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Timely access to Medicaid coverage offers many potential benefits to justice-involved adults reentering the community. In 2015 Indiana’s Section 1115 Medicaid waiver (the Healthy Indiana Plan [HIP]...

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. studies of SARS-CoV-2 infection have examined infections in nonrandom samples (1) or seroprevalence in specific populations* (2), which are limited in their generalizability and cannot be used to accurately calculate infection-fatality rates. During April 25-29, 2020, Indiana conducted statewide random sample testing of persons aged ≥12 years to assess prevalence of active infection and presence of antibodies to SARS-CoV-2; additional nonrandom sampling was conducted in racial and ethnic minority communities to better understand the impact of the virus in certain racial and ethnic minority populations. Estimates were adjusted for nonresponse to reflect state demographics using an iterative proportional fitting method. Among 3,658 noninstitutionalized participants in the random sample survey, the estimated statewide point prevalence of active SARS-CoV-2 infection confirmed by reverse transcription-polymerase chain reaction (RT-PCR) testing was 1.74% (95% confidence interval [CI] = 1.10-2.54); 44.2% of these persons reported no symptoms during the 2 weeks before testing. The prevalence of immunoglobulin G (IgG) seropositivity, indicating past infection, was 1.09% (95% CI = 0.76-1.45). The overall prevalence of current and previous infections of SARS-CoV-2 in Indiana was 2.79% (95% CI = 2.02-3.70). In the random sample, higher overall prevalences were observed among Hispanics and those who reported having a household contact who had previously been told by a health care provider that they had COVID-19. By late April, an estimated 187,802 Indiana residents were currently or previously infected with SARS-CoV-2 (9.6 times higher than the number of confirmed cases [17,792]) (3), and 1,099 residents died (infection-fatality ratio = 0.58%). The number of reported cases represents only a fraction of the estimated total number of infections. Given the large number of persons who remain susceptible in Indiana, adherence to evidence-based public health mitigation and containment measures (e.g., social distancing, consistent and correct use of face coverings, and hand hygiene) is needed to reduce surge in hospitalizations and prevent morbidity and mortality from COVID-19.

Background Hospices provide end-of-life care to patients who have complex health care needs and whose symptoms are difficult to control. Understanding why some hospices offer inpatient hospice care to patients could bring more evidence for policy makers and researchers to focus on the role of inpatient care in hospice. Purpose The purpose of this study was to examine market and organizational factors that are associated with the provision of hospice inpatient care. Methodology This study used a retrospective, longitudinal design (2009-2013). The study sample was drawn from three data resources: the Area Health Resources Files, the Provider of Services files, and Hospice Cost Reports from Centers for Medicare & Medicaid Services. The sample size was 2,391 hospices or 10,999 hospice observations over 5 years. A generalized linear mixed-effects model was used to examine the association between market and organizational factors and hospice inpatient services offering. Results On average, 94.59% of hospices offer inpatient services to patients. Proportion of adults who were over 65 years old (OR = 1.12) and Medicare-managed care penetration (OR = 1.02) were positively associated with the provision of hospice inpatient services. The number of hospitals with hospice program was negatively related to hospice inpatient services offering (OR = .95). Other factors such as nursing skill mix, volunteer dependence, and census region were also associated with inpatient services offering. Practice implications The age demand of hospice care and Medicare-managed care penetration are related to hospice inpatient services offering. Hospices located in the market with more competition from hospitals that offer hospice program are less likely to offer inpatient care.

Background Recruiting healthcare providers as research subjects often rely on in-person recruitment strategies. Little is known about recruiting provider participants via electronic recruitment methods. In this study, conducted during the COVID-19 pandemic, we describe and evaluate a primarily electronic approach to recruiting primary care providers (PCPs) as subjects in a pragmatic randomized controlled trial (RCT) of a decision support intervention. Methods We adapted an existing framework for healthcare provider research recruitment, employing an electronic consent form and a mix of brief synchronous video presentations, email, and phone calls to recruit PCPs into the RCT. To evaluate the success of each electronic strategy, we estimated the number of consented PCPs associated with each strategy, the number of days to recruit each PCP and recruitment costs. Results We recruited 45 of 63 eligible PCPs practicing at ten primary care clinic locations over 55 days. On average, it took 17 business days to recruit a PCP (range 0–48) and required three attempts (range 1–7). Email communication from the clinic leaders led to the most successful recruitments, followed by brief synchronous video presentations at regularly scheduled clinic meetings. We spent approximately $89 per recruited PCP. We faced challenges of low email responsiveness and limited opportunities to forge relationships. Conclusion PCPs can be efficiently recruited at low costs as research subjects using primarily electronic communications, even during a time of high workload and stress. Electronic peer leader outreach and synchronous video presentations may be particularly useful recruitment strategies. Trial registration ClinicalTrials.gov, NCT04295135. Registered 04 March 2020.

Objective Given time constraints, poorly organized information, and complex patients, primary care providers (PCPs) can benefit from clinical decision support (CDS) tools that aggregate and synthesize problem-specific patient information. First, this article describes the design and functionality of a CDS tool for chronic noncancer pain in primary care. Second, we report on the retrospective analysis of real-world usage of the tool in the context of a pragmatic trial. Materials and methods The tool known as OneSheet was developed using user-centered principles and built in the Epic electronic health record (EHR) of 2 health systems. For each relevant patient, OneSheet presents pertinent information in a single EHR view to assist PCPs in completing guideline-recommended opioid risk mitigation tasks, review previous and current patient treatments, view patient-reported pain, physical function, and pain-related goals. Results Overall, 69 PCPs accessed OneSheet 2411 times (since November 2020). PCP use of OneSheet varied significantly by provider and was highly skewed (site 1: median accesses per provider: 17 [interquartile range (IQR) 9–32]; site 2: median: 8 [IQR 5–16]). Seven “power users” accounted for 70% of the overall access instances across both sites. OneSheet has been accessed an average of 20 times weekly between the 2 sites. Discussion Modest OneSheet use was observed relative to the number of eligible patients seen with chronic pain. Conclusions Organizations implementing CDS tools are likely to see considerable provider-level variation in usage, suggesting that CDS tools may vary in their utility across PCPs, even for the same condition, because of differences in provider and care team workflows.

Telehealth became a crucial vehicle for health care delivery in the United States during the COVID-19 pandemic. However, little research exists on inequities in telehealth utilization among the pediatric population. This study examines disparities in telehealth utilization in a population of publicly insured children. This observational, retrospective study used administrative data from Alabama's stand-alone Children's Health Insurance Program, ALL Kids. Rates of any telehealth use for March to December 2020 were examined. In addition-to capture lack of health care utilization-rates of having no medical claims were examined and compared with March to December 2019 and 2018. Multinomial logit models were estimated to investigate how telehealth use and having no medical claims (reference category: having medical claims but no telehealth) were associated with race/ethnicity, rural-urban residence, and family income. Of the 106,478 enrollees over March to December 2020, 13.4% had any telehealth use and 24.7% had no medical claims. The latter was greater than no medical claims in 2019 (19.5%) and 2018 (20.7%). Black and Hispanic children had lower odds of any telehealth use (odds ratio [OR]: 0.81

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. Based on the response continuum theory, those requiring several reminders to participate are more like nonrespondents than those who participate in a study upon first invitation, thus allowing for an examination of factors affecting participation.Study participants from the Indiana Population Prevalence SARS-CoV-2 Study were divided into 3 groups (eg, waves) based upon the number of reminders that were needed to induce participation. Independent variables were then used to determine whether key demographic characteristics as well as other variables hypothesized to influence study participation differed by wave using chi-square analyses. Specifically, we examined whether race, age, gender, education level, health status, tobacco behaviors, COVID-19-related symptoms, reasons for participating in the study, and SARS-CoV-2 positivity rates differed by wave.Respondents included 3658 individuals, including 1495 in wave 1 (40.9%), 1246 in wave 2 (34.1%), and 917 in wave 3 (25%), for an overall participation rate of 23.6%. No significant differences in any examined variables were observed across waves, suggesting similar characteristics among those needing additional reminders compared with early participants.Using established techniques, we found no evidence of nonresponse bias in a random sample with a relatively low response rate. A hypothetical additional wave of participants would be unlikely to change original study conclusions. Successive wave analysis is an effective and easy tool that can allow public health researchers to assess, and possibly adjust for, nonresponse in any epidemiological survey that uses reminders to encourage participation.

In this study, we provide updated information on salaries of academic health administration (HA) faculty members based on data collected in 2015, 2018, and 2021 and examine characteristics associated with earnings. We present mean inflation-adjusted salaries by demographic characteristics, education, experience, productivity, and job activities. We find that salaries of assistant, associate, and full professors have kept up with inflation and there have not been significant changes in salary by any characteristics over time. As in previous iterations of similar survey data, there remain differences in salary by both gender and race. Higher salaries were associated with having a 12-month contract, being tenured or tenure-track, having an administrative position, and being in a department whose focus is not primarily teaching. Findings from our study will be of interest to individuals on the HA job market, hiring committees, and doctoral students preparing for a position after graduation.

Background SARS-CoV-2 reinfections are a public health concern because of the potential for transmission and clinical disease, and because of our limited understanding of whether and how well an infection confers protection against subsequent infections. Despite the public health importance, few studies have reported rigorous estimates of reinfection risk. Methods Leveraging Indiana University’s comprehensive testing program to identify both asymptomatic and symptomatic SARS-CoV-2 cases, we estimated the incidence of SARS-CoV-2 reinfection among students, faculty, and staff across the 2020–2021 academic year. We contextualized the reinfection data with information on key covariates: age, sex, Greek organization membership, student vs faculty/staff affiliation, and testing type. Results Among 12,272 people with primary infections, we found a low level of SARS-CoV-2 reinfections (0.6%; 0.4 per 10,000 person-days). We observed higher risk for SARS-CoV-2 reinfections in Greek-affiliated students. Conclusions We found evidence for low levels of SARS-CoV-2 reinfection in a large multi-campus university population during a time-period prior to widespread COVID-19 vaccination.

Health insurers use narrow and tiered networks to lower costs by contracting with, or favoring, selected providers. Little is known about the contemporary effects of narrow or tiered networks on key metrics. The purpose of this systematic review was to synthesize the evidence on how narrow and tiered networks impact cost, access, quality, and patient steering. We searched PubMed, MEDLINE, and Cochrane Central Register of Controlled Trials databases for articles published from January 2000 to June 2020. Both narrow and tiered networks are associated with reduced overall health care costs for most cost-related measures. Evidence pertaining to access to care and quality measures were more limited to a narrow set of outcomes or were weak in internal validity, but generally concluded no systematic adverse effects on narrow or tiered networks. Narrow and tiered networks appear to reduce costs without affecting some quality measures. More research on quality outcomes is warranted.

With the passage of the Affordable Care Act, states were given the option to expand their Medicaid programs. Since then, thirty-eight states and Washington, D.C., have done so. Previous work has identified the widespread effects of expansion on enrollment and the financial implications for individuals, hospitals, and the federal government, yet administrative expenditures have not been considered. Using data from all fifty states for the period 2007-17, our study estimated the effects of Medicaid expansion overall, as well as differing effects by the size and nature of the expansions. Using a quasi-experimental approach, we found no overall effect of expansion on administrative spending. However, the size of the expansion may have produced differing effects. States with small expansions experienced some increases in administrative spending, whereas states with large expansions experienced some decreases in administrative spending, including a $77 reduction in per enrollee administrative spending compared with nonexpansion states. As more states consider expanding their Medicaid programs, our findings provide evidence of potential effects.

CONTEXT State health officials (SHOs), the executive and administrative leaders of state public health, play a key role in policy development, must be versed in the relevant/current evidence, and provide expertise about health issues to the legislature and the governor. OBJECTIVE To provide an empirical examination of SHO backgrounds and qualifications over time. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional survey of current/former SHOs. MAIN OUTCOME MEASURES State health official educational backgrounds; public health experience; previous employment setting. RESULTS Two-thirds of respondents (64.6%) reported having a medical degree, approximately half (48.3%) a formal public health degree, and almost one-quarter (21.8%) a management degree. The majority had governmental public health experience at some prior point in their career (70.0%). Almost two-thirds worked in governmental public health immediately before becoming an SHO. The proportion that was female increased significantly by decade from 5.6% in the 1970s/80s to 46.4% in the 2010s (P = .02). CONCLUSIONS The main finding from this study shows that more than two-thirds of SHOs have had governmental public health experience at some point in their career. This is not a new trend as there were no statistical differences in public health experience by decade. More than half of the SHOs were appointed to the role directly from governmental public health, indicating that their public health experience is timely and likely germane to their appointment as SHO. Findings also indicate improvements in gender diversity among one of the most influential leadership roles in governmental public health whereas significant changes in racial and ethnic diversity were not identified. Women are increasingly being appointed as SHOs, indicating increasing gender diversity in this influential position. Given that governmental public health employees are predominantly women, there is still room for gender equity improvements in executive leadership roles. This is coupled with the need for further racial and ethnic diversity improvements as well.

OBJECTIVES: Medicaid and Children’s Health Insurance Program plans publicly report quality measures, including follow-up care after psychiatric hospitalization. We aimed to understand failure to meet this measure, including measurement definitions and enrollee characteristics, while investigating how follow-up affects subsequent psychiatric hospitalizations and emergency department (ED) visits. METHODS: Administrative data representing Alabama’s Children’s Health Insurance Program from 2013 to 2016 were used to identify qualifying psychiatric hospitalizations and follow-up care with a mental health provider within 7 to 30 days of discharge. Using relaxed measure definitions, follow-up care was extended to include visits at 45 to 60 days and visits to a primary care provider. Logit regressions estimated enrollee characteristics associated with follow-up care and, separately, the likelihood of subsequent psychiatric hospitalizations and/or ED visits within 30, 60, and 120 days. RESULTS: We observed 1072 psychiatric hospitalizations during the study period. Of these, 356 (33.2%) received follow-up within 7 days and 566 (52.8%) received it within 30 days. Relaxed measure definitions captured minimal additional follow-up visits. The likelihood of follow-up was lower for both 7 days (−18 percentage points; 95% confidence interval [CI] −26 to −10 percentage points) and 30 days (−26 percentage points; 95% CI −35 to −17 percentage points) regarding hospitalization stays of ≥8 days. Meeting the measure reduced the likelihood of subsequent psychiatric hospitalizations within 60 days by 3 percentage points (95% CI −6 to −1 percentage point). CONCLUSIONS: Among children, receipt of timely follow-up care after a psychiatric hospitalization is low and not sensitive to measurement definitions. Follow-up care may reduce the need for future psychiatric hospitalizations and/or ED visits.

BACKGROUND In U.S. hospitals, boards of directors (BODs) have numerous governance responsibilities including overseeing hospital activities and guiding strategic decisions. BODs can help hospitals adapt to changes in their markets including those stemming from a shift from fee-for-service to value-based purchasing. The recent increase in market turbulence for hospitals has brought renewed attention to the work of BODs. PURPOSE The aim of the study was to examine trends in hospital BOD structure and activities and determine whether these changes are commensurate with approaches designed to respond to market pressures. METHODOLOGY/APPROACH We examined hospital level data from The Governance Institute Survey (2009, 2011, 2013, and 2015) and corresponding years of the American Hospital Association Annual Survey in a pooled, cross-sectional design. We conducted individual multivariate models with adjustments for hospital and market characteristics, comparing the changes in BOD structures, demographics, and activities over time. FINDINGS The sample included 1,811 hospital-year observations, including 682 unique facilities. We found that BODs in 2015 had less internal management (β = -2.25, p < .001) and fewer employed and nonemployed physicians (β = -8.28, p < .001) involved on the BOD. Moreover, compared to 2009, racial and ethnic minorities (2013 β = 2.88, p < .001) and women (2013 β = 1.60, p = .045; 2015 β = 2.06, p = .049) on BODs increased over time. In addition, BODs were significantly less likely to spend time on the following activities in 2015, as compared to 2009: discussing strategy and setting policy (β = -5.46, p = .002); receiving reports from management, board committees, and subsidiaries (β = -29.04, p < .001); and educating board members (β = -4.21, p < .001). Finally, BODs had no changes in the type of committees reported over time. PRACTICE IMPLICATIONS Our results indicate that hospital BODs deploy various strategies to adapt to current market trends. Hospital decision-makers should be aware of the potential effects of board structure on organization's position in the changing health care market.

BACKGROUND Hospice is the key provider of end-of-life care to patients. As the number of U.S. hospice agencies has rapidly increased, the performance has been scrutinized more deeply. PURPOSE To foster understanding of how hospice performance is measured and what factors are associated with performance, we conducted a systematic review of empirical research on hospice performance in the United States. METHODS Both structure-process-outcome and structure-conduct-performance frameworks were applied to categorize and summarize the hospice performance literature. A total of 36 studies were included in the systematic review. RESULTS Hospice agencies adopted different strategies (e.g., service provision strategy and staffing strategy) to improve performance. Two strategic approaches (innovation and volunteer usage) were associated with better outcomes. Hospice organizational factors, market environment, and patient characteristics were related to hospice strategic conduct and performance. Majority of hospice performance studies have examined the relationship between hospice structure and strategic conduct/process, with fewer studies focusing on structure performance and even fewer concentrating on strategy performance. PRACTICE IMPLICATIONS Patient, organizational, and market factors are associated with hospice strategic conduct and performance. The majority of the literature considered the impact of hospice organizational characteristics, whereas only a few studies included patient and market factors. The summarization of factors that may influence hospice performance provides insight to different stakeholders.

High-deductible health plans (HDHPs) are becoming more popular owing to their potential to curb rising health care costs. Relative to traditional health insurance plans, HDHPs involve higher out-of-pocket costs for consumers, which have been associated with lower utilization of health services. We focus specifically on the impact that HDHPs have on the use of preventive services. We critique the current evidence by discussing the benefits and drawbacks of the research designs used to examine this relationship. We also summarize the findings from the most methodologically sophisticated studies. We conclude that the balance of the evidence shows that HDHPs are reducing the use of some preventive service, especially screenings. However, it is not clear if HDHPs affect all preventive services. Additional research is needed to determine why variability in conclusions exists among studies. We describe an agenda for future research that can further inform public health decision makers on the impact of HDHPs on prevention.

BACKGROUND: Changes in payment models incentivize hospitals to vertically integrate into sub-acute care (SAC) services. Through vertical integration into SAC, hospitals have the potential to reduce the transaction costs associated with moving patients throughout the care continuum and reduce the likelihood that patients will be readmitted. PURPOSE: The purpose of this study is to examine the correlates of hospital vertical integration into SAC. METHODOLOGY/APPROACH: Using panel data of U.S. acute care hospitals (2008–2012), we conducted logit regression models to examine environmental and organizational factors associated with hospital vertical integration. Results are reported as average marginal effects. FINDINGS: Among 3,775 unique hospitals (16,269 hospital-year observations), 25.7% vertically integrated into skilled nursing facilities during at least 1 year of the study period. One measure of complexity, the availability of skilled nursing facilities in a county (ME = −1.780, p < .001), was negatively associated with hospital vertical integration into SAC. Measures of munificence, percentage of the county population eligible for Medicare (ME = 0.018, p < .001) and rural geographic location (ME = 0.069, p < .001), were positively associated with hospital vertical integration into SAC. Dynamism, when measured as the change county population between 2008 and 2011 (ME = 1.19e−06, p < .001), was positively associated with hospital vertical integration into SAC. Organizational resources, when measured as swing beds (ME = 0.069, p < .001), were positively associated with hospital vertical integration into SAC. Organizational resources, when measured as investor owned (ME = −0.052, p < .1) and system affiliation (ME = −0.041, p < .1), were negatively associated with hospital vertical integration into SAC. PRACTICE IMPLICATIONS: Hospital adaption to the changing health care landscape through vertical integration varies across market and organizational conditions. Current Centers for Medicare and Medicaid reimbursement programs do not take these factors into consideration. Vertical integration strategy into SAC may be more appropriate under certain market conditions. Hospital leaders may consider how to best align their organization’s SAC strategy with their operating environment.

Introduction Social determinants of health are critical drivers of health status and cost, but are infrequently screened or addressed in primary care settings. Systematic approaches to identifying individuals with unmet social determinants needs could better support practice workflows and linkages of patients to services. A pilot study examined the effect of a risk-stratification tool on referrals to services that address social determinants in an urban safety-net population. Methods An intervention that risk stratified patients according to the need for wraparound was evaluated in a stepped wedge design (i.e., phased implementation at the clinic level during 2017). Staff at nine federally qualified health centers received a daily report predicting patients’ needs for social worker, dietitian, behavioral health, and other wraparound services (categorized as low, rising, or high risk). Outcomes included referrals and uptake of appointments to wraparound services. Results Among 238,087 encounters, providing clinic staff with risk-stratification scores increased the odds that a patient would be referred to a social worker. For patients categorized as high risk, the odds of a social work referral was 65% higher than controls and similar patients, but lower effect sizes were observed for individuals categorized with rising and low risk. Among referred patients, the intervention was generally associated with increased odds of kept appointments. Conclusions This study provided preliminary evidence that risk-stratification interventions to identify patients in need of wraparound services to address social determinants can increase referrals and uptake of services that may address social drivers of disease burden.

Significance Infection with the novel coronovirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a worldwide pandemic of COVID-19 disease. Efforts to design local, regional, and national responses to the virus are constrained by a lack of information on the extent of the epidemic as well as inaccuracies in newly developed diagnostic tests. In this study we analyze data from testing randomly selected Indiana state residents for infection or previous exposure to SARS-CoV-2 and derive estimates of the statewide COVID-19 prevalence in an attempt to address potential biases arising from nonresponse and diagnostic testing errors., 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. This paper describes statistical methods used to address nonresponse among various demographic groups and to adjust for testing errors to reduce bias in the estimates of the overall disease prevalence in Indiana. These adjustments were implemented through Bayesian methods, which incorporated all available information on disease prevalence and test performance, along with external data obtained from census of the Indiana statewide population. Both adjustments appeared to have significant impact on the unadjusted estimates, mainly due to upweighting data in study participants of non-White races and Hispanic ethnicity and anticipated false-positive and false-negative test results among both the PCR and antibody tests utilized in the study.

BackgroundPrior 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.MethodsWe pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide seroprevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection.ResultsAmong 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV ConclusionsSymptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.Research in ContextEvidence before this studyUsing multiple journal articles queried from MEDLINE as well as a Cochrane systematic review, we examined all studies that described symptoms known to be associated with COVID-19. We further examined the guidelines from WHO and CDC on the symptoms those public health authorities consider to be associated with COVID-19. Most of the evidence comes from China, Italy, and the United States. Collectively prior research and guidance suggests there are a dozen symptoms reported by individuals who tested positive for COVID-19 in multiple countries. Symptoms include fever, cough, fatigue, anosmia, ageusia, shortness of breath, chills, myalgias, headache, sore throat, chest pain, and gastrointestinal issues. The evidence is generally of low quality as it is descriptive in nature, and it is biased towards hospitalized patients. Most studies report the proportion of patients hospitalized or testing positive for infection who report one or more symptoms within 3-14 days prior to hospitalization or infection. There has been little validation of symptoms among hospitalized or non-hospitalized patients. Furthermore, according to a Cochrane review, no studies to date assess combinations of different signs and symptoms.Added value of this studyThis study employs multiple, rigorous methods to examine the ability of specific symptoms as well as symptom combinations/groups to predict laboratory-confirmed (RT-PCR) infection of SARS-CoV-2. Furthermore, the study is unique in its large sample drawn exclusively from community-based populations rather than hospitalized patients.Implication of all the available evidenceCombining the evidence from this study with prior research suggests that anosmia and ageusia are key symptoms that differentiate COVID-19 from influenza-like symptoms. Clinical screening protocols for COVID-19 should look for these symptoms, which are not commonly asked of patients who present to urgent care or hospital with flu-like symptoms.Key pointsImportant symptoms specific to COVID-19 are fever, anosmia, ageusia, and cough. Two-thirds of symptoms were highly specific (>90.0%), yet most symptoms individually possessed a PPV

Objectives To assess whether using coronavirus disease 2019 (COVID-19) community activity level can accurately inform strategies for routine testing of facility staff for active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design Cross-sectional study. Setting and Participants In total, 59,930 nursing home staff tested for active SARS-CoV-2 infection in Indiana. Measures Receiver operator characteristic curves and the area under the curve to compare the sensitivity and specificity of identifying positive cases of staff within facilities based on community COVID-19 activity level including county positivity rate and county cases per 10,000. Results The detection of any infected staff within a facility using county cases per 10,000 population or county positivity rate resulted in an area under the curve of 0.648 (95% confidence interval 0.601‒0.696) and 0.649 (95% confidence interval 0.601‒0.696), respectively. Of staff tested, 28.0% were certified nursing assistants, yet accounted for 36.9% of all staff testing positive. Similarly, licensed practical nurses were 1.4% of staff, but 4.7% of positive cases. Conclusions and Implications We failed to observe a meaningful threshold of community COVID-19 activity for the purpose of predicting nursing homes with any positive staff. Guidance issued by the Centers for Medicare and Medicaid Services in August 2020 sets the minimum frequency of routine testing for nursing home staff based on county positivity rates. Using the recommended 5% county positivity rate to require weekly testing may miss asymptomatic infections among nursing home staff. Further data on results of all-staff testing efforts, particularly with the implementation of new widespread strategies such as point-of-care testing, is needed to guide policy to protect high-risk nursing home residents and staff. If the goal is to identify all asymptomatic SARS-Cov-2 infected nursing home staff, comprehensive repeat testing may be needed regardless of community level activity.

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 tobacco use 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= 8,214) underwent SARS-CoV-2 testing in nonclinical settings. Each participant was tested for current (viral PCR) and past (antibody) infection in April or June of 2020. Before testing, participants provided demographic information and self-reported health status and tobacco behaviors (smoking, chewing, vaping/e-cigarettes). Using descriptive statistics and a bivariate logistic regression model, we examined the association between health status and use of tobacco with SARS-CoV-2 positivity on either PCR or antibody tests.Results Compared to people with self-identified “excellent” or very good health status, those reporting “good” or “fair” health status had a higher risk of past or current infections. Positive smoking status was inversely associated with SARS-CoV-2 infection. Chewing tobacco was associated with infection and the use of vaping/e-cigarettes was not associated with infection. Conclusions In a statewide, community-based population drawn for seroprevalence studies, we find that overall health status is associated with infection rates. Unlike in studies of COVID-19 patients, smoking status was inversely associated with SARS-CoV-2 positivity. More research is needed to further understand the nature of this relationship.

EXECUTIVE SUMMARY Recent data suggest that a majority of hospitals now engage in some form of Lean process improvement in an attempt to reduce costs and/or improve quality. The literature on Lean healthcare has evolved from describing theoretical benefits, implementation barriers, and best practices to studies describing where implementations have occurred and their outcomes. Nevertheless, previous studies are mostly limited to case studies in which Lean was implemented on a limited basis in a healthcare facility. In this article, we present lessons learned from the largest implementation of Lean in a single healthcare system composed of 16 hospitals, a health plan, and many outpatient clinics. Our analysis of 1,144 rapid improvement events (RIEs) over a 5-year period revealed that 45% were associated with some organizational benefit in several categories, including cost reductions, time savings, a reduction in clinical and nonclinical defects, and a reduction in workflow steps. As the organization became more experienced with RIEs, the benefits realized changed from mostly cost reductions to a more diverse mix of benefits, with time savings becoming the most common. RIEs implemented in certain settings and/or by certain types of employees were associated with the likelihood of realizing a benefit. Based on these analyses, we provide recommendations to hospital and health system leaders interested in optimizing their Lean implementations-especially on a large enterprise-wide scale.

BACKGROUND Hospice performance is an overlooked area in the health care field due to the difficulty of measuring quality of care and the infrequent quality inspection. Based on the daily reimbursement mechanism for different levels of hospice care, inpatient services provision could influence both hospice-level length of stay (LOS) and financial performance. PURPOSE The objective of this study was to explore the relationship between hospice inpatient services provision and hospice utilization and financial performance. METHODOLOGY/APPROACH A longitudinal secondary data set (2009-2013) was merged from three sources: (a) Hospice Cost Reports from the Centers for Medicare & Medicaid Services, (b) the Provider of Services files, and (c) the Area Health Resources Files. The dependent variable in this study was hospice average LOS and financial performance measured by total operating margin (TOM) and return on assets. The independent variable was hospice inpatient services' offering. Mixed-effects regression models were used in the multivariate regression analyses. RESULTS When comparing to hospices not providing inpatient services, offering inpatient services by staff was negatively related to average LOS (b = -0.063, p < .05) and TOM (b = -0.022, p < .05). The combination method with providing inpatient services by staff and under arrangement was negatively associated with return on assets (b = -0.073, p < .05). CONCLUSION Hospice inpatient services provision was associated with average LOS and financial performance. PRACTICE IMPLICATIONS Offering the inpatient services to patients by staff decreased average LOS and TOM. Hospice agencies may seek strategies to maintain their financial sustainability through outsourcing.

Timely access to Medicaid coverage offers many potential benefits to justice-involved adults reentering the community. In 2015 Indiana's Section 1115 Medicaid waiver (the Healthy Indiana Plan [HIP]) expanded eligibility for low-income adults. To expedite coverage for justice-involved adults, Indiana subsequently improved interagency coordination in two ways. First, the Indiana Department of Correction began initiating Medicaid applications for those in custody. Second, Medicaid began temporarily suspending coverage for people while they were incarcerated instead of discontinuing it. Prison release data from the Indiana Department of Correction linked to Medicaid enrollment data indicate that before HIP was implemented, approximately 9 percent of justice-involved adults received Medicaid coverage within 120 days of release. After HIP implementation, coverage rates increased by 9 percentage points. After both interagency coordination policies were implemented, an additional 29-percentage-point increase in coverage occurred. Furthermore, coverage effective within seven days of release increased by 14 percentage points after the interagency coordination policies went into effect. These findings support the notion that policies and procedures encouraging interagency coordination are beneficial in increasing timely access to Medicaid coverage for justice-involved people.

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. Objective The objective of this study was to leverage a comprehensive range of clinical, behavioral, social risk, and social determinants of health factors in order to develop decision models capable of identifying patients in need of various wraparound social services. Methods We used comprehensive patient- and population-level data sets to build decision models capable of predicting need for behavioral health, dietitian, social work, or other social service referrals within a safety-net health system using area under the receiver operating characteristic curve (AUROC), sensitivity, precision, F1 score, and specificity. We also evaluated the value of population-level social determinants of health data sets in improving machine learning performance of the models. Results Decision models for each wraparound service demonstrated performance measures ranging between 59.2%% and 99.3%. These results were statistically superior to the performance measures demonstrated by our previous models which used a limited data set and whose performance measures ranged from 38.2% to 88.3% (behavioural health: F1 score P Conclusions Precision health–enabled decision models that leverage a wide range of patient- and population-level data sets and advanced machine learning methods are capable of predicting need for various wraparound social services with good performance.

Workplace incivility is low-intensity, nonspecific, discourteous behavior towards others and may negatively affect employee and organizational outcomes. This exploratory study sought to examine the prevalence of and factors related to experiencing several different types of workplace incivility using a national sample of Health Administration full-time faculty members in the United States. We found that 27–36% of respondents have experienced at least one type of uncivil behavior from students, coworkers, or supervisors. Further, 4–9% of faculty respondents experience such incidents frequently. Faculty respondents who experienced workplace incivility were significantly more likely to report lower job satisfaction and indicated an intention to leave their position within the next three years. Academic leaders should work to foster an environment where incivility towards others is actively discouraged, as it may contribute to dissatisfaction and turnover.

Objective Biomedical informatics attracts few underrepresented racial minorities (URMs) into PhD programs. We examine graduation trends from 2002 to 2017 to determine how URM representation has changed over time. We also examine academic job placements by race and identify individual and institutional characteristics associated with URM graduates being successfully placed in academic jobs. Materials and Methods We analyze a near census of all research doctoral graduates from US-accredited institutions, surveyed at graduation by the National Science Foundation Survey of Earned Doctorates. Graduates of biomedical informatics-related programs were identified using self-reported primary and secondary disciplines. Data are analyzed using bivariate and multivariable logistic regressions. Results During the study period, 2426 individuals earned doctoral degrees in biomedical informatics-related disciplines. URM students comprised nearly 12% of graduates, and this proportion did not change over time (2002–2017). URMs included Hispanic (5.7%), Black (3.2%), and others, including multi-racial and indigenous American populations (2.8%). Overall, 82.3% of all graduates accepted academic positions at the time of graduation with significantly more Hispanic graduates electing to go into academia (89.2%; P Discussion and Conclusion The proportion of URM candidates among biomedical informatics doctoral graduates has not increased over time and remains low. In order to improve URM recruitment and retention within academia, leaders in biomedical informatics should replicate strategies used to improve URM graduation rates in other fields.

Objective The Mental Health Parity and Addiction Equity Act (MHPAEA) of 2008 mandates equivalent insurance coverage for mental health (MH) and substance use disorders (SUD) to other medical and surgical services covered by group insurance plans, Medicaid, and Children's Health Insurance Programs (CHIP). We explored the impact of MHPAEA on enrollees in ALL Kids, the Alabama CHIP. Methods We use ALL Kids claims data for October 2008 to December 2014. October 2008 through September 2009 marks the period before MHPAEA implementation. We evaluated changes in MH/SUD-related utilization and program costs and changes in racial/ethnic disparities in the use of MH/SUD services for ALL Kids enrollees using 2-part models. This allowed analyses of changes from no use to any use, as well as in intensity of use. Results No significant effect was found on overall MH service-use. There were statistically significant increases in inpatient visits and length of stay and some increase in overall MH costs. These increases may not be clinically important and were concentrated in 2009 to 2011. Disparities in utilization between African-American and non-Hispanic white enrollees were somewhat exacerbated, whereas disparities between other minorities and non-Hispanic whites were reduced. Conclusions Findings indicate that MHPAEA led to a 14.3% increase in inpatient visits, a 12.5% increase in length of inpatient stay, and a 7.8% increase in MH costs. The increases appear limited to 2009 to 2011, suggesting existing pent-up "needs" among enrollees for added MH/SUD services that resulted in a temporary spike in service use and cost immediately after MHPAEA, which subsequently subsided.

Given low rates of uptake of the COVID-19 vaccine for children 12-17 and 5-11 years old, research is needed to understand parental behaviors and behavioral intentions related to COVID-19 vaccination for their children. In the state of Indiana, we conducted a non-random, online survey of parents or caregivers (N = 10,266) about their COVID-19 vaccine intentions or behaviors, demographic characteristics, and potential motivating reasons for getting the vaccine. In terms of behaviors/intentions, 44.8% of participants indicated they were vaccine acceptors (i.e., had already had their children vaccinated or would as soon as it was possible), 13.0% indicated they were vaccine hesitators (i.e., wanted to wait and see), and 42.2% indicated they were vaccine rejecters (i.e., would not vaccinate or only would if mandated). Compared to vaccine rejecters, vaccine hesitators were more likely to be motivated by perceptions of vaccine safety and efficacy, normative influences such as close friends/family who had been vaccinated and a recommendation from a provider, as well as if they were vaccinated themselves. These findings have implications for the development of targeted vaccine promotion strategies, such as social norms messaging and a focus on vaccine safety, in order to increase COVID-19 vaccination for eligible children.

Due to the ongoing opioid use disorder crisis, improved access to opioid treatment programs (OTPs) is needed. However, OTPs operate in a complex regulatory environment which may limit their ability to positively affect health outcomes. The objective of this study was to examine how the number and type of state OTP regulations are associated with opioid-related deaths, hospitalizations, and emergency department visits.Cross-sectional data capturing information about OTP state-level regulations collected by Jackson et al. was combined with other secondary sources. OTP regulations were categorized based on the nature of their focus. Analyses include bivariate and multivariable regressions that controlled for region and other state laws that can affect opioid outcomes.In bivariate analysis, a greater number of OTP regulations was positively correlated with both deaths and emergency visits. Moreover, a greater number of regulations in the Physical Facilities Management category (e.g., rules related to restrooms, lighting, and signage) was positively correlated with both deaths and hospitalizations. The number of regulations in the Staffing Requirement category was positively associated with emergency visits. In adjusted analysis, the number of regulations in the Physical Facilities Management category was positively associated with opioid-related deaths.States with a higher number of regulations had poorer opioid-related outcomes. Additional research is needed to support policy decisions that can improve access to OTPs and reduce avoidable deaths, hospitalizations, and emergency visits.

This paper presents longitudinal data representing federal funding for health services research and discusses the observed trends in the larger context of overall funding for research and development in the United States. By putting into context public and private funding trends, the authors examine how these trends effect the supply and demand of the health services research workforce.

In 2016, AcademyHealth continued its longstanding efforts to understand the health services research (HSR) workforce, to inform its changing needs through the commissioning of several papers and an invitational conference. This paper serves to summarize the commissioned studies that appear in the current issue of this journal.

The demand for Long-Term Care (LTC) is steadily increasing as Baby Boomers age and enter retirement. High turnover rates among employees in LTC creates challenges for supervisors and administrators, and can negatively impact quality of care. This study examines manager-subordinate relationship quality using Leader-Member Exchange Theory (LMX) as an antecedent to turnover among low-wage earners in the LTC environment. Survey data measuring LMX, job satisfaction, and demographic information was collected at time 1, and turnover data was collected 18 months later at time 2. The results reveal that all four LMX dimensions were rated significantly different among subordinates who left versus those who stayed, however, only the LMX dimension of supervisor loyalty was a significant predictor of turnover among low wage earners. Our study adds a more nuanced view of the reasons low-wage employees turnover, and presents implications for clinical managers and LTC organizations more broadly.

Expanding eligibility for Medicaid was a central goal of the Affordable Care Act (ACA), which continues to be debated and discussed at the state and federal levels as further reforms are considered. In an effort to provide a synthesis of the available research, we systematically reviewed the peer-reviewed scientific literature on the effects of Medicaid expansion on the original goals of the ACA. After analyzing seventy-seven published studies, we found that expansion was associated with increases in coverage, service use, quality of care, and Medicaid spending. Furthermore, very few studies reported that Medicaid expansion was associated with negative consequences, such as increased wait times for appointments-and those studies tended to use study designs not suited for determining cause and effect. Thus, there is evidence to document improvements in several areas of health care delivery following the ACA Medicaid expansion. We outline areas for future research that can further reduce current knowledge gaps.

Background Increasingly, health care providers need to exchange information to meet policy expectations and business needs. A variety of health information organizations (HIOs) provide services to facilitate health information exchange (HIE). However, the future of these organizations is unclear. Purpose The aim of this study was to explore the environmental context, potential futures, and survivability of community HIOs, enterprise HIEs, and electronic health record vendor-mediated exchange using the population ecology theory. Approach Qualitative interviews with 33 key informants representing each type of HIE organization were analyzed using template analysis. Results Community HIOs, enterprise HIEs, and electronic health record vendors exhibited a high degree of competition for resources, especially in the area of exchange infrastructure services. Competition resulted in closures in some areas. In response to environmental pressures, each organizational type was endeavoring to differentiate its services and unique use case, as well as pursing symbiotic relationships or attempting resource partitioning. Conclusion HIOs compete for similar resources and are reacting to environmental pressures to better position themselves for continued survival and success. Our ecological research perspective helps move the discourse away from situation of a single exchange organization type toward a view of the broader dynamics and relationships of all organizations involved in facilitating HIE activities. Practice implications HIOs are attempting to partition the environment and differentiate services. HIE options should not be construed as an "either/or" decision, but one where multiple and complementary participation may be required.

EXECUTIVE SUMMARY Because Medicare reimbursements are now, in part, based on patient satisfaction scores, hospitals are increasingly concerned about improving patient satisfaction. However, little is known about the different characteristics that are associated with higher patient satisfaction. This study was conducted to systematically review the patient satisfaction literature and to identify predictors of patient satisfaction based on measures from the HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey. We searched the PubMed and Scopus databases from January 2007 to February 2015 for relevant peer-reviewed studies. A total of 41 studies met our inclusion criteria and were categorized into three groups (levels) based on the types of predictors used in the study: patient (12 articles, 29.9%), hospital (29 articles, 70.1%), or market (4 articles, 9.7%) predictors. We present a narrative review of the included studies in which certain patient- and hospital-level predictors were consistently associated with higher patient satisfaction (e.g., patient perception of well-managed pain and not-for-profit status) or lower patient satisfaction (e.g., racial/ethnic minority, hospital's safety net status, metropolitan area). Moreover, several predictors had mixed relationships with patient satisfaction across studies (e.g., teaching status, number of beds). Finally, we found that only a small number of studies have examined the association between market-level predictors and patient satisfaction.

The Internal Revenue Service (IRS) recently introduced tax code revisions requiring stricter oversight of community benefit activities (CBAs) conducted by tax-exempt, not-for-profit hospitals. We examine the impact of this tax requirement on CBAs among these hospitals relative to for-profit and government hospitals that were not subject to the new policy. We employed a quasi-experimental, difference-in-difference study design using a longitudinal observational approach and used secondary data collected by the American Hospital Association (years 2006-2010 including 20,538 hospital year observations). Findings show a significant increase in the reporting of 7 of the 13 CBAs among tax-exempt, not-for-profit hospitals compared with other hospitals after the policy change. Examples include partnering to conduct community health assessments ( b = 0.035, p = .002) and using capacity assessments to identify unmet community health needs ( b = 0.041, p = .001). Recent tax revisions are associated with increases in reported CBAs among tax-exempt, not-for-profit hospitals. As the debate continues regarding tax exemption status for not-for-profit hospitals, policy makers should expand efforts for enhanced accountability.