Browsing by Subject "public health"
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Item An Analysis of Public Sunscreen Distribution in the United States During the COVID-19 Pandemic(Elsevier, 2022) Szeto, Mindy D.; Kokoska, Ryan E.; Maghfour, Jalal; Rundle, Chandler W.; Presley, Colby L.; Harp, Taylor; Hamp, Austin; Wegener, Victoria; Hugh, Jeremy; Dellavalle, Robert P.; Dermatology, School of MedicineItem Applied Public Health Informatics: An eHealth Discipline Focused on Populations(2020-12) Dixon, Brian E.; Epidemiology, School of Public HealthThe discipline of public health informatics, part of the broader eHealth field, brings methods, knowledge, and theories from computer science and information science to support population health and well-being. This branch of informatics is most often found in governmental public health agencies that focus on population-level activities, including surveillance of disease as well as disease prevention. There are several specialised public health information systems used to prevent or mitigate disease, including syndromic surveillance, electronic laboratory reporting, and population health dashboards. This article defines and describes public health informatics and its role in eHealth. The article further discusses the role of public health information systems and challenges they face for the future. Strengthening public health will require greater investment in interoperability as well as analytics and the workforce. Disease outbreaks like COVID-19, Ebola, and H1N1 demonstrate the need for robust public health informatics applications and methods. Yet there is much work to be done to evolve existing tools and methods to strengthen the public health infrastructure for the next pandemic.Item Area-level incarceration and STI risk among a cohort of justice-involved adolescents and adults(2014-11) Wiehe, Sarah E.; Rosenman, Marc; Scanlon, Michael L.; Fortenberry, J. Dennis; Aalsma, Matthew C.Background: Living in areas of high incarceration is associated with increased risk of STI; however, STI risk with respect to both this area-level exposure and an individual’s involvement with the justice system is not known. Objective: Among individuals before and after arrest or incarceration, assess the association between area-level incarceration rates and risk of chlamydia, gonorrhea, or syphilis. Methods: Retrospective cohort study of individuals living in Marion County (Indianapolis), Indiana who were arrested or in jail, prison, juvenile detention, or juvenile prison between 2005-2008 (N=97,765). Area-level incarceration exposure was defined by the proportion of person-days incarcerated among the total population*365 within a census block group. A 1-year period was assessed before and after a randomly-selected arrest/incarceration per person. Multivariable logistic regression, controlling for age, race, STI history, and year, was performed to assess chlamydia, gonorrhea, or syphilis risk by quartile area-level incarceration exposure, adjusting for individual clustering and stratifying by gender. Results: Area-level incarceration was associated with increased odds of each STI, with a dose response relationship particularly among those with an arrest or jail stay. Women with a history of arrest or jail/prison stay and living in high incarceration areas had higher odds of STI, compared to men with comparable incarceration history and living in similar areas.Item Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services(Oxford Press, 2018-01) Kasthurirathne, Suranga N.; Vest, Joshua R.; Menachemi, Nir; Halverson, Paul K.; Grannis, Shaun J.; Health Policy and Management, School of Public HealthIntroduction A growing variety of diverse data sources is emerging to better inform health care delivery and health outcomes. We sought to evaluate the capacity for clinical, socioeconomic, and public health data sources to predict the need for various social service referrals among patients at a safety-net hospital. Materials and Methods We integrated patient clinical data and community-level data representing patients’ social determinants of health (SDH) obtained from multiple sources to build random forest decision models to predict the need for any, mental health, dietitian, social work, or other SDH service referrals. To assess the impact of SDH on improving performance, we built separate decision models using clinical and SDH determinants and clinical data only. Results Decision models predicting the need for any, mental health, and dietitian referrals yielded sensitivity, specificity, and accuracy measures ranging between 60% and 75%. Specificity and accuracy scores for social work and other SDH services ranged between 67% and 77%, while sensitivity scores were between 50% and 63%. Area under the receiver operating characteristic curve values for the decision models ranged between 70% and 78%. Models for predicting the need for any services reported positive predictive values between 65% and 73%. Positive predictive values for predicting individual outcomes were below 40%. Discussion The need for various social service referrals can be predicted with considerable accuracy using a wide range of readily available clinical and community data that measure socioeconomic and public health conditions. While the use of SDH did not result in significant performance improvements, our approach represents a novel and important application of risk predictive modeling.Item Automating Provider Reporting of Communicable Disease Cases using Health Information Technology(Office of the Vice Chancellor for Research, 2014-04-11) Dixon, Brian E.; Lai, Patrick T. S.; Kirbiyik, Uzay; Grannis, Shaun J.Introduction Disease surveillance is a core public health (PH) function, which enables PH authorities to monitor disease outbreak and develop programs and policies to reduce disease burden. To manage and adjudicate cases of suspected communicable disease, PH workers gather data elements about persons, clinical care, and providers from various clinical sources, including providers, laboratories, among others. Current processes are paper-based and often yield incomplete and untimely reporting across different diseases requiring time-consuming follow-up by PH authorities to get needed information. Health information technology (HIT) refers to a wide range of technologies used in health care settings, including electronic health records and laboratory information systems. Health information exchange (HIE) involves electronic sharing of data and information between HIT systems, including those used in PH. Previous research has shown that using HIE to electronically report laboratory results to PH can improve surveillance practice, yet there has been little utilization of HIE for improving provider-based disease reporting [1]. Methods Our study uses an intervention to electronically pre-populate provider-based communicable disease case reporting forms with existing clinical, laboratory and patient data available through one of the largest and oldest HIE infrastructures in the U.S., the Indiana Network for Patient Care. Evaluation of the intervention will be conducted utilizing mixed methods in a concurrent design framework in which qualitative methods are embedded within the quantitative methods. Quantitative data will include reporting rates, timeliness and burden and report completeness and accuracy, analyzed using interrupted time-series and other pre-post comparisons. Qualitative data regarding pre-post provider perceptions of report completeness, accuracy, and timeliness, reporting burden, data quality, benefits, utility, adoption, utilization and impact on reporting workflow will be collected using semi-structured interviews and open-ended survey items. Data will be triangulated to find convergence or agreement by cross-validating results to produce a contextualized portrayal of the facilitators and barriers to implementation and use of the intervention. Results The intervention has been implemented in seven primary care clinics in the metropolitan Indianapolis area plus one rural clinic in Edinburgh. Analysis of baseline data shows that provider-based reports vary in their completeness, yet they contain critical information not available from laboratory information systems [2]. Furthermore, PH workers access a range of sources to gather the data they need to investigate disease cases [3]. Discussion and Conclusion By applying mixed research methods and measuring context, facilitators and barriers, and individual, organizational and data quality factors that may impact adoption and utilization of the intervention, we will document whether and how the intervention streamlines provider-based manual reporting workflows, lowers barriers to reporting, increases data completeness, improves reporting timeliness and captures a greater portion of communicable disease burden in the community. Early results are promising, and continued evaluation will be completed over the next 24 months.Item Beliefs About the Direct Comparison of E-Cigarettes and Cigarettes(Taylor & Francis, 2017) Hershberger, Alexandra R.; Karyadi, Kenny A.; VanderVeen, J. Davis; Cyders, Melissa A.; Psychology, School of ScienceBackground: Recent data suggests that positive beliefs about electronic cigarettes (e-cigs) use can lead to later e-cig use. Considering that many advertisements claim that e-cigs are superior to cigarettes, individuals' likelihood to view e-cigs more favorably than cigarettes can also influence subsequent e-cig use; however, no studies have directly assessed such a comparison. Objectives: The present study created and validated the Comparing E-Cigarettes and Cigarettes questionnaire (CEAC), which asks individuals to directly compare e-cigs and cigarettes on a number of dimensions, in two independent samples. Methods: In sample 1 (451 undergraduates; mean age = 20.35, SD = 5.44, 72.4% female, 73.4% Caucasian) we explored the factor structure of the CEAC and in sample 2 (699 community adults collected via Amazon's Mechanical Turk; mean age = 34.04, SD = 10.9, 47.7% female, 83.3% Caucasian) we replicated the factor structure. Results: Exploratory factor analysis suggested a three-factor structure: General Benefits (α = 0.80), General Effects (α = 0.86), and Health Benefits (α = 0.88), which was replicated via confirmatory factor analysis, χ2 = 4.36; RMSEA = 0.07, 90% CI = 0.06–0.08; TLI = 0.99; CFI = 0.99, and was relatively invariant across product use and gender. Individuals reported viewing e-cigs as safer and more beneficial than cigarettes and these beliefs were higher in e-cig users. Conclusions: Future work should establish how these comparative beliefs are influenced by e-cig use and/or influence subsequent transition to and increases in e-cig use. Although e-cigs are likely less harmful than cigarettes, and thus these comparative beliefs represent that state of nature, e-cigs are not completely without risk.Item Challenges in Translating National and State Reopening Plans Into Local Reopening Policies During the COVID-19 Pandemic(Sage, 2021-03) Vest, Joshua R.; Blackburn, Justin; Yeager, Valerie A.; Health Policy and Management, School of Public HealthPandemic events, such as coronavirus disease 2019 (COVID-19), affect health and economics at national and international scales, but in the United States, health care delivery and public health practice occur at the local level. Transmission control and eventual economic recovery require detailed guidance for communities, cities, metropolitan areas, and states. Our recent experience as consultants on the control and reopening plans for the city of Indianapolis and Marion County, Indiana, illustrated challenges with national plans, highlighted fundamental tensions in identifying the best course for policy, and emphasized gaps in the evidence base and our public health resources.Item Changing epidemiology of firearm injury: a cohort study of non-fatal firearm victimisation before and during the COVID-19 pandemic, Indianapolis, Indiana(British Medical Journal, 2022-03-01) Magee, Lauren A.; Lucas, Bailee; Fortenberry, J. Dennis; Medicine, School of MedicineObjective To examine victimisation rates, geographic patterns and neighbourhood characteristics associated with non-fatal firearm injury rates before and during the COVID-19 pandemic. Design A retrospective cohort study. Setting City of Indianapolis, Indiana, USA, 1 January 2017–30 June 2021. Participants Intentional non-fatal firearm injury victims from Indianapolis Metropolitan Police Department records. The study included information on 2578 non-fatal firearm injury victims between ages 0 and 77 years. Of these victims, 82.5% were male and 77.4% were black. Primary and secondary outcome measures Rates of non-fatal firearm injuries per 100 000 population by victim age, race, sex and incident motive. Prepandemic and peripandemic non-fatal firearm injury rates. Results Non-fatal shooting rates increased 8.60%, from 57.0 per 100 000 person-years in prepandemic years to 65.6 per 100 000 person-years during the pandemic (p<0.001). Rates of female victims (15.2 vs 23.8 per 100,000; p<0.001) and older victims (91.3 vs 120.4 per 100,000; p<0.001) increased significantly during the pandemic compared with the prepandemic period. Neighbourhoods with higher levels of structural disadvantage (IRR: 1.157, 95% CI 1.012 to 1.324) and prepandemic firearm injury rates (IRR: 1.001, 95% CI 1.001 to 1.002) was positively associated with higher rates of non-fatal firearm injuries during the pandemic, adjusting for neighbourhood characteristics. Conclusions Non-fatal firearm injuries increased significantly during the COVID-19 pandemic, particularly among female and older victims. Efforts are needed to expand and rethink current firearm prevention efforts that both address the diversification of victimisation and the larger societal trauma of firearm violence.Item Characteristics and Outcomes of Critically Ill Children With Multisystem Inflammatory Syndrome(Wolters Kluwer, 2022-11) Snooks, Kellie; Scanlon, Matthew C.; Remy, Kenneth E.; Shein, Steven L.; Klein , Margaret J.; Zee-Cheng, Janine; Rogerson, Colin M.; Rotta, Alexandre T.; Lin, Anna; McCluskey, Casey K.; Carroll , Christopher L.; Pediatrics, School of MedicineObjectives: To characterize the prevalence of pediatric critical illness from multisystem inflammatory syndrome in children (MIS-C) and to assess the influence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain on outcomes. Design: Retrospective cohort study. Setting: Database evaluation using the Virtual Pediatric Systems Database. Patients: All children with MIS-C admitted to the PICU in 115 contributing hospitals between January 1, 2020, and June 30, 2021. Measurements and Main Results: Of the 145,580 children admitted to the PICU during the study period, 1,338 children (0.9%) were admitted with MIS-C with the largest numbers of children admitted in quarter 1 (Q1) of 2021 (n = 626). The original SARS-CoV-2 viral strain and the D614G Strain were the predominant strains through 2020, with Alpha B.1.1.7 predominating in Q1 and quarter 2 (Q2) of 2021. Overall, the median PICU length of stay (LOS) was 2.7 days (25–75% interquartile range [IQR], 1.6–4.7 d) with a median hospital LOS of 6.6 days (25–75% IQR, 4.7–9.3 d); 15.2% received mechanical ventilation with a median duration of mechanical ventilation of 3.1 days (25–75% IQR, 1.9–5.8 d), and there were 11 hospital deaths. During the study period, there was a significant decrease in the median PICU and hospital LOS and a decrease in the frequency of mechanical ventilation, with the most significant decrease occurring between quarter 3 and quarter 4 (Q4) of 2020. Children admitted to a PICU from the general care floor or from another ICU/step-down unit had longer PICU LOS than those admitted directly from an emergency department. Conclusions: Overall mortality from MIS-C was low, but the disease burden was high. There was a peak in MIS-C cases during Q1 of 2021, following a shift in viral strains in Q1 of 2021. However, an improvement in MIS-C outcomes starting in Q4 of 2020 suggests that viral strain was not the driving factor for outcomes in this population.Item Community Health Information Resource Guide: Volume 1 - Data(The Polis Center at IUPUI, 2011-06) Comer, Karen F; Derr, Michelle; Seyffarth, Chris; Thomaskutty, Champ; Kandris, Sharon; Ritchey, MatthewThis resource guide contains useful information for those who would like to use data to assess the health status of an Indiana community. Targeted users include local organizations such as county health departments and community health coalitions. Being able to access and use relevant data and information resources is a common hurdle for those interested in assessing and advancing community health. As a result of this need and at the request of the Community Advisory Council of the Community Health Engagement Program, we developed this resource guide to assist individuals, organizations, and coalitions in Indiana in identifying appropriate resources that guide their community health research and evaluation activities. The term “data” is used in this volume in reference to both data and information sources. While data consist of raw facts and figures, information is formed by analyzing the data and applying knowledge to it so that the findings are more meaningful and valuable to the community. The benefit of using data is that you can often manipulate it for your specific purposes. The benefit of using information sources is that the work of generating meaning from the data might already have been done, while a potential downside is that the available sources might not answer your specific questions. There are diverse sources of data that can be used as a basis for community health evaluation and decision making. Those looking to use data must consider multiple factors before determining the appropriate data to seek and use.