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.

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.

Laws Governing State Health Official Appointments: A Legal and Historical Review.

Objective: The current study presents the legal epidemiological review of State Health Official (SHO) appointment laws, including the evolution of educational and experience requirements of SHOs over time. Findings can inform the discussion about state laws and the substantive, multidisciplinary qualifications essential to successfully leading state public health agencies in the 21st century.

Methods: Standard policy surveillance methods were used to collect and assess the statutes governing SHO appointment and eligibility from all 50 states and the District of Columbia between 1995 and 2020.

Daniel J McCarty, MD: A Giant of Rheumatology.

There is no doubt that Dr Daniel J McCarty warrants inclusion among the giants of rheumatology. He has made major contributions to both clinical and scientific knowledge in our field, and his impact has been long-lasting and paradigm shifting. He is perhaps best known for his pioneering work in crystal arthritis, but as an astute clinician, he is also responsible for describing several other novel rheumatic conditions and developing innovative treatment protocols.

Design and Implementation of the Diabetes Impact Project: A Multisector Partnership to Reduce Diabetes Burden in Indianapolis Communities.

Context: Community-level health disparities have not arisen suddenly but are the result of long-term systemic inequities. This article describes the design and implementation of a community-engaged multisector partnership to address health disparities by reducing the diabetes burden in 3 Indianapolis communities through the implementation of evidence-based strategies across the prevention continuum.

Program: The project has 5 foundational design principles: engage partners from multiple sectors to address community health, focus on geographic communities most affected by the health disparity, practice authentic community engagement, commit for the long term, and utilize a holistic approach spanning the prevention continuum.

Successive Wave Analysis to Assess Nonresponse Bias in a Statewide Random Sample Testing Study for SARS-CoV-2.

Introduction: Nonresponse bias occurs when participants in a study differ from eligible nonparticipants in ways that can distort study conclusions. The current study uses successive wave analysis, an established but underutilized approach, to assess nonresponse bias in a large-scale SARS-CoV-2 prevalence study. Such an approach makes use of reminders to induce participation among individuals.

Indoor Public Mask-Wearing Behavior Changes in Response to National, State, and Local COVID-19 Policies.

Objective: To estimate changes in public mask-wearing behavior in response to public health policies during COVID-19.

Design: Panel of observed public mask-wearing.

Setting: Counts of adult behavior in Marion County, Indiana, between November 15, 2020, and May 31, 2021.

Primary Care Case Conferences to Mitigate Social Determinants of Health: A Case Study from One FQHC System.

Objective: Given the increasing difficulty healthcare providers face in addressing patients' complex social circumstances and underlying health needs, organizations are considering team-based approaches including case conferences. We sought to document various perspectives on the facilitators and challenges of conducting case conferences in primary care settings.

Study Design: Qualitative study using semi-structured telephone interviews.

Association of Health Status and Nicotine Consumption with SARS-CoV-2 positivity rates.

Background: Much of what is known about COVID-19 risk factors comes from patients with serious symptoms who test positive. While risk factors for hospitalization or death include chronic conditions and smoking; less is known about how health status or nicotine consumption is associated with risk of SARS-CoV-2 infection among individuals who do not present clinically.

Methods: Two community-based population samples (including individuals randomly and nonrandomly selected for statewide testing, n = 8214) underwent SARS-CoV-2 testing in nonclinical settings.

Institutional factors associated with hospital partnerships for population health: A pooled cross-sectional analysis.

Background: Hospitals are increasingly engaging in partnerships to address population health in response to national policies, such as value-based payment models. However, little is known about how institutional factors influence hospital partnerships for population health.

Purpose: Guided by institutional theory, we examine the association between institutional pressures (coercive, normative, and mimetic isomorphism) and hospital partnerships for population health.

Primary Care-Based Case Conferences and Reductions in Health Care Utilization.

Case conferences are collaborative, interdisciplinary team meetings that facilitate consensus on individual patients' health management plans, coordinate services, and initiate referrals. This approach is well-suited to address the social needs and risks of complex patients. Evidence of this approach in primary care settings to change patient outcomes is limited.

Impact of Medicaid expansion on smoking prevalence and quit attempts among those newly eligible, 2011-2019.

Introduction: Low-income populations have higher rates of smoking and are disproportionately affected by smoking-related illnesses. This study assessed the long-term impact of increased coverage for tobacco cessation through Medicaid expansion on past-year quit attempts and prevalence of cigarette smoking.

Methods: Using data from CDC's annual Behavioral Risk Factor Surveillance System 2011-2019, we conducted difference-in-difference regression analyses to compare changes in smoking prevalence and past-year quit attempts in expansion states versus non-expansion states.

Choice of measurement approach for area-level social determinants of health and risk prediction model performance.

Objective: The objective of this paper is to provide empirical guidance by comparing the performance of six different area-level SDoH measurement approaches in predicting patient referral to a social worker and hospital admission after a primary care visit.

Methods: We compared the performance of six area-level SDoH measurement approaches in predicting patient referral to a social worker and hospital admission after a primary care visit using random forest classification algorithm. Data came from 209,605 patient encounters at a federally qualified health center.

Hospital Partnerships for Population Health: A Systematic Review of the Literature.

The U.S. healthcare system continues to experience high costs and suboptimal health outcomes that are largely influenced by social determinants of health.

Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study.

Background: Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods.

How Many SARS-CoV-2-Infected People Require Hospitalization? Using Random Sample Testing to Better Inform Preparedness Efforts.

Context: Existing hospitalization ratios for COVID-19 typically use case counts in the denominator, which problematically underestimates total infections because asymptomatic and mildly infected persons rarely get tested. As a result, surge models that rely on case counts to forecast hospital demand may be inaccurately influencing policy and decision-maker action.

Objective: Based on SARS-CoV-2 prevalence data derived from a statewide random sample (as opposed to relying on reported case counts), we determine the infection-hospitalization ratio (IHR), defined as the percentage of infected individuals who are hospitalized, for various demographic groups in Indiana.

Bayesian estimation of SARS-CoV-2 prevalence in Indiana by random testing.

From 25 to 29 April 2020, the state of Indiana undertook testing of 3,658 randomly chosen state residents for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the agent causing COVID-19 disease. This was the first statewide randomized study of COVID-19 testing in the United States. Both PCR and serological tests were administered to all study participants.

The evaluation of the correct use and ease-of use of the ELLIPTA DPI in children with asthma.

Rationale: Asthma studies show many children use inhalers incorrectly even after instruction. For two age groups of children with asthma, we determined the proportions who used the once-daily ELLIPTA dry-powder inhaler (DPI) correctly, and who found it easy to use.

Methods: This was a multicenter, single-arm, stratified, open-label, placebo study (NCT03478657).

Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study.

Background: Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods.

Safety of Rimegepant, an Oral CGRP Receptor Antagonist, Plus CGRP Monoclonal Antibodies for Migraine.

Objective: Evaluate the safety and tolerability of oral rimegepant when used for acute treatment concomitantly with a monoclonal antibody (mAb) targeting the calcitonin gene-related peptide (CGRP) ligand or receptor (CGRP mAb) for the preventive treatment of migraine.

Background: The efficacy of CGRP mAbs for the preventive treatment of migraine and the small molecule CGRP receptor antagonist rimegepant for acute treatment has been demonstrated in randomized controlled clinical trials. Over the past few years, the US Food and Drug Administration has approved 4 CGRP mAbs for the preventive treatment of migraine and 2 small molecule CGRP receptor antagonists for the acute treatment of migraine.

Population Point Prevalence of SARS-CoV-2 Infection Based on a Statewide Random Sample - Indiana, April 25-29, 2020.

Population prevalence of persons infected with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), varies by subpopulation and locality. U.S.

Precision Health-Enabled Machine Learning to Identify Need for Wraparound Social Services Using Patient- and Population-Level Data Sets: Algorithm Development and Validation.

Background: Emerging interest in precision health and the increasing availability of patient- and population-level data sets present considerable potential to enable analytical approaches to identify and mitigate the negative effects of social factors on health. These issues are not satisfactorily addressed in typical medical care encounters, and thus, opportunities to improve health outcomes, reduce costs, and improve coordination of care are not realized. Furthermore, methodological expertise on the use of varied patient- and population-level data sets and machine learning to predict need for supplemental services is limited.