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Greater investment in the social determinants of health (SDOH) is positively associated with improved health outcomes of both individuals and their communities, which in turn may help to bend the health care cost curve and reduce health care spending. The purpose of this study was to examine the relationship between local governments' spending on the SDOH and the health care costs of privately insured nonelderly adults. Annual spending by local governments on the SDOH for the years 2007-2017 was obtained from the Census of Governments. Annual health care costs for privately insured nonelderly adults for the years 2013-2017 was obtained from the Health Care Cost Institute. Bivariate and multivariate regression analyses were performed to examine the association between county-level local governments' per capita spending on the SDOH and the per member health care costs of privately insured adults living in these counties controlling for community characteristics. All analyses were conducted in 2021. For near-elderly adults ages 55-64, health care costs were significantly higher in counties with the lowest levels of local governmental spending on the SDOH. For adults ages 18-54, in contrast, health care costs were unrelated to local governmental spending. Investments of local governments in the SDOH may have rather limited potential to yield meaningful savings in health care costs for privately insured nonelderly adults at the population level, especially once such investments exceed a minimum threshold.

We conducted a community seroprevalence survey in Arizona, from September 12 to October 1, 2020, to determine the presence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used the seroprevalence estimate to predict SARS-CoV-2 infections in the jurisdiction by applying the adjusted seroprevalence to the county’s population. The estimated community seroprevalence of SARS-CoV-2 infections was 4.3 times greater (95% confidence interval = 2.2, 7.5) than the number of reported cases. Field surveys with representative sampling provide data that may help fill in gaps in traditional public health reporting. (Am J Public Health. 2022;112(1):38–42. https://doi.org/10.2105/AJPH.2021.306568 )

Estimate the number of full-time equivalents (FTEs) needed to fully implement Foundational Public Health Services (FPHS) at the state and local levels in the United States.Current and full implementation cost estimation data from 168 local health departments (LHDs), as well as data from the Association of State and Territorial Health Officials and the National Association of County and City Health Officials, were utilized to estimate current and "full implementation" staffing modes to estimate the workforce gap.The US state and local governmental public health workforce needs at least 80 000 additional FTEs to deliver core FPHS in a post-COVID-19 landscape. LHDs require approximately 54 000 more FTEs, and states health agency central offices require approximately 26 000 more.Governmental public health needs tens of thousands of more FTEs, on top of replacements for those leaving or retiring, to fully implement core FPHS.Transitioning a COVID-related surge in staffing to a permanent workforce requires substantial and sustained investment from federal and state governments to deliver even the bare minimum of public health services.

This article has been temporarily removed by the publisher, Wolters Kluwer, due to a data quality issue. We regret any confusion this may have caused. This article will be published once production is complete on the Public Health Workforce Interest and Needs Survey supplemental issue.There is little empirical evidence regarding the magnitude of the COVID-19 response across the public health workforce and the extent to which other public health programs were called upon to contribute to the response, potentially leading to less work being done in other public health programs during the COVID-19 pandemic.To assess the composition of the workforce that contributed to the COVID-19 pandemic response during 2020-2022.A large, cross-sectional, nationally representative survey of the state and local public health agency workforce through the Public Health Workforce Interest and Needs Survey (PH WINS).Nearly all state health agency-central offices (SHA-COs) and Big City Health Coalition (BCHC) member public health departments as well as a nationally representative sample of other local health departments (LHDs) with more than 25 staff members and serving more than 25 000 people participated in fall 2021.A sample of all individuals working at each SHA-CO or LHD as part-time or full-time employees, contractors, or other employee types was used. A total of 44 732 responses (35% of eligible respondents) were received.Main outcomes included the proportion of full-time equivalent (FTE) effort devoted to COVID-19 response work by quarter (Q) from Q1 2020 through Q1 2022. Predictors of interest included individual- and agency-level demographics, most notably an individual's self-reported public health program area.Staffing and hiring for the COVID-19 pandemic response was an ongoing effort that began in 2020 and lasted through 2022. During the pandemic, all public health program areas contributed at least 20% of their workforce time to COVID-19 response, peaking at 47-83% of the staff time, depending on the program area.There was a considerable public health opportunity cost to the public health systems' large and prolonged COVID-19 response. Persistent understaffing in the public health system remains an important issue.

The COVID-19 pandemic has prompted concern about the integrity of the US public health infrastructure. Federal, state, and local governments spend $93 billion annually on public health in the US, but most of this spending is at the state level. Thus, shoring up gaps in public health preparedness and response requires an understanding of state spending. We present state spending trends in eight categories of public health activity from 2008 through 2018. We obtained data from the Census Bureau for all states except California and coded the data by public health category. Although overall national health expenditures grew by 4.3 percent in this period, state governmental public health spending saw no statistically significant growth between 2008 and 2018 except in injury prevention. Moreover, state spending levels on public health were not restored after cuts experienced during the Great Recession, leaving states ill equipped to respond to COVID-19 and other emerging health needs.

Objective The purpose of this study was to review changes in public health finance since the 2012 Institute of Medicine (IOM) report "For the Public's Health: Investing in a Healthier Future." Design Qualitative study involving key informant interviews. Setting and participants Purposive sample of US public health practitioners, leaders, and academics expected to be knowledgeable about the report recommendations, public health practice, and changes in public health finance since the report. Main outcome measures Qualitative feedback about changes to public health finance since the report. Results Thirty-two interviews were conducted between April and May 2019. The greatest momentum toward the report recommendations has occurred predominantly at the state and local levels, with recommendations requiring federal action making less progress. In addition, much of the progress identified is consensus building and preparation for change rather than clear changes. Overall, progress toward the recommendations has been slow. Conclusions Many of the achievements reported by respondents were characterized as increased dialogue and individual state or local progress rather than widespread, identifiable policy or practice changes. Participants suggested that public health as a field needs to achieve further consensus and a uniform voice in order to advocate for changes at a federal level. Implications for policy and practice Slow progress in achieving 2012 IOM Finance Report recommendations and lack of a cohesive voice pose threats to the public's health, as can be seen in the context of COVID-19 emergency response activities. The pandemic and the nation's inadequate response have highlighted deficiencies in our current system and emphasize the need for coordinated and sustained core public health infrastructure funding at the federal level.

Objectives. To quantify changes in US health care spending required to reach parity with high-resource nations by 2030 or 2040 and identify historical precedents for these changes. Methods. We analyzed multiple sources of historical and projected spending from 1970 through 2040. Parity was defined as the Organisation for Economic Co-operation and Development (OECD) median or 90th percentile for per capita health care spending. Results. Sustained annual declines of 7.0% and 3.3% would be required to reach the median of other high-resource nations by 2030 and 2040, respectively (3.2% and 1.3% to reach the 90th percentile). Such declines do not have historical precedent among US states or OECD nations. Conclusions. Traditional approaches to reducing health care spending will not enable the United States to achieve parity with high-resource nations; strategies to eliminate waste and reduce the demand for health care are essential. Public Health Implications. Excess spending reduces the ability of the United States to meet critical public health needs and affects the country’s economic competitiveness. Rising health care spending has been identified as a threat to the nation’s health. Public health can add voices, leadership, and expertise for reversing this course.

Landmark reports from reputable sources have concluded that the United States wastes hundreds of billions of dollars every year on medical care that does not improve health outcomes. While there is widespread agreement over how wasteful medical care spending is defined, there is no consensus on its magnitude or categories. A shared understanding of the magnitude and components of the issue may aid in systematically reducing wasteful spending and creating opportunities for these funds to improve public health. To this end, we performed a review and crosswalk analysis of the literature to retrieve comprehensive estimates of wasteful medical care spending. We abstracted each source’s definitions, categories of waste, and associated dollar amounts. We synthesized and reclassified waste into 6 categories: clinical inefficiencies, missed prevention opportunities, overuse, administrative waste, excessive prices, and fraud and abuse. Aggregate estimates of waste varied from $600 billion to more than $1.9 trillion per year, or roughly $1800 to $5700 per person per year. Wider recognition by public health stakeholders of the human and economic costs of medical waste has the potential to catalyze health system transformation.

Context Governments at all levels work to ensure a healthy public, yet financing, organization, and delivery of public health services differ across the United States. A 2012 Institute of Medicine Finance report provided a series of recommendations to ensure a high-performing and adequately funded public health infrastructure. Objectives This review examines the influence of the Finance report's 10 recommendations on public health policy and practice. Design This review utilized peer-reviewed and gray literature published since 2012. Eligibility criteria Documents that address at least one of the Finance report's 10 recommendations and contain information on either official actions taken in response to the Finance report or evidence of the report's influence on the practice community. Results Of 2394 unique documents found, a total of 56 documents met the eligibility criteria. Review of these 56 documents indicated that the most substantial activity related to the recommendations was focused on the "minimum package of public health services" concept and establishment of a uniform chart of accounts. Discussion Progress has been mixed on the Finance report recommendations. Improved tracking and auditing of public health activity appears to be advancing, yet financial benchmarks remain unmet. Challenges remain in determining actual investment in public health and equitable resource allocation approaches. State and local health department use of cost estimation methodology and a uniform chart of accounts tool has contributed to an increase in understanding and improvement in public health spending. Conclusions The Finance report has served as a strong impetus for advocating for an increased investment in governmental public health. Efforts are bolstered by informed public health practitioners and stakeholders but often stymied by policy makers who must balance complex competing issues and priorities. Although many successes have occurred, further work is needed toward improving investment in the nation's public health.

Thomas Frieden’s “health impact pyramid” presents a hierarchy in which the wide base of the pyramid of socioeconomic factors at a population level has more impact on the health of the public than do individually focused interventions at the pyramid’s top. From this pyramid perspective, the US spending priorities are misaligned, as expenses targeted at public health and socioeconomic factors are far outstripped by spending on individual health care services at the top of the pyramid. The nation’s ongoing debate on health care reform continues to focus on access to individual health care services, despite evidence demonstrating the health impacts of population-level efforts at the base of the pyramid and the synergistic health impacts of health and social service collaboration. We examine the need for improved systems alignment through the lens of the health impact pyramid. We catalog the types of misalignments and their social, political, and systems genesis. We identify promising opportunities to realign US health spending toward the socioeconomic factor base of the health impact pyramid and emphasize the need to integrate and align public health, social services, and medical care in the United States.

Vaccination enrollment requirements are an important tool used to improve vaccination coverage among school-aged children. However, all states permit varying exemptions that allow students to stay enrolled without receiving some (or all) vaccinations. In Arizona, schools are required to report vaccination data on their kindergarten and 6th grade students annually to the Arizona Department of Health Services (ADHS). We analyzed trends in herd immunity and personal belief exemptions in Arizona schools from 2015 to 2018. We also identified multiple correlates of herd immunity at the school level. Our results demonstrate decreased herd immunity statewide and by school type and an increased rate of personal belief exemptions during this period. These findings contribute to the body of literature suggesting that vaccine hesitancy is growing, resulting in suboptimal vaccination coverage for children. Moreover, this research has several policy implications, especially for states permitting multiple exemption types and lax exemption criteria.

Will counties that reallocate money from law enforcement to social services improve subsequent markers of population wellbeing? In this study, we measure the association between county government spending across multiple sectors and Life Expectancy at Birth (LEB) in the U.S. using data from the U.S. Census Bureau. We constructed a Structural Equation Model to determine whether social expenditure, building infrastructure, and spending on law and order were positively or negatively associated with LEB three-years after initial spending. The analysis compared data between 2002-05 and 2007-10 and was stratified for urban and rural counties. In rural counties, a one-standard-deviation increase in social spending increased subsequent LEB by 0.58 (SE 0.16) and 0.36 (SE 0.16) years in 2005 and 2010, respectively. In urban counties, a one-standard-deviation increase in building infrastructure spending increased subsequent LEB by 1.14 (SE 0.51) and 1.05 (SE 0.49) years in 2005 and 2010, respectively. In 2002, a one-standard-deviation increase in law and order spending significantly decreased subsequent life expectancy, 2.2 (SE 1.27) and 0.46 (SE 0.13) years in urban and rural counties, respectively. Similarly, investments in building infrastructure for urban counties and social services for rural counties were associated with subsequently higher life expectancy three years later after initial investments., Highlights • Funding for public health and other social interventions is associated with subsequent improvements in life expectancy. • Spending in the social services is more closely tied to future life expectancy at birth in rural counties. • In urban counties spending on building infrastructure is associated with more future gains in life expectancy at birth.

Objectives. To examine the accuracy of official estimates of governmental health spending in the United States. Methods. We coded approximately 2.7 million administrative spending records from 2000 to 2018 for public health activities according to a standardized Uniform Chart of Accounts produced by the Public Health Activities and Services Tracking project. The official US Public Health Activity estimate was recalculated using updated estimates from the data coding. Results. Although official estimates place governmental public health spending at more than $93 billion (2.5% of total spending on health), detailed examination of spending records from state governments shows that official estimates include substantial spending on individual health care services (e.g., behavioral health) and that actual spending on population-level public health activities is more likely between $35 billion and $64 billion (approximately 1.5% of total health spending). Conclusions. Clarity in understanding of public health spending is critical for characterizing its value proposition. Official estimates are likely tens of billions of dollars greater than actual spending. Public Health Implications. Precise and clear spending estimates are material for policymakers to accurately understand the effect of their resource allocation decisions.

Objective To improve the understanding of local health departments' (LHDs') capacity for and perceived barriers to using quantitative/economic modeling information to inform policy and program decisions. Design We developed, tested, and deployed a novel survey to examine this topic. Setting The study's sample frame included the 200 largest LHDs in terms of size of population served plus all other accredited LHDs (n = 67). The survey was e-mailed to 267 LHDs; respondents completed the survey online using SurveyMonkey. Participants Survey instructions requested that the survey be completed from the perspective of the entire health department by LHD's top executive or designate. A total of 63 unique LHDs responded (response rate: 39%). Main outcome measure(s) Capacity for quantitative and economic modeling was measured in 5 categories (routinely use information from models we create ourselves; routinely use information from models created by others; sometimes use information from models we create ourselves; sometimes use information from models created by others; never use information from modeling). Experience with modeling was measured in 4 categories (very, somewhat, not so, not at all). Results Few (9.5%) respondents reported routinely using information from models, and most who did used information from models created by others. By contrast, respondents reported high levels of interest in using models and in gaining training in their use and the communication of model results. The most commonly reported barriers to modeling were funding and technical skills. Nearly all types of training topics listed were of interest. Conclusions Across a sample of large and/or accredited LHDs, we found modest levels of use of modeling coupled with strong interest in capacity for modeling and therefore highlight an opportunity for LHD growth and support. Both funding constraints and a lack of knowledge of how to develop and/or use modeling are barriers to desired progress around modeling. Educational or funding opportunities to promote capacity for and use of quantitative and economic modeling may catalyze use of modeling by public health practitioners.

Objective To explore whether health outcomes are influenced by both governmental social services spending and hospital provision of community health services. Design We combined hospital provision of community health services data from the American Hospital Association with local governmental spending data from the US Census Bureau. Longitudinal models regressed community health outcomes for 2012-2016 on local government spending on health, social services, and education from 5 years previously, controlling for sociodemographic and hospital marketplace characteristics, spatial autocorrelation, and state-level random effects. For counties with hospitals, models also included county-level data on hospitals' provision of community health services. Setting All analyses were performed at the county level for US counties between 2012 and 2016. Participants Complete spending, hospital, and health outcomes data were available for a total of 2379 counties. Main outcome measures We examined relationships between governmental spending, hospital service provision, and 5 population health outcome measures: years of potential life lost prior to age 75 years per 100 000 population, percentage of population in fair or poor health, percentage of adults who are physically inactive, deaths due to injury per 100 000 population, and percentage of births that are of low birth weight. Results Governmental investments in health, social services, and education positively impacted key health outcomes but mainly in counties with 1 or more hospitals present. Hospitals' provision of community health services also had a significant positive impact on health outcomes. Conclusions Hospital provision of community health services and increases in local governmental health and social services spending were both associated with improved health. Collaboration between local governments and hospitals may help ensure that public and private community health resources synergistically contribute to the public's health. Local policy makers should consider service provision by the private sector to leverage the public investments in health and social services.

Supplemental Digital Content is Available in the Text., Objective: To assess the financial competencies and skills of the state and local public health workforce. Design: Analysis of the 2017 wave of the Public Health Workforce Interests and Needs Survey (PH WINS). Bivariate statistics and logistic regression models identified correlates and predictors of financial skills and skills gaps in the workforce. Setting: PH WINS was fielded to a nationally representative sample of all staff at all local health departments serving 25 000 or more persons and all state health agency staff. Participants: A total of 47 604 people responded to PH WINS in 2017 (overall response rate 48%). Main Outcome Measures: Financial competencies were measured in 3 areas: public health program and service delivery, public health agency funding, and public health agency business planning. Results: A moderate percentage of the state and local public health workforce (36.7%-40.6%) reported that financial skills were not applicable to their job. Skill levels tended to be modestly but significantly higher for the state health workforce than for the local health workforce. Correlates of financial proficiency and skills gaps varied for the 3 areas assessed and by state versus local setting. In general, administrators, managers and executives, older individuals, and persons working in decentralized or shared departments tended to have higher levels of financial skills proficiency. Persons working in clinical roles, supervisors, newer managers, and persons reporting higher levels of burnout were more likely to report a skills gap. Conclusions: There are areas of notable strengths in state and local public health workforce financial skills. Yet portions of the workforce that may have been subjected to newer financial training approaches did not consistently report higher financial skills. Findings suggest areas for further improvement in the financial competency of the state and local public health workforce.

The COVID-19 pandemic has prompted concern about the integrity of the US public health infrastructure. Federal, state, and local governments spend $93 billion annually on public health in the US, but most of this spending is at the state level. Thus, shoring up gaps in public health preparedness and response requires an understanding of state spending. We present state spending trends in eight categories of public health activity from 2008 through 2018. We obtained data from the Census Bureau for all states except California and coded the data by public health category. Although overall national health expenditures grew by 4.3 percent in this period, state governmental public health spending saw no statistically significant growth between 2008 and 2018 except in injury prevention. Moreover, state spending levels on public health were not restored after cuts experienced during the Great Recession, leaving states ill equipped to respond to COVID-19 and other emerging health needs.

CDC recommends universal indoor masking by students, staff members, faculty, and visitors in kindergarten through grade 12 (K-12) schools, regardless of vaccination status, to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 (1). Schools in Maricopa and Pima Counties, which account for >75% of Arizona's population (2), resumed in-person learning for the 2021-22 academic year during late July through early August 2021. In mid-July, county-wide 7-day case rates were 161 and 105 per 100,000 persons in Maricopa and Pima Counties, respectively, and 47.6% of Maricopa County residents and 59.2% of Pima County residents had received at least 1 dose of a COVID-19 vaccine. School districts in both counties implemented variable mask policies at the start of the 2021-22 academic year (Table). The association between school mask policies and school-associated COVID-19 outbreaks in K-12 public noncharter schools open for in-person learning in Maricopa and Pima Counties during July 15-August 31, 2021, was evaluated.

Public health in the rural United States is a complex and underfunded enterprise. While urban–rural disparities have been a focus for researchers and policymakers alike for decades, inequalities continue to grow. Life expectancy at birth is now 1 to 2 years greater between wealthier urban and rural counties, and is as much as 5 years, on average, between wealthy and poor counties. This article explores the growth in these disparities over the past 40 years, with roots in structural, economic, and social spending differentials that have emerged or persisted over the same time period. Importantly, a focus on place-based disparities recognizes that the rural United States is not a monolith, with important geographic and cultural differences present regionally. We also focus on the challenges the rural governmental public health enterprise faces, the so-called “double disparity” of worse health outcomes and behaviors alongside modest investment in health departments compared with their nonrural peers. Finally, we offer 5 population-based “prescriptions” for supporting rural public health in the United States. These relate to greater investment and supporting rural advocacy to better address the needs of the rural United States in this new decade.

Objectives. To examine spending and resource allocation decision-making to address health and social service integration challenges within and between governments. Methods. We performed a mixed methods case study to examine the integration of health and social services in a large US metropolitan area, including a city and a county government. Analyses incorporated annual budget data from the city and the county from 2009 to 2018 and semistructured interviews with 41 key leaders, including directors, deputies, or finance officers from all health care–, health-, or social service–oriented city and county agencies; lead budget and finance managers; and city and county executive offices. Results. Participants viewed public health and social services as qualitatively important, although together these constituted only $157 or $1250 total per capita spending in 2018, and per capita public health spending has declined since 2009. Funding streams can be siloed and budget approaches can facilitate or impede service integration. Conclusions. Health and social services should be integrated through greater attention to the budgetary, jurisdictional, and programmatic realities of health and social service agencies and to the budget models used for driving the systems-level pursuit of population health.

The US public and private sectors now spend more than $3 trillion on health each year. While critical studies have examined the relationship between public spending on health and health outcomes, relatively little is known about the impact of broader public-sector spending on health. Using county-level public finance data for the period 1972-2012, we estimated the impact of local public hospital spending and nonhospital health spending on all-cause mortality in the county. Overall, a 10 percent increase in nonhospital health spending was associated with a 0.006 percent decrease in all-cause mortality one year after the initial spending. This effect was larger and significant in counties with greater proportions of racial/ethnic minorities. Our results indicate that county nonhospital health spending has health benefits that can help reduce costs and improve health outcomes in localities across the nation, though greater focus on population-oriented services may be warranted.

Upstream spending on social determinants of health can lead to improved downstream population health outcomes but intermediate steps between these end points are unclear. The purpose of this study was to determine the longitudinal impacts of government spending on hospital visits for potentially preventable conditions. The authors used secondary data sets from 2007-2014 to measure county-level Prevention Quality Indicator (PQI) rates, local government health and social services spending, hospital-provided community health services, and other sociodemographics. Mixed effects models regressed county PQI rates on deviation from mean local government spending from 4 years previously to account for lag between spending and outcomes. Thirty-two states reported PQI data; complete data were available for 1660 counties. Controlling for baseline spending levels, a 1-time $10 per capita increase in social services spending was associated with 1.9 fewer preventable hospitalizations (per 100,000) within 4 years (

OBJECTIVE To generate estimates of the direct costs of mounting simultaneous emergency preparedness and response activities to respond to 3 major public health events. DESIGN A cost analysis was performed from the perspective of the public health department using real-time activity diaries and retrospective time and activity self-reporting, wage and fringe benefit data, and financial records to track costs. SETTING Maricopa County Department of Public Health (MCDPH) in Arizona. The nation's third largest local public health jurisdiction, MCDPH is the only local health agency serving Maricopa's more than 4 000 000 residents. Responses analyzed included activities related to a measles outbreak with 2 confirmed cases, enhanced surveillance activities surrounding Super Bowl XLIX, and ongoing Ebola monitoring, all between January 22, 2015, and March 4, 2015. PARTICIPANTS Time data were sought from all MCDPH staff who participated in activities related to any of the 3 relevant responses. In addition, time data were sought from partners at the state health department and a community hospital involved in response activities. Time estimates were received from 128 individuals (response rate 88%). MAIN OUTCOME MEASURE Time and cost to MCDPH for each response and overall. RESULTS Total MCDPH costs for measles-, Super Bowl-, and Ebola-related activities from January 22, 2015, through March 4, 2015, were $224 484 (>5800 hours). The majority was for personnel ($203 743) and the costliest response was measles ($122 626 in personnel costs). In addition, partners reported working more than 700 hours for these 3 responses during this period. CONCLUSIONS Funding for public health departments remains limited, yet public health responses can be cost- and time-intensive. To effectively plan for future public health responses, it may be necessary to share experiences and financial lessons learned from similar public health responses. External partnerships represent a key contribution for responses such as those examined. It can be expensive for local public health departments to mount effective responses, especially when multiple responses occur simultaneously.

Objectives Public health and social services spending have been shown to improve health outcomes at the county level, although there are significant state and regional variations in such spending. Texas offers an important opportunity for examining nuances in the patterns of association between local government health and social services spending and population health outcomes. The primary objectives of this study were to describe local investments in education, health, and social services at the county-area level for all of Texas from 2002 through 2012 and to examine how changes in local investment over time were associated with changes in health outcomes. Methods We used two large secondary data sources for this study. First, US Census Bureau data were used to measure annual spending by all local governments on public hospitals, community health care and public health, and >1 dozen social services. Second, County Health Rankings & Roadmaps data measured county health outcomes. We performed regression models to examine the association between increases in local government spending and a county's health outcomes ranking 4 years later. Multilevel mixed-effects linear regression models accounted for mean spending in each category, county health factors ranking, and county and state random effects. Results Local governments in Texas spent an average of $4717 per capita across all health and social services. Although spending was relatively consistent across 2002-2012, there was notable variation in spending across counties and services. Regression models found that changes in four spending categories were associated with significant improvements in health outcomes: fire and ambulance, community health care and public health, housing and community development, and libraries. For each, an additional one-time investment of $15 per capita was associated with a 1-spot improvement in statewide county health rankings within 4 years. Conclusions Existing evidence regarding the association between social services spending and health outcomes may not yield sufficiently granular data for policy makers within a single state. Investments in certain social services in Texas were associated with improvements in health outcomes, as measured by improvements in the County Health Rankings, in the years subsequent to spending increases. Similar analyses in other states and regions may yield actionable avenues for policy makers to improve population health.

There is little evidence to demonstrate the impact on local health outcomes of spending that occurs outside the health care sector. We leveraged novel data from the US Census Bureau to measure the independent impact of a community's health and nonhealth expenditures on a broad measure of overall health-the County Health Rankings-over time. Using lagged longitudinal models that accounted for correlations of health outcomes and expenditures within counties, we found significant positive associations between expenditures and County Health Rankings for seven of the fourteen expenditure categories examined: community health care and public health, public hospitals, fire protection, K-12 education, corrections, libraries, and housing and community development. These areas of social spending have modest but detectable positive associations with population health, whether or not they primarily target health. Achieving improved health outcomes through a culture-of-health ethos should involve the consideration of public expenditures in both health and other social service areas.

Background Many health departments collaborate with community organizations on community health improvement processes. While a number of resources exist to plan and implement a community health improvement plan (CHIP), little empirical evidence exists on how to leverage and expand partnerships when implementing a CHIP. The purpose of this study was to identify characteristics of the network involved in implementing the CHIP in one large community. The aims of this analysis are to: 1) identify essential network partners (and thereby highlight potential network gaps), 2) gauge current levels of partner involvement, 3) understand and effectively leverage network resources, and 4) enable a data-driven approach for future collaborative network improvements. Methods We collected primary data via survey from n = 41 organizations involved in the Health Improvement Partnership of Maricopa County (HIPMC), in Arizona. Using the previously validated Program to Analyze, Record, and Track Networks to Enhance Relationships (PARTNER) tool, organizations provided information on existing ties with other coalition members, including frequency and depth of partnership and eight categories of perceived value/trust of each current partner organization. Results The coalition’s overall network had a density score of 30 %, degree centralization score of 73 %, and trust score of 81 %. Network maps are presented to identify existing relationships between HIPMC members according to partnership frequency and intensity, duration of involvement in the coalition, and self-reported contributions to the coalition. Overall, number of ties and other partnership measures were positively correlated with an organization’s perceived value and trustworthiness as rated by other coalition members. Conclusions Our study presents a novel use of social network analysis methods to evaluate the coalition of organizations involved in implementing a CHIP in an urban community. The large coalition had relatively low network density but high degree centralization—meaning key organizations link organizations otherwise not tightly partnering. Coalition members rated each other highly on trust, a positive sign for future partnership development efforts. Examination of network maps reveal key organizations that can be targeted for future partnership facilitation and expansion. Future network data collection will enable exploration of longitudinal trends and exploration of network characteristics versus health behavior, status, and outcome changes.

School nurses often play large roles in implementation of school vaccination requirements aimed at controlling the spread of communicable disease. We analyzed the association between the presence of a school nurse and school-level vaccination rates in Arizona. Using school-level data from Arizona sixth-grade schools ( n = 749), we regressed average sixth-grade school-level immunization rates on presence of a school nurse (registered nurse [RN] or licensed practical nurse [LPN]) and school-level socioeconomic status (SES), controlling for other school- and district-level characteristics. Schools with a nurse had higher overall vaccination rates than those without a nurse (96.1% vs. 95.0%, p < .01). For schools in the lowest SES quartile, the presence of a school nurse was associated with approximately 2 percentage point higher immunization rates. These findings add to the growing literature that defines the impact of school nurses on student health status and outcomes, emphasizing the value of school nurses, especially in lower SES schools.

Supplemental material, Online_Appendix for Government Health and Social Services Spending Show Evidence of Single-Sector Rather Than Multi-Sector Pursuit of Population Health by J. Mac McCullough in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

BACKGROUND Modern public health emphasizes population-focused services, which may require collaborative work both across and within organizations. Studies have explored interorganizational collaborations, but there are little data regarding collaborations within public health organizations. PURPOSE We measured intraorganizational collaboration and identified barriers and facilitators to collaboration within a large public health department through a mixed-methods study. METHODOLOGY/APPROACH Our study occurred at the Maricopa County (Arizona) Department of Public Health, the third largest local public health jurisdiction in the United States. To measure collaboration, we surveyed staff using the relational coordination tool. To identify barriers and facilitators to collaboration, we performed key informant interviews with department personnel. RESULTS Relational coordination scores varied according to the focus of the service; clinical services had significantly lower levels of relational coordination than population-focused services (p < .01). We found high levels of mutual respect and lower levels of shared knowledge across services. Facilitators to collaboration included purposive cross-program meetings around specific topics, the organization's structure and culture, and individuals' social identities. Barriers included raised expectations for collaboration, low slack resources, member's self-interest, and trust. CONCLUSION The relational coordination of services varied significantly according to the focus of the service. Population-focused public health services had higher levels of relational coordination than individually focused services. Collaboration was facilitated and impeded by both well-known and potentially emergent factors, such as purposive cross-service meetings and organizational culture. PRACTICE IMPLICATIONS Population-focused services possessed higher levels of collaboration than individually focused services. Intraorganizational collaboration for improved population health relies on deliberate support from senior management and structured activities to increase shared knowledge and mutual respect.

Introduction We examined the percentage of local government taxes (“fiscal allocation”) dedicated to local health departments on a national level, as well as correlates of local investment in public health. Methods Using the most recent data available—the 2008 National Association of City and County Health Officials Profile survey and the 2007 U.S. Census Bureau Census of Local Governments—generalized linear regression models examined associations between fiscal allocation and local health department setting, governance, finance, and service provision. Models were stratified by the extent of long-term debt for the jurisdiction. Analyses were performed in 2014. Results Average fiscal allocation for public health was 3.31% of total local taxes. In multivariate regressions, per capita expenditures, having a local board of health and public health service provision were associated with higher fiscal allocation. Stratified models showed that local board of health and local health department taxing authority were associated with fiscal allocation in low and high long-term debt areas, respectively. Conclusions The proportion of all local taxes allocated to local public health is related to local health department expenditures, service provision, and governance. These relationships depend upon the extent of long-term debt in the jurisdiction.

The conceptual importance of social services to health outcomes is well known and recent empirical evidence has linked social services spending to better population health outcomes. Yet little research has been devoted to what social services spending actually entails as it relates to population health and whether broadly similar spending patterns may exist across communities. The purpose of this study was to identify empirical patterns in spending, and explore health status and outcome correlates with social services spending. Spending data come from the 2012 U.S. Census Bureau's Census of Governments, which includes spending data for 14 social services within 3129 U.S. counties. Additional 2012 demographic, socioeconomic, and population health data were obtained and analyzed at the county-level in 2017. Hierarchical cluster analysis revealed 5 clusters of counties according to local government spending. One group had significantly lower income, social services spending, health indicators, and health outcomes than other counties. Two other groups had relatively high income, high social services spending, and strong health outcomes and indicators. Yet these latter two groups invested differently, with one spreading spending across a larger number of social services and the other concentrating spending in a smaller number of services such as education. Determining the extent to which spending approaches contribute to population health may offer communities guidance for maximizing population health. While it cannot establish causality, this study adds to the literature regarding the ways in which communities invest in both health care and social services to prevent disease and promote population health.

Infants born at full term have better health outcomes. However, one in ten babies in the United States are born via a medically unnecessary early elective delivery: induction of labor, a cesarean section, or both before thirty-nine weeks gestation. In 2011 the Texas Medicaid program sought to reduce the rate of early elective deliveries by denying payment to providers for the procedure. We examined the impact of this policy on clinical care practice and perinatal outcomes by comparing the changes in Texas relative to comparison states. We found that early elective delivery rates fell by as much as 14 percent in Texas after this payment policy change, which led to gains of almost five days in gestational age and six ounces in birthweight among births affected by the policy. The impact on early elective delivery was larger in magnitude for minority patients. Other states may look to this Medicaid payment reform as a model for reducing early elective deliveries and disparities in infant health.

Introduction Each year, the County Health Rankings rate the health outcomes of each county in the U.S. A common refrain is that poor counties perform worse than wealthier ones. This article examines that assumption and specifically analyzes characteristics of counties that have performed better in terms of health outcomes than their wealth alone would suggest. Methods Data from the 2013 County Health Rankings were used, as were 2012 financial and demographic information collected by the U.S. Census Bureau. A logistic model was constructed to examine the odds of a county “overperforming” in the rankings relative to community wealth. Analyses were performed in 2016. Results Communities that were wealthier performed better on the rankings. However, more than 800 of 3,141 counties overperformed by ranking in a better health outcomes quartile than their county’s wealth alone would suggest. Regression analyses found that for each additional percentage point of total public spending that was allocated toward community health care and public health, the odds of being an overperformer increased by 3.7%. Conclusions Community wealth correlates with health, but not always. Population health outcomes in hundreds of counties overperform what would be expected given community wealth alone. These counties tend to invest more in community health care and public health spending and other social services. Although the level of a community’s wealth is outside the control of practitioners, shifting the proportion of spending to certain social services may positively impact population health.

Although numerous software and data storage systems are used by local health departments to manage clinical and nonclinical data needs, information is lacking regarding current usage patterns. This study examines and analyzes current usage of clinical data storage and software types by local health departments and identifies characteristics of local health departments associated with these usage patterns., Context: Numerous software and data storage systems are employed by local health departments (LHDs) to manage clinical and nonclinical data needs. Leveraging electronic systems may yield improvements in public health practice. However, information is lacking regarding current usage patterns among LHDs. Objective: To analyze clinical and nonclinical data storage and software types by LHDs. Design: Data came from the 2015 Informatics Capacity and Needs Assessment Survey, conducted by Georgia Southern University in collaboration with the National Association of County and City Health Officials. Participants: A total of 324 LHDs from all 50 states completed the survey (response rate: 50%). Main Outcome Measures: Outcome measures included LHD's primary clinical service data system, nonclinical data system(s) used, and plans to adopt electronic clinical data system (if not already in use). Predictors of interest included jurisdiction size and governance type, and other informatics capacities within the LHD. Bivariate analyses were performed using χ2 and t tests. Results: Up to 38.4% of LHDs reported using an electronic health record (EHR). Usage was common especially among LHDs that provide primary care and/or dental services. LHDs serving smaller populations and those with state-level governance were both less likely to use an EHR. Paper records were a common data storage approach for both clinical data (28.9%) and nonclinical data (59.4%). Among LHDs without an EHR, 84.7% reported implementation plans. Conclusions: Our findings suggest that LHDs are increasingly using EHRs as a clinical data storage solution and that more LHDs are likely to adopt EHRs in the foreseeable future. Yet use of paper records remains common. Correlates of electronic system usage emerged across a range of factors. Program- or system-specific needs may be barriers or facilitators to EHR adoption. Policy makers can tailor resources to address barriers specific to LHD size, governance, service portfolio, existing informatics capabilities, and other pertinent characteristics.

Objective: Little is known about the nationwide patterns in the use of public health informatics systems by local health departments (LHDs) and whether LHDs tend to possess informatics capacity across a broad range of information functionalities or for a narrower range. This study examined patterns and correlates of the presence of public health informatics functionalities within LHDs through the creation of a typology of LHD informatics capacities. Methods: Data were available for 459 LHDs from the 2013 National Association of County and City Health Officials Profile survey. An empirical typology was created through cluster analysis of six public health informatics functionalities: immunization registry, electronic disease registry, electronic lab reporting, electronic health records, health information exchange, and electronic syndromic surveillance system. Three-categories of usage emerged (Low, Mid, High). LHD financial, workforce, organization, governance, and leadership characteristics, and types of services provided were explored across categories. Results: Low-informatics capacity LHDs had lower levels of use of each informatics functionality than high-informatics capacity LHDs. Mid-informatics capacity LHDs had usage levels equivalent to high-capacity LHDs for the three most common functionalities and equivalent to low-capacity LHDs for the three least common functionalities. Informatics capacity was positively associated with service provision, especially for population-focused services. Conclusion: Informatics capacity is clustered within LHDs. Increasing LHD informatics capacity may require LHDs with low levels of informatics capacity to expand capacity across a range of functionalities, taking into account their narrower service portfolio. LHDs with mid-level informatics capacity may need specialized support in enhancing capacity for less common technologies.

Objective: Little is known about the nationwide patterns in the use of public health informatics systems by local health departments (LHDs) and whether LHDs tend to possess informatics capacity across a broad range of information functionalities or for a narrower range. This study examined patterns and correlates of the presence of public health informatics functionalities within LHDs through the creation of a typology of LHD informatics capacities.Methods: Data was available for 459 LHDs from the 2013 National Association of County and City Health Officials Profile survey. An empirical typology was created through cluster analysis of six public health informatics functionalities: immunization registry, electronic disease registry, electronic lab reporting, electronic health records, health information exchange, electronic syndromic surveillance system. Three-categories of usage emerged (Low, Mid, High). LHD financial, workforce, organization, governance, and leadership characteristics, and types of services provided were explored across categories.Results: Low-informatics capacity LHDs had lower levels of use of each informatics functionalities than high-informatics capacity LHDs. Mid-informatics capacity LHDs had usage levels equivalent to high-capacity LHDs for the three most common functionalities and equivalent to low-capacity LHDs for the three least common functionalities. Informatics capacity was positively associated with service provision, especially for population-focused services.Conclusion: Informatics capacity is clustered within LHDs. Increasing LHD informatics capacity may require LHDs with low levels of informatics capacity to expand capacity across a range of functionalities, taking into account their narrower service portfolio. LHDs with mid-level informatics capacity may need specialized support in enhancing capacity for less common technologies.

Objective Antibiotics are commonly recognized as non-indicated for acute bronchitis and upper respiratory tract infection (URI), yet their widespread use persists. Clinical decision support in the form of electronic warnings is hypothesized to prevent non-indicated prescriptions. The purpose of this study was to identify the effect of clinical decision support on a common type of non-indicated prescription. Materials and methods Using National Ambulatory Medical Care Survey data from 2006 to 2010, ambulatory visits with a primary diagnosis of acute bronchitis or URI and orders for antibiotic prescriptions were identified. Visits were classified on the basis of clinician report of decision-support use. Generalized estimating equations were used to assess the effect of decision support on likelihood of antibiotic prescription receipt, controlling for patient, provider, and practice characteristics. Results Clinician use of decision support increased sharply between 2006 (16% of visits) and 2010 (55%). Antibiotic prescribing for acute bronchitis and URI increased from ∼35% of visits in 2006 to ∼45% by 2010. Use of decision support was associated with a 19% lower likelihood of receiving an antibiotic prescription, controlling for patient, provider, and practice characteristics. Discussion In spite of the increased use of decision-support systems and the relatively fewer non-indicated antibiotic prescriptions resulting from the use of decision support, a secular upward trend in non-indicated antibiotic prescribing offset these improvements. Conclusions The overall effect of decision support suggests an important role for technology in reducing non-indicated prescriptions. Decision support alone may not be sufficient to eliminate non-indicated prescriptions given secular trends.

Background Health information exchange (HIE) is an important tool for improving efficiency and quality and is required for providers to meet Meaningful Use certification from the United States Centers for Medicare and Medicaid Services. However widespread adoption and use of HIE has been difficult to achieve, especially in settings such as smaller-sized physician practices and federally qualified health centers (FQHCs). We assess electronic data exchange activities and identify barriers and benefits to HIE participation in two underserved settings. Methods We conducted key-informant interviews with stakeholders at physician practices and health centers. Interviews were recorded, transcribed, and then coded in two waves: first using an open-coding approach and second using selective coding to identify themes that emerged across interviews, including barriers and facilitators to HIE adoption and use. Results We interviewed 24 providers, administrators and office staff from 16 locations in two states. They identified barriers to HIE use at three levels—regional (e.g., lack of area-level exchanges; partner organizations), inter-organizational (e.g., strong relationships with exchange partners; achieving a critical mass of users), and intra-organizational (e.g., type of electronic medical record used; integration into organization’s workflow). A major perceived benefit of HIE use was the improved care-coordination clinicians could provide to patients as a direct result of the HIE information. Utilization and perceived benefit of the exchange systems differed based on several practice- and clinic-level factors. Conclusions The adoption and use of HIE in underserved settings appears to be impeded by regional, inter-organizational, and intra-organizational factors and facilitated by perceived benefits largely at the intra-organizational level. Stakeholders should consider factors both internal and external to their organization, focusing efforts in changing modifiable factors and tailoring HIE efforts based on all three categories of factors. Collective action between organizations may be needed to address inter-organizational and regional barriers. In the interest of facilitating HIE adoption and use, the impact of interventions at various levels on improving the use of electronic health data exchange should be tested. Electronic supplementary material The online version of this article (doi:10.1186/1472-6963-14-415) contains supplementary material, which is available to authorized users.