Associations between food insecurity and other social risk factors among U.S. adults.

BACKGROUND: Food insecurity (FI) often co-exists with other social risk factors, which makes addressing it particularly challenging. The degree of association between FI and other social risk factors across different levels of income and before and during the COVID-19 pandemic is currently unknown, impeding the ability to design effective interventions for addressing these co-existing social risk factors. OBJECTIVE: To determine the association between FI and other social risk factors overall and across different levels of income-poverty ratios and before (2019) and during (2020-2021) the pandemic. DESIGN: We used nationally representative data from the 2019-2021 National Health Interview Survey for our cross-sectional analysis. Social risk factors available in NHIS included difficulties paying for medical bills, difficulties paying for medications, receiving income assistance, receiving rental assistance, and "not working last week". SUBJECTS: 93,047 adults (≥18 years old). KEY RESULTS: Individuals with other social risk factors (except receiving income assistance) were more likely to report FI, even after adjusting for income and education inequalities. While poverty leads to a higher prevalence of FI, associations between FI and other social risk factors were stronger among people with higher incomes, which may be related to their ineligibility for social safety net programs. Associations were similar before and during the pandemic, perhaps due to the extensive provision of social safety net programs during the pandemic. CONCLUSIONS: Future research should explore how access to a variety of social safety net programs may impact the association between social risk factors. With the expiration of most pandemic-related social supports, further research and monitoring are also needed to examine FI in the context of increasing food and housing costs. Our findings may also have implications for the expansion of income-based program eligibility criteria and screening for social risk factors across all patients and not only low-income people.

Navigating the Landscape: Barriers and Facilitators in Electronic Case Reporting Implementation Across Public Health Agencies.

OBJECTIVE: The objectives were to identify barriers and facilitators for electronic case reporting (eCR) implementation associated with "organizational" and "people"-based knowledge/processes and to identify patterns across implementation stages to guide best practices for eCR implementation at public health agencies. DESIGN: This qualitative study uses semistructured interviews with key stakeholders across 6 public health agencies. This study leveraged 2 conceptual frameworks for the development of the interview guide and initial codebook and the organization of the findings of thematic analysis. SETTING: Interviews were conducted virtually with informants from public health agencies at varying stages of eCR implementation. PARTICIPANTS: Investigators aimed to enroll 3 participants from each participating public health agency, including an eCR lead, a technical lead, and a leadership informant. MAIN OUTCOME MEASURES: Patterns associated with barriers and facilitators across the eCR implementation stage. RESULTS: Twenty-eight themes were identified throughout interviews with 16 informants representing 6 public health agencies at varying stages of implementation. While there was variation across these levels, 3 distinct patterns were identified, including themes that were described (1) solely as a barrier or facilitator for eCR implementation regardless of implementation stages, (2) as a barrier for those in the early stages but evolved into a facilitator for those in later stages, and (3) as facilitators that were unique to the late-stage implementation. CONCLUSION: This study elucidated critical national, organizational, and person-centric best practices for public health agencies. These included the importance of engagement with the national eCR team, integrated development teams, cross-pollination, and developing solutions with the broader public health mission in mind. While the implementation of eCR was the focus of this study, the findings are generalizable to the broader data modernization efforts within public health agencies.

Association of social vulnerability and influenza vaccination rates for Annual Medicare Enrollees at the county-level in the United States.

INTRODUCTION: Influenza is a preventable acute respiratory illness with a high potential to cause serious complications and is associated with high mortality and morbidity in the US. We aimed to determine the specific community-level vulnerabilities for different race/ethnic communities that are most predictive of influenza vaccination rates. METHODS: We conducted a machine learning analysis (XGBoost) to identify community-level social vulnerability features that are predictive of influenza vaccination rates among Medicare enrollees across counties in the US and by race/ethnicity. RESULTS: Population density per square mile in a county is the most important feature in predicting influenza vaccination in a county, followed by unemployment rates and the percentage of mobile homes. The gain relative importance of these features are 11.6%, 9.2%, and 9%, respectively. Among whites, population density (17% gain relative importance) was followed by the percentage of mobile homes (9%) and per capita income (8.7%). For Black/African Americans, the most important features were population density (12.8%), percentage of minorities in the county (8.0%), per capita income (6.9%), and percent of over-occupied housing units (6.8%). Finally, for Hispanics, the top features were per capita income (8.4%), percentage of mobile homes (8.0%), percentage of non-institutionalized persons with a disability (7.9%), and population density (7.6%). CONCLUSIONS: Our study may have implications for the success of large vaccination programs in counties with high social vulnerabilities. Further, our findings suggest that policies and interventions seeking to increase rates of vaccination in race/ethnic minority communities may need to be tailored to address their specific socioeconomic vulnerabilities.

Can allostatic load in pregnancy explain the association between race and subsequent cardiovascular disease risk: A cohort study.

OBJECTIVE: To assess the relationship between allostatic load, a measure of cumulative chronic stress in early pregnancy and cardiovascular disease risk, 2-7 years postpartum, and pathways contributing to racial disparities in cardiovascular disease risk. DESIGN: Secondary analysis of a prospective cohort study. SETTING MULTICENTER POPULATION: Pregnant women. METHODS: Our primary exposure was high allostatic load in the first trimester, defined as at least 4 of 12 biomarkers (systolic blood pressure, diastolic blood pressure, body mass index, cholesterol, low-density lipoprotein, high-density lipoprotein, high-sensitivity C-reactive protein, triglycerides, insulin, glucose, creatinine and albumin) in the unfavourable quartile. Logistic regression was used to test the association between high allostatic load and main outcome adjusted for confounders: time from index pregnancy and follow up, age, education, smoking, gravidity, bleeding in the first trimester, index adverse pregnancy outcomes, and health insurance. Each main outcome component and allostatic load were analysed secondarily. Mediation and moderation analyses assessed the role of high allostatic load in racial disparities of cardiovascular disease risk. MAIN OUTCOME MEASURE: Incident cardiovascular disease risk: hypertension, or metabolic disorders. RESULTS: Cardiovascular disease risk was identified in 1462/4022 individuals (hypertension: 36.6%, metabolic disorder: 15.4%). After adjustment, allostatic load was associated with cardiovascular disease risk (adjusted odds ratio [aOR] 2.0, 95% CI 1.8-2.3), hypertension (aOR 2.1, 95% CI 1.8-2.4) and metabolic disorder (aOR 1.7, 95% CI 1.5-2.1). Allostatic load was a partial mediator between race and cardiovascular disease risk. Race did not significantly moderate this relationship. CONCLUSIONS: High allostatic load during pregnancy is associated with cardiovascular disease risk. The relationships between stress, subsequent cardiovascular risk and race warrant further study.

Social vulnerability predictors of drug poisoning mortality: A machine learning analysis in the United States.

BACKGROUND AND OBJECTIVES: Drug poisoning is a leading cause of unintentional deaths in the United States. Despite the growing literature, there are a few recent analyses of a wide range of community-level social vulnerability features contributing to drug poisoning mortality. Current studies on this topic face three limitations: often studying a limited subset of vulnerability features, focusing on small sample sizes, or solely including local data. To address this gap, we conducted a national-level analysis to study the impacts of several social vulnerability features in predicting drug mortality rates in the United States. METHODS: We used machine learning to investigate the role of 16 social vulnerability features in predicting drug mortality rates for US counties in 2014, 2016, and 2018-the most recent available data. We estimated each vulnerability feature's gain relative contribution in predicting drug poisoning mortality. RESULTS: Among all social vulnerability features, the percentage of noninstitutionalized persons with a disability is the most influential predictor, with a gain relative contribution of 18.6%, followed by population density and the percentage of minority residents (13.3% and 13%, respectively). Percentages of households with no available vehicles, mobile homes, and persons without a high school diploma are the following features with gain relative contributions of 6.3%, 5.8%, and 5.1%, respectively. CONCLUSION AND SCIENTIFIC SIGNIFICANCE: We identified social vulnerability features that are most predictive of drug poisoning mortality. Public health interventions and policies targeting vulnerable communities may increase the resilience of these communities and mitigate the overdose death and drug misuse crisis.

Impact of Florida's prescription drug monitoring program on drug- related fatal vehicle crashes: a difference-in-differences approach.

BACKGROUND: Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs. To prevent prescription opioid misuse in Florida, Prescription Drug Monitoring Programs (PDMPs) were implemented in September 2011. OBJECTIVE: To examine the impact of Florida's implementation of a mandatory PDMP on drug-related MVCs occurring on public roads. METHODS: We employed a difference-in-differences approach to estimate the difference in prescription drug-related fatal crashes in Florida associated with its 2011 PDMP implementation relative to those in Georgia, which did not use PDMPs during the same period (2009-2013). The analyses were conducted in 2020. RESULTS: In Florida, there was a significant decline in drug-related vehicle crashes during the 22 months post-PDMP. PDMP implementation was associated with approximately two (-2.21; 95% CI -4.04 to -0.37; p<0.05) fewer prescribed opioid-related fatal crashes every month, indicating 25% reduction in the number of monthly crashes. We conducted sensitivity analyses to investigate the impact of PDMP implementation on central nervous system depressants and stimulants as well as cocaine and marijuana-related fatal crashes but found no robust significant reductions. CONCLUSIONS: The implementation of PDMPs in Florida provided important benefits for traffic safety, reducing the rates of prescription opioid-related vehicle crashes.

The Impact of Halting Elective Admissions in Anticipation of a Demand Surge Due to the Coronavirus Pandemic (COVID-19).

BACKGROUND: In anticipation of a demand surge for hospital beds attributed to the coronavirus pandemic (COVID-19) many US states have mandated that hospitals postpone elective admissions. OBJECTIVES: To estimate excess demand for hospital beds due to COVID-19, the net financial impact of eliminating elective admissions in order to meet demand, and to explore the scenario when demand remains below capacity. RESEARCH DESIGN: An economic simulation to estimate the net financial impact of halting elective admissions, combining epidemiological reports, the US Census, American Hospital Association Annual Survey, and the National Inpatient Sample. Deterministic sensitivity analyses explored the results while varying assumptions for demand and capacity. SUBJECTS: Inputs regarding disease prevalence and inpatient utilization were representative of the US population. Our base case relied on a hospital admission rate reported by the Center for Disease Control and Prevention of 137.6 per 100,000, with the highest rates in people aged 65 years and older (378.8 per 100,000) and 50-64 years (207.4 per 100,000). On average, elective admissions accounted for 20% of total hospital admissions, and the average rate of unoccupied beds across hospitals was 30%. MEASURES: Net financial impact of halting elective admissions. RESULTS: On average, hospitals COVID-19 demand for hospital bed-days fell well short of hospital capacity, resulting in a substantial financial loss. The net financial impact of a 90-day COVID surge on a hospital was only favorable under a narrow circumstance when capacity was filled by a high proportion of COVID-19 cases among hospitals with low rates of elective admissions. CONCLUSIONS: Hospitals that restricted elective care took on a substantial financial risk, potentially threatening viability. A sustainable public policy should therefore consider support to hospitals that responsibly served their communities through the crisis.

Association of Post-discharge Service Types and Timing with 30-Day Readmissions, Length of Stay, and Costs.

BACKGROUND: Although early follow-up after discharge from an index admission (IA) has been postulated to reduce 30-day readmission, some researchers have questioned its efficacy, which may depend upon the likelihood of readmission at a given time and the health conditions contributing to readmissions. OBJECTIVE: To investigate the relationship between post-discharge services utilization of different types and at different timepoints and unplanned 30-day readmission, length of stay (LOS), and inpatient costs. DESIGN, SETTING, AND PARTICIPANTS: The study sample included 583,199 all-cause IAs among 2014 Medicare fee-for-service beneficiaries that met IA inclusion criteria. MAIN MEASURES: The outcomes were probability of 30-day readmission, average readmission LOS per IA discharge, and average readmission inpatient cost per IA discharge. The primary independent variables were 7 post-discharge health services (institutional outpatient, primary care physician, specialist, non-physician provider, emergency department (ED), home health care, skilled nursing facility) utilized within 7 days, 14 days, and 30 days of IA discharge. To examine the association with post-discharge services utilization, we employed multivariable logistic regressions for 30-day readmissions and two-part models for LOS and inpatient costs. KEY RESULTS: Among all IA discharges, the probability of unplanned 30-day readmission was 0.1176, the average readmission LOS per discharge was 0.67 days, and the average inpatient cost per discharge was $5648. Institutional outpatient, home health care, and primary care physician visits at all timepoints were associated with decreased readmission and resource utilization. Conversely, 7-day and 14-day specialist visits were positively associated with all three outcomes, while 30-day visits were negatively associated. ED visits were strongly associated with increases in all three outcomes at all timepoints. CONCLUSION: Post-discharge services of different types and at different timepoints have varying impacts on 30-day readmission, LOS, and costs. These impacts should be considered when coordinating post-discharge follow-up, and their drivers should be further explored to reduce readmission throughout the health care system.

Analysis of Excess Deaths During the COVID-19 Pandemic in the State of Florida.

Objectives. To determine the number of excess deaths (i.e., those exceeding historical trends after accounting for COVID-19 deaths) occurring in Florida during the COVID-19 pandemic.Methods. Using seasonal autoregressive integrated moving average time-series modeling and historical mortality trends in Florida, we forecasted monthly deaths from January to September of 2020 in the absence of the pandemic. We compared estimated deaths with monthly recorded total deaths (i.e., all deaths regardless of cause) during the COVID-19 pandemic and deaths only from COVID-19 to measure excess deaths in Florida.Results. Our results suggest that Florida experienced 19 241 (15.5%) excess deaths above historical trends from March to September 2020, including 14 317 COVID-19 deaths and an additional 4924 all-cause, excluding COVID-19, deaths in that period.Conclusions. Total deaths are significantly higher than historical trends in Florida even when accounting for COVID-19-related deaths. The impact of COVID-19 on mortality is significantly greater than the official COVID-19 data suggest.

The Impact of Medicaid Expansion for Adults Under the Affordable Care Act on Preventive Care for Children: Evidence From the Southern United States.

INTRODUCTION: The Affordable Care Act of 2010 expanded Medicaid to low-income adults at or below 138% of the Federal Poverty Level (FPL). The aim of this study was to examine if expanding Medicaid to adults had an impact on preventive health care utilization of children from low-income families (focusing on families with annual incomes 0%-99% and 100%-199% of the FPL). METHODS: This study used data from the 2016 and 2017 National Survey of Children's Health and a quasi-experimental difference-in-differences method. The dependent variable was the number of preventive care visits in the past year and the primary independent variable was the Medicaid expansion status of the state. Louisiana expanded Medicaid in 2016 (treatment group) and neighboring nonexpansion states of Texas and Mississippi constituted the control group. Differences in dependent variable were calculated between survey years 2016 and 2017. RESULTS: In Louisiana, the change in the predicted probability of at least 1 preventive care visit among children of ages 0-17 years, from 0% to 99% FPL families, was higher by 26 percentage points after Medicaid was expanded (2017 vs. 2016), as compared with the change in the predicted probability (2017 vs. 2016) of at least 1 preventive care visit among children of ages 0-17 years, from 0% to 99% FPL families in the nonexpansion states, Texas and Mississippi. CONCLUSIONS: Children in poverty residing in a Medicaid expansion state, Louisiana, had increased likelihood of having an annual preventive care visit after expansion of Medicaid eligibility under the Affordable Care Act, as compared with children in nonexpansion states. Thus, this study showed that the implications of the public health insurance expansion for adults were not limited to adult health outcomes, but extended to children's health care utilization.

Time Spent Eating, by Immigrant Status, Race/Ethnicity, and Length of Residence in the United States.

INTRODUCTION: Time spent eating is associated with obesity and diet-related diseases. We examined the association between time adults spent eating, immigrant status, race/ethnicity, and race/ethnicity among adults in the United States. METHODS: We used multivariate linear regression to analyze a cross-sectional, nationally representative sample of respondents aged 19 years or older (N = 192,486) from the 2016 American Time Use Survey. The outcome measures were time spent per day on primary eating and drinking and secondary eating. The predictors were immigrant status, race/ethnicity, and years spent living in the United States. RESULTS: Multivariate adjusted minutes per day spent on primary eating and drinking were 66.4 for noncitizens, 66.5 for naturalized citizens, and 60.1 for US-born individuals. Multivariate adjusted minutes per day spent on secondary eating were 11.1 for noncitizens, 12.2 for naturalized citizens, and 12.9 for US-born individuals. Minutes per day spent on primary eating and drinking for immigrants by length of residence in the United States was 69.7 minutes for 5 years or less of residence, 67.9 minutes for 6 to 10 years of residence, 63.6 minutes for 11 to 15 years of residence, and 63.6 minutes for more than 15 years of residence. Minutes per day spent on secondary eating for immigrants by length of residence was 5.5 minutes for 5 years or less of residence, 9.7 minutes for 6 to 10 years of residence, 8.4 minutes for 11 to 15 years of residence, and 12.6 minutes for more than 15 years of residence. CONCLUSION: Time spent eating varied by immigrant status and length of residence in the United States.

Post-Discharge Services for Different Diagnoses Than Index Hospitalization Predict Decreased 30-Day Readmissions Among Medicare Beneficiaries.

BACKGROUND: Efforts to reduce hospital readmissions include post-discharge interventions related to the illness treated during the index hospitalization (IH). These efforts may be inadequate because readmissions are precipitated by a wide range of health conditions unrelated to the primary diagnosis of the IH. OBJECTIVE: To investigate the relationship between post-discharge health services utilization for the same or a different diagnosis than the IH and unplanned 30-day readmission. DESIGN AND PARTICIPANTS: The study sample included 583,199 all-cause IHs among 2014 Medicare fee-for-service beneficiaries. For all-cause IH, as well as individually for heart failure, myocardial infarction, and pneumonia IH, we used multivariable logistic regressions to investigate the association between post-discharge services utilization and readmission. MAIN MEASURES: The outcome was unplanned 30-day readmission. Primary independent variables were post-discharge services utilization, including institutional outpatient, office-based primary care, office-based specialist, office-based non-physician practitioner, emergency department, home health care, and skilled nursing facility providers. KEY RESULTS: Among all-cause IH, 11.7% resulted in unplanned 30-day readmissions, and only 18.1% of readmissions occurred for the same primary diagnosis as IH. A substantial majority of post-discharge health services were utilized for a primary diagnosis differing from IH. Compared with no visit, institutional outpatient visits for the same primary diagnosis as IH (odds ratio [OR], 0.33; 95% confidence interval [CI], 0.31-0.34) and for a different primary diagnosis than IH (OR, 0.36; 95% CI, 0.35-0.37) were similarly strongly associated with decreased unplanned 30-day readmission. Primary care physician, specialist, non-physician practitioner, and home health care showed similar patterns. IH for heart failure, myocardial infarction, and pneumonia manifested similar patterns to all-cause IH both in terms of post-discharge services utilization and in terms of its impact on readmission. CONCLUSIONS: To reduce unplanned 30-day readmission more effectively, discharge planning should include post-discharge services to address health conditions beyond the primary cause of the IH.

Predictors and Costs of 30-Day Readmissions After Index Hospitalizations for Alcohol-Related Disorders in U.S. Adults.

BACKGROUND: In 2015, the Hospital Readmissions Reduction Program mandated financial penalties to hospitals with greater rates of readmissions for certain conditions. Alcohol-related disorders (ARD) are the fourth leading cause of 30-day readmissions. Yet, there is a dearth of national-level research to identify high-risk patient populations and predictors of 30-day readmission. This study examined patient- and hospital-level predictors for index hospitalizations with principal diagnosis of ARD and predicted the cost of 30-day readmissions. METHODS: The 2014 Nationwide Readmissions Database was used to identify ARD-related index hospitalizations. Multivariable logistic regression was used to estimate patient- and hospital-level predictors for readmissions, and a 2-part model was used to predict the incremental cost conditional upon readmission. RESULTS: In 2014, 285,767 index hospitalizations for ARD were recorded, and 18.9% of ARD-associated hospitalizations resulted in at least one 30-day readmission. Patients who were males, aged 45 to 64 years, Medicaid enrollees, living in urban and low-income areas, or with 1 to 2 comorbidities had high risk of readmission. Index hospitalization costs were higher among readmitted patients ($8,840 vs. $8,036, p < 0.01). Predicted mean costs for readmissions on index stay with ARD were greater among those aged 45 to 64 years ($1,908, p < 0.001), Medicare enrollees ($2,133, p < 0.001), rural residents ($1,841, p < 0.01), living in high-income areas ($1,876, p < 0.001), with 4 or more comorbidities ($2,415, p < 0.001), or admitted in large metropolitan hospitals ($2,032, p < 0.001), with large number of beds ($1,964, p < 0.001), with government ownership ($2,109, p < 0.001), or with low volume of ARD cases ($2,155, p < 0.001). CONCLUSIONS: One in 5 ARD-related index hospitalizations resulted in a 30-day readmission. Overall, costs of index hospitalizations for ARD were $2.3 billion, of which $512 million were spent on hospitalizations that resulted in at least 1 readmission. There is a need to develop patient-centric health programs to reduce readmission rates and costs among ARD patients.

Patient Characteristics and Causes of Facial Fractures in the State of California.

PURPOSE: Each year, more than 400,000 emergency department (ED) visits in the United States are due to facial fractures. To inform targeted interventions to prevent facial fractures, the purpose of this study was to identify patient characteristics associated with causes of facial fractures in California. MATERIALS AND METHODS: The 2005 to 2011 California State Emergency Department Database was used for this cross-sectional study. The study population was composed of all ED visits for facial fractures. The primary outcome was cause of injury: fall, firearm injury, motor vehicle traffic accident, pedal cycle accident, pedestrian accident, transport accident, and assault. Predictor variables included patient characteristics, such as age, gender, insurance type, and race and ethnicity. Multivariable logistic regression models were used. RESULTS: There were 198,870 ED visits for facial fractures from 2005 to 2011. The patients' average age was 35.7 years. Most ED visits were by male patients (71%), privately insured patients (35%), and white patients (52%). Approximately 65% of visits were on weekdays and 93% were routinely discharged. Closed fractures of nasal bones, other facial bones, orbital floor, malar and maxillary bones, and mandible were the most prevalent (91%) facial fractures. Assaults (44%), falls (24%), and motor vehicle traffic crashes (6%) were the top 3 causes of facial fractures. Elderly patients (odds ratio [OR] = 6.17), female patients (OR = 2.25), and Medicare enrollees (OR = 1.51) were statistically more likely to have fall-related fractures than patients 45 to 64 years old, male patients, and privately insured patients. Blacks (OR = 0.46) and micropolitan residents (OR = 0.76) were statistically less likely to have fall-related fractures than whites and metropolitan residents. CONCLUSIONS: Violence among youth and falls among the elderly are predominant causes of facial fractures. The uninsured contribute to more than one fourth of ED visits for facial fractures. Interventions targeted at these population groups can curb the prevalence of these fractures.

Emergency Department Utilization for Substance Use-Related Disorders and Assessment of Treatment Facilities in New York State, 2011-2013.

BACKGROUND: Annually, 1.8 million New York (NY) residents experience substance use disorders (SUDs). Even though emergency departments (EDs) continue to experience high numbers of SUD-related visits, only 15% receive treatment. OBJECTIVES: This study estimates hospital-based EDs rates for SUDs in the State of New York. Also, the geographic distribution of substance use treatment centers and EDs are mapped to correlate utilization with access to care. METHODS: The 2011-2013 Healthcare Cost and Utilization Project's NY State Emergency Department Database provided information on utilization of services in EDs, charges, diagnoses, and discharge, as well as patient demographic variables. All patients within NY who had visited the ED for SUDs comprised the study population. Geographic mapping of EDs and substance abuse treatment centers at the county-level is based on data from the National Emergency Department Inventory and National Survey of Substance Abuse Treatment Services, respectively. RESULTS: A total of 492,419 ED visits for SUDs were reported through 2011-2013. Despite NY's Medicaid expansion in 2012, ED visits increased in 2013. About $856 million was spent in treating SUDs in EDs, with average charge of $1,764 per visit. Conclusions/Importance: Alcohol and drug-induced mental disorders are increasingly prevalent in New York's EDs. There is a need to develop health policies and programs to improve access to care for SUDs in urban states.

Fewer immigrants have preventable ED visits in the United States.

OBJECTIVE: The aim of this study is to examine differences in having preventable emergency department (ED) visits between noncitizens, naturalized and US-born citizens in the United States. METHODS: We linked the 2008-2012 Medical Expenditure Panel Survey with National Health Interview Survey data to draw a nationally representative sample of US adults. Univariate analysis described distribution of preventable ED visits identified by the Prevention Quality Indicators across immigration status. We also assessed the association between preventable ED visits and immigration status, controlling for demographics, socioeconomic status, health service utilization, and health status. We finally applied the Oaxaca-Blinder decomposition method to measure the contribution of each covariate to differences in preventable ED services utilization between US natives, naturalized citizens, and noncitizens. RESULTS: Of US natives, 2.1% had any preventable ED visits within the past years as compared to 1.0% of noncitizens and 1.5% of naturalized citizens. Multivariate results also revealed that immigrants groups had significantly lower odds (adjusted OR: naturalized citizen 0.77 [0.61-0.96], noncitizen 0.62 [0.48-0.80]) of having preventable ED visits than natives. Further stratified analysis by insurance status showed these differences were only significant among the uninsured and public insurance groups. Race/ethnicity and health insurance explained about 68% of the difference in preventable ED service utilization between natives and noncitizens. CONCLUSION: Our study documents the existing differences in preventable ED visits across immigration status, and highlights the necessity to explore unmet health needs among immigrants and eliminate disparities.

The Effect of Telehealth Interventions on Quality of Life of Cancer Patients: A Systematic Review and Meta-Analysis.

INTRODUCTION: In 2016, ∼1.7 million new cases of cancer were diagnosed. Cancer patients can have physical, functional, and psychosocial issues when dealing with cancer treatment. Telehealth has been effectively introduced to help deliver treatment to patients suffering from chronic disease; however, there is little consensus on its effectiveness in administering sociobehavioral cancer treatments. Thus, this study determines the benefits of telehealth-based interventions providing emotional and symptom support in improving quality of life (QOL) among cancer patients. METHODS: Two researchers conducted comprehensive searches on PubMed, SCOPUS, Medline, PsycINFO, ERIC, Psychology and Behavioral Collection, and Medline Complete. Key search terms included telehealth or telemedicine and QOL and cancer. Articles were included if they assessed a telehealth-delivered intervention for adult cancer patients and provided a QOL assessment. Data were extracted to calculate mean effect sizes for QOL measures on the effectiveness of telehealth relative to usual care (UC) for cancer treatments. RESULTS: Out of 414 articles identified in our initial search, nine articles fit our inclusion criteria. Both telehealth (Hedges g = 0.211, p = 0.016) and standard of care (Hedges g = 0.217, p < 0.001) cancer treatment delivery methods demonstrated small, but statistically significant improvements in QOL measures. However, there were no statistically significant differences in effectiveness between the telehealth interventions and UC (p = 0.76). CONCLUSIONS: The results indicate that telehealth interventions are as effective at improving QOL scores in patients undergoing cancer treatment as in-person UC. Further studies should be undertaken on different modalities of telehealth to determine its appropriate and effective use in interventions to improve the QOL for cancer patients undergoing treatment.

The feasibility and promise of mobile technology with community health worker reinforcement to reduce rural preterm birth.

OBJECTIVES: (1) Assess feasibility of a smartphone platform intervention combined with Community Health Worker (CHW) reinforcement in rural pregnant women; (2) Obtain data on the promise of the intervention on birth outcomes, patient activation, and medical care adherence; and (3) Explore financial implications of the intervention using return on investment (ROI). SAMPLE: A total of 98 rural pregnant women were enrolled and assigned to intervention or control groups in this two-group experimental design. INTERVENTION: The intervention group received usual prenatal care plus a smartphone preloaded with a tailored prenatal platform with automated texting, chat function, and hyperlinks and weekly contact from the CHW. The control group received usual prenatal care and printed educational materials. MEASUREMENTS: Demographics, health risk data, interaction with platform, medical records, hospital billing charges, Client Satisfaction Questionnaire-8, satisfaction comments, and the Patient Activation Measure. RESULTS: A total of 77 women completed the study. The intervention was well-received, showed promise for improving birth outcomes, patient activation, and medical care adherence. Financial analysis showed a positive ROI under two scenarios. CONCLUSIONS: Despite several practical issues, the study appears feasible. The intervention shows promise for extending prenatal care and improving birth outcomes in rural communities. Further research is needed with a larger and more at-risk population to appreciate the impact of the intervention.

Measuring the Cost and Value of Quality Improvement Initiatives for Local Health Departments.

OBJECTIVE: To demonstrate an approach to measuring the cost and value of quality improvement (QI) implementation in local health departments (LHDs). DESIGN: We conducted cost estimation for 4 LHD QI projects and return-on-investment (ROI) analysis for 2 selected LHD QI projects. SETTING AND PARTICIPANTS: Four Nebraska LHDs varying in rurality and jurisdiction size. MAIN OUTCOME MEASURES: Total costs, unit costs, incremental cost-effectiveness ratios, and ROI. RESULTS: The 4 QI projects vary significantly in their cost estimates. Estimated ROI ratios for 2 QI projects predicted significant savings in health care utilization for respective program participants. A QI project focused on improving breastfeeding rates in WIC (women, infants, and children) clients had a predicted ROI ratio of 3230% and a QI project for improving participation in a Chronic Disease Self-Management Program would need only 34 new participants to have a positive ROI. CONCLUSIONS: We demonstrated how data can be collected and analyzed for cost estimation and ROI analysis to quantify the economic value of QI for LHDs. Our ROI analysis shows that QI initiatives have great potential to enhance the value of LHDs' public health services. A better understanding of the costs and value of QI will enable LHDs to appropriately allocate and utilize their limited resources for suitable QI initiatives.

Hospital-Based Emergency Department Visits With Dental Conditions: Impact of the Medicaid Reimbursement Fee for Dental Services in New York State, 2009-2013.

OBJECTIVES: Hospital-based emergency department (ED) visits for dental problems have been on the rise. The objectives of this study are to provide estimates of hospital-based ED visits with dental conditions in New York State and to examine the impact of Medicaid reimbursement fee for dental services on the utilization of EDs with dental conditions. METHODS: New York State Emergency Department Database for the year 2009-2013 and Health Resources and Services Administration's Area Health Resource File were used. All ED visits with diagnosis for dental conditions were selected for analysis. RESULTS: The present study found a total of 325,354 ED visits with dental conditions. The mean age of patient was 32.4 years. A majority of ED visits were made by those aged 25-44 years (49%). Whites comprised 52.1% of ED visits. Proportion of Medicaid increased from 22% (in 2009) to 41.3% (in 2013). For Medicaid patients, the mean ED charges and aggregated ED charges were $811.4 and $88.1 million, respectively. Eleven counties had fewer than 4 dentists per 10,000 population in New York State. CONCLUSION: High-risk groups identified from the study are those aged 25-44 years, uninsured, covered by Medicaid and private insurance, and residing in low-income areas. The study highlights the need for increased Medicaid reimbursement for dentists and improves access to preventive dental care especially for the vulnerable groups.