

64.9

75.8

Mental healthprovider (rate per
100,000)

200.7

260.5

212.3

104.6

263.2

169.5

238.1

263.4

Dentist (rate per
100,000)

72.9

57.9

62.9

31.1

64.1

57.1

67.1

71.4

Physicallyinactive %Obesity %

24.7%

24.2%

26.3%

30.6%

26%

27%

29%

23%

32.3%

32.4%

35.0%

35.3%

34%

34%

35%

30%

Diabetes %

11.9%

11.8%

13.0%

12.1%

12%

12%

13%

11%

Smoking %

20.2%

20.3%

22.1%

24.7%

21%

22%

24%

17%

96

Weighted Average

Indianapolis
MSA

Cincinnati
MSA

DaytonMSA

RuralCounties

Ohio
Avg.

Indiana
Avg.

Kentucky
Avg.

U.S.
Overall

Excessive
18.9%
19.2%
18.5%
18.5%
18%
19%
17%
19%
drinking %Source: This data is compiled from the 2021 County Health Rankings Report. More information on data sources used byCounty Health Rankings can be found here: https://www.countyhealthrankings.org/explore-health-rankings/measuresdata-sources/2021-measures9714. Appendix C: Supplemental Data for Social Determinants of Health
For the following supplemental figures, secondary data sources were used. Weighted averages for each
MSA were calculated based off county-level averages and populations. The population of each county
was used as a weight for every MSA level estimate. Counties included in each MSA calculation can befound in the footnote on page 11.

Figure C1. Violent Crime Rate by MSA (per 100,000)
350.00312.28282.07

Violent Crimes per 100,000

300.00250.00200.00150.0088.09

100.0050.00
0.00

Dayton MSA

Cincinnati MSA

Rural Counties

County Health Rankings Data

Violent Crimes per 100,000

Figure C2. Violent Crime Rate by County
500
450
400
350
300
250
200
150
100
50
0

County Health Rankings Data

98

Table C1. Secondary Data Indicators for County-Level Economic Stability
%
%
Food
%
Population Population Environment
Children
Food
LimitedIndex*
Population
Data Source:
Insecure
Access to
Food2019
CountyData Source:
HealthyInsecure
Health Rankings
Feeding
Data Source:
Food
America’s
2019 County
Data Table

Data Source:
2019 County
HealthRankings

CountyAdams, OH
19%
4%
Auglaize, OH
2%
10%
Boone, KY
9%
6%
Brown, OH
15%
4%
Butler, OH
12%
7%
Campbell, KY
12%8%Champaign, OH
12%
1%
Clark, OH
15%
11%
Clermont, OH
12%
9%
Clinton, OH
15%
9%Darke, OH
12%2%
Dearborn, IN
11%7%Franklin, IN
11%
5%Grant, KY
8%
14%Greene, OH
12%
8%Hamilton, OH
13%
9%Highland, OH
17%
2%
Kenton, KY
11%6%
Miami, OH
12%
3%
Montgomery, OH
14%
10%
Ohio, IN
11%
Preble, OH
12%0%
Ripley, IN
1%
12%
Shelby, OH
11%
6%
Union, IN
16%
Warren, OH
9%5%
United States
11%6%
Region’s Mean
13%
*Rating scale = 1 is the worst, 10 is the best

6.7
8.7
8.5
7.6
7.8
7.9
8.3
6.9
7.8
7.2
8.3
8.0
8.3
7.3
7.7
7.3
7.3
7.9
8.2
7.0
8.3
8.4
8.1
8.5
7.8

Feeding
America’s
2019 County
Data Table%Of Food
InsecureandSNAPineligible

Data
Source:
Map theMeal Gap(2019 data)%
Populationthat areHousing
Cost
Burdened

26%
12%
10%
19%
15%
12%
16%
19%
13%
20%
15%
13%
16%
18%
15%
18%
22%
13%
13%
21%
13%
15%
15%
14%
12%
9%
15%
16%

35%
59%
46%
48%
52%
42%
56%
45%
60%
47%
54%
57%
52%
20%
57%
43%
42%
41%
58%
44%
62%
59%
52%
56%
56%
75%
50%
51%

26%
18%
21%
25%
25%
27%
19%
25%
24%
25%
19%
23%
19%
26%
24%
30%
26%
22%
21%
28%
16%
21%
22%
19%
24%
20%
28%
23%

Data Source:
ACS

99

Community Voices Defining Access to Quality Health Care
Defining Barriers to Accessing Quality Health Care According to Region’s Community
Members
This section highlights what healthy living, quality health care, and accessible health care means from acommunity perspective. Many barriers to a healthy life and to health care identified by community
members (outlined in this section) align with SDOH-related barriers discussed above. The barriers
discussed in this section emerged as themes from focus groups and interviews with community
members. Significantly, community members identified SDOH-related barriers without being
prompted to discuss SDOH. This supports the appropriateness of the SDOH framework in this Regional
CHNA and in strategic planning moving forward.
In focus groups and interviews,
community members were asked todefine “health.” Overall, health isAccording to community members, to have accessible healthdefined by community members as
care is to have confidence that, when needed, community
holistic; living a healthy life means tomembers will know what services are available, where to findbe physically, mentally, andthem, will not have cause to fear seeking them, and will not
spiritually safe and well. In focus
suffer social stigmatization or economic debt for using them.
group, interview, and Regional CHNA
To have accessible health care is to be able to receive
community survey data, community
physical, mental, and spiritual support in order to live amembers shared barriers thatholistically healthy life.
prevent or have prevented themfrom accessing the health care theyneeded when they needed it andfrom leading a healthy life in the region. Community members identified experiences related to
information accessibility and service availability; affordability and health insurance; and feeling unsafe
and having negative past experiences as barriers to accessing quality health care when they need it.

100Barriers Rooted in Limited Accessibility to Healthcare Information and Service Availability
Lack of Centralized, Up-to-Date Information
on Healthcare Services and Providers
Community Members’ Access to Quality HealthAcross the region, 14% to 20% of Regional
Care is Limited by:
CHNA community survey respondents• A Lack of Centralized, Up-to-Date
reported they do not know where to get
Information on Healthcare Services andhealth care that is right for them (Figure
ProvidersC3). In focus groups and interviews,• A Limited or Lack of Access to Culturally
community members identified a need for acentralized resource where they could more
and/or LGBTQ+ Competent Healthcare
easily find a healthcare provider in their
Professionals
insurance network at a reasonable• A Limited Number of Service
geographic distance and find a healthcare
Appointments and Appointment Times
professional that matches
race/gender/culture preferences. In focus
groups and interviews, community
members and providers alike highlighted the difficulty in finding accurate information because insurance
policies, healthcare staff, and services change often. Community members reported that evenorganizations did not keep their websites up-to-date. Community members and providers agree in focus
groups and interviews that outside of one’s department, there is little understanding of what services
are available, even within the same service organization or hospital system. As a result of the difficulty in
identifying a healthcare professional, community members report opting not to receive health care.
Community members reported that the lack of a centralized resource for healthcare service information
also means there is a lack of a centralized resource for local public health information that is trusted.
Community members suggest that if there was a resource where the public could search for healthcare
professionals that meet their preferences and this source was found reliable, this resource could also beleveraged to communicate accurate health information and discredit misinformation (for example with
COVID-19).
Mental health care, primary care, and reproductive health care were three areas where community
members most often expressed a need for having a preference of physician gender and race. In focus
groups, Black, African New Americans and immigrants, and Muslim community members also identified
poorer quality in terms of maternal health care during delivery and postnatal periods. For example,
Muslim community members recalled experiences where male doctors were sent to deliver the baby or
perform an exam on the mother, despite making specific requests for female doctors only. Black andMuslim adults expressed a feeling of disempowerment at hospitals during delivery, feeling little power
to advocate for their needs or fearing a backlash when they do advocate for themselves or a loved one.

101

Figure C3. Barrier to Care: Not Knowing Where to Go to Get
CareOverall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
I do not know where to go to get the care that is right for
me.

14%

20%
18%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Limited or Lack of Access to Culturally and/or LGBTQ+ Competent Healthcare Professionals
A greater percentage of Regional CHNA community survey respondents in the Cincinnati MSA and inrural counties reported not being able to find a doctor who understood/respected their culture and/or
gender identity or sexual orientation compared to Dayton MSA. The same is also true for Regional CHNA
community survey respondents who reported not being able to find a healthcare professional who
spoke their language or had translation services (Figure C4).
According to UC interview data, misgendering and obtaining gender-affirming prescriptions andtreatments are priority issues for health care among the LGBTQ+ community. In rural areas, these issues
are exacerbated as there are often limitations on the number of providers who have the medical andsocial skills to support LGBTQ+ community members. When competent providers are not available,interviewees indicated that community members oftentimes choose to discontinue care altogether.
Community members in focus groups and interviews who do not speak English, who speak English as asecond language, or who are advocates for immigrant community members identified cultural andlanguage barriers as a primary cause for low quality health care for minority communities. “Asian
immigrants who have been here for a while still feel they are not getting quality care because doctors do
not understand their culture or parts of their language. That is a persistent problem. There are people
here who could help bridge the language barrier and they need to do that,” explained a focus groupmember. “Another thing I’ve noticed is many providers simply look at the skill sets of the interpreter but
it turns out they can just speak the language but do not have an understanding of the culture and thatcan be disastrous. It’s very important to have an interpreter who does not just interpret the language
but who also has the ability to understand the cultural context of the patient,” explained a physician.

102

Figure C4. Barriers to Care: Inclusivity

Overall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
I experience discrimination in healthcare due to my race
and/or culture.

8%

I can't find a doctor who understands/respects my culture.

7%

I can’t find a doctor/provider who speaks/uses my languageor has translation services available.
I experience discrimination in healthcare due to my gender
and/or identity/sexual orientation.
I can't find a doctor who respects my gender identity orsexual orientation.

14%
10%
13%
10%
12%

7%

11%

7%
8%

14%
12%
15%
13%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Black community members in focus groups expressed feelings that “my doctor doesn’t listen to me.”Asian and Hispanic community members expressed feelings of not being understood. Community
members across all focus groups expressed a feeling that healthcare professionals do not know about or
understand the impact of community members’ past experiences or traumas on the experience ofreceiving health care, including culturally specific traumas faced by immigrants, experiences of racism inAmerica, being a victim of violence, and/or traumas related to poverty. In fact, among Regional CHNA
community survey respondents who reported not being comfortable talking with healthcare providers,
49% or more in the MSAs and rural counties reported that feeling heard would improve their
comfortability (Figure C5).
Regional CHNA community survey results also show that compared to White community members,
multiracial and other race individuals (Asian, American Indian/Alaskan Native, Native Hawaiian or PacificIslander or another race that is not Black, White or multiracial), and younger community members are
more likely to report being uncomfortable speaking with healthcare professionals. When community
members do not feel heard they reported being more hesitant to trust a diagnosis, to follow treatment
plans, and/or to attend future healthcare appointments, according to focus groups.

103

Figure C5. Opportunities to Increase Patient Comfortability inAccessing Care
Which of the following would make you feel more comfortable talking with ahealthcare provider? Check all that apply.

Feeling that my healthcare provider was listening
to me or understood my health concerns

49%
56%
51%

They were of the same race or cultural backgroundas myself

41%
39%
37%

If I were able to talk to my provider without feelingembarrassed about my health concerns

28%
31%

Being able to talk to my provider in person rather
than virtually

37%
37%

If I trusted providers would have my best interestin mind

22%
25%

They were of the same gender as myself

18%

Being able to talk to my provider over the phone orcomputer rather than in person

15%

If there were no other people in the room whentalking to my provider

14%
12%
13%

Other reason

3%
5%
3%

If it were easier to communicate through aninterpreter (if needed)

2%
4%

32%

23%
24%

14%

They use words I can understand

44%
42%

23%
22%
26%
23%

7%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Limited Number of Service Appointments and Appointment Times
About one in three Regional CHNA community survey respondents across the region reported having to
wait a long time in a waiting or exam room and/or not being able to make an appointment for healthcare because appointments were not available after work hours or during weekends (Figure C6).
Across focus groups, community members reported similar experiences. In particular, mental healthcare, OB/GYN, and other medical specialist’s care were the most common healthcare services that
community members reported having to wait multiple months for a first appointment. In focus group
and Regional CHNA community survey data, veterans also reported long wait times for VA healthcare
services. Community members in focus groups that reported not having to wait long to get an
appointment reported it was due to having private insurance, a flexible work schedule, and/or apersonal connection to a physician who could fast-track a referral. These results are also replicated in
the Regional CHNA community survey data as well.

104

Figure C6. Lack of Appointment Accessibility

Overall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
34%
32%
34%

I have to wait a long time in the waiting or exam room tosee a doctor.
21%
18%
18%

I have trouble getting someone to call me back forappointments.

31%
32%
31%

I can't make an appointment because they are not available
after hours or on weekends.

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Furthermore, community members highlighted that even after overcoming barriers to getting an
appointment, the quality of the healthcare services is diminished when doctors rush into and out of
appointments. While physicians know the “15-minute appointment” to be a policy goal, community
members associate the short appointments as:a. an indication that healthcare professionals care more about making money than making thebest decisions for the health of the patientb. a reason to doubt diagnosis or treatment plans because doctors do not know enough about thepatient’s symptoms or stresses at homec. a reason to avoid health care overall in the future, for what is the point of paying for anotherdoctor visit if it’s only for 15 minutes?
d. an impossible time frame for community members with disabilities or language barriers to havea meaningful conversation with a physician with a good level of comprehension on both sides
Due to the long waits for getting a first appointment, community members reported being caught in an
uncomfortable position when that appointment turns out to be a negative experience. Community
members are left with the choice to continue services with a healthcare professional that makes them
uncomfortable/doubt diagnosis or wait another long period to be a “new patient” somewhere else.
Community members are in a particularly vulnerable position when it comes to mental health, where agood relationship with a clinician is critical to success but service availability is acutely low; and when it
comes to specialty services that require immediate intervention.

105

Barriers Rooted in High Healthcare Costs and Convoluted Insurance Policies
Limited or Lack of Resources to Pay
for and/or Receive Healthcare Service

Community Members’ Access to Quality

Upwards of one in five Regional CHNA
Health Care is Limited by:community survey respondents across• Limited or Lack of Financial Resources to Pay
the region reported not being able tofor Healthcare Service
afford their medications and/or toafford to go to the doctor (Figure C7). In• Limited or Lack of Transportation
focus groups, community members• Limited or Lack of Technology Resources toreported the unknown cost of a
Receive Health Carehealthcare service (e.g., a “surprise• Limited Experience Navigating Healthmedical bill”) made them avoid seeking
Insurance Systems
health care even when they knew theyneeded care. This was true even forsome focus group participants that had
private health insurance and identified as likely having enough money to cover costs. Community
members shared that they would be more motivated to receive health care if they were clearly
informed of the cost ahead of time. Even if it was a more expensive intervention, they could plan ahead
for the expense.
In focus groups with community members, a limited or lack of transportation was a primary reason for
not receiving needed health care. This also includes commutes being too long (in distance, in time, orboth), even when individuals have access to a personal vehicle or public transportation. In particular,
improved coordination of health care and transportation and other services is needed for low income
and older adult community members. “There should be more convenience for the elders of any
community to access health care. Transportation is needed because the elders don’t drive. Any time
there is an appointment they should make sure there is transportation to get them to the appointment.
There are others who have pacemakers and are living on machines, and the language barriers make it
hard for them to read instructions and learn how to maintain those machines. So, there needs to be
regular house nurses. Often times, elders are more traumatized over how to handle [medical] gadgets
than taking care of their sickness,” explained a community member. Community members transitioningout of jail/prison, shelters, and/or recovery/halfway housing also identified the need for morecoordination between their healthcare and social service providers.
Access to reliable internet has become a basic need. Healthcare institutions are shifting more and moreof their patient communication/service options to online platforms. According to Regional CHNA
community survey results, about 15% of community members in rural counties and the Cincinnati MSA
reported not having reliable internet or a computer for telehealth.

106Figure C7. Barriers to Care: Resources

Overall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
I do not have a reliable computer or internet to do Telehealthservices.
I do not have a telephone to make doctors/healthcare
appointments.

16%

9%

5%

15%
12%

9%

I can't afford my medications.

15%

I can't afford to go to the doctor.

21%
18%
19%

21%
21%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Limited Experience Navigating Healthcare and Health Insurance Systems
Community members in focus groups explained they only learned how to navigate the healthcare
system after negative and/or expensive experiences. Young professionals new to employee-based
health care and managing their own healthcare insurance expressed a lack of knowledge as to what
their insurance covers and how to anticipate healthcare costs. Veteran community members explainedthat they struggle with not only the navigation of the VA health system, but also the insurance
policies/networks of their spouse and children. New American, immigrant, second generation
Americans, and Black community members expressed a desire for more knowledge and skills navigating
health care and insurance because their families have limited generational knowledge of the workings ofhealthcare and insurance systems. Service providers to low-income community members identified aneed for better informing the public on Medicare options, particularly for adults who are uninsured but
not yet Medicaid eligible. Furthermore, focus group participants were generally not aware of financial
assistance policies related to healthcare expenses.
“As a child we didn’t go to the doctor. So now, as an adult we struggle with going to the doctor,”
explained a Black community member.

107

Barriers Rooted in Negative Past Experiences and Negative Perceptions of the Healthcare System
Perceptions that Healthcare Providers
Care More About Money
Community Members’ Access to Quality
Overall, community members in eachregion of this Regional CHNA perceive
Health Care is Limited by:that the healthcare system does not• Perceptions that Healthcare Providers Carehave the best interest of community
More About Money
members in mind (Figure C8). Across• Feeling Unsafe in Receiving Carefocus groups, community members• Experiences of Discrimination whenspoke about healthcare providers,Receiving Care
hospitals, clinics, pharmacies, insurance• Fear of Judgementcompanies, health departments, etc. as asingle system that generally favors profit
over what is best for patients.
Community members, in general, do not distinguish a physician/clinician from hospital administration.
In focus groups, positive perceptions of health care were associated with single physicians that spent“extra” time or “went above and beyond” to get a community member connected with a needed
service. In these cases, community members saw these doctors as “different from the system. They careabout what is best for [people], not our money.”

Figure C8. Community Member Perception of Healthcare
SystemOverall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
20%

I don’t get health care because I don't think the healthcare
system has my best interests in mind.

14%
18%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Feeling Unsafe in Receiving Care
Feeling safe in getting to and receiving health care is a concern among community members. Interview,
focus group, and Regional CHNA community survey data highlighted that the COVID-19 pandemic has
had a significant impact on community members’ sense of feeling safe to receive healthcare services.
Healthcare professionals reported in focus groups that people are signing out of hospitals because they
are scared to stay overnight, lest contracting COVID-19. “Volumes remain high in emergency
departments. Not due to COVID patients, but its fallout of not managing health over the past year: notmanaging diabetes or hypertension, ignoring that stomach pain for fear of being infected. This is incombination with all the people that lost their jobs due to COVID, and therefore their health insurance.

108

We need more effort to tell the public that it is safe to seek health care in the ER,” explained an
Emergency Room Physician.
In expert interviews, providers and community advocates noted that some community members will notseek health care even when they need it due to fear that they will be punished or stigmatized for theircitizenship status.
In focus groups, Black and older adult community members identified a lack of feeling safe in theirhomes/neighborhoods as a health risk, but also as a barrier to accessing health care (e.g., waiting for abus is not safe), food (e.g., not safe to walk to go grocery shopping), and to socializing (e.g., not safe toattend local social events).
According to Regional CHNA community survey data regression analysis, community members
unemployed and looking for work, who are men, in race category Other, who have a military
background, who do not have private insurance, living in the Cincinnati MSA, and/or who have limited
or no English language ability are significantly more affected by the safety barrier to receiving
healthcare. 77 Across the region, community members in the Cincinnati MSA were more likely to feelunsafe receiving health care due to COVID-19 compared to the rest of the region (Figure C9). However,Regional CHNA community survey data shows an opportunity to improve comfort levels related to
COVID-19 by offering more telehealth services (Figure C10).

77

The outcome for this multiple linear regression was calculated by taking the average of responses to the last two questions inFigure C9 regarding feeling unsafe going to healthcare facilities. Lower scores indicate the safety barrier to receiving health careis less of an issue. On average, males have an expected mean safety scale score 0.15 higher than females, adjusting for all otherpredictors. (b = 0.15, p < 0.001); On average, “Other” race individuals have an expected mean safety scale score 0.29 higher
than White individuals, adjusting for all other predictors. (b = 0.29, p < 0.001); Those living in Cincinnati MSA have an expected
mean safety scale score 0.21 higher than those in Dayton MSA, and 0.16 higher than those in Rural counties, adjusting for allother predictors. (b = -0.21, p < 0.001; b = -0.16, p < 0.001); Active military and veterans have expected mean safety scalescores 0.25 points higher than those not in the military, adjusting for all other predictors. (b = 0.25, p < 0.001); Those without
private insurance have expected mean safety scale scores 0.31 points higher than those with private insurance, adjusting for allother predictors. (b = 0.31, p < 0.001); Those who speak no English have expected mean safety scale scores 0.64 points higher
than those who speak English fluently, adjusting for all other predictors. (b = 0.64, p < 0.05); Those who speak limited English
have expected mean safety scale scores 0.37 points higher than those who speak English fluently, adjusting for all otherpredictors. (b = 0.37, p < 0.001); Those who are unemployed and looking for work have an expected mean safety scale score0.24 points higher than those fully employed, adjusting for all other predictors. (b = 0.24, p < 0.001).

109

Figure C9. Barriers to Care: Safety

Overall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
41%
42%
45%

I put off health care because I think my symptoms will improveon their own.
I don't get health care because I fear what it will say about myhealth.
I feel unsafe in the location/neighborhood of the healthcare
facility.

13%
15%
7%

I feel unsafe going to a healthcare facility because I fear I could
get COVID-19.

19%

15%
13%
18%

32%
24%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

110

Figure C10. Opportunities to Increase Patient Comfortability inAccessing Care
Which of the following would make you feel more comfortable talking with ahealthcare provider? Check all that apply.

Feeling that my healthcare provider was
listening to me or understood my healthconcerns

49%
51%

56%

41%
39%
37%

They were of the same race or cultural
background as myself
If I were able to talk to my provider without
feeling embarrassed about my healthconcerns

28%
31%

Being able to talk to my provider in person
rather than virtually

37%
37%

22%

If I trusted providers would have my bestinterest in mind

25%

They were of the same gender as myself

18%

Being able to talk to my provider over thephone or computer rather than in person

15%

If there were no other people in the room
when talking to my provider

14%
12%
13%

Other reason

3%
5%
3%

If it were easier to communicate through aninterpreter (if needed)

2%
4%

32%

23%
24%

14%

They use words I can understand

44%
42%

23%
22%
26%
23%

7%

Data Source: Regional CHNA Community Survey Results

Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

111

Negative Past Health Care Experiences Rooted in Discrimination
As shown in Figures C11 and C12, community members reported in the community survey that theyexperience barriers related to inclusivity. In focus group and Regional CHNA community survey data,
community members reported having personally experienced discrimination by a healthcare
professional. As community members generally perceive all healthcare institutions as a single system, asingle experience of discrimination or experiences someone they know, perpetuates a negative
perception of all healthcare institutions and healthcare professionals. Experiences of discrimination also
make it easier for disinformation to take hold, like in the case of COVID-19 vaccinations, according toBlack community members in focus groups.

Figure C11. Barriers to Care: Inclusivity

Overall, how often have the following been true for you when seeking/receiving
health care? % Sometimes to Always
I experience discrimination in health care due to my race
and/or culture.

8%

I can't find a doctor who understands/respects my culture.

7%

I can’t find a doctor/provider who speaks/uses my languageor has translation services available.

11%

7%

I can't find a doctor who respects my gender identity orsexual orientation.

13%
10%
12%

7%

I experience discrimination in health care due to my gender
and/or identity/sexual orientation.

14%
10%

8%

14%
12%
15%
13%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

Fear of Judgement or a Negative Diagnosis
Across focus groups, community members reported feeling judged by healthcare providers, rather thanbeing supported to overcome unhealthy habits. Community members in recovery, homeless community
members, and incarcerated/justice-involved community members also reported feeling judged bymental healthcare providers. In general, when community members spoke about feeling judged, it went
hand in hand with healthcare professionals “talking down” to community members. In fact, Regional
CHNA community survey data regression analysis shows that community members who are men, thosefalling in race category “Other”, less educated, unemployed and looking for work, involved in the
military, with a disability, speak little to no English, and/or without private insurance are significantly
more affected by the barrier to healthcare of stigma and fear of negative diagnosis. 78
78

The outcome for this multiple linear regression was calculated by taking the average of responses to the two questions inFigure C12, as well as the question regarding fear of what the healthcare provider will say about their health in Figure C9. The
scale is a 5-point scale. Lower scores indicate the stigma and fear barrier to receiving healthcare is less of an issue. On average,
males have an expected mean stigma scale score 0.11 higher than females, adjusting for all other predictors. (b = 0.11, p <0.001); On average, “Other” race individuals have an expected mean stigma scale score 0.17 higher than White individuals,

112

Community members who are caretakers of family members were also more likely to describe
experiences of being judged and undermined by healthcare professionals.

Figure C12. Barriers to Care: Stigma

Overall, how often have the following been true for you whenseeking/receiving health care? % Sometimes to Always
I don't get health care because I fear the healthcare
workers will judge me.

11%

I don't get health care because I fear what my friends,
family, or community will think about me for going.

7%

16%
14%
13%

11%

Data Source: Regional CHNA Community Survey Results
Cincinnati MSA

Dayton-Kettering MSA

Rural Counties

adjusting for all other predictors. (b = 0.17, p < 0.001); Those with a graduate degree or higher have an expected mean stigma
scale score 0.10 points lower than those with a high school diploma/GED, adjusting for all other predictors. (b = -0.10, p < 0.05);
Those living in Cincinnati MSA have an expected mean stigma scale score 0.11 higher than those in Dayton MSA, and 0.09
higher than those in Rural counties, adjusting for all other predictors. (b = -0.11, p < 0.001; b = -0.09, p < 0.001); Active militaryand veterans have expected mean stigma scale scores 0.37 points higher than those not involved with the military, adjusting for
all other predictors. (b = 0.37, p < 0.001); Those without private insurance have expected mean stigma scale scores 0.26 points
higher than those with private insurance, adjusting for all other predictors. (b = 0.26, p < 0.001); Those who speak no English
have expected mean stigma scale scores 0.73 points higher than those who speak English fluently, adjusting for all otherpredictors. (b = 0.73, p < 0.05); Those who speak limited English have expected mean stigma scale scores 0.39 points higher
than those who speak English fluently, adjusting for all other predictors. (b = 0.39, p < 0.001); Those who are unemployed andlooking for work have an expected mean stigma scale score 0.18 points higher than those fully employed, adjusting for all otherpredictors. (b = 0.18, p < 0.05); Those with a disability have an expected mean stigma scale score 0.17 points higher than those
without a disability, adjusting for all other predictors. (b = 0.17, p < 0.001).

113

15. Appendix D: Service Model, Policy and Practice Initiatives
Identified by Region’s Healthcare Professionals and Community
Members
The service model, policy, and practice initiatives in the list below were identified
by asking healthcare professionals and community members about what is working
well when it comes to health care in the region or their neighborhoods. These
insights can be leveraged in order to identify common goals, action steps, andstrategic partners. These are the assets/resources health systems should focus onwhen designing strategies for addressing the prioritized health needs. More details
about the listed initiatives can be found in the following section.
1. Good Food Purchasing Program
2. Mobile Food and Basic Needs Truck
3. Initiate partnership with City planning agencies
4. Better leverage public transportation agencies/transit authorities
5. Health and Cultural Fairs
6. School-based Healthcare Model
7. LGBTQ+ affirming care practices based on Human Rights Campaign’s Healthcare Equality Index
8. Peer Supporter Model
9. Strategic coordination between healthcare provider and pharmacies
10. Invest in centralized resource for community members to find services, providers that meetneeds/preferences, and healthcare cost transparency across the region
11. Culturally competent design of healthcare spaces
12. Coordinate advocacy efforts
13. Maintain best practices (and failed practices to avoid) learned from regional collaboration
during COVID-19 pandemic and in Opioid epidemic.
14. Doula Model
15. Community Health Worker Model and On-site Social Workers
16. Improve and initiate partnerships with Community Based Organizations
17. Invest in future healthcare workforce through partnering with schools and Career Stat Network
Hospitals
18. Establish regional approach to screening for health and SDOH-related needs/supports
19. Additional safety and prevention interventions
20. Additional partnership opportunities

Recommendations from Community and Providers: Service Model, Policy, and Practice
Initiative
1. Good Food Purchasing Program, as modeled by Cincinnati Public Schools. Cincinnati Public
School District (CPS) adopted the Good Food Purchasing Program and is a model for healthy
local food messaging, food education, and leveraging system-level purchasing power to improve
food security in their communities (https://goodfoodcities.org/portfolio/cincinnati/).
a. There is the opportunity for healthcare and hospital systems to adopt the program aswell, leveraging their purchasing power to drive improved regional food systems and114

local supply chains. The region’s health system can also look to the coalition practices
Cincinnati Public Schools used to adopt the program.
b. “Coalition of stakeholders came together to advocate that CPS should adopt this policy;
other partners worked with the food service director to make the shift doable… To makechange in food security, you need to get the attention of big distributors like Cisco. [Toget their attention, you need large institutions like CPS and hospitals] to request union,
organic poultry in order to get the distributor to be incentivized to carry it, for example.”-Regional Food Systems Expert
2. Mobile Food and Basic Needs Truck. This was identified by older adults in Dayton as the best
way for them to access healthy foods and ingredients to cook themselves in theirneighborhoods, as opposed to frozen meals they receive weekly. The truck also carries basic
household supplies and cleaners and provides coupons/vouchers to increase affordability.
Having the truck come directly to apartment buildings was key to older adults accessing
foods/goods, even providing help to carry groceries to their door. Green Umbrella for healthy
food systems in the region were identified as a potential partner. The Urban Institutes’
Disrupting Food Insecurity model (https://apps.urban.org/features/disrupting-food-insecurity/)and strategies to address root causes (https://apps.urban.org/features/disrupting-foodinsecurity/Strategies_full%20list.pdf) is also another framework through which to identify action
steps for the region.
3. Initiate partnership with City planning agencies. Healthcare professionals and community
experts identified opportunity to increase partnership and engagement with city planning
agencies in order to think about health care in neighborhood design, increase equity in locationof health providers, as well as making more equitably accessible outdoor and other recreational
spaces. Healthy Places by Design was identified as a potential partner. Better partnerships with
Community councils and movement organizations that neighborhoods have in order to build
trust and ongoing engagement.
4. Better leverage public transportation agencies/transit authorities. Transit authorities reportbeing more flexible than perceived to be by healthcare professionals/administrators. Transit
experts explained being a public service and adapting to healthcare providers’ and community
members’ needs to the best of their ability. Transit authorities would be better positioned toserve community if healthcare institutions took on responsibility for Medicaid billing, rather
than requiring transit authority to learn it. Successful models:a. Days with big buses for free transportation for vaccinations, back-to-school physicals,
dentist visitsb. Individualized service contracts with healthcare provider centersc. Dedicated day of appointments for patients using public transport
d. RTA Works with veteran service commission for vet to get to non-emergency medical
appointments- those are coordinated with Lyft, Uber, Taxi to find the cheapest rideavailable. Benefit is that it costs less than what transit would charge. The challenge isthey are not disability accessible. Uber and Lyft let us get to veteran faster than transit

115

could get to them; Transit authority does all the scheduling, so veteran does not have toworry about it.
e. Shuttle service set for certain days from shelters to health/mental provider- standing
contract.
5. Health and Cultural Fairs. Immigrant, New Americans, Hispanic, Black and Asian community
groups identified local health fairs and cultural fairs where health tents were present as aneffective model for accessing health care (e.g., learning about available services, preventative
care, building relationships with healthcare professionals, etc.)
6. School-based Healthcare Model
How does the initiative address community health needs?
Establishing working partnerships with school districts increases access to health care forcommunity members and promotes more preventative health care behavior and wellness.
Partnerships can lead to school-based clinics and mobile health clinics being hosted in school
parking lots (e.g., youth physicals, mammograms, dentistry care, etc.). School-based health careincreases access in terms of affordability (can be free) and accessibility (timesaving, lower
transportation needed).
When school districts have positive relationships with communities, schools can provide
healthcare professionals the opportunity to build trust with communities as well, improving thequality of health care in the region.
School-based healthcare initiatives were reported by rural county community members as
having positive outcomes. In developing initiatives, be intentional about providing health care ina non-stigmatizing way.
How does the initiative address structural barriers to improved health outcomes and healthequity?
Healthcare initiatives successful in school settings are more often associated with preventative
health care behavior and wellness. Prioritizing these partnerships can help to balance how theregion approaches treating illness versus preventing illness.
7. LGBTQ+ affirming care practices based on Human Rights Campaign’s Healthcare Equality Index
8. Peer Supporter Model
How does the initiative address community health needs?
Peer Supporter Model increases access to and quality of mental health care for higher-risk
community groups. Healthcare professionals, social service providers and community membersin this Regional CHNA identified that the Peer Supporter Model is/would be effective for better
serving:••First responders
Community members with lived experiences with substance abuse disorders
116

•
•
•
•
•

Community members with lived experiences with human trafficking
Community members with lived experiences with domestic violence
Military active duty and veteransBlue Star Family Members
Caretakers for family members

How does the initiative address structural barriers to improved health outcomes and healthequity?
Peer Supporter Model shifts power dynamics towards more equitable power over knowledge
and system navigation skills. Peer Supporter Model shifts power to the community, particularly
those with lived experiences. Peer Supporter Model also increases employment opportunities
and professional development of communities currently facing healthcare inequities. Down theline, this is also a viable solution to increasing workforce diversity among mental healthcare
professionals: community members helped by Peer Supporters can be inspired to pursue mental
healthcare careers; and Peer Supporters themselves gain experience with a range of mental
healthcare career tracks in which they could pursue.
Strategic Action Steps Identified by Regional CHNA
•

•
•
•

•

•

•

Collaborate to advocate for sustainable funding sources for long-term support of Peer
Supporters across the region. Current billing is not sustainable on its own, hospitals
currently have to find additional funding to employ Peer supporters.
Collaborate to advocate for integration of Peer Supporters throughout region’s healthsystemPeer Supporters can be strategically placed within the health system to align withpriority populations
Working group to assess what is working well in the Peer Supporter model, what could
be better in the region, including standardized certifications and certification
accessibility
Strategically recruit new Peer Supporters (providing them with transparent knowledge
and skills for navigating health care) from community-based organizations that
represent priority populations in order to create collaborative and trusting partnerships
for all future health initiatives.
Train healthcare professionals on how to pay/bill for Peer Supporters and how to work
effectively with Peer Supporters on-site in emergency departments, Fire/EMS stations,
Police departments, etc. Peers on-site are also effective in terms of continuous
education for medical staff in terms of cultural competency and trauma-informed
treatment/care.
In first responder partnership, consult on legislation to clarify if what is told to a Peer
Supporter is confidential or discoverable (currently policy in draft stages to introduce it).

9. Strategic coordination between healthcare provider and pharmacies. Charity pharmacies havebeen found to reduce ER visits among community members using the charity pharmacy. If
emergency departments invested resources into charity pharmacies, their costs associated withtreating uninsured community members would be reduced. In addition, primary care physicians117

could increase knowledge of patients’ adherence to prescriptions by communicating more withpharmacies to track pick-up dates. National Association of Free Clinics and Charitable Healthcare
Network can be a model for partnering with pharmacists.
10. Invest in centralized resource for community members to find services, providers that meetneeds/preferences, and healthcare cost transparency across the region. Prioritize usability andlanguage. Invest in community members’ skills and knowledge to know costs of care ahead oftime and increase transparency of cost assistance policies. Also, invest in community partners’
knowledge and ability to leverage Medicaid benefits for community members, and billing forservices they are providing.
11. Culturally competent design of healthcare spaces. This involves the consideration of how thephysical space of where health care is provided impacts how safe and welcomed community
members feel.
12. Coordinate advocacy efforts. Lead region to publicly recognize racism as a public health crisis.
POLICYLINK was identified as a resource for helping to coordinate service, funding and policy
partnerships in health care - this can help to identify action steps to overcome competitive
structures.
13. Maintain best practices (and failed practices to avoid) learned from regional collaboration
during COVID-19 pandemic and in Opioid epidemic. Healthcare professionals identified benefitsof COVID-19 collaborations that the region’s health system can keep or advocate to continue:
a. Collective action designed funding, less restrictive dollars
b. Regular meetings where boots-on-the-ground staff were recognized as experts;
meetings included funders, boots-on-the-ground staff, and CEO/Director administratorsthat had decision-making power (meetings were not individually helped by level of staff)
c. Private businesses engaged (e.g., Kroger provided their data analytics team, mapped
distribution of foods when all partners submitted their data to Kroger)
d. Children’s Hospital and UC contributed to data and strategic interventions
14. Doula Model. According to Community Health Advocates for Black community members,
increasing access to doulas is an effective way to increase cultural relevancy of maternal healthcare and to personalize support for women -prenatal, birth, and postnatal.
15. Community Health Worker (CHW) Model and On-site Social Workers
How does the initiative address community health needs?
To address healthcare affordability, CHWs/LSWs can specialize in:
•
•
•
•
•

Interpretation of insurance policy and navigation of insurance customer service
Medicare/Medicaid eligibility and navigation of application process
Hospital financial assistance policies and procedures
Navigation of prescription costs and charitable pharmacy eligibility/transition
Navigation of basic needs for older adults118

To address economic stability, CHWs/LSWs can specialize in directly connecting (e.g., meetingsocial workers with community members, making phone calls with community members, etc.)
community members to social services like transportation, housing, food pantry, SNAP, etc.
CHWs can increase the quality of health care when:

CHWs are on staff or have an on-site office (e.g., in emergency departments, hospitals,
clinics, doctor offices, schools, health departments, etc.)
Have mutually respectful and collaborative professional relationships with healthcare
professionals with whom they work
Are compensated with wages and benefits that reflect the value added to the quality ofhealth care and health outcomes for the system’s community members

CHWs and Social Workers can increase the quality of health care because:







They increase the cultural relevancy of health care in that they often share cultural
backgrounds, language, and lived experiences with community members/patients.
Healthcare professionals may not be able to increase their face-to-face time withpatients. CHWs/LSWs can provide that extra time with patients needed for screening
for needs and information sharing.
CHWs can build working relationships with healthcare professionals, offering
opportunities for CHWs/LSWs to pass on best practices in cultural and traumainformed care to healthcare professionals.
CHWs can support transitions when community members are changing providers,
adding a new provider, etc.

Providers and community members identified the following areas where CHWs/LSWs would
have great impact:






On-site in jails/courts for community members transitioning back into the communityand for individuals on probation. Medical issues can contribute to someone breaking
probation. While these occurrences are typically resolved, the resolution takes a while.
This period triggers a lot of stress and fear in an individual on probation.
On-site at shelters for community members transitioning out of shelter into thecommunity
Embedded in community-based organizations (CBOs), schools, and cultural centers
On-site in emergency departments, health department programs, clinics, healthprovider offices

How does the initiative address structural barriers to improved health outcomes and healthequity?
CHW Model shifts power dynamics towards more equitable power over knowledge and systemnavigation skills. CHW Model shifts power to the community, particularly women of color. CHW
Model also increases employment opportunities and professional development of communities
currently facing healthcare inequities. Down the line, this is also a viable solution to increasing
workforce diversity among healthcare professionals: community members helped by CHWs as

119

children or young adults can be inspired to pursue healthcare careers; and CHWs themselves
gain experience with a range of healthcare career tracks in which they could pursue.
Strategic Action Steps Identified by Regional CHNA
•
•
•

•
•

•
•

Collaborate to advocate for sustainable funding sources for long-term support of CHWs
across the region.
Collaborate to advocate for integration of CHWs throughout region’s health system.
CHWs can be strategically placed within the health system to align with diseasepriorities, for example heart and/or lung disease clinics, diabetes specialists,
maternity/OBGYNs, etc.
Set regional standards of skills/knowledge for CHWs that align with priorities, fundtrainings to make the skills/knowledge available to current and prospective CHWs.
Strategically recruit new CHWs (providing them with transparent knowledge and skills
for navigating health care) from community-based organizations that represent priority
populations in order to create collaborative and trusting partnerships for all future
health initiatives.
Train healthcare professionals on how to pay/bill for CHWs and how to work effectively
with CHWs on-site.
While published in 2016, UHCAN’s Integrating Community Health Workers in Ohio’s
Health Care Teams outlines a number of specific action steps and CHW models for theregion to consider. https://www.chcf.org/wpcontent/uploads/2021/02/IntegratingCHWsOhiosHealthCareTeams.pdf

16. Improve and initiate partnerships with Community Based Organizations (CBOs) to identify
CHWs, consult on translation services, build trust between healthcare professional andcommunity members, identify/promote culturally relevant prevention/wellness programming(e.g., social connectivity, yoga, food education). “We counted there were 32 different countries
represented in Dayton. I’m lucky the only time I’m with a doctor is during my annual physicalbut communication wise there are some medical terms I have a hard time understanding what
they are in English. With the doctor it seems they don’t have a lot of time to spend. We may get
15 minutes if lucky. That presents some challenges right there. Maybe if they had a list with
common medical terms in English and other languages,” suggested an Asian community
member.
Region’s healthcare providers to standardize HIPAA interpretation for the region and in
preparation of HIPAA policy changes and future CBO partnerships to address SDOH (e.g., mental
health and health care in jails; for community members transitioning in/out of shelter system
and justice system; between hospitals and county health departments).
17. Invest in future healthcare workforce through partnering with schools and Career Stat
Network Hospitals. Hospitals feel huge pressure of hiring locally, but not finding the talent pool.
This is where systems can come together. Partner with schools to increase youth exposure to
the diversity of healthcare careers and their career paths while still in school. Partner with120

apprenticeships, internships, and community colleges. Also, improving healthcare experiences
across communities will inspire more members to pursue healthcare professions.
18. Establish regional approach to screening for health and SDOH-related needs/supports,
including the sharing of screening results.
19. Additional safety and prevention interventions identified by community:
a. Lobbying region’s states to pass Erin's Law, which requires all public schools to
implement a prevention-oriented child sexual abuse program.
b. Sharing the Safer Campus Guidebook
c. Safe Bars helps bars, restaurants, breweries, and other alcohol-serving spaces create
safe and welcoming cultures for patrons, and safe and respectful spaces.
20. Additional health care and community organization partnership opportunities, identified bycommunity:a. Early childhood centers
b. Mental Health First Aid training providers
c. Crossroads Centerd. All-in Cincinnati for economic stability of Black womene. Urban League
f. The Center for Closing the Health Gap for engaging community
g. Catholic Social Services for reaching immigrant populationh. Helen Jones-Kelley at Montgomery County ADAMH board
i. Caracole, which provides HIV/AIDS prevention, housing, case management, andpharmacy services
j. Heartland Trans Wellness
k. Central Clinic’s transgender wellness programl. Queen’s Village
m. UC welcomes the opportunity to support this work. Please reach out with your request
and I will do my best to connect you with potential resources at UC. This could be interms of research support, interns, co-ops, Service-Learning classes, funding support topay interns, collaboration on grants, sprints, etc. Paula.Harper@uc.edu
n. Regional veteran and Blue Star family organizations that provide a range of social
services for veterans and their families when connected to them. Healthcare
professionals can play a larger role in making those introductions.

12116. Appendix E: Local Implementation of Best Practices to Overcome
Barriers to Health Care
Staff Development and Recruitment
There is opportunity to increase organizations’ implementation of best practices across all areas, withfewer than half of providers indicating their organization has successfully implemented most bestpractices surveyed. However, healthcare providers working in the Dayton MSA are most likely to report
implementation of the various best practices surveyed. Among best practices related to staff
development and recruitment, the most common successfully implemented best practice is recruiting
diverse staff that is representative of the populations served with four in ten providers in the Cincinnati
MSA and Rural regions, and six in ten providers in the Dayton MSA, indicating their organization has
successfully implemented this (Figure E1).

Figure E1. Best Practices Surrounding Staff Development andRecruitment for Healthcare Providers% My department or organization successfully implements this in some or all areas
42%

Recruits diverse staff that is representative of all the
populations your department serves

59%

41%

Provides requirements for continued learning of new
medical data/techniques/treatments

32%

Provides time for continued learning of new medical
data/techniques/treatments

33%

Provides time for continued professional development incultural competency

33%

51%

35%
34%
35%
30%

Provides scholarships or apprenticeships for minority
individuals to begin careers as a healthcare professional

26%

45%
45%
43%

34%
41%
36%

Provides requirements for continued professional
development in cultural competency
26%

Has recruiting strategies to maintain adequate staffing
levels

34%
27%

27%
32%
29%

Trains all providers in trauma-informed care
0%

20%

40%

60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

122

Ensuring Cultural Relevance of Services
While 6 in 10 providers in Dayton MSA indicate their organizations successfully provide services andgeneral information in first languages spoken by community members (Figure E2), fewer than half ofproviders in all regions indicate that their organization:oooUses patient demographic data to identify disparities in healthcare access and outcomes
Supports cultural preferences for disease management
Embeds cultural references into services and general information resources

Figure E2. Best Practices in Ensuring Cultural Relevance ofServices for Healthcare Providers% My department or organization successfully implements this in some or all areas
Provides general information resources in first languages
spoken by community members

41%

Provides services in first languages spoken by community
members

40%
43%

62%

48%

Supports cultural preferences for disease management

34%
31%

Uses patient demographic data to identify disparities inhealthcare access and outcomes

30%
39%
29%

Embeds cultural references into services and general
information resources

35%
37%
33%
0%

20%

40%

61%

48%

60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

123

Screening and Care Coordination
Providers in Dayton MSA are more likely to indicate that their organizations are successfully
implementing best practices surrounding screening and care coordination.
ooooMore than half of these providers indicate their organization screens for social
needs/risk factors
Prioritizes patient feedback in decision-making
Coordinates care with patients’ other providers/specialists
Shares information securely for care coordination purposes

There are opportunities to improve organizations’ screening for adversity and other SDOH; fewer thanhalf of providers screen for ACEs, food security, and housing stability (Figure E3).

Figure E3. Best Practices in Screening and Care Coordination for
Healthcare Providers% My department or organization successfully implements this in some or all
areas
45%
51%

Shares client information securely for care coordination
purposes

45%
45%

Coordinates care with patients’ other healthcare
providers/specialists

41%
42%

Prioritizes patient feedback in organizational/serviceproviding decision-making

65%
54%

Screens for other social needs/risk factors

35%
37%

52%

Creates flexible billing or payment models for clients withfinancial barriers

37%
38%

50%

31%
31%

Screens for housing stability

72%

45%

29%
42%
31%

Screens for food security

29%
36%
31%

Screens for Adverse Childhood Experiences (ACEs)
0%

20%

40%

60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

124

Collaboration
Providers across the regions are most likely to indicate they successfully collaborate with mental healthproviders and public health departments, though still only about one-half or fewer indicated this (FigureE4). Successful collaborations with the justice system, schools, transportation services, food and housing
services are relatively uncommon among providers. Further, few providers indicate that theysuccessfully collaborate with members of the community in designing strategies.

Figure E4. Best Practices in Collaboration among Healthcare
Providers% Myself, my department or organization successfully collaborates with providers
in this category
Mental healthcare providers

38%
42%

Public Health Departments

38%
46%
37%

Employment services or programs

26%
34%
24%

Members of the community in designing strategies

28%
34%
30%

Food services or programs

27%
33%
26%

Housing services or programs

26%
33%
24%

Transportation services or programs

27%
30%
26%

Schools

33%
30%
31%

53%

26%
29%
22%

Justice System

32%
27%
34%

Oral health services or programs
0%

20%

40%

60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

125

Data and Information
Again, Dayton MSA social service providers are more likely to report successful best practice
implementation in all areas relative to social service providers working in the other two regions. About 4
in 10 providers indicate they use a shared, standardized client screening tool (Figure E5). While about
one-half of providers in Dayton MSA indicate their organization successfully disaggregates data to lookat outcomes by demographics, less than one-third of providers in other regions indicate this bestpractice implementation. Similar to healthcare providers, social service agencies have an opportunity toincrease screening for adversities in order to link clients to needed care/interventions.

Figure E5. Best Practices in Data and Information Policies andPractices for Social Service Providers% My department or organization successfully implements this in some or all areas
45%

Shares client information securely for care coordination
purposes

35%

52%

43%
49%
37%

Uses a shared, standardized client screening tool
27%
28%

Disaggregates data (i.e., we always compare engagement
and outcomes rates by age, race, gender identity, etc.)24%

Screens for Adverse Childhood Experiences (ACEs)

31%
0%

20%

46%
38%

40%

60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

126

Responsive Client Services
Social service agencies, especially those in Rural counties and within Cincinnati MSA, have an
opportunity to increase their coordination and community outreach to ensure clients are provided
holistic services. About one third or fewer of all providers in Rural counties and Cincinnati MSA (Figure
E6):o Coordinate care with clients’ other providerso Engages community members in policy and practice discussionso Partners with local community leaders to develop culturally relevant solutions

Figure E6. Best Practices in Responsive Client Services for Social
Service Providers% My department or organization successfully implements this in some or all areas
Conducts targeted community outreach (i.e., materials arein multiple languages and uses cultural references/support
experiences relevant to the specific population)

42%

54%

39%
31%

Coordinates care with clients’ other providers

52%

34%
30%

Partners with local community leaders to develop
culturally relevant solutions

31%
35%

Allows for flexibility in services

32%
29%

Engages community members in policy and practice
discussions

30%
0%

20%

40%

48%
45%
43%
60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

127

Workforce Development in the Social Sector
Similar to healthcare providers, the most prevalent best practice surrounding workforce development
for social service providers is in recruiting diverse staff who are representative of the populations they
serve; still fewer than half of providers in Rural and Cincinnati regions do this successfully (Figure E7).
There is also an opportunity to increase social service workforce development surrounding traumainformed care, with fewer than half of providers in all regions perceiving this has been successfully
implemented.

Figure E7. Best Practices in Workforce Development for Social
Service Providers% My department or organization successfully implements this in some or all areas
Recruits diverse staff that is representative of all the
populations your department serves

45%
42%

Ensures employee performance management
incorporates client outcome measures

34%
33%
23%

Trains all providers in trauma-informed care
Increases/supports capacity of providers in underserved
communities

34%

33%
28%
0%

20%

40%

59%

51%
46%
44%
60%

80%

100%

Data Source: Regional CHNA Provider Survey
Rural Counties

Dayton-Kettering MSA

Cincinnati MSA

A Regional Assets datafile was created to capture the individuals and organizations who were identified
by their peers as implementing one or more of these best practices successfully. As a resource for
ongoing planning and partnerships, the Regional Assets datafile will be managed by The Health
Collaborative and shared with community partners.

12817. Appendix F: Original Data-Driven Recommendations
Based on the themes that emerged from multiple data collection strategies, the following broad
recommendations were proposed to guide THC in the setting of regional health priorities.
Research demonstrates that community members experiencing lower economic stability, and access toquality health care are at greater risk of heart disease, diabetes, obesity, disability, lung disease,maternal complications, mental health, arthritis, vision concerns, dental concerns and allergies. To
address these health concerns, the community will need to address housing stability, food security,
healthcare affordability, and improving patient-provider relationships.
Recommendation 1: Improve healthcare access and quality.
The health of the community hinges on access to quality health care. To address the healthcare
access and quality needs defined by the community across the region, The Health Collaborative
may consider the following priorities:• Strengthen collaboration with community partners who serve priority populations (i.e.,
increase in resources provided to community-based organization (CBOs), consultingwith CBOs as community health experts, and committing to more long-term
partnerships that CBOs can count on.)• Increase workforce diversity across health fields and at every level• Improve patient-provider interactions to increase trust and transparency• Increase transparency of costs of health care and financial assistance polices
Recommendation 2: Improve economic stability through collaboration and coordination.
Economic stability (i.e., having enough food, money to pay bills, and a safe place to live) is a key
predictor of several health needs. One’s economics is also correlated with one experiencing
structural barriers (i.e., high-cost healthcare system) and access barriers (i.e., lack of insurance,
unable to afford medications or a doctor’s visit, etc.). Therefore, a regional approach to improvehealth will be limited if the economic factors are not addressed. These factors include:•••

Safe and stable housing
Food security
Health care affordability

Potential priorities for THC may be:••

Increase collaboration with local food security and housing stability efforts.
Improve communication, referral and data sharing with partners who are addressing
healthcare affordability (i.e., including bringing community health workers and social
workers on-site (in ERs, clinics, offices, etc.).

Recommendation 3: Adapt metrics to monitor diversity, equity and inclusion (DEI) across all priorities.
The above recommendations are inclusive of DEI best practices for service providing organizations.
The Health Collaborative leadership are also committed to DEI, which is another necessarycomponent of successful DEI strategies. To ensure implementation of strategies that support DEI,
THC should take the time to establish metrics for all priorities that will allow the region to trackprogress towards DEI goals.
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