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.

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.

Indiana's Public Health Investment Holds Insights For Other States.

Indiana has a business-friendly environment, but historical underinvestment in public health has yielded poor health outcomes. In 2023, when trust in governmental public health was strained nationwide, Indiana increased public health spending by 1,500 percent. In this article, we explain how Indiana achieved this unprecedented legislative victory for public health, describing the context, approach, and lessons learned. Specifically, an Indiana University report linking economic vitality and overall health sparked the creation of a governor's commission charged with exploring ways to address Indiana's shortcomings. Working with the Indiana Department of Health, the commission developed multisectoral coalitions and business and government partnerships, and it maintained consistent and coordinated communication with policy makers. Lessons learned included the value of uncoupling public health from partisan narratives, appointing diverse commission membership with strategically selected cochairs, involving local leaders, and ensuring local decision-making control. We believe that Indiana's approach holds insights for other states interested in strengthening public health funding in the current era.

Market Factors Associated with Comprehensive Behavioral Health Crisis Care Availability: A Resource Dependence Theory Study.

Behavioral health crisis care (BHCC) is a care delivery model for individuals experiencing acute distress related to a mental health or substance use disorder. We examined market factors associated with comprehensive BHCC availability using 2022 data on mental health treatment facilities (n = 9385) obtained from the Substance Abuse and Mental Health Services Administration. We aggregated facility-level data by county (n = 3142) and merged with county-level market factors. Logistic regression models were used to examine the adjusted associations between market factors and BHCC availability. We found that 468 (14.9%) counties had at least one mental health treatment facility offering comprehensive BHCC services. Specifically, counties with more mental health providers (Adjusted Odds Ratio = 2.26, Confidence Interval = 1.32-3.86) and metropolitan counties (AOR = 3.26, CI = 1.95-5.43) had higher odds of having a comprehensive BHCC facility. Our findings highlight the importance of developing the mental health workforce to increase BHCC availability and a need to address disparities in rural counties.

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.

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.

Availability of behavioral health crisis care and associated changes in emergency department utilization.

OBJECTIVE: To determine whether availability of behavioral health crisis care services is associated with changes in emergency department (ED) utilization. DATA SOURCES AND STUDY SETTING: We used longitudinal panel data (2016-2021) on ED utilization from the Healthcare Cost and Utilization Project's State ED Databases and a novel dataset on crisis care services compiled using information from the Substance Abuse and Mental Health Services Administration's National Directories of Mental Health Treatment Facilities. A total of 1002 unique zip codes from Arizona, Florida, Kentucky, Maryland, and Wisconsin were included in our analyses. STUDY DESIGN: To estimate the effect of crisis care availability on ED utilization, we used a linear regression model with zip code and year fixed effects and standard errors accounting for clustering at the zip code-level. ED utilization related to mental, behavioral, and neurodevelopmental (MBD) disorders served as our primary outcome. We also examined pregnancy-related ED utilization as a nonequivalent dependent variable to assess residual bias in effect estimates. DATA COLLECTION/EXTRACTION METHODS: We extracted data on crisis care services offered by mental health treatment facilities (n = 14,726 facility-years) from the National Directories. MBD-related ED utilization was assessed by applying the Clinical Classification Software Refined from the Healthcare Cost and Utilization Project to the primary ICD-10-CM diagnosis code on each ED encounter (n = 101,360,483). All data were aggregated to the zip code-level (n = 6012 zip-years). PRINCIPAL FINDINGS: The overall rate of MBD-related ED visits between 2016 and 2021 was 1610 annual visits per 100,000 population. Walk-in crisis stabilization services were associated with reduced MBD-related ED utilization (coefficient = -0.028, p = 0.009), but were not significantly associated with changes in pregnancy-related ED utilization. CONCLUSIONS: Walk-in crisis stabilization services were associated with reductions in MBD-related ED utilization. Decision-makers looking to reduce MBD-related ED utilization should consider increasing access to this promising alternative model.