Ohio journal of public health最新文献

{"title":"Increasing Capacity for Evaluation of Community-Based Organizations: Lessons from the Ohio Equity Institute","authors":"D. Walker, Matthew J. Depuccio, Jennifer L. Hefner, Cynthia J. Sieck, T. Hogan, A. McAlearney, C. Swoboda, Timothy R. Huerta","doi":"10.18061/ojph.v4i2.8469","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8469","url":null,"abstract":"Background: Community-based organizations (CBOs) play an important role delivering disease prevention and health promotion activities to address community health needs and improve the health of individuals living in their communities. While CBOs play this important role, evaluation of the services they deliver is hampered by limited infrastructure to systematically collect data from these organizations. To address this gap, we report on a case study of the development of the Ohio Equity Institute (OEI) Data Portal. The OEI is a statewide initiative that supports 65 CBOs across Ohio to deliver 3 evidence-based interventions (ie, CenteringPregnancy, Community Health Workers, and Home Visiting) to address infant mortality in underserved populations. Methods: Employing principles of community-engaged stakeholder research and user-centered design, we conducted Plan-Do-Study-Act cycles, including semistructured interviews with 43 key informants, to improve the development, implementation, and use of the OEI Data Portal. Results: This process identified both technical and implementation challenges, and offered opportunities to make improvements to the data collection system itself as well as to the integration of this system with CBO workflows. These improvements yielded significant gains in terms of the quantity and quality of data submission, ultimately contributing to ongoing outcome evaluation efforts. Conclusion: Our findings provide important insight into the challenges experienced by CBOs when participating in a statewide CBO data evaluation infrastructure development and implementation. As Ohio and other states push to expand collaborations between CBOs and health care organizations, leaders should leverage existing data collection to facilitate a more comprehensive and effective process.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47597339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perspectives of Treatment Consumers, Treatment Providers, and Law Enforcement on Drug Treatment and Prevention","authors":"Shauna P. Acquavita, L. Lowe, Kayleigh A Fiser, R. T. Sherba","doi":"10.18061/ojph.v4i2.8299","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8299","url":null,"abstract":"Background: While much of the literature has focused on examining barriers to substance use disorders (SUD) treatment with individuals with SUD, there is a dearth of research from the perspective of treatment providers and law enforcement, 2 groups who witness the challenges for addressing SUD. Methods: Using content analysis, this qualitative study explored the perspectives of individuals with SUD, treatment providers, and law enforcement on recommendations about SUD treatment and prevention. Data from 12 focus groups with individuals with SUD were analyzed and triangulated with interviews from treatment providers and law enforcement. Cross case analysis was utilized to identify common categories. Results: The categories identified included education, judicial system, psychosocial barriers, resources, stigma, stages of change, and treatment. Results indicated all groups had similar ideas on how to address SUD. Participants provided recommendations in each category for addressing SUD. Conclusion: Individuals with SUD, treatment providers, and law enforcement officers are affected by complex issues of SUD on micro, mezzo, and macro levels. Public health professionals can help to facilitate changes by advocating for prevention and intervention methods to be implemented to address SUD.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49641987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health Disparities Among Sexual and Gender Minority Adults in Ohio","authors":"Hannah E. Albrechta, M. Katz, Megan E. Roberts","doi":"10.18061/ojph.v4i2.8561","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8561","url":null,"abstract":"Background: Many documented disparities associated with health behaviors and access to health care impact the health outcomes of sexual and gender minorities (SGM). The current study aimed to gain insight into the health dispari-ties experienced by SGM adults living in Ohio to obtain data to plan future health-related programs. Methods: A secondary data analysis was conducted using 2018 Ohio Behavior Risk Factor Surveillance System (BRFSS) data. Health behaviors, health care access, and health outcomes were analyzed by sexual orientation (n=11 301) and gender identity (n=11 426) to determine health disparities faced by sexual minority males, sexual minority females and transgender individuals. Results: Significant SGM health disparities in Ohio are related to substance use (ie, binge drinking, current smoking status, e-cigarette use, and marijuana use); poor physical and mental health status; lack of health care coverage; and experiencing COPD, emphysema, or chronic bronchitis (all p < 0.001). In addition, fewer sexual minority females reported being within recommended breast cancer screening guidelines than heterosexual females (p < 0.05). Conclusion: Sexual and gender minority adults in Ohio report disparities associated with several health behaviors and access to health care. These findings may be due to factors at the patient level (eg, experiencing minority stress), provider level (eg, implicit bias), system level (eg, discrimination), and/or society level (eg, lack of legal protections). Study results will be used to plan health campaigns and programs targeted to SGM adults and providers to achieve health equity for the SGM population in Ohio.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47991814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Regional Income, Race, and Educational Level on Incidence of Diabetes and Heart Disease in Ohio","authors":"James R. Bolchalk, Sangeeta Gupta","doi":"10.18061/ojph.v4i2.8121","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8121","url":null,"abstract":"Background: Socioeconomic factors such as income, education, race, age, and weight are thought to be contributing factors for the incidence of chronic diseases such as diabetes and cardiovascular disease. Diabetes and cardiovascular disease are not only serious health complications but also cause significant financial burden to the health care system, both in Ohio and the US. This study seeks to examine the relationship of these socioeconomic factors to the prevalence of these 2 diseases in Ohio using the data available from Behavioral Risk Factor Surveillance Systems (BRFSS). Methods: Fourteen regions in Ohio were analyzed using logistic regression for socioeconomic impacts on diabetes and cardiovascular disease. Data for this study were obtained from the Behavioral Risk Factor Surveillance Systems (BRFSS) for the years 2011 through 2018. Results: Our results indicate that a strong relationship exists between age and weight with both diabetes and cardiovascular disease in all 14 regions of Ohio, as expected. However, the contribution of the other socioeconomic factors, except income and education levels, is less certain. Conclusion: This study suggests that besides promoting public health programs that focus on weight and age, effort should be made to evolve strategies promoting increased levels of income augmentation in the population.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49391711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Supply of Authorized Providers for Medication-Assisted Treatment in Ohio","authors":"Ariana Pitcher, W. Xu","doi":"10.18061/ojph.v4i2.8439","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8439","url":null,"abstract":"Background: Ohio experiences among the highest drug overdose rates nationally. The Drug Addiction Treatment Act (DATA) of 2000 permits qualified clinicians to use medication-assisted treatment (MAT) to treat opioid dependency. This study characterizes clinicians authorized to perform MAT and examines whether these clinicians are geographically collocated in areas with higher opioid burdens. Methods: Data of DATA providers in 2019 came from the Substance Abuse and Mental Health Administration. Opioid overdose mortality rates were extracted from the County Health Rankings and Roadmaps to represent disease burdens in local areas. The DATA provider density is represented by the number of DATA-waivered providers per 100 000 population for each county. We used Pearson correlational tests to examine the correlations between the local DATA provider density and the opioid mortality rate.Results: Most of the DATA providers were physicians (57%), followed by nurse practitioners (27%) and physician assistants (4%). The average waivered provider density was 13.90 per 100 000 population. The local density of DATA providers and local opioid overdose death rates are moderately correlated (P < 0.001).Conclusion: Physicians still represent most waivered providers in Ohio. While DATA providers were located in some areas with high needs for opioid treatments, our data suggest that other areas with high opioid burdens likely have an inadequate workforce supply to reduce opioid burdens. Without an adequate DATA workforce, policies that focus on MAT care access to address the opioid epidemic may be in vain.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49664536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparison of Nonprofit Hospital Charity Care Policies and Community Benefit in Central Ohio to Peer Cities","authors":"Sarah Clagg, Andrew Wapner, Jeff Klingler, S. Schweikhart","doi":"10.18061/ojph.v4i2.8438","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8438","url":null,"abstract":"Background: Nonprofit hospitals in the United States are required to provide community benefits, including charity care, to receive tax exemption from the federal government. Central Ohio's nonprofit hospitals have agreed to the same charity care policies, which may be unique compared to other communities across the county. The aim of this research is to compare the charity care policies of hospitals in Columbus, Ohio, to their peer cities, investigating if hospitals in similar cities have common shared charity care thresholds and to determine if hospitals in peer cities provided similar levels of community benefit. Methods: Tax data from nonprofit hospitals in 21 cities were collected and analyzed using Microsoft Excel (Microsoft Corporation). City community benefit data was summed and averaged using Excel to create a graphical representation of the data. Results: Only Columbus, Ohio, and Providence, Rhode Island, reported the same charity care thresholds across hospitals. Data demonstrate that Columbus provides less community benefit in dollars to total expenses compared to peer cities; however, this appears to be only true regarding other community benefit excluding charity care. Columbus was near the median among cities examined in regard to percentage of charity care to total community benefit. Conclusion: Results suggest variability in the amount and type of community benefit nonprofit hospitals provide. Central Ohio hospitals have the same charity care thresholds and spent approximately the same in total community benefit however it is not transparent how these funds are utilized. Current federal regulations do not assess whether the community benefits reported are affecting community health outcomes.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46824132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Home Health Aides: The Burgeoning Backbone of the Health Care System","authors":"Margo H. Schmiederer","doi":"10.18061/ojph.v4i2.8374","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8374","url":null,"abstract":"No abstract available.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48008565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ohio Journal of Public Health Vol. 4, Issue 2 (January 2022): Full Issue","authors":"Ohio Public Health Association Opha","doi":"10.18061/ojph.v4i2.8823","DOIUrl":"https://doi.org/10.18061/ojph.v4i2.8823","url":null,"abstract":"No abstract available.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41495244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Relationship Between Medical Diagnoses, Risk Perceptions, and Social Distancing Compliance: An Analysis of Data from the Toledo Adolescent Relationships Study.","authors":"Ian Y King, Wendy D Manning, Monica A Longmore, Peggy C Giordano","doi":"10.18061/ojph.v4i2.8352","DOIUrl":"10.18061/ojph.v4i2.8352","url":null,"abstract":"<p><strong>Background: </strong>The health belief model suggests that individuals' beliefs affect behaviors associated with health. This study examined whether Ohioans' pre-existing medical health diagnoses affected their belief about personal health risk and their compliance with social distancing during the coronavirus disease 2019 (COVID-19) pandemic. Prior research examining physical and mental diagnoses and social distancing compliance is nearly nonexistent. We examined whether physical and mental health diagnoses influenced individuals' beliefs that their health is at risk and their adherence with social distancing guidelines.</p><p><strong>Methods: </strong>The study used longitudinal cohort data from the Toledo Adolescent Relationships Study (TARS) (n = 790), which surveyed Ohioans prior to and during the COVID-19 pandemic. Dependent variables included belief that an individual's own health was at risk and social distancing compliance. Independent variables included physical and mental health diagnoses, pandemic-related factors (fear of COVID-19, political beliefs about the pandemic, friends social distance, family social distance, COVID-19 exposure), and sociodemographic variables (age, gender, race/ethnicity, educational level).</p><p><strong>Results: </strong>Individuals who had a pre-existing physical health diagnosis were more likely to believe that their personal health was at risk during the pandemic but were not more likely to comply with social distancing guidelines. In contrast, individuals who had a pre-existing mental health diagnosis were more compliant with social distancing guidelines but were not more likely to believe their personal health was at risk. Individuals who expressed greater fear of COVID-19 believed their health is more at risk than those who expressed lower levels of fear.</p><p><strong>Conclusion: </strong>Health considerations are important to account for in assessments of responses to the pandemic, beliefs about personal health risk, and social distancing behavior. Additional research is needed to understand the divergence in the findings regarding physical health, beliefs about personal health risk, and social distancing compliance. Further, research is needed to understand how mental health issues impact decision-making related to social distancing compliance.</p>","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":"4 2","pages":"34-42"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030274/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10620800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Social Determinants Screening/Mapping Tools to Identify Needs and Resources for Student-Run Free Clinic Patients","authors":"Akanksha Dadlani, Cooper Johnson, R. Fischbein, Stacey Gardner-Buckshaw, Amy Lee, J. Boltri","doi":"10.18061/ojph.v4i1.8073","DOIUrl":"https://doi.org/10.18061/ojph.v4i1.8073","url":null,"abstract":"Background: Social determinants of health have been well accepted as contributing to health outcomes. They are a vital aspect of health care delivery and must be a consideration, especially among free clinic populations. Social determinants of health have also become a required element of medical school curricula. The Student Outreach to Area Residents Student-Run Free Clinic based out of Northeast Ohio Medical University piloted a student-led program that implemented social determinants of health screening and community resource referral as a part of integrated health care delivery for all its patients. Methods: We described the development of a screening tool, protocol, and creation of community resource referral materials. We also described the tracking of patient-reported needs and mapping of location and accessibility of community resources. One hundred patients were surveyed through convenience sampling, and results were used for program improvement. Results/Conclusion: After collecting and analyzing survey results, it was found that the 2 most frequently requested determinants were mental health and utilities services, and the most available community resource was emergency food services. We also mapped these results by zip code and found gaps between need and distribution of services. We demonstrated the utility of mapping to identify points of improvement for the future. We also provided lessons learned related to effective social determinants of health screening, community resource referral, and overall program implementation in student-run free clinics. We further explained the benefits of including similar student-led programs as a way for students to gain practical experience related to social determinants of health.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47318834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}