Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study.

INTRODUCTION: Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation. METHODS: This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression. RESULTS: Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study. DISCUSSION: Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

The Relationship Between Dental Provider Density and Receipt of Dental Care Among Medicaid-enrolled Adults.

OBJECTIVE: We sought to measure the association of dental provider density and receipt of dental care among Medicaid-enrolled adults. METHODS: We used four years of Indiana Medicaid claims and enrollment data (2015 to 2018) and the Area Health Resources File to examine the relationship between any dental visit (ADV) or any preventive dental visit (PDV) and three county-level measures of dental provider density (the total number of Medicaid-participating dentists, a binary indicator of a federally qualified health center (FQHC) with a Medicaid-participating dentist, and the overall county dentist-to-population ratio). RESULTS: The likelihood of ADV or PDV increased with greater density of Medicaid-participating dentists as well as dentists accepting Medicaid working at an FQHC within the county. The overall dentist-to-population ratio was not associated with dental care use among the adult Medicaid population. CONCLUSION: Dentist participation in Medicaid program may be a modifiable barrier to Medicaid-enrolled adults' receipt of dental care.

State Policies Associated with Availability of Mobile Crisis Teams.

Mobile crisis teams are comprised of multidisciplinary mental health professionals that respond to mental health crisis calls in community settings. This study identified counties with mobile crisis teams and examined state policies associated with mobile crisis teams. Descriptive statistics and geographic information system software were used to quantify and map counties with mobile crisis teams in the United States. Relationships between state policies and mobile crisis teams were examined using an adjusted logistic regression model, controlling for county characteristics and accounting for clustering by state. Approximately 40% (n = 1,245) of all counties in the US have at least one mobile crisis team. Counties in states with legislation in place to fund the 988 Suicide and Crisis Lifeline were more likely to have a mobile crisis team (Adjusted Odds Ratio (AOR): 2.0; Confidence Interval (CI): 1.23-3.26), whereas counties in states with 1115 waivers restricting Medicaid benefits were less likely to have a mobile crisis team (AOR: 0.43; CI: 0.21-0.86). Additionally, counties with the largest population were more likely to have a mobile crisis team (AOR: 2.20; CI:1.43-3.38) than counties with the smallest population. Having a mobile crisis teams was positively associated with legislation to fund 988. Legislation that encourages expansion of existing crisis care services, specifically funding aimed at mobile crisis teams, may help increase availability of services for people who are experiencing a mental health crisis in the community.

The relationship between preventive dental care and overall medical expenditures.

OBJECTIVES: To examine the relationship between preventive dental visits (PDVs) and medical expenditures while mitigating bias from unobserved confounding factors. STUDY DESIGN: Retrospective data analysis of Indiana Medicaid enrollment and claims data (2015-2018) and the Area Health Resources Files. METHODS: An instrumental variable (IV) approach was used to estimate the relationship between PDVs and medical and pharmacy expenditures among Medicaid enrollees. The instrument was defined as the number of adult enrollees with at least 1 nonpreventive dental claim per total Medicaid enrollees within a Census tract per year. RESULTS: In naive analyses, enrollees had on average greater medical expenditures if they had a prior-year PDV (ß = $397.21; 95% CI, $184.23-$610.18) and a PDV in the same year as expenditures were measured (ß = $344.81; 95% CI, $193.06-$496.56). No significant differences in pharmacy expenditures were observed in naive analyses. Using the IV approach, point estimates of overall medical expenditures for the marginal enrollee who had a prior-year PDV (ß = $325.17; 95% CI, -$708.03 to $1358.37) or same-year PDV (ß = $170.31; 95% CI, -$598.89 to $939.52) were similar to naive results, although not significant. Our IV approach indicated that PDV was not endogenous in some specifications. CONCLUSIONS: This is the first study to present estimates with causal inference from a quasi-experimental study of the effect of PDVs on overall medical expenditures. We observed that prior- or same-year PDVs were not related to overall medical or pharmacy expenditures.

Associations between Outpatient Laboratory Test Age and Healthcare Utilization in Type 2 Diabetes Care.

Purpose: To examine the longitudinal relationship between the age or shelf-life of common type 2 diabetes laboratory tests for serum creatinine, cholesterol, and glycated hemoglobin A1c conducted in outpatient settings and subsequent inpatient hospitalizations and emergency department visits. Methods: This study analyzes panel data from two healthcare delivery systems' electronic health records (EHR) for patients aged 18 years and older managing type 2 diabetes. We used EHR data to quantify the age of three laboratory tests: serum creatinine, cholesterol, and glycated hemoglobin A1c. Encounter data were used to determine the frequency of inpatient hospitalizations and emergency department visits. Negative binomial regressions with fixed effects were performed to compute marginal effects, levels of statistical significance, and 95% confidence intervals. Results: The average age for serum creatinine laboratory tests was 1.51 months (95%CI: 1.49-1.53). We computed older average ages for hemoglobin A1c (mean:6.17 months; 95%CI: 6.11-6.23) and serum creatinine tests (mean: 8.73; 95%CI: 8.65-8.81). Older laboratory tests were associated with an increase in the total expected counts of subsequent inpatient hospitalizations (ME = 0.047; p < 0.001) and ED visits (ME = 0.034; p < 0.001). Conclusion: Findings from this study indicate that older type 2 diabetes laboratory tests are associated with increases in the total expected count of subsequent inpatient hospitalizations and emergency department visits. Future research should examine the actionability of laboratory test values to determine associations with healthcare outcomes. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01250-0.

Economic Burden Associated With Untreated Mental Illness in Indiana.

Importance: There is a paucity of systematically captured data on the costs incurred by society-individuals, families, and communities-from untreated mental illnesses in the US. However, these data are necessary for decision-making on actions and allocation of societal resources and should be considered by policymakers, clinicians, and employers. Objective: To estimate the economic burden associated with untreated mental illness at the societal level. Design, Setting, and Participants: This cross-sectional study used multiple data sources to tabulate the annual cost of untreated mental illness among residents (≥5 years old) in Indiana in 2019: the US National Survey on Drug Use and Health, the National Survey of Children's Health, Indiana government sources, and Indiana Medicaid enrollment and claims data. Data analyses were conducted from January to May 2022. Main Outcomes and Measures: Direct nonhealth care costs (eg, criminal justice system, homeless shelters), indirect costs (unemployment, workplace productivity losses due to absenteeism and presenteeism, all-cause mortality, suicide, caregiver direct health care, caregiver productivity losses, and missed primary education), and direct health care costs (disease-related health care expenditures). Results: The study population consisted of 6 179 105 individuals (median [SD] age, 38.0 [0.2] years; 3 132 806 [50.7%] were women) of whom an estimated 429 407 (95% CI, 349 526-528 171) had untreated mental illness in 2019. The economic burden of untreated mental illness in Indiana was estimated to be $4.2 billion annually (range of uncertainty [RoU], $2.1 billion-$7.0 billion). The cost of untreated mental illness included $3.3 billion (RoU, $1.7 billion-$5.4 billion) in indirect costs, $708.5 million (RoU, $335 million-$1.2 billion) in direct health care costs, and $185.4 million (RoU, $29.9 million-$471.5 million) in nonhealth care costs. Conclusion and Relevance: This cross-sectional study found that untreated mental illness may have significant financial consequences for society. These findings put into perspective the case for action and should be considered by policymakers, clinicians, and employers when allocating societal resources and funding. States can replicate this comprehensive framework as they prioritize key areas for action regarding mental health services and treatments.

Adoption of Best Practices in Behavioral Health Crisis Care by Mental Health Treatment Facilities.

OBJECTIVE: The authors aimed to examine adoption of behavioral health crisis care (BHCC) services included in the Substance Abuse and Mental Health Services Administration's (SAMHSA's) best practices guidelines. METHODS: Secondary data from SAMHSA's Behavioral Health Treatment Services Locator in 2022 were used. BHCC best practices were measured on a summated scale capturing whether a mental health treatment facility (N=9,385) adopted BHCC best practices, including provision of these services to all age groups: emergency psychiatric walk-in services, crisis intervention teams, onsite stabilization, mobile or offsite crisis responses, suicide prevention, and peer support. Descriptive statistics were used to examine organizational characteristics (such as facility operation, type, geographic area, license, and payment methods) of mental health treatment facilities nationwide, and a map was created to show locations of best practices BHCC facilities. Logistic regressions were performed to identify facilities' organizational characteristics associated with adopting BHCC best practices. RESULTS: Only 6.0% (N=564) of mental health treatment facilities fully adopted BHCC best practices. Suicide prevention was the most common BHCC service, offered by 69.8% (N=6,554) of the facilities. A mobile or offsite crisis response service was the least common, adopted by 22.4% (N=2,101). Higher odds of adopting BHCC best practices were significantly associated with public ownership (adjusted OR [AOR]=1.95), accepting self-pay (AOR=3.18), accepting Medicare (AOR=2.68), and receiving any grant funding (AOR=2.45). CONCLUSIONS: Despite SAMHSA guidelines recommending comprehensive BHCC services, a fraction of facilities have fully adopted BHCC best practices. Efforts are needed to facilitate widespread uptake of BHCC best practices nationwide.

Unmet mental health need and subsequent substance use in individuals with a history of depression: Are there differences between metro and nonmetro areas?

BACKGROUND AND OBJECTIVES: More than nine million U.S. adults have a co-occurring mental health and substance use disorder. The self-medication hypothesis suggests that individuals with unmet need may alleviate the symptoms of their mental illness by using alcohol or drugs. We examine the relationship between unmet mental health need and subsequent substance use among individuals with a history of depression as well as differences in metro and nonmetro areas. METHODS: We used repeated cross-sectional data from the National Survey on Drug Use and Health (NSDUH), 2015-2018 after identifying individuals with depression in the past year (n = 12,211). We used logistic regressions with interaction terms to examine the association between unmet need for mental health care and substance use by geographic location. RESULTS: Unmet mental health need was associated with increased use of marijuana (odds ratio [OR] = 1.32, 95% confidence interval [CI]: 1.08-1.64), illicit drugs (OR = 1.75, 95% CI: 1.19-2.58), and prescription drugs (OR = 1.89, 95% CI: 1.19-3.00) among individuals with depression, which did not vary by geographic location. Unmet need was not associated with increased heavy alcohol drinking (OR = 0.87, 95% CI: 0.60-1.26). DISCUSSION AND CONCLUSIONS: No differences in substance usage between metro and nonmetro populations were observed for those with an unmet need for mental health care. We found support for the self-medication hypothesis among individuals with depression with respect to alcohol. SCIENTIFIC SIGNIFICANCE: We examine whether individuals with depression and unmet care needs are more likely to self-medicate with substances including prescription drugs. Due to higher unmeet needs in nonmetro areas, we examine whether the likelihood of self-medication differs in metro and nonmetro areas.

Social determinants of health and emergency department utilization in Alabama Children's Health Insurance Program.

OBJECTIVES: Injuries are the leading cause of death among children and youth in the United States, representing a major concern to society and to the public and private health plans covering pediatric patients. Data from ALL Kids, Alabama's Children's Health Insurance Program, were used to evaluate the relationship between community-level social determinants of health (SDOH) and pediatric emergency department (ED) use and differences in these associations by age and race. STUDY DESIGN: This was a retrospective, pooled cross-sectional analysis. METHODS: We used ALL Kids data to identify ED visits (injury and all-cause) among children who were enrolled at any time from 2015 to 2017. Exploratory factor analysis was used to categorize SDOH from 18 selected Census tract-level variables. Multilevel Poisson regression models were used to evaluate the effects of community and individual factors and their interactions. RESULTS: Census tract-level SDOH were grouped as low socioeconomic status (SES), urbanicity, and immigrant-density factors. Low SES and urbanicity factors were associated with ED visits (injury and all-cause). The low SES and urbanicity factors also moderated the association between race and ED visits (injury and all-cause). CONCLUSIONS: The environment in which children live influences their ED use; however, the impact varies by age, race, and Census tract factors. Further studies should focus on specific community factors to better understand the relationship among SDOH, individual characteristics, and ED utilization.

In-person classroom instruction and risk of SARS-CoV-2 infection among undergraduates at Indiana University, Fall 2020.

Objective: To examine how in-person classroom instruction was related to risk of SARS-CoV-2 infection in undergraduate students. Participants: Indiana University undergraduate students (n = 69,606) enrolled in Fall 2020, when courses with in-person and remote instruction options were available. Methods: Students participated weekly in mandatory SARS-CoV-2 RT-PCR asymptomatic testing by random selection, supplemented with symptomatic testing as needed. We used log-binomial regression models to estimate the association between number of in-person credit hours and the risk of SARS-CoV-2 infection over the course of the semester. Results: Overall 5,786 SARS-CoV-2 cases were observed. Increased in-person credit hour exposures were not associated with increased risk of SARS-CoV-2 overall [aRR (95% CI): 0.98 (0.97,0.99)], nor within specific subgroups (Greek affiliation and class). Conclusions: In-person instruction did not appear to increase SARS-CoV-2 transmission in a university setting with rigorous protective measures in place, prior to mass vaccine rollout and prior to delta variant emergence.

Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo.

To date, nutritional epidemiology has relied heavily on relatively weak methods including simple observational designs and substandard measurements. Despite low internal validity and other sources of bias, claims of causality are made commonly in this literature. Nutritional epidemiology investigations can be improved through greater scientific rigor and adherence to scientific reporting commensurate with research methods used. Some commentators advocate jettisoning nutritional epidemiology entirely, perhaps believing improvements are impossible. Still others support only normative refinements. But neither abolition nor minor tweaks are appropriate. Nutritional epidemiology, in its present state, offers utility, yet also needs marked, reformational renovation. Changing the status quo will require ongoing, unflinching scrutiny of research questions, practices, and reporting-and a willingness to admit that "good enough" is no longer good enough. As such, a workshop entitled "Toward more rigorous and informative nutritional epidemiology: the rational space between dismissal and defense of the status quo" was held from July 15 to August 14, 2020. This virtual symposium focused on: (1) Stronger Designs, (2) Stronger Measurement, (3) Stronger Analyses, and (4) Stronger Execution and Reporting. Participants from several leading academic institutions explored existing, evolving, and new better practices, tools, and techniques to collaboratively advance specific recommendations for strengthening nutritional epidemiology.

Work-life balance among health administration faculty before and during the COVID-19 pandemic.

This current study examines measures of work-life balance among health administration faculty prior to and during the COVID-19 pandemic. A repeated cross-sectional design is used to analyze data collected from a national survey in 2018 and 2021. Changes in six different outcome measures of work-life balance were examined using multivariable logistic regression, controlling for health administration faculty characteristics. Compared to 2018 respondents, faculty respondents in 2021 were more likely to report that family and personal matters were interfering with their ability to do their job (OR = 1.93, p=0.001). Females more frequently reported that their career had suffered because of personal issues/obligations (OR = 1.82, p=0.003) but were less likely to report having enough time to get their teaching (OR = 0.68, p=0.026). Respondents with children 18 years or younger reported higher rates of regularly having to miss a meeting or event at home (OR = 1.88, p<0.001) and an event at work (OR = 3.74, p<0.001). These faculty also more frequently reported that family or personal matters were interfering with their ability to do their job (OR = 3.04, p<0.001) and that their career suffered because of personal issues/obligations (OR = 2.09, p=0.001). Given the implications of work-life conflicts to organizational outcomes, academic leaders and university decision-makers should consider adopting strategies to mitigate the effects of these disruptions to the work-life equilibrium of academics.

Quantifying Electronic Health Record Data Quality in Telehealth and Office-Based Diabetes Care.

OBJECTIVE: Data derived from the electronic health record (EHR) are commonly reused for quality improvement, clinical decision-making, and empirical research despite having data quality challenges. Research highlighting EHR data quality concerns has largely been examined and identified during traditional in-person visits. To understand variations in data quality among patients managing type 2 diabetes mellitus (T2DM) with and without a history of telehealth visits, we examined three EHR data quality dimensions: timeliness, completeness, and information density. METHODS: We used EHR data (2016-2021) from a local enterprise data warehouse to quantify timeliness, completeness, and information density for diagnostic and laboratory test data. Means and chi-squared significance tests were computed to compare data quality dimensions between patients with and without a history of telehealth use. RESULTS: Mean timeliness or T2DM measurement age for the study sample was 77.8 days (95% confidence interval [CI], 39.6-116.4). Mean completeness for the sample was 0.891 (95% CI, 0.868-0.914). The mean information density score was 0.787 (95% CI, 0.747-0.827). EHR data for patients managing T2DM with a history of telehealth use were timelier (73.3 vs. 79.8 days), and measurements were more uniform across visits (0.795 vs. 0.784) based on information density scores, compared with patients with no history of telehealth use. CONCLUSION: Overall, EHR data for patients managing T2DM with a history of telehealth visits were generally timelier and measurements were more uniform across visits than for patients with no history of telehealth visits. Chronic disease care relies on comprehensive patient data collected via hybrid care delivery models and includes important domains for continued data quality assessments prior to secondary reuse purposes.

Faculty salaries in health administration: trends and correlates 2015-2021.

In this study, we provide updated information on salaries of academic health administration (HA) faculty members based on data collected in 2015, 2018, and 2021 and examine characteristics associated with earnings. We present mean inflation-adjusted salaries by demographic characteristics, education, experience, productivity, and job activities. We find that salaries of assistant, associate, and full professors have kept up with inflation and there have not been significant changes in salary by any characteristics over time. As in previous iterations of similar survey data, there remain differences in salary by both gender and race. Higher salaries were associated with having a 12-month contract, being tenured or tenure-track, having an administrative position, and being in a department whose focus is not primarily teaching. Findings from our study will be of interest to individuals on the HA job market, hiring committees, and doctoral students preparing for a position after graduation.

Measuring rurality in health services research: a scoping review.

PURPOSE: This study is a scoping review of the different methods used to measure rurality in the health services research (HSR) literature. METHODS: We identified peer-reviewed empirical studies from 2010-2020 from seven leading HSR journals, including the Journal of Rural Health, that used any definition to measure rurality as a part of their analysis. From each study, we identified the geographic unit (e.g., county, zip code) and definition (e.g., Rural Urban Continuum Codes, Rural Urban Commuting Areas) used to classify categories of rurality. We analyzed whether geographic units and definitions used to classify rurality differed by focus area of studies, including costs, quality, and access to care. Lastly, we examined the number of rural categories used by authors to assess rural areas. FINDINGS: In 103 included studies, five different geographic units and 11 definitions were used to measure rurality. The most common geographic units used to measure rurality were county (n = 59, 57%), which was used most frequently in studies examining cost (n = 12, 75%) and access (n = 33, 57.9%). Rural Urban Commuting Area codes were the most common definition used to measure rurality for studies examining access (n = 13, 22.8%) and quality (n = 10, 44%). The majority of included studies made rural versus urban comparisons (n = 82, 80%) as opposed to focusing on rural populations only (n = 21, 20%). Among studies that compared rural and urban populations, most studies used only one category to identify rural locations (n = 49 of 82 studies, 60%). CONCLUSION: Geographic units and definitions to determine rurality were used inconsistently within and across studies with an HSR focus. This finding may affect how health disparities by rural location are determined and thus how resources and federal funds are allocated. Future research should focus on developing a standardized system to determine under what circumstances researchers should use different geographic units and methods to determine rurality by HSR focus area.

Assessing the use of a clinical decision support tool for pain management in primary care.

Objective: Given time constraints, poorly organized information, and complex patients, primary care providers (PCPs) can benefit from clinical decision support (CDS) tools that aggregate and synthesize problem-specific patient information. First, this article describes the design and functionality of a CDS tool for chronic noncancer pain in primary care. Second, we report on the retrospective analysis of real-world usage of the tool in the context of a pragmatic trial. Materials and methods: The tool known as OneSheet was developed using user-centered principles and built in the Epic electronic health record (EHR) of 2 health systems. For each relevant patient, OneSheet presents pertinent information in a single EHR view to assist PCPs in completing guideline-recommended opioid risk mitigation tasks, review previous and current patient treatments, view patient-reported pain, physical function, and pain-related goals. Results: Overall, 69 PCPs accessed OneSheet 2411 times (since November 2020). PCP use of OneSheet varied significantly by provider and was highly skewed (site 1: median accesses per provider: 17 [interquartile range (IQR) 9-32]; site 2: median: 8 [IQR 5-16]). Seven "power users" accounted for 70% of the overall access instances across both sites. OneSheet has been accessed an average of 20 times weekly between the 2 sites. Discussion: Modest OneSheet use was observed relative to the number of eligible patients seen with chronic pain. Conclusions: Organizations implementing CDS tools are likely to see considerable provider-level variation in usage, suggesting that CDS tools may vary in their utility across PCPs, even for the same condition, because of differences in provider and care team workflows.

SARS-CoV-2 reinfections in a US university setting, Fall 2020 to Spring 2021.

BACKGROUND: SARS-CoV-2 reinfections are a public health concern because of the potential for transmission and clinical disease, and because of our limited understanding of whether and how well an infection confers protection against subsequent infections. Despite the public health importance, few studies have reported rigorous estimates of reinfection risk. METHODS: Leveraging Indiana University's comprehensive testing program to identify both asymptomatic and symptomatic SARS-CoV-2 cases, we estimated the incidence of SARS-CoV-2 reinfection among students, faculty, and staff across the 2020-2021 academic year. We contextualized the reinfection data with information on key covariates: age, sex, Greek organization membership, student vs faculty/staff affiliation, and testing type. RESULTS: Among 12,272 people with primary infections, we found a low level of SARS-CoV-2 reinfections (0.6%; 0.4 per 10,000 person-days). We observed higher risk for SARS-CoV-2 reinfections in Greek-affiliated students. CONCLUSIONS: We found evidence for low levels of SARS-CoV-2 reinfection in a large multi-campus university population during a time-period prior to widespread COVID-19 vaccination.

Disparities in Telehealth Utilization in a Population of Publicly Insured Children During the COVID-19 Pandemic.

Telehealth became a crucial vehicle for health care delivery in the United States during the COVID-19 pandemic. However, little research exists on inequities in telehealth utilization among the pediatric population. This study examines disparities in telehealth utilization in a population of publicly insured children. This observational, retrospective study used administrative data from Alabama's stand-alone Children's Health Insurance Program, ALL Kids. Rates of any telehealth use for March to December 2020 were examined. In addition-to capture lack of health care utilization-rates of having no medical claims were examined and compared with March to December 2019 and 2018. Multinomial logit models were estimated to investigate how telehealth use and having no medical claims (reference category: having medical claims but no telehealth) were associated with race/ethnicity, rural-urban residence, and family income. Of the 106,478 enrollees over March to December 2020, 13.4% had any telehealth use and 24.7% had no medical claims. The latter was greater than no medical claims in 2019 (19.5%) and 2018 (20.7%). Black and Hispanic children had lower odds of any telehealth use (odds ratio [OR]: 0.81, P < 0.01; OR: 0.68, P < 0.01) and higher odds of no medical claims (OR: 1.11, P < 0.05; OR: 1.73, P < 0.05) than non-Hispanic White children. Rural residents had lower odds of telehealth use than urban residents. Those in the highest family income-based fee group had higher odds of telehealth use than the lowest family income-based fee group. As telehealth will likely continue to play an important role in health care delivery, additional efforts/investments are required to ensure telehealth does not further exacerbate inequities in pediatric health care access.

Does preventive dental care reduce nonpreventive dental visits and expenditures among Medicaid-enrolled adults?

OBJECTIVE: To determine whether preventive dental visits are associated with fewer subsequent nonpreventive dental visits and lower dental expenditures. DATA SOURCES: Indiana Medicaid enrollment and claims data (2015-2018) and the Area Health Resource File. STUDY DESIGN: A repeated measures design with individual and year fixed effects examining the relationship between preventive dental visits (PDVs) and nonpreventive dental visits (NPVs) and dental expenditures. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: Of 28,152 adults (108,349 observation-years) meeting inclusion criteria, 36.0% had a dental visit, 27.8% a PDV, and 22.1% a NPV. Compared to no PDV in the prior year, at least one was associated with fewer NPVs (ß = -0.13; 95% CI -0.12, -0.11), lower NPV expenditures (ß = -$29.12.53; 95% CI -28.07, -21.05), and lower total dental expenditures (-$70.12; 95% -74.92, -65.31), as well as fewer PDVs (ß = -0.24; 95% CI -0.26, -0.23). CONCLUSIONS: Our findings suggest that prior year PDVs are associated with fewer subsequent NPVs and lower dental expenditures among Medicaid-enrolled adults. Thus, from a public insurance program standpoint, supporting preventive dental care use may translate into improved population oral health outcomes and lower dental costs among certain low-income adult populations, but barriers to consistent utilization of PDV prohibit definitive findings.