Lessons Learned From Applying a Monitoring and Evaluation Framework to Economic, Social, and Other Health Impacts of the COVID-19 Pandemic.

Individual and community-level COVID-19 mitigation policies can have effects beyond direct COVID-19 health outcomes, including social, behavioral, and economic outcomes. These social, behavioral, and economic outcomes can extend beyond the pandemic period and have disparate effects on populations. Public Health-Seattle & King County (PHSKC) built on the Centers for Disease Control and Prevention's community mitigation strategy framework to create a local project tracking near-real-time data to understand factors affected by mitigation approaches, inform decision-making, and monitor and evaluate community-level disparities during the pandemic. This case study describes the framework and lessons learned from PHSKC's collation, use, and dissemination of local data from 20 data sources to guide community and public health decision-making. Social, behavioral, economic, and health indicators were regularly updated and disseminated through interactive dashboards and products that examined data in the context of applicable policies. Data disaggregated by demographic characteristics and geography highlighted inequities, but not all datasets contained the same details; local surveys or qualitative data were used to fill gaps. Project outcomes included informing city and county emergency response planning related to implementation of financial and food assistance programs. Key lessons learned included the need to (1) build on existing processes and use automated processes and (2) partner with other sectors to use nontraditional public health data for active dissemination and data disaggregation and for real-time data contextualized by policy changes. This project provided programs and communities with timely, reliable data to understand where to invest recovery funding. A similar framework could position other health departments to examine social and economic effects during future public health emergencies.

A Good Farewell? Positive Exits from Federal Housing Assistance and Lower Acute Healthcare Utilization.

Little is known regarding the health outcomes of people who exit from housing assistance and if that experience varies by the circumstances under which a person exits. We asked two questions: (1) does the type of exit from housing assistance matter for healthcare utilization? And (2) how does each exit type compare to remaining in housing assistance in terms of healthcare utilization? This retrospective cohort study of 5550 exits between 2012 and 2018 used data from two large, urban public housing authorities in King County, Washington. Exposures were exiting from housing assistance and type of exit (positive, neutral, negative). Outcomes were emergency department visits, hospitalizations, and well-child checks (among those aged < 6) in the year following exit from housing assistance. After adjustment for demographics and baseline healthcare utilization, people with positive exits had 26% (95% confident interval: 6-39%) lower odds of having 1 + ED visits in the year following exit than people with negative exits and 20% (95% CI: 6-31%) lower odds than those who continued receiving housing assistance. Neutral and negative exits did not differ substantially from each other, and both exit types appear to be detrimental to health, with higher levels of ED visits and hospitalizations and lower levels of well-child checks. Why people exit from housing assistance matters. Those with negative exits experience poorer outcomes and efforts should be made to both prevent this kind of exit and mitigate its impact.

Paediatric Major Trauma: A Retrospective Observational Comparison of Mortality in Prehospital Bypass and Secondary Transfer in the East of England.

Background More than half of seriously injured children are not initially treated at a major trauma centre (MTC). Children may be transported by private vehicle to a trauma unit (TU). Children may also be transported by emergency medical services (EMS) to the nearest TU with approximately one in five of these undergoing secondary transfer to an MTC. Most trauma networks permit TU bypass to an MTC. However, the evidence on outcomes between transfer and bypass is limited. This study aimed to evaluate the use of the trauma network by comparing outcomes between paediatric major trauma patients by the method of presentation. Methods In this retrospective observational study, a consecutive sample of paediatric (<16 years old) major trauma patients transported to the regional MTC (Cambridge University Hospitals NHS Foundation Trust (CUH)) between 1st January 2015 and 31st December 2020 was included. Patients were excluded if they arrived at the MTC >24 hours post-injury or were transported to the MTC as the nearest hospital. Patients were divided into four groups: self-presented to MTC, MTC as nearest hospital, bypass and secondary transfer. Results A total of 315 patients (28 'self-presented', 55 'nearest', 58 'bypass' and 174 'secondary transfers') were included. The median age was 9.4 [3.7-13.6] years, and n=209 (66.3%) were male. The median Injury Severity Score (ISS) was 16.0 [9.0-25.0] and n=190 (60.3%) had an ISS >15. There was no difference in 30-day mortality between the 'bypass' and 'secondary transfer' groups. There was a significantly longer hospital and intensive care unit length of stay (LOS) in the bypass group compared to other groups, both p<0.001. The median time to definitive care was five hours greater in the secondary transfer group compared to 'bypass' (bypass 117.6 minutes [100.8-136.6], secondary transfer 418.8 minutes [315.6-529.8]). Conclusion There was no significant difference in 30-day mortality of paediatric major trauma patients who underwent secondary transfer compared to those transported directly from the scene to the MTC, despite significant time delays in reaching definitive care.

Social Participation Experiences of Families Raising a Young Child With Autism Spectrum Disorder: Implications for Mental Health and Well-Being.

IMPORTANCE: Social participation (SP) is an important facilitator of positive mental health for children and families. Children are dependent on their families to mediate SP, yet families of children with autism spectrum disorder (C-ASD) seemingly limit SP because of behavioral and functional challenges in community environments. The resulting isolation can affect the child's and the family's mental health. OBJECTIVE: To distill the essence of everyday SP experiences in the community of families raising C-ASD. DESIGN: Data collected via in-depth, semistructured interviews with a purposive sample and analyzed in the phenomenological tradition. SETTING: Community. PARTICIPANTS: We recruited seven families with English-speaking parents (ages 18-64 yr) raising one C-ASD (age 2-8 yr). Families with more than one C-ASD or those whose C-ASD was diagnosed with complex medical condition or a neurological or genetic disorder were excluded. RESULTS: The essence of experiences of SP emerged in the form of three themes depicting the mismatch between societal expectations for SP and families' experience: (1) "the struggle," (2) "it's hard to feel like you belong," and (3) what we "have to do." CONCLUSIONS AND RELEVANCE: As a collective, families expressed desire for everyday community SP and could do so only in select environments with core groups. The findings, as interpreted through the lens of mental health promotion, reveal opportunities to reduce barriers and to promote meaningful family SP so as to facilitate positive mental health and well-being through the transactional intersecting characteristics of the child with ASD, the family, and the community. What This Article Adds: This study illuminates the experience of SP of families raising a young C-ASD, highlighting both supports and barriers. Practitioners can use this information to potentially prevent isolation and promote both child and family mental health and well-being.

Social, Economic and Overall Health Impacts of COVID-19 on People Living with Disabilities in King County, WA.

The COVID-19 pandemic and the associated mitigation measures to reduce the spread of disease affected the social, economic, and overall health of individuals. Quantitative administrative datasets typically did not contain demographic information that allowed for reporting or analysis of the impacts of COVID-19 on people living with disabilities. Understanding the experiences of this population during the pandemic can inform the design of public health responses that are more robust and better connected to community. This paper describes a qualitative participatory study with a diverse sample of people living with disabilities in King County, WA. Through 2 listening sessions and 35 semi-structured interviews, it examines what impacts COVID-19 brought for people living with disabilities; elucidates the supports that were helpful in addressing COVID-19 impacts; examines inequities faced by the disability community; and sheds light on how to engage with this community to inform the public health emergency response. The process, protocols, findings, and lessons learned are replicable by other local health departments and could be incorporated as part of routine data collection and considered for future public health emergencies.

Cross-Sector Monitoring and Evaluation Framework: Social, Economic, and Health Conditions Impacted During the COVID-19 Pandemic.

Public Health 3.0 approaches are critical for monitoring disparities in economic, social, and overall health impacts following the COVID-19 pandemic and its associated policy changes to slow community spread. Timely, cross-sector data as identified using this approach help decisionmakers identify changes, track racial disparities, and address unintended consequences during a pandemic. We applied a monitoring and evaluation framework that combined policy changes with timely, relevant cross-sector data and community review. Indicators covered unemployment, basic needs, family violence, education, childcare, access to health care, and mental, physical, and behavioral health. In response to increasing COVID-19 cases, nonpharmaceutical intervention strategies were implemented in March 2020 in King County, Washington. By December 2020, 554 000 unemployment claims were filed. Social service calls increased 100%, behavioral health crisis calls increased 25%, and domestic violence calls increased 25%, with disproportionate impact on communities of color. This framework can be replicated by local jurisdictions to inform and address racial inequities in ongoing COVID-19 mitigation and recovery. Cross-sector collaboration between public health and sectors addressing the social determinants of health are an essential first step to have an impact on long-standing racial inequities. (Am J Public Health. 2021;111(S3):S215-S223. https://doi.org/10.2105/AJPH.2021.306422).

Linking Health and Housing Data to Create a Sustainable Cross-Sector Partnership.

In response to the growing regional (and national) focus on health and housing intersections, two public housing authorities (PHAs) in Washington-the King County Housing Authority and the Seattle Housing Authority-joined with Public Health-Seattle & King County to form the Housing and Health (H&H) partnership in 2016. H&H linked Medicaid health claims with PHA administrative data to create a sustainable public-facing dashboard that informs health and housing stakeholders such as an Accountable Community of Health (a governing body that oversees local Medicaid transformation projects), managed care organizations, and PHAs, allowing insights into the low-income communities they serve.

Sub-County Life Expectancy: A Tool to Improve Community Health and Advance Health Equity.

Compared with people in other developed countries, Americans live shorter lives, have more disease and disability, and lag on most population health measures. Recent research suggests that this poor comparative performance is primarily driven by profound local place-based disparities. Several initiatives successfully used sub-county life expectancy estimates to identify geographic disparities, generate widespread interest, and catalyze multisector actions. To explore the feasibility of scaling these efforts, the Centers for Disease Control and Prevention and the Council of State and Territorial Epidemiologists initiated a multiphase project - the Sub-County Assessment of Life Expectancy. Phase I participants reviewed the literature, assessed and identified appropriate tools, calculated locally relevant estimates, and developed methodological guidance. Phase I results suggest that most state and local health departments will be able to calculate actionable sub-county life expectancy estimates despite varying resources, expertise, and population sizes, densities, and geographies. To accelerate widespread scaling, we describe several successful case examples, identify user-friendly validated tools, and provide practical tips that resulted from lessons learned.

Development of Emotion Self-Regulation Among Young Children with Autism Spectrum Disorders: The Role of Parents.

Emotional self-regulation (ESR) challenges are well-documented in the diagnostic profiles of children with Autism; however, less is known about the development of ESR and the role of parents in ESR development for this population. Thirty-seven young children with autism and one of their parents participated in a home-based, observational study exploring the associations between the children's social communication and sensory processing characteristics and their parents' behaviors associated with ESR development. Findings revealed that parent use of physical and language behaviors were associated with child social communication abilities. No associations between child sensory processing and parent behaviors were found. Understanding the interactive processes between parents and children with ASD has implications for the development of parent-based interventions that increase child ESR.

Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990-2014: a census tract-level analysis for the Global Burden of Disease Study 2015.

BACKGROUND: Health outcomes are known to vary at both the country and local levels, but trends in mortality across a detailed and comprehensive set of causes have not been previously described at a very local level. Life expectancy in King County, WA, USA, is in the 95th percentile among all counties in the USA. However, little is known about how life expectancy and mortality from different causes of death vary at a local, neighbourhood level within this county. In this analysis, we estimated life expectancy and cause-specific mortality within King County to describe spatial trends, quantify disparities in mortality, and assess the contribution of each cause of death to overall disparities in all-cause mortality. METHODS: We applied established so-called garbage code redistribution algorithms and small area estimation methods to death registration data for King County to estimate life expectancy, cause-specific mortality rates, and years of life lost (YLL) rates from 152 causes of death for 397 census tracts from Jan 1, 1990, to Dec 31, 2014. We used the cause list developed for the Global Burden of Disease 2015 study for this analysis. Deaths were tabulated by age group, sex, census tract, and cause of death. We used Bayesian mixed-effects regression models to estimate mortality overall and from each cause. FINDINGS: Between 1990 and 2014, life expectancy in King County increased by 5·4 years (95% uncertainty interval [UI] 5·0-5·7) among men (from 74·0 years [73·7-74·3] to 79·3 years [79·1-79·6]) and by 3·4 years (3·0-3·7) among women (from 80·0 years [79·7-80·2] to 83·3 years [83·1-83·5]). In 2014, life expectancy ranged from 68·4 years (95% UI 66·9-70·1) to 86·7 years (85·0-88·2) for men and from 73·6 years (71·6-75·5) to 88·4 years (86·9-89·9) for women among census tracts within King County. Rates of YLL by cause also varied substantially among census tracts for each cause of death. Geographical areas with relatively high and relatively low YLL rates differed by cause. In general, causes of death responsible for more YLLs overall also contributed more significantly to geographical inequality within King County. However, certain causes contributed more to inequality than to overall YLLs. INTERPRETATION: This census tract-level analysis of life expectancy and cause-specific YLL rates highlights important differences in health among neighbourhoods in King County that are masked by county-level estimates. Efforts to improve population health in King County should focus on reducing geographical inequality, by targeting those health conditions that contribute the most to overall YLLs and to inequality. This analysis should be replicated in other locations to more fully describe fine-grained local-level variation in population health and contribute to efforts to improve health while reducing inequalities. FUNDING: John W Stanton and Theresa E Gillespie.

Using Small-Area Estimation to Calculate the Prevalence of Smoking by Subcounty Geographic Areas in King County, Washington, Behavioral Risk Factor Surveillance System, 2009-2013.

INTRODUCTION: King County, Washington, fares well overall in many health indicators. However, county-level data mask disparities among subcounty areas. For disparity-focused assessment, a demand exists for examining health data at subcounty levels such as census tracts and King County health reporting areas (HRAs). METHODS: We added a "nearest intersection" question to the Behavioral Risk Factor Surveillance System (BRFSS) and geocoded the data for subcounty geographic areas, including census tracts. To overcome small sample size at the census tract level, we used hierarchical Bayesian models to obtain smoothed estimates in cigarette smoking rates at the census tract and HRA levels. We also used multiple imputation to adjust for missing values in census tracts. RESULTS: Direct estimation of adult smoking rates at the census tract level ranged from 0% to 56% with a median of 10%. The 90% confidence interval (CI) half-width for census tract with nonzero rates ranged from 1 percentage point to 37 percentage points with a median of 13 percentage points. The smoothed-multiple-imputation rates ranged from 5% to 28% with a median of 12%. The 90% CI half-width ranged from 4 percentage points to 13 percentage points with a median of 8 percentage points. CONCLUSION: The nearest intersection question in the BRFSS provided geocoded data at subcounty levels. The Bayesian model provided estimation with improved precision at the census tract and HRA levels. Multiple imputation can be used to account for missing geographic data. Small-area estimation, which has been used for King County public health programs, has increasingly become a useful tool to meet the demand of presenting data at more granular levels.

Innovations in user-defined analysis: dynamic grouping and customized user datasets in VistaPHw.

Flexible, ready access to community health assessment data is a feature of innovative Web-based data query systems. An example is VistaPHw, which provides access to Washington state data and statistics used in community health assessment. Because of its flexible analysis options, VistaPHw customizes local, population-based results to be relevant to public health decision-making. The advantages of two innovations, dynamic grouping and the Custom Data Module, are described. Dynamic grouping permits the creation of user-defined aggregations of geographic areas, age groups, race categories, and years. Standard VistaPHw measures such as rates, confidence intervals, and other statistics may then be calculated for the new groups. Dynamic grouping has provided data for major, successful grant proposals, building partnerships with local governments and organizations, and informing program planning for community organizations. The Custom Data Module allows users to prepare virtually any dataset so it may be analyzed in VistaPHw. Uses for this module may include datasets too sensitive to be placed on a Web server or datasets that are not standardized across the state. Limitations and other system needs are also discussed.