Policy

Indicator Profile

Policy is a law, regulation, procedure, administrative action, incentive, or decision implemented by governments and other institutions. Institutional policies (e.g., local government policies, health care settings, employers) can significantly shape many social determinants of health associated with prevention and management of chronic diseases, including cardiovascular disease (CVD).

For example, local government policies that incentivize primary care physicians to practice where there is a shortage of health care providers can improve health care access. Employers that pay family-supporting wages can reduce financial stress, housing instability, and other CVD risk factors. Policies and practices can also inadvertently perpetuate structural racism and other forms of discrimination that then affect health.

Table of Contents

Indicators

Case Example

References

Indicators

This toolkit provides guidance for measuring five indicators related to policy that influence inequities across various social and environmental factors, leading to differential risks for developing CVD or differential access to and receipt of health care. The five policy indicators are measured at different levels of analysis, including organization, city, county, and state.

Living Wage Policy

Why is this indicator relevant?

A robust body of literature has established a strong link between income and health and well-being.¹ The American Heart Association notes the link between lower wage and the likelihood of increased cardiovascular risk factors.² Given this evidence, the American Public Health Association recommends all governance levels enact living wage legislation.³ Living wage policies are mandates for employers to pay their employees a wage at or above the state or federal minimum wage.⁴ Increasing wages through living wage policies may affect health outcomes by increasing access to medical care, housing, and food and by improving mental health through greater job satisfaction and increased leisure time.^5,6Living wage laws are associated with decreased rates of hypertension, along with better birth outcomes and lower rates of poverty, suicide mortality, and sexually transmitted infections.^7,8,9 This is consistent with emerging evidence that minimum wage policies may similarly affect racial health inequities as well.¹⁰

This indicator can be assessed by the following measures. Click on each measure to learn more:

Measure 1: City and County Minimum Wage
Definition	A database of minimum wages set by local ordinance. In most cases, local ordinances create minimum wages higher than the state minimum wage.
Data Availability	City, county
Data Source(s)	Minimum Wage Inventory: To help inform policymakers and other stakeholders, the UC Berkeley Labor Center maintains an up-to-date inventory of these laws, with details on wage levels, scheduled increases, and other law details, as well as links to the ordinances. Users can download an Excel workbook with details of local wage ordinances for the United States or view details for an individual city or county. Note: Data are available only for 55 cities and counties.

Measure 1: City and County Minimum Wage
Definition	Dollar amount of the minimum wage in a state as of January 1, 2021. The federal minimum wage is $7.25 per hour. States without a minimum wage or with minimum wages lower than $7.25 per hour are superseded by the federal minimum wage.
Data Availability	State
Data Source(s)	State Minimum Wage Laws: Users can download a table of current minimum wages by state or select an individual state to see details on its current minimum wage policies. Historical data are also available and are shown for changes by state for 1968–1981, 1988–1998, 2000–2006, 2007–2013, 2014–2019, and 2020–2021. The source for this data is the U.S. Department of Labor. PolicyMap: PolicyMap is a data warehouse of more than 50,000 indicators on demographics, income and spending, housing, lending, quality of life, economy, education, health, and federal regulations. A free (basic) subscription provides access to indicators developed using publicly available data sources via a single-layer mapping tool. A paid (standard) subscription provides access to multilayer mapping, analysis tools, and data downloads (CSV format). Users can view a state’s minimum wage by hovering over the state within the Open Map view (this feature is free). This measure is also accessible by navigating to Incomes & Spending > Income > Minimum Wage. Data on state minimum wage are from the U.S. Department of Labor and are accurate as of January 1, 2022. Users wanting to download the data for further analyses need to pay for a standard subscription.

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Spending Per Capita (Health Care, Education, and Parks and Green Space)

Why is this indicator relevant?

Per capita spending indicates how much economic production value is attributed to each citizen. Government spending on goods and services, such as health, education, and green space, can strongly affect health.

The United States spends almost twice as much on medical care as other high-income nations.¹¹ In 2020 alone, the United States spent $11,946 per capita on health consumption expenditures, $4,000 more per capita than other nations.¹²However, the United States lags other nations on many health outcome indicators and faces inequities in health spending distribution.¹³ Investments in prevention programs focusing on risk factors for CVD and other chronic diseases can reduce overall health costs.¹⁴

Higher educational attainment is linked to better health and longevity.¹⁵ The United States spends less on education per capita than other high-income countries. Specifically, the United States spends an average of $13,185 per student, representing 7.9% of public funding, which is short of meeting the United Nations Educational, Scientific, and Cultural Organization’s benchmark of 15% of public expenditure on education.¹⁶ Increased government spending to expand educational opportunity access may reduce CVD risk factors.¹⁷

Research shows that green space access is associated with well-being.¹⁸ A minimum of 9 m² of green space per individual, with an ideal urban green space (UGS) value of 50 m² per capita, is recommended.¹⁹ There is also a known relationship between a lack of access to green space and increased CVD risk, further supporting government spending on efforts to increase residents’ proximity to parks and other outdoor recreational opportunities.^20,21,22 However, there are disparities in green space distribution in the United States, indicating the need to ensure equitable funding to improve equitable access.²³

Measure 1: City and County Minimum Wage
Definition	Per capita expenditures on health and hospitals by state government.
Data Availability	State
Data Source(s)	Urban-Brookings Tax Policy Center: The Tax Policy Center website contains data on per capita state spending by budget category (e.g., health and hospitals) that is updated annually. Users can download a workbook containing annual data for 2004–2019. The Tax Policy Center uses data from the U.S. Census Bureau’s Annual Survey of State and Local Government Finances. Urban Institute State and Local Finance Data Tool: Exploring the Census of Governments: The State and Local Finance Data Tool on the Urban Institute’s website allows users to search data revenue and expenditure data for/by various government levels for individual (or multiple) states across multiple years (1977–2019). The data are from the U.S. Census Bureau’s Census of Governments and Annual Survey of State and Local Government Finances; additional data are from the U.S. Bureau of Economic Analysis and the U.S. Bureau of Labor Statistics. Users can select the analysis unit they wish to see. To access data on this measure, users can click Get Started > State > state of interest > Health and Hospital Direct Expenditures categories (E052) > year of interest > Per Capita.

Measure 1: City and County Minimum Wage
Definition	Per capita spending on health care from all payers (Medicare, Medicaid, and private health insurance).
Data Availability	State
Data Source(s)	Health Expenditures by State of Residence, 1991–2014: Health accounts by state of residence present aggregate and per capita estimates of health care spending by type of establishment delivering care (e.g., hospitals, physicians and clinics, nursing homes) and for medical products (prescription drugs, over-the-counter medicines and sundries, and durable medical products such as eyeglasses and hearing aids) purchased in retail outlets. Source of aggregate funding and per enrollee estimates by state are also provided for Medicare, Medicaid, and private health insurance. Users can download either the health expenditures by state of residence summary tables or detailed data from the Centers for Medicare & Medicaid Services (CMS) website. The website also provides useful guidance on analyzing the data. Kaiser Family Foundation: The Kaiser Family Foundation website provides annual data for 1991–2014 on total per capita spending on health care by state. The CMS Office of the Actuary produces health expenditures by state of residence and health expenditures by state of provider every 5 years. The State Health Expenditure Accounts are a subcomponent of the National Health Expenditure Accounts (NHEA), the official government estimates of health spending in the United States. Users can search this measure by navigating to Health Costs & Budgets > Health Care Expenditures by State > Health Care Expenditures per Capita by State of Residence.

Measure 1: City and County Minimum Wage
Definition	The amount of money public schools spent (on teacher and administrator salaries, supplies, building maintenance, field trips, etc.) per pupil for elementary and secondary public education.
Data Availability	State
Data Source(s)	National Center for Education Statistics (NCES): NCES is the primary federal entity for collecting and analyzing data related to education in the United States. The NCES Digest of Education Statistics is an annual report that contains a set of tables covering education data from prekindergarten through graduate school, including total expenditures per pupil by state. Users can access data for this measure by clicking the link below, selecting the year of interest in the drop-down menu at the top of the website, and then navigating to Chapter 2: Elementary and Secondary Education > 236 Expenditures > Total and current expenditures per pupil in fall enrollment in public elementary and secondary schools, by function and state or jurisdiction. Data can be downloaded as an Excel workbook and is available for 1995–2019.

Measure 1: City and County Minimum Wage
Definition	Per capita direct expenditures by state and local government on parks and recreation (state and local parks).
Data Availability	Local, State
Data Source(s)	Urban Institute State and Local Finance Data Tool: Exploring the Census of Governments: The Urban Institute’s State and Local Finance Tool allows users to search data revenue and expenditure data by various government levels for individual (or multiple) states across multiple years (1977–2019), including parks and recreation. Data come largely from the U.S. Census Bureau’s Census of Governments and Annual Survey of State and Local Government Finances; additional data are from the U.S. Bureau of Economic Analysis and the U.S. Bureau of Labor Statistics. To access data on this measure, users can click Get Started > State > state of interest > Parks & Rec Direct Expenditures series (E084) > year of interest > Per Capita.

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Sick Leave Policies

Why is this indicator relevant?

There is a link between paid sick leave (the ability to receive pay while absent from work due to illness, injury, or disability) and mortality risk among working adults in the United States.²⁴ Currently, state- and/or local-level sick leave policies that require some form of sick leave benefits are in place in 21 states.²⁵ Workers in states without paid sick leave policies are less likely to access health care and more likely to either attend work while sick or lose income due to missed work.²⁶ In March 2020, 78% of private industry workers and civilian workers reported having access to sick leave benefits, compared with 91% of government workers.²⁷ Individuals with fewer sick leave benefits have higher potential for death from heart disease.²⁸

Sick leave policies protect employees against loss of income for temporary absences due to illness or disability. This indicator can be assessed by the following measure. Click on the measure to learn more:

Measure 1: City and County Minimum Wage
Definition	State and local government laws requiring employers to provide paid sick leave to qualified individuals.
Data Availability	City, State
Data Source(s)	National Conference of State Legislatures (NCSL): The NCSL provides details on state-level paid sick leave laws. Currently, 13 states and Washington, D.C., have enacted such laws. Data were gathered from individual state websites, and users can navigate to these sources from the NSCL site. The page was last updated on July 21, 2020. Workplace Fairness Website: The Workplace Fairness website contains a compilation of areas (city and states) with statutes representing minimum paid sick leave requirements. Example Survey Instrument The following survey measure is available to assess sick leave policies: American Time Use Survey (ATUS) Leave Module The U.S. Bureau of Labor Statistics (BLS) ATUS measures the amount of time people spend doing various activities, such as paid work, childcare, volunteering, and socializing. The ATUS Leave Module questionnaire asks respondents about access to paid and unpaid leave from their jobs and ability to adjust work schedules and locations. The module covers six areas: access to paid leave, access to unpaid leave, leave taken in the past week, schedule adjustments, nonuse of leave, and health. The entire questionnaire is available on the U.S. Bureau of Labor Statistics website. To access questions for this measure, search for “access to paid leave.” Link: https://www.bls.gov/tus/questionnaires/lvmquestionnaire.pdf
Additional Measurement Considerations	Because laws about employee qualifications for sick leave coverage vary (and are subject to change), there are no data available on the proportion of workers by state or other locale who are covered by sick leave policies. However, interested parties can do the analysis for individual areas by estimating the proportion of workers who meet the stated requirements using employee characteristics data from BLS, the American Community Survey, or other sources. BLS completes an annual National Compensation Survey that provides annual national estimates of the proportion of workers covered by paid sick leave policies in 2020 (78% in March 2020). See https://www.ncsl.org/research/labor-and-employment/paid-sick-leave.aspx for more details. Additional analysis of sick leave laws can include coding laws for applicable coverage and resulting inequities²⁹ and conducting regression analysis to estimate the effects of sick leave access on health outcomes, specifically for populations of interest to users.³⁰

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Smoke-Free Policies

Why is this indicator relevant?

Cigarette smoking causes 480,000 deaths per year; 41,000 of those deaths are from secondhand exposure. Smoke-free policies prohibit smoking in designated public areas and indoor spaces. These policies establish smoke-free standards through state and local ordinances.³¹ Currently, about 61% of the total United States population is covered by smoke-free indoor air policies in public spaces.³² These policies help reduce both smokers’ consumption and nonsmokers’ exposure to secondhand smoke.

Smoking is a major cause of CVD, leading to approximately one of every four deaths from CVD.³³ Secondhand smoke exposure also causes heart disease in nonsmokers. More than 33,000 nonsmokers die every year in the United States from coronary heart disease caused by secondhand smoke exposure. Secondhand smoke exposure can also increase heart attack and stroke risk in nonsmokers.

Studies show that most cigarette smokers start smoking before the age of 26.³⁴ Smoking policies across learning institutions are important for promoting and enforcing smoke-free environments. Since 2017, at least 2,082 U.S. colleges and universities instituted smoke free policies.³⁵

Smoke-free policies prohibit smoking in designated public areas and indoor spaces. This indicator can be assessed by the following measure. Click on the measure to learn more:

Measure 1: City and County Minimum Wage
Definition	State and local government laws related to smoking in public places (organized by worksites, restaurants, and bars) and on campuses (i.e., public schools K–12, private schools K–12, public colleges, and private colleges).
Data Availability	City, State
Data Source(s)	State Tobacco Activities Tracking and Evaluation (STATE) System: CDC’s Office on Smoking and Health developed the STATE system as an interactive application that presents current and historical state-level data on tobacco use and prevention. Users can download state highlights and detailed custom reports related to a variety of smoke-free indoor and campus legislation (including indoor air laws and e-cigarette access), as well as explore interactive maps and factsheets on key data points. Data availability varies based on variables of interest, with some measures available as recently as 2022. CDC collects data from a variety of data sources, including the Behavioral Risk Factor Surveillance System (BRFSS), the Substance Abuse and Mental Health Services Administration (SAMHSA), and the Youth Risk Behavior Surveillance System (YRBSS).

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Social Determinants of Health (SDOH) Measures in Electronic Health Records (EHRs)

Why is this indicator relevant?

SDOH are the conditions where people live, learn, work, and play that affect a wide range of health and quality-of-life risks and outcomes.³⁶ Measuring SDOH is crucial in identifying patients who are at risk for poor health outcomes and in identifying areas where prevention or intervention efforts should be allocated at various levels (e.g., health system, community, and individual levels).

In health care settings, providers use EHRs to document patient care and clinical data.³⁷ However, qualitative information about patients’ lifestyles is usually documented in unstructured clinical notes. Although SDOH information is often collected, the lack of standardized data elements, assessment tools, measurable inputs, and data collection practices in clinical notes greatly limits the utility of this information.³⁸

Digitization of clinical records helps integrate SDOH into EHRs, enhancing standardization of SDOH data collection and facilitating patient-level assessment for specific health outcomes risk.³⁹ The American Heart Association promotes SDOH assessment as a component of routine care for individuals with heart disease and advises using patient EHRs to collect SDOH data.⁴⁰ Overall, the inclusion of CVD risk factors in EHRs is a useful tool in population health surveillance.⁴¹ The Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE) is an example of a tool that facilitates the standardized collection and entry of SDOH data into EHRs.⁴²

SDOH are the conditions where people live, learn, work, and play that affect a wide range of health and quality-of-life risks and outcomes. In health care settings, EHRs are an opportunity to collect data on SDOH to improve patient care and address the social needs of patients. This indicator can be assessed by the following measures. Click on each measure to learn more:

Measure 1: City and County Minimum Wage
Definition	Patient-level information on unmet social needs and social determinants of health. Data collected from patient SDOH screening can be entered into EHRs and can be used to improve patient care.
Data Availability	Individual
Data Source(s)	Example Survey Instrument The following screening tools assess patient social needs and can be used for standardized collection and entry of patient SDOH data into EHRs: Health-Related Social Needs Screening Tool The Health-Related Social Needs Screening Tool was originally developed for the Centers for Medicare & Medicaid Services (CMS) Accountable Health Communities (AHC) models. This screening tool includes 10 questions about five core domains: housing instability, food insecurity, transportation problems, utility help needs, and interpersonal safety. It also includes supplemental questions on financial strain, employment, family and community support, education, physical activity, substance use, mental health, and disabilities. The entire survey is available on the CMS website. Link: https://innovation.cms.gov/files/worksheets/ahcm-screeningtool.pdf Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE) PRAPARE is a national standardized patient risk assessment protocol designed to equip health care providers and their community partners to assess individuals’ SDOH. The assessment protocol has 18 core questions and four optional questions across four domains: personal characteristics, family and home, money and resources, and social and emotional health. The survey has been translated into 25 languages and is available on the PRAPARE website. Link: https://prapare.org/the-prapare-screening-tool/
Additional Measurement Considerations	For guidance on what measures are considered SDOH and more information on the SDOH key areas, please refer to CDC’s Healthy People 2030 Social Determinants of Health website. SDOH data can inform risk assessments for chronic disease, including CVD. SDOH data within EHRs can also be used for predictive analyses to forecast health care utilization and health outcomes.³⁹ Health care providers can capture data on patient social needs using the ICD-10-CM “Z codes” (categories Z55–Z65), which identify nonmedical factors that may influence a patient’s health status. ICD-10 Z codes collect SDOH information such as education and literacy level, employment and housing status, psychosocial issues, social environment circumstances (e.g., social exclusion, discrimination), access to adequate food or water, and occupational exposure to risk factors such as dust, radiation, or toxic agents.

Measure 1: City and County Minimum Wage
Definition	The number and type of SDOH measures in screener questions (or otherwise) in the EHRs of clinics, community health organizations, and other health systems.
Data Availability	Health care organization (e.g., health systems, clinics, Federally Qualified Health Centers [FQHCs], other health care settings)
Data Source(s)	Currently, there are no publicly available data sources capturing the breadth or scope of SDOH data availability within EHRs. However, users may follow the steps below to collect data for this indicator: Identify health systems within your site’s catchment area that utilize EHRs to track patient health data. Engage health systems and request access to their EHR template. For cases in which there are multiple EHRs, choose the EHR with the broadest patient reach. Determine the number of SDOH measures present in the EHRs, categorizing them into the five main SDOH areas: Economic Stability Education Social and Community Context Health and Health Care Neighborhood and Built Environment For each measure, calculate the percentage of missing data within SDOH. Create a summary of the number of SDOH indicators with more than 30% missing data. Sites may also assess the use of a validated SDOH screening tool within EHRs (yes/no response). Aggregate and analyze the results of missing data, category representation, and validated screening tool use based on your site’s capabilities and interests.
Additional Measurement Considerations	For guidance on what measures are considered SDOH and more information on the SDOH key areas, please refer to CDC’s Healthy People 2030 Social Determinants of Health website. SDOH data can inform risk assessments for chronic disease, including CVD. SDOH data within EHRs can also be used for predictive analyses to forecast health care utilization and health outcomes.³⁹ Health care providers can capture data on patient social needs using the ICD-10-CM “Z codes” (categories Z55–Z65), which identify nonmedical factors that may influence a patient’s health status. ICD-10 Z codes collect SDOH information such as education and literacy level, employment, housing, psychosocial issues, social environment circumstances (e.g., social exclusion, discrimination), access to adequate food or water, and occupational exposure to risk factors like dust, radiation, or toxic agents.

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Case Example

This case example was developed from the Health Equity Indicators (HEI) Pilot Study. Seven health care organizations participated in the HEI Pilot Study from January 2022 to April 2022 to pilot-test a subset of HEIs in order to assess the feasibility of gathering and analyzing data on these indicators within health care settings. The pilot case examples document participating sites’ experiences with data collection and lessons learned from piloting the HEIs.

Site: ProMedica Toledo Hospital
Focus Area: Policy
Measure: Patient Social Determinants of Health

This content presents an example of how one health care site, ProMedica Toledo Hospital (ProMedica), collected data on the health equity indicator, social determinants of health (SDOH) measures in electronic health records (EHRs). SDOH are conditions where people live, learn, work, and play that affect a wide range of health and quality-of-life risks and outcomes.⁴³Measuring SDOH is crucial in identifying patients who are at risk for poor health outcomes and in identifying areas where prevention or intervention efforts should be allocated. The American Heart Association promotes SDOH assessment as a component of routine care for individuals with heart disease and advises data availability within patient EHRs.⁴⁴ Overall, the inclusion of cardiovascular disease (CVD) risk factors in EHRs is a useful tool in population health surveillance.⁴⁵ ProMedica Toledo Hospital used the patient SDOH measure to assess SDOH measures in EHRs. Patient SDOH are defined as patient-level information on unmet social needs. Data collected from patient SDOH screening can be entered into EHRs and used to improve patient care. For more information on the patient SDOH measure, please see the SDOH measures in EHRs indicator in the Policy Indicator Profile.

The description of ProMedica’s data analysis methods, data sources, challenges, and facilitators summarized below reflects insights gathered during the Health Equity Indicators for CVD Pilot Study conducted between January and April of 2022.

Health Equity in Action: ProMedica Toledo Hospital

ProMedica Toledo Hospital is a 794-bed hospital in Toledo, Ohio, that serves approximately 122,000 patients, of whom 87% are White, 7% are Black/African American, and 2% are Hispanic/Latino. The hospital houses a trauma unit and an acute care center and employs specialty physicians and primary care physicians. ProMedica offers inpatient and outpatient health care services. To meet its mission of improving patient health and well-being, ProMedica uses an SDOH screening tool as part of its inpatient and outpatient patient assessment workflow.

Overview of ProMedica’s data collection methods

Indicator: SDOH Measures in EHRs

Measure: Patient SDOH

Data Collection Method: Primary data collection

Data Source: EHRs

Data Availability: Patient-level

Application/Use: Exploratory analysis of the relationship among various SDOH, race and ethnicity, and CVD interventions and outcomes utilizing an existing SDOH screening tool.

Data Collection and Analysis Methods. ProMedica has an established method for collecting SDOH data and did not pilot-test this indicator. However, ProMedica shared information about their SDOH data collection and analysis process as part of the pilot.

ProMedica collects primary data on SDOH using a screening tool administered to adult patients who agree to participate at ProMedica’s cardiac care clinic. The screening tool is part of patients’ existing pre-appointment registration process. Patients complete the screener via ProMedica’s EHR portal up to a week before their appointment, via the online patient portal or the tablet in the hospital waiting room. The housing and food screening is mandatory for inpatient admissions to the hospital. The screening is voluntary for outpatient visits. The ProMedica team reported an 85% to 90% completion rate among those who participate in the screening. Clinic staff also collect SDOH data during intake, as part of the medical history and physical examination.

The screening tool comprises 32 questions and gathers patient data across 14 domains, including housing, transportation access, behavioral health, financial strain, and education level. After the screening, the EHR assigns a patient risk score that informs the interventions and resources to be provided to the patient. ProMedica conducts an annual community-level health needs assessment by analyzing clinical data by race, ethnicity, and other SDOH to identify any unfavorable differences in treatment, diagnosis, and health outcomes across different population subgroups. Patient ZIP codes are also used to identify geographic patterns in SDOH and clinical data. The findings from this analysis accelerated the development of ProMedica’s health equity plan and facilitated engagement with key partners, including their organizational leadership, to address identified inequities.

Facilitators. Awareness and involvement of ProMedica’s EHR reporting team and leadership buy-in and support were the two significant facilitators for data collection. The team’s engagement provided foresight into potential data collection issues.

Challenges and Limitations. Because ProMedica uses an existing SDOH screening tool already embedded in their EHR and patient workflows, they did not report any major barriers specific to collecting SDOH data. However, there are barriers to capturing inpatient SDOH needs. Inpatients are not able to benefit from completing the SDOH screening in the privacy of their own home, yet may be reluctant to answer SDOH questions posed by the hospital staff. Furthermore, ProMedica raised concerns about adding measures to their screening tools, noting risk of staff and patient survey fatigue, lower response rates, and lower data quality.

Future Plans. ProMedica noted that collecting data on SDOH measures within the EHR supports and enhances their ongoing health equity efforts. Given that many of their patients indicate social needs, the team plans to continue their data collection efforts to understand and address SDOH, including building SDOH dashboards and other data visualization tools. Additionally, they plan to leverage the data collected in the outpatient settings to inform community strategies and broader population-level programs.

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References

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