State Of Ohio Research Articles

The Rule of Judicial Political Affiliation in Criminal Sentencing Outcomes

Legislative efforts to bring consistency to criminal sentencing outcomes has been much discussed in academic literature and Congressional hearings alike. Despite these efforts disparate sentencing outcomes persist. Researchers have studied many variables seeking to understand these disparities but have been unable to form a consensus around the cause. Perhaps because of the lack of a firm understanding of the issue among researchers, legislative intervention at both the state and federal level has largely failed to address the issue of judicial characteristics that may drive sentencing disparities. As a result, absent from the conversation on criminal sentencing reform is empirical and anecdotal evidence about how judges make determinations within the range of outcomes specified by the legislature. New data on federal sentencing outcomes collected by Harvard researchers, however, finds a direct connection between the political party of the President who appointed the federal judge and the length of a defendant’s sentence. As the Harvard study reports, federal judges appointed by Republican presidents sentence defendants on average to three more months in prison than federal judges appointed by Democratic presidents. Republican-appointed judges in the federal system also sentence black defendants more harshly than Democratic-appointed judges. As will be discussed in this Article, the central premise of the Harvard political sentencing study – that judicial political affiliation influences sentencing outcomes, even those that are highly guided by legislative criteria – also holds true on the state level with respect to elected, rather than appointed, judges. As we report, empirical evidence from the state of Ohio demonstrates that elected Republican judges sentence defendants to lengthier terms of incarceration than elected Democratic judges by a statistically significant margin. This evidence suggests that, rather than being entirely guided by specified statutory criteria, judges bring preexisting sentencing ideologies to the bench and make decisions with a range of sentencing outcomes based at least in part on their individual philosophies and beliefs. Based on these findings, we argue that in order to address the issue of sentencing disparities, reform efforts should take action to specifically address the behavior and motivation of individual judges.

Arsenic and Atrazine in Drinking Water and the Risk of Gestational Diabetes

Arsenic and atrazine in drinking water and the risk of gestational diabetes BackgroundThere is limited evidence that arsenic and atrazine are associated with an increased risk of gestational diabetes. The objective of this study is to assess the potential association between exposure to arsenic and atrazine in drinking water and the risk of gestational diabetes. MethodsGestational diabetes was ascertained from birth certificate data from the Ohio Department of Health for 428,804 mothers delivering between 2006 – 2008 in the state of Ohio. Exposure data in this study were obtained at the county level from the Safe Drinking Water Information System (SDWIS) and at the community level from the Atrazine Monitoring Program (AMP). Logistic regression models were used to assess the association between both environmental chemicals and gestational diabetes while controlling for year, maternal race/ethnicity, maternal age, maternal education, cigarette use during pregnancy, pre-pregnancy BMI, and socio-economic indicators. Sensitivity analyses were performed to control for gestational hypertension and eclampsia, and by restricting to counties where less than 20% and less than 10% of residents rely on private well water. ResultsThere was no evidence for an association between a one-unit increase in average annual arsenic concentrations (µg/L) and the risk of gestational diabetes in fully-adjusted models [Odds Ratio= 0.97, 95%CI=0.96 – 0.98]. The sensitivity analyses yielded similar results to the full models. There was some evidence of an association between average gestational atrazine exposure and the risk of gestational diabetes in fully adjusted models [Odds Ratio= 1.26, 95%CI=0.97 – 1.63]. ConclusionsThis study provides some evidence of an association between gestational diabetes and atrazine in drinking water. No association between arsenic in drinking water and gestational diabetes was observed. Further research is needed on the role that these and other chemicals may play in gestational diabetes.

Characterization of community-wide transmission of SARS-CoV-2 in congregate living settings and local public health-coordinated response during the initial phase of the COVID-19 pandemic.

BackgroundClusters of COVID‐19 cases amplify the pandemic and are critical targets for intervention, but comprehensive cluster‐level data are not collected systematically by federal or most state public health entities. This analysis characterizes COVID‐19 clusters among vulnerable populations housed in congregate living settings across an entire community and describes early mitigation efforts.MethodsThe Cuyahoga County Board of Health identified and interviewed COVID‐19 cases and exposed contacts, assessing possible connections to congregate living facilities within its jurisdiction from March 7, 2020, to May 15, 2020, during the first phase of the pandemic, while state of Ohio stay‐at‐home orders were in effect. A multi‐disciplinary team‐based response network was mobilized to support active case finding and develop facility‐focused containment strategies.ResultsWe identified a cascade of 45 COVID‐19 clusters across community facilities (corrections, nursing, assisted living, intermediate care, extended treatment, shelters, group homes). Attack rates were highest within small facilities (P < .01) and large facilities requiring extensive support to implement effective containment measures. For 25 clusters, we identified an index case who frequently (88%) was a healthcare worker. Engagement of clinical, community, and government partners through public health coordination efforts created opportunities to rapidly develop and coordinate effective response strategies to support the facilities facing the dawning impact of the pandemic.ConclusionsActive cluster investigations can uncover the dynamics of community transmission affecting both residents of congregate settings and their caregivers and help to target efforts toward populations with ongoing challenges in access to detection and control resources.

A Novel Health-Transportation Partnership Paves The Road For Young Driver SafetyThrough Virtual Assessment.

Motor vehicle crashes remain the leading cause of adolescent mortality and injury in the United States. For young drivers, crash risk peaks immediately after licensure and declines during the next two years, making the point of licensure an important safety intervention opportunity. Legislation in Ohio established a unique health-transportation partnership among the State of Ohio, Children's Hospital of Philadelphia, and Diagnostic Driving, Inc., to identify underprepared driver license applicants through a virtual driving assessment system. The system, a computer-based virtual driving test, exposes drivers to common serious crash scenarios to identify critical skill deficits and is delivered in testing centers immediately before the on-road examination. A pilot study of license applicants who completed it showed that the virtual driving assessment system accurately predicted which drivers would fail the on-road examination and provided automated feedback that informed drivers on their skill deficits. At this time, the partnership's work is informing policy changes around integrating the virtual driving assessment system into licensing and driver training with the aim of reducing crashes in the first months of independent driving. The system can be developed to identify deficits in safety-critical skills that lead to crashes in new drivers and to address challenges that the coronavirus disease 2019 pandemic has introduced to driver testing and training.

Developing Continuing Education for Ohio’s Local Boards of Health

Background: Public health functions at the county level and city level through the work of local health departments (LHDs). Local boards of health (LBoHs) work closely with LHDs as an administrative oversight body. In 2013, legislation was passed in the state of Ohio pertaining to the accreditation of LHDs, which included a provision requiring that Ohio’s LBoH members engage in 2 hours of continuing education (CE) per year. To assist LBoHs in fulfilling these requirements, a partnership was developed between the Ohio Association of Boards of Health (OABH) and the Kent State University College of Public Health (KSU-CPH) to deliver CE content.&#x0D; Methods: The process for developing the CE modules encompasses 3 steps: (1) needs assessment, (2) module development and delivery, and (3) evaluation. Feedback was solicited from Ohio’s LBoH members to determine topics of interest for CE modules. Taking this feedback, a curated set of 8 modules will be developed. Module content will be derived from graduate courses within KSU-CPH as well as from subject matter experts. The modules will be delivered online to LBoH members during their regularly scheduled meetings.&#x0D; Results: This program proposes to fulfill state requirements that LBoH members regularly engage in CE. Partner-ing with KSU-CPH allows for the use of academic content in these trainings.&#x0D; Conclusion: An adequately trained public health workforce is essential for a well-functioning public health system, which includes governing entities like LBoHs. There is limited understanding of how workforce development can be targeted specifically to LBoHs. This CE program contributes to current efforts to promote workforce development within the field of public health.

First Record of the Blue Crawfish, Cambarus monongalensis Ortmann, 1905 (Decapoda: Cambaridae), from Ohio, USA

This paper documents the first record of the blue crawfish, Cambarus monongalensis Ortmann, 1905, in the state of Ohio, United States. The blue crawfish is a small- to medium-sized primary burrowing crayfish common in western Pennsylvania and West Virginia. Because of the prevalence of this species on the east side of the Ohio River, numerous researchers have sought the blue crawfish in Ohio—to no avail. On 16 May 2020, turkey hunters in Monroe County, Ohio, located a blue-colored crayfish and sent photos to one of the authors of this study. On 19 May 2020, the authors sampled in the vicinity of where the photo was taken and located 4 sites that yielded a total of 5 blue crawfish specimens, confirming the existence of this species in Ohio. Further research is needed on the blue crawfish to determine its range and abundance in Ohio, and to explore factors relating to its biogeography.

Pedestrian Fatal Crash Location Analysis in Ohio using Exploratory Spatial Data Analysis Techniques

Pedestrian safety is a top priority within the transportation planning community as cities promote sustainable transportation, alternative travel modes, and healthy lifestyles. If people feel unsafe while walking, they will choose other modes of transportation if they are able. To prioritize safety, it is important to know where pedestrian crashes are occurring and with what severity. Using spatial statistical methods including nearest neighbor index, Moran’s I, local indicators of spatial autocorrelation (LISA), and Getis-Ord G-statistic, this study seeks to analyze the pedestrian fatality locations within the state of Ohio over a 10-year period (2007–2016) to identify hot spots, cold spots, and spatial patterns across three different spatial scales: county, census tract, and traffic analysis zone (TAZ). It seeks to understand the effects of aggregated data across these spatial scales on the outcome of the analysis and determine the most useful spatial scale at which to study pedestrian fatalities. The study concludes that spatial analyses at small scales are most informative. It goes on to recommend locations within Ohio for further analysis based on the resulting maps, including areas with outliers. As of writing this, there is no current statewide pedestrian fatality analysis for the state of Ohio.

The Cost of Providing the Foundational Public Health Services in Ohio.

To examine levels of expenditure and needed investment in public health at the local level in the state of Ohio pre-COVID-19. Using detailed financial reporting from fiscal year (FY) 2018 from Ohio's local health departments (LHDs), we characterize spending by Foundational Public Health Services (FPHS). We also constructed estimates of the gap in public health spending in the state using self-reported gaps in service provision and a microsimulation approach. Data were collected between January and June 2019 and analyzed between June and September 2019. Eighty-four of the 113 LHDs in the state of Ohio covering a population of almost 9 million Ohioans. In FY2018, Ohio LHDs spent an average of $37 per capita on protecting and promoting the public's health. Approximately one-third of this investment supported the Foundational Areas (communicable disease control; chronic disease and injury prevention; environmental public health; maternal, child, and family health; and access to and linkages with health care). Another third supported the Foundational Capabilities, that is, the crosscutting skills and capacities needed to support all LHD activities. The remaining third supported programs and activities that are responsive to local needs and vary from community to community. To fully meet identified LHD needs in the state pre-COVID-19, Ohio would require an additional annual investment of $20 per capita on top of the current $37 spent per capita, or approximately $240 million for the state. A better understanding of the cost and value of public health services can educate policy makers so that they can make informed trade-offs when balancing health care, public health, and social services investments. The current environment of COVID-19 may dramatically increase need, making understanding and growing public health investment critical.

20. POINT-OF-CARE ULTRASOUND EDUCATION FOR PEDIATRIC RESIDENTS: A MULTICENTER NEEDS ASSESSMENT

Background Point-of-care ultrasound (POCUS) is rapidly growing as a non-invasive imaging modality to enhance procedural safety and efficiently reach diagnoses. Despite established applications in general pediatrics and high value to many pediatric subspecialties, it is not widely used in residency and no national standard currently exists for inclusion of POCUS in training curricula. Objectives To profile the current state of POCUS education in pediatric residencies in the State of Ohio. Methods We defined our population as pediatric residents in the state of Ohio (N=558). We developed an electronic survey with guidance from POCUS content experts, a survey methodologist, and residency program leadership. The survey was piloted locally using family medicine residents. We randomly sampled 369 pediatric residents from the 9 programs in the state; stratifying by level of training and scaled to the relative size of each residency. Results Our response rate was 59.6% (220/369). While 36% of respondents received POCUS education in medical school, only 15% have received it in residency (Table 1). Most respondents (86%) were interested in receiving POCUS education in residency and 67% believed that it should in fact be required. Specifically, they felt that POCUS would be useful for performing procedures (95%), learning clinical topics (94%), and improving patient safety (74%). Most of the residents surveyed (61%) felt that POCUS education would significantly benefit their careers regardless of subspecialty plans. In contrast, 85% had performed zero scans in residency. Barriers to POCUS education include the lack of an established curriculum (75%), competing priorities (58%), and inadequate knowledge and experience of faculty (52%). Conclusions Pediatric residents want POCUS training and consider it beneficial to their future practice. Despite this, more than half receive no POCUS education in residency or medical school. Focusing upon further POCUS-specific curriculum development and faculty education may help address this educational gap.

Gene Therapy for Spinal Muscular Atrophy: Safety and Early Outcomes.

Historically, autosomal recessive 5q-linked spinal muscular atrophy (SMA) has been the leading inherited cause of infant death. SMA is caused by the absence of the SMN1 gene, and SMN1 gene replacement therapy, onasemnogene abeparvovec-xioi, was Food and Drug Administration approved in May 2019. Approval included all children with SMA age <2 years without end-stage weakness. However, gene transfer with onasemnogene abeparvovec-xioi has been only studied in children age ≤8 months. In this article, we report key safety and early outcome data from the first 21 children (age 1-23 months) treated in the state of Ohio. In children ≤6 months, gene transfer was well tolerated. In this young group, serum transaminase (aspartate aminotransferase and alanine aminotransferase) elevations were modest and not associated with γ glutamyl transpeptidase elevations. Initial prednisolone administration matched that given in the clinical trials. In older children, elevations in aspartate aminotransferase, alanine aminotransferase and γ glutamyl transpeptidase were more common and required a higher dose of prednisolone, but all were without clinical symptoms. Nineteen of 21 (90%) children experienced an asymptomatic drop in platelets in the first week after treatment that recovered without intervention. Of the 19 children with repeated outcome assessments, 11% (n = 2) experienced stabilization and 89% (n = 17) experienced improvement in motor function. In this population, with thorough screening and careful post-gene transfer management, replacement therapy with onasemnogene abeparvovec-xioi is safe and shows promise for early efficacy.

Quantifying the decrease in emergency department imaging utilization during the COVID-19 pandemic at a multicenter healthcare system in Ohio.

PurposeTo illustrate the change in emergency department (ED) imaging utilization at a multicenter health system in the state of Ohio during the COVID-19 pandemic.MethodsA retrospective observational study was conducted assessing ED imaging volumes between March 1, 2020, and May 11, 2020, during the COVID-19 crisis. A rolling 7-day total value was used for volume tracking and comparison. Total imaging utilization in the ED was compared with new COVID-19 cases in our region. Utilization was first categorized by modality and then by plain films and computed tomography (CT) scans grouped by body part. CT imaging of the chest was specifically investigated by assessing both CT chest only exams and CT chest, abdomen, and pelvis (C/A/P) exams. Ultimately, matching pair-wise statistical analysis of exam volumes was performed to assess significance of volume change.ResultsOur multicenter health system experienced a 46% drop in imaging utilization (p < 0.0001) during the pandemic. Matching pair-wise analysis showed a statistically significant volume decrease by each modality and body part. The exceptions were non-contrast chest CT, which increased (p = 0.0053), and non-trauma C/A/P CT, which did not show a statistically significant volume change (p = 0.0633).ConclusionED imaging utilization trends revealed through actual health system data will help inform evidence-based decisions for more accurate volume predictions and therefore institutional preparedness for current and future pandemics.

Integrating Human Trafficking Data: A Case Study of Conceptual and Operational Variation in Ohio

ABSTRACT This paper describes the process and methods of integrating human trafficking data across agency record sources. This study focuses on the process of collecting and integrating comprehensive human trafficking data for research purposes. Using a case study framework for the state of Ohio, we first explore the variation in human trafficking definitions used across agencies and the implications for integrating data sources. Second, we describe how these disparate sources of data were integrated with the goal of estimating the prevalence of human trafficking. Third, we describe the need for conceptual and operational clarification in how agencies define and measure human trafficking victimization as we identified a lack of uniformity in definitions and variability in the types of measured items. In conducting this statewide prevalence study, we identified challenges to integrating agency record data across sources based on variation in definitions and variable inclusion which led to conceptual ambiguity. We offer three practical recommendations to improving conceptual and operational approaches to human trafficking measurement. In particular, attending carefully to the process of data collection can improve measurement to promote change in practice that facilitates more effective intervention.

Leveraging Prescription Drug Monitoring Programs to Evaluate Opioid Policy Interventions

Research ObjectiveA variety of state and federal policies have been enacted to curtail prescription opioid overdoses, including implementation of statewide opioid prescribing guidelines and rescheduling of hydrocodone from DEA Schedule III to Schedule II. We aimed to use data from the Ohio Prescription Drug Monitoring Program (PDMP) to evaluate the effects of these policies.Study DesignRetrospective study of all opioid prescriptions dispensed in the state of Ohio from 2010 to 2017. We first determined the number and characteristics of opioid prescriptions stratified by specialty. We then used an interrupted time series analysis to determine the effect on opioid prescribing after (a) the release of statewide opioid prescribing guidelines in 2012 and (b) the federal rescheduling of hydrocodone in 2014.Population StudiedThe state of Ohio. Prescriptions for the nine most common pill form opioid pain relievers dispensed in Ohio were included. The PDMP includes all prescriptions dispensed to individuals in the state, regardless of payer.Principal FindingsThe number and characteristics of opioid prescriptions and trends over time varied greatly between different prescriber specialties. The mean number of pills/prescription and morphine content of the prescriptions were highest for physical medicine/rehabilitation (91.2 pills, 1532 mg, n = 1 680 579), anesthesiology/pain (89.3 pills, 1484 mg, n = 3 261 449), hematology/oncology (88.2 pills, 1534 mg, n = 516,596), and neurology (84.4 pills, 1230 mg, n = 573 389). Overall, family medicine (21.8%) and internal medicine (17.6%) prescribed the most opioids. The implementation of emergency department opioid prescribing guidelines was associated with a 12% decrease (95% CI −17.7% to −6.3%) in the level of statewide total prescriptions/month and an additional decrease of 0.9% (95% CI −1.1% to −0.7%) relative to the trend before the guidelines. Rescheduling of hydrocodone was associated with a level change of −26 358 (95% CI −36 700 to −16 016) prescriptions (−5.8%) and an additional decrease of −1568 (95% CI −2296 to −839) prescriptions/month. Rescheduling was associated with a temporary substitution effect (increase) of codeine and with a decrease in the prescribing of tramadol.ConclusionsThe characteristics of opioid prescriptions vary widely by specialty and suggest the need for specialty‐specific guidance. Opioid guidelines targeting the emergency department were associated with a decrease in prescribing beyond the secular trend. The rescheduling of hydrocodone was associated with a decrease in hydrocodone prescriptions beyond the secular trend, but also appeared to affect the prescribing of other opioids as well.Implications for Policy or PracticePDMPs are state‐based prescribing databases that can be used to influence prescriber decision‐making at the point of care. However, their powerful data can also be used to describe prescribing behaviors overall and evaluate the effectiveness of implemented opioid‐related policies.

Visualizing Opportunity Index Data Using a Dashboard Application: A Tool to Communicate Infant Mortality-Based Area Deprivation Index Information.

An area deprivation index (ADI) is a geographical measure that accounts for socioeconomic factors (e.g., crime, health, and education). The state of Ohio developed an ADI associated with infant mortality: Ohio Opportunity Index (OOI). However, a powerful tool to present this information effectively to stakeholders was needed. We present a real use-case by documenting the design, development, deployment, and training processes associated with a dashboard solution visualizing ADI data. The Opportunity Index Dashboard (OID) allows for interactive exploration of the OOI and its seven domains-transportation, education, employment, housing, health, access to services, and crime. We used a user-centered design approach involving feedback sessions with stakeholders, who included representatives from project sponsors and subject matter experts. We assessed the usability of the OID based on the effectiveness, efficiency, and satisfaction dimensions. The process of designing, developing, deploying, and training users in regard to the OID is described. We report feedback provided by stakeholders for the OID categorized by function, content, and aesthetics. The OID has multiple, interactive components: choropleth map displaying OOI scores for a specific census tract, graphs presenting OOI or domain scores between tracts to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. Changes based on parameter and filter selections are described using a general use-case. In the usability evaluation, the median task completion success rate was 83% and the median system usability score was 68. The OID could assist health care leaders in making decisions that enhance care delivery and policy decision making regarding infant mortality. The dashboard helps communicate deprivation data across domains in a clear and concise manner. Our experience building this dashboard presents a template for developing dashboards that can address other health priorities.

When Second Best Might Be the Best: Using Hospitalization Data to Monitor the Novel Coronavirus Pandemic.

The novel coronavirus' high rate of asymptomatic transmission combined with a lack of testing kits call for a different approach to monitor its spread and severity. We proposed the use of hospitalizations and hospital utilization data to monitor the spread and severity. A proposed threshold of a declining 7-day moving average over a 14-day period, “7&14” was set to communicate when a wave of the novel coronavirus may have passed. The state of Ohio was chosen to illustrate this threshold. While not the ideal solution for monitoring the spread of the epidemic, the proposed approach is an easy to implement framework accounting for limitations of the data inherent in the current epidemic. Hospital administrators and policy makers may benefit from incorporating this approach into their decision making.

Challenges and Facilitators of Implementing a Physician-approved Naloxone Protocol: A Mixed-methods Study.

In 2015, the State of Ohio passed legislation to allow pharmacists to dispense naloxone under a physician-approved protocol. The legislation allows all individuals authorized under a physician-approved protocol to personally furnish naloxone without requiring clients to be seen by a licensed prescriber, thus expanding the capacity of Ohio's community distribution programs. We aimed to evaluate the implementation of legislation allowing for a physician-approved protocol in pharmacies and other naloxone distribution sites in Ohio, and to compare barriers and facilitators of implementing the law changes among sites that implemented a physician-approved protocol versus sites that did not. The study used a convergent parallel mixed-method design. Random samples from all pharmacies registered with the State of Ohio Board of Pharmacy and community naloxone distribution sites were selected. Quantitative data were collected via survey (n = 168) and qualitative data were collected via semi-structured interviews (n = 17). Most survey respondents agreed that the policy has expanded access to naloxone at their site for individuals who want or need the medication. Both pharmacies and other naloxone distribution sites identified that leadership and organizational support facilitated protocol implementation and cost, stigma, and lack of naloxone demand challenged protocol implementation. The study identified barriers and facilitators to the implementation of a physician-approved protocol within Ohio. The majority of respondents stated they could implement a protocol. However, barriers of cost, lack of public awareness of naloxone availability, and stigma remain for pharmacies and other naloxone distribution sites.

The Need And Benefit of Implementing Telemedicine in Clinical Practice

The Need And Benefit of Implementing Telemedicine in Clinical Practice

State of Ohio v. Ross Compton: Internet-enabled medical device data introduced as evidence of arson and insurance fraud

The data generated by Internet of Things devices is increasingly being introduced as evidence in court. The first US case involving the introduction of medical data from a pacemaker as evidence of arson and insurance fraud was State of Ohio v Compton. The purpose of this article is three-fold. First, the article explores this case, looking in particular at the facts of the case and the charges brought against the defendant. Second, the article critically examines the decision of the trial court judge during the suppression hearing for the evidence from the pacemaker. In this hearing, the judge ruled that the search and seizure did not violate the Fourth Amendment rights of the defendant and allowed the pacemaker data to be entered as evidence against him. Third, the article considers the implications of this decision for future cases involving Internet-of-Things (IoT) medical data. Ultimately, the constitutional protections of IoT medical device data and the circumstances under which the data from these devices will be collected and used as evidence, are issues that currently demand the attention of legal and digital forensics professionals and warrant public debate.

Responsible Return to Essential and Non-Essential Surgery During the COVID-19 Pandemic

Non-essential surgery had largely been suspended during the COVID-19 Pandemic. Enormous amounts of resources were utilized to shift surgical practices to a “disaster footing” with most elective surgeons assuming new roles to offset the anticipated burden from surgical and medical personnel delivering acute care. As the number of COVID-19-infected patients began to plateau in the state of Ohio, a four-phase “Responsible Return to Surgery” approach was adopted in concert with the Ohio Department of Health and the Ohio Hospital Association. This approach was adopted understanding that a simple return to the status quo prior to the COVID-19 pandemic might be harmful to patients, providers, and staff. The discrete phases undertaken at our quaternary care institution for a responsible return to non-essential surgery are outlined with the goal of ensuring timely care, minimizing community transmission, and preserving personal protective equipment. Operationalizing these phases relied upon the widespread use of telehealth, systematic COVID-19 testing, and real-time monitoring of hospital and personal protective equipment resources.

Estimating the burden of the opioid epidemic for adults and adolescents in Ohio counties.

Quantifying the opioid epidemic at the local level is a challenging problem that has important consequences on resource allocation. Adults and adolescents may exhibit different spatial trends and require different interventions and resources so it is important to examine the problem for each age group. In Ohio, surveillance data are collected at the county level for each age group on measurable outcomes of the opioid epidemic, overdose deaths, and treatment admissions. However, our interest lies in quantifying the unmeasurable construct, representing the burden of the opioid epidemic, which drives rates of the outcomes. We propose jointly modeling adult and adolescent surveillance outcomes through a multivariate spatial factor model. A generalized spatial factor model within each age group quantifies a latent factor related to the number of opioid-associated treatment admissions and deaths. By assuming a multivariate conditional autoregressive model for the spatial factors of adults and adolescents, we allow the adolescent model to borrow strength from the adult model (and vice versa), improving estimation. We also incorporate county-level covariates to help explain spatial heterogeneity in each of the factors. We apply this approach to the state of Ohio and discuss the findings. Our framework provides a coherent approach for synthesizing information across multiple outcomes and age groups to better understand the spatial epidemiology of the opioidepidemic.