Abstract The Patient-Driven Payment Model (PDPM) launched on October 1, 2019, restructured Medicare payments to reflect resident needs over service quantity, aiming to improve quality and efficiency in nursing homes (NH). PDPM’s shift towards resident needs (rather than therapy minutes) may lead to greater nurse utilization, which may potentially improve the quality of care. This study draws on the resource-based view (RBV) theory to understand the association between the PDPM and NH quality of care mediated by nurse staffing intensity. Utilizing a longitudinal design (2017-2021), seven different datasets were merged (Cost reports, Payroll Base Journal (PBJ), Care Compare, Area Health Resource File (AHRF), HHS Provider Relief Fund, CDC NH COVID-19 public files, and CDC COVID-19 Data Tracker). Structural equation modeling (SEM) was used to assess the direct and indirect effects of PDPM on care quality, with nursing staffing intensity serving as a mediator. NH quality of care was operationalized using quality-measure five-star rating and staffing intensity by RN, LPN, and CNA hours per resident. We examined the direct effect of PDPM on quality of care and the indirect effect of PDPM on quality through nurse staffing. Control variables included organizational and market-level factors, and COVID-19-related variables. The result suggests an increase in RN staffing post-PDPM but a decrease in CNA hours (p< 0.001). PDPM had an indirect positive effect on quality through RNs while negative through CNAs. PDPM also showed a positive direct effect on quality. Policy implication highlights the complex interplay between different staffing roles and the impact on quality.

Background: Over 45% of people with HIV (PWH) in the United States at least 50 years old and are at heightened risk of aging-related comorbidities including end-stage kidney disease (ESKD), for which kidney transplant is the optimal treatment. Among ESKD patients, PWH have lower likelihood of waitlisting, a requisite step in the transplant process, than individuals without HIV. It is unknown what proportion of the inequity by HIV status can be explained by demographics, medical characteristics, substance use history, and geography. Methods: The United States Renal Data System, a national database of all individuals ESKD, was used to create a cohort of people with and without HIV through Medicare claims linkage (2007–2017). The primary outcome was waitlisting. Inverse odds ratio weighting was conducted to assess what proportion of the disparity by HIV status could be explained by individual characteristics. Results: Six thousand two hundred and fifty PWH were significantly younger at ESKD diagnosis and more commonly Black with fewer comorbidities. PWH were more frequently characterized as using tobacco, alcohol and drugs. Positive HIV-status was associated with 57% lower likelihood of waitlisting [adjusted hazard ratio (aHR): 0.43, 95% confidence interval (CI): 0.46–0.48, P < 0.001]. Controlling for demographics, medical characteristics, substance use and geography explained 39.8% of this observed disparity (aHR: 0.69, 95% CI: 0.59–0.79, P < 0.001). Conclusion: PWH were significantly less likely to be waitlisted, and 60.2% of that disparity remained unexplained. HIV characteristics such as CD4 + counts, viral loads, antiretroviral therapy adherence, as well as patient preferences and provider decision-making warrant further study.

School readiness is a topic of great interest to early childhood and maternal child health initiatives, such as the Maternal, Infant, and Early Childhood Home Visiting (MIECHV) programme. However, there is a lack of information about best practices or strategies in home visiting and their relative effectiveness in improving school readiness, making this topic appropriate for improvement through Continuous Quality Improvement (CQI) methods. In 2022, Alabama developed a Key Driver Diagram (KDD) for improving school readiness efforts within the home visiting programme using synchronous online focus groups as a method of qualitative data collection with early childhood and home visiting experts. Findings from this study include development of a KDD that includes aims, key drivers, and secondary drivers. The KDD represents the first of many steps toward a unified theory of change. Future efforts will include development of a CQI change package and testing change ideas in the field.

Objectives: The US government implemented the Hospital Readmission Reduction Program on 1 October 2012 to reduce readmission rates through financial penalties to hospitals with excessive readmissions. We conducted a pooled cross-sectional analysis of US hospitals from 2009 to 2015 to determine the association of the Hospital Readmission Reduction Program with 30-day readmissions. Methods: We utilized multivariable linear regression with year and state fixed effects. The model was adjusted for hospital and market characteristics lagged by 1 year. Interaction effects of hospital and market characteristics with the Hospital Readmission Reduction Program indicator variable was also included to assess whether associations of Hospital Readmission Reduction Program with 30-day readmissions differed by these characteristics. Results: In multivariable adjusted analysis, the main effect of the Hospital Readmission Reduction Program was a 3.80 percentage point ( p < 0.001) decrease in readmission rates in 2013–2015 relative to 2009–2012. Hospitals with lower readmission rates overall included not-for-profit and government hospitals, medium and large hospitals, those in markets with a larger percentage of Hispanic residents, and population 65 years and older. Higher hospital readmission rates were observed among those with higher licensed practical nurse staffing ratio, larger Medicare and Medicaid share, and less competition. Statistically significant interaction effects between hospital/market characteristics and the Hospital Readmission Reduction Program on the outcome of 30-day readmission rates were present. Teaching hospitals, rural hospitals, and hospitals in markets with a higher percentage of residents who were Black experienced larger decreases in readmission rates. Hospitals with larger registered nurse staffing ratios and in markets with higher uninsured rate and percentage of residents with a high school education or greater experienced smaller decreases in readmission rates. Conclusion: Findings of the current study support the effectiveness of the Hospital Readmission Reduction Program but also point to the need to consider the ability of hospitals to respond to penalties and incentives based on their characteristics during policy development.

Background: Medicare and Medicaid payments significantly influence nursing homes' financial health, affecting their overall revenue. The introduction of the Patient-Driven Payment Model (PDPM) in 2019 may incentivize nursing homes to adapt strategically. This study, rooted in contingency theory, examines how staffing changes, particularly in nursing and therapy, affect nursing homes' financial performance post-PDPM. Methods: The study utilized secondary data from various sources, including Centers for Medicare and Medicaid Services (CMS) Medicare cost reports, Brown University's Long Term Care Focus (LTCFocus), distribution data, and CDC's nursing home (NH) coronavirus disease 2019 (COVID-19) public file. Financial performance, operationalized by operating margin, is the dependent variable, while the independent variable, PDPM is operationalized as pre-PDPM [2018] and post-PDPM [2020-2022]. Staffing intensity, measured by reported therapy and clinical staffing hours per resident per day, serves as the moderator. Organizational, market-level, COVID-19, and year fixed effects variables are used as controls. We modeled the data using facility fixed effect regression. Results: Our study results indicate that an increase of one hour registered nurse (RN) per resident day, licensed practical nurse (LPN) per resident day, and certified nursing assistant (CNA) per resident day postPDPM is associated with an RN -0.04%, LPN -0.03% and CNA -0.01% decrease in operating margin (P<0.001). High Medicare facilities experienced a higher increase in operating margin by 2.1% compared to a decline in low Medicare facilities by -0.90%. Conclusions: The findings highlight the complex interplay between staffing patterns, PDPM, and financial performance in nursing homes.

OBJECTIVES This study measured the extent to which the COVID-19 pandemic disrupted follow-up care for children and adolescents with acute mental health hospitalizations and the use of telehealth to offset barriers to in-person follow-up care. METHODS The study used statewide claims data from Alabama’s Children’s Health Insurance Program, ALL Kids, from 2017 to 2022. Logit regressions measured associations between receipt of follow-up care within 30 days of acute mental health hospitalization and patient characteristics, timing of the COVID-19 pandemic, and receipt of care via telehealth. Interaction terms and likelihood ratio tests measured whether patient characteristics were associated with follow-up over time. RESULTS Of 1698 mental health hospitalizations, 1323 (77.9%) received follow-up care from a mental health provider within 30 days, with no statistically meaningful difference before (78.3%) vs after (77.4%) the COVID-19 pandemic. Lower rates of timely follow-up were observed for children in age groups 10 years and older, those with diagnoses for behavioral disorders and suicidal ideation/intentional self-harm relative to mood disorders, and racial/ethnic groups other than non-Hispanic white. Approximately 23% of follow-up was via telehealth. We observed no statistically meaningful changes in associations between patient characteristics and follow-up during the COVID-19 pandemic. CONCLUSIONS Follow-up after a mental health hospitalization, an important quality measure for mental health care, was unchanged during the COVID-19 pandemic. Telehealth was not used prior to the COVID-19 pandemic but may have helped maintain follow-up care rates. Disparities in receipt of follow-up care were observed prior to the COVID-19 pandemic and persisted despite telehealth options.

Nursing homes expressed concern about potential severe adverse financial outcomes of COVID-19, with worries extending to the possibility of some facilities facing closure. Maintaining a strong financial well-being is crucial, and there were concerns that the pandemic might have significantly impacted both expenses and income. This longitudinal study aimed to analyze the financial performance of nursing homes during COVID-19 pandemic. Specifically, we examined the impact of the pandemic on nursing home operating margins, operating revenue per resident day, and operating cost per resident day. The study utilized secondary data from various sources, including CMS Medicare cost reports, Brown University’s Long Term Care Focus (LTCFocus), CMS Payroll-Based Journal, CMS Care Compare, Area Health Resource File, Provider Relief Fund distribution data, and CDC’s NH COVID-19 public file. The sample consisted of 45 833 nursing home-year observations from 2018 to 2021. Fixed-effects regression analysis was employed to assess the impact of the pandemic on financial performance while controlling for various organizational and market characteristics. The study found that nursing homes’ financial performance deteriorated during the COVID-19 pandemic. Operating margins decreased by approximately 4.3%, while operating costs per resident day increased by $26.51, outweighing the increase in operating revenue per resident day by about $17. Occupancy rates, payer mix, and staffing intensity were found to impact financial performance. The study highlights the significant financial impact of the COVID-19 pandemic on nursing homes. While nursing homes faced substantial financial strains, the findings offered lessons for the future, underscoring the need for nursing homes to improve the accuracy of their cost reports and enhance financial transparency and accountability.

Abstract To promote more value in skilled nursing facility spending in the US, CMS modified the way it pays for nursing homes (NH) services on October 1, 2019. The new Medicare reimbursement methodology, the Patient Driven Payment Model (PDPM), moves away from the traditional system focused on therapist minutes to a value-based focused on resident clinical characteristics. Using contingency theory, this study explores NH responses to PDPM by: 1) examining whether NH’s therapist and nursing staffing patterns are aligning with the policy incentives; and 2) whether the adjustments are resulting in improved financial performance. Seven different datasets were merged for 2017– 2021: Medicare cost reports, Payroll Based Journal, NH Compare, Area Health Resource File, HHS Provider Relief Fund, CDC NH COVID-19 public file, and CDC COVID-19 Data Tracker. The data was modelled using random-effects regression, and we tested for potential moderation effect of staffing on the relationship between PDPM and financial performance. Dependent variables were nursing and therapy staffing intensity, while the independent variable was PDPM for model 1. Dependent variable was operating margin, moderator variable was staffing intensity, and independent variable was PDPM for model 2. Organizational, community level, and COVID-19 related variables were used as controls. Results suggest that PDPM was associated with an increase in RN and LPN staffing intensity, but a decrease in Physical Therapist, Physical Therapist Assistant, and Occupational Therapist Assistant staffing intensity (p< 0.05). PDPM had a positive impact on financial performance moderated by RN and PT staffing intensity (p< 0.05). Policy and managerial implications are discussed.

During the early days and months of the COVID-19 pandemic, healthcare facilities experienced a slump in non-COVID-related visits, and there was an increasing interest in telehealth to deliver healthcare services for adult and pediatric patients. The study investigated telehealth use variation by race/ethnicity and place of residence for the pediatric enrollees of the Alabama Medicaid program. This retrospective observational study examined Alabama Medicaid claims data from March to December 2020 for enrollees less than 19 years. There were 637,792 pediatric enrollees in the Alabama Medicaid program during the study period, and 16.9% of them had used telehealth to meet healthcare needs. This study employed a multivariate Poisson mixed-effects model with robust error variance to obtain differences in telehealth utilization and found that Non-Hispanic Black children were 80% as likely, Hispanic children were 55% as likely, and Asian Children were 46% as likely to have used telehealth compared to Non-Hispanic White children. Pediatric enrollees in large rural areas and isolated areas were significantly less likely (IRR: 0.90 for both, p<0.05) to use telehealth than those in urban areas. This study's findings suggest that attention needs to be paid to addressing race/ethnicity disparities in accessing telehealth services.

OBJECTIVES: Injuries are the leading cause of death among children and youth in the United States, representing a major concern to society and to the public and private health plans covering pediatric patients. Data from ALL Kids, Alabama's Children's Health Insurance Program, were used to evaluate the relationship between community-level social determinants of health (SDOH) and pediatric emergency department (ED) use and differences in these associations by age and race. STUDY DESIGN: This was a retrospective, pooled cross-sectional analysis.METHODS: We used ALL Kids data to identify ED visits (injury and all-cause) among children who were enrolled at any time from 2015 to 2017. Exploratory factor analysis was used to categorize SDOH from 18 selected Census tract- level variables. Multilevel Poisson regression models were used to evaluate the effects of community and individual factors and their interactions.RESULTS: Census tract-level SDOH were grouped as low socioeconomic status (SES), urbanicity, and immigrant-density factors. Low SES and urbanicity factors were associated with ED visits (injury and all-cause). The low SES and urbanicity factors also moderated the association between race and ED visits (injury and all-cause).CONCLUSIONS: The environment in which children live influences their ED use; however, the impact varies by age, race, and Census tract factors. Further studies should focus on specific community factors to better understand the relationship among SDOH, individual characteristics, and ED utilization.

Abstract Financial stability and well-being are critical for the success of any organization. COVID-19 put nursing homes (NH) in a financial bind, affecting their costs and revenues and mounting pressure on them despite government intervention. NHs have been one of the weak links in our care continuum for the U.S. healthcare system, and the pandemic caused havoc in the industry. Given the pandemic impact on NH operating cost and revenue, this study examined the level to which financial performance in NHs deteriorated. Six different datasets were merged for 2018–2021: Medicare cost reports, Payroll-Based Journal, NH Compare, Area Health Resource File, HHS Provider Relief Fund, and CDC COVID-19 Data Tracker. The data was modeled using random-effects regression. Dependent variables were operating revenue per patient day, operating cost per patient day, and operating margin. Independent variable was pre- and post-COVID-19. Organizational, community-level, and COVID-19-related variables were used as controls. Results suggest that the impact of COVID-19 was associated with an increase in operating cost per patient day (β=56.64, p< 0.05), and a decrease in operating margin (β=-8.04, p< 0.05), but the associated operating revenue per patient day (β=26.78, p< 0.05), did not increase at the rate at which the operating cost increased. The increase in operating cost per patient day compared to the operating revenue per patient day was double. Given the negative impact of the COVID-19 pandemic on NH’s financial performance, policymakers should monitor the financial health of NH. Further deterioration in financial performance may result in NH closures and reduced access to long-term care.

The Advisory Committee on Blood and Tissue Safety and Availability recently voted to remove the statutory National Institutes of Health research criteria and institutional review board requirements for performing kidney transplantation using kidneys from donors with HIV. This policy change may subsequently increase utilization of such organs.1 Despite excellent kidney transplant outcomes, single-center studies have demonstrated significantly lower kidney transplant waitlist addition rates for people with HIV (PWH) in the United States as compared with those without HIV, a requisite step for deceased donor kidney transplantation.2-4 Should adoption of transplantation using kidneys from donors with HIV increase following the implementation of this policy, understanding waitlist addition nationally is imperative. Acknowledging the lack of granularity in HIV-specific data, we used the United States Renal Data System and accompanying Medicare claims data to identify a cohort of PWH (January 1, 2007–December 31, 2016) with end-stage kidney disease (ESKD) and compared waitlist addition rates among PWH with ESKD patients without HIV. This study was approved by the Institutional Review Board at the University of Alabama at Birmingham. Among 602 006 incident patients whose primary payer was Medicare,5 HIV status was defined using the Chronic Conditions Data Warehouse algorithm (sensitivity: 93.2%; specificity: 99.4%). PWH with claims for an opportunistic infection within 90 d of dialysis initiation were excluded. Cox proportional hazards and Fine and Gray competing risks regressions were used to examine the likelihood of waitlist addition. The 6250 PWH were younger, more commonly African American, and more commonly reported alcohol dependence, drug dependence, and tobacco use. Cumulative incidence of waitlist addition within 5 y of dialysis initiation was 11.1% among PWH and 15.3% among ESKD patients without HIV. Following adjustment for demographics, comorbid conditions, and geography, HIV was associated with 52% lower likelihood of waitlist addition (adjusted hazard ratio: 0.48; 95% confidence interval, 0.43-0.52; P < 0.001; Table 1). After accounting for competing risks of death and living donor kidney transplantation before waitlist addition, a similar inequity was observed (adjusted subdistribution hazard ratio: 0.45; 95% confidence interval, 0.42-0.49; P < 0.001). TABLE 1. - Unadjusted and adjusted likelihood of waitlist addition among ESKD patients within 5 y and within all observed time following dialysis initiation 5 y, HR (95% CI) a Full follow-up, HR (95% CI) a Unadjusted PWH (ref: HIV–) 0.90 (0.83-0.98) 0.64 (0.54-0.75) PWH (ref: HIV–) b 0.93 (0.86-0.99) 0.62 (0.58-0.68) aHR (95% CI) b aHR (95% CI) b Adjusted PWH (ref: HIV–) 0.48 (0.43-0.52) 0.27 (0.21-0.35) PWH (ref: HIV–) b 0.45 (0.42-0.49) 0.25 (0.20-0.32) Bold values indicate significance at P < 0.05.aAdjusted for age, race, ethnicity, sex, WHO obesity class, alcohol abuse, drug abuse, diabetes, hypertension, cancer, peripheral vascular disease, nonambulatory status, assistance needed for daily activities, atherosclerotic heart disease, cerebrovascular disease, amputation, coronary obstructive pulmonary disease, institutionalized (yes/no), functional status, tobacco use, rurality, ESKD network, and year of dialysis initiation.bCompeting risk model.aHR, adjusted HR; CI, confidence interval; ESKD, end-stage kidney disease; HIV–, HIV negative; HR, hazard ratio; PWH, people with HIV; WHO, World Health Organization. This disparity in waitlist addition experienced by PWH has been described in single-center data,2-4 and commonly attributed to clinical factors, specifically severity of HIV infection as defined by CD4 counts, HIV viral loads, presence of opportunistic infections, substance use, and failure to complete transplant evaluation. Reported substance use was included in our analysis, but, despite attempts to account for HIV-specific characteristics through the exclusion of PWH with opportunistic infections, we were unable to completely account for such, nor could we assess where this disparity manifests, including referral rates or evaluation completions. Reliance upon Medicare claims data also resulted in an older cohort, potentially resulting in lower waitlist addition rates. Thus, the magnitude of the disparity between PWH and ESKD patients with HIV may have been overestimated or developed earlier at referral or evaluation. Despite these limitations, this observed inequity is confirmed by studies that collected HIV-specific characteristics, referral, and evaluation data. Given advances in transplantation for PWH, national data collection should be revised to capture early steps in transplantation and HIV-specific characteristics to ensure equitable access to and outcomes of transplantation.2-4

The epidemiology of human immunodeficiency virus (HIV) has shifted such that Black individuals disproportionately represent incident HIV diagnoses. While risk of end-stage kidney disease (ESKD) among people with HIV (PWH) has declined with effective antiretroviral therapies, a substantial racial disparity in ESKD burden exists with the greatest prevalence among Black PWH. Disparities in waitlisting for kidney transplantation, the optimal treatment for ESKD, exist for both PWH and Black individuals without HIV, but it is unknown whether these characteristics together exacerbate such disparities. Six hundred two thousand six ESKD patients were identified from the United States Renal Data System (January 1, 2007 to December 31, 2017), and HIV-status was determined through Medicare claims. Cox proportional hazards regression was used to determine waitlisting rates. Multiplicative interaction terms between HIV-status and race were examined. The 6250 PWH were significantly younger, more commonly Black, and less commonly female than those without HIV. HIV-status and race were independently associated with 50% and 12% lower likelihood of waitlisting, respectively [adjusted hazard ratio (aHR): 0.50, 95% confidence interval (CI): 0.36-0.69, p < 0.001; aHR: 0.88, 95% CI: 0.87-0.90, p < 0.001]. There was also a significant interaction present between HIV-status and Black race (aHR: 0.80, 95% CI: 0.66-0.98, p < 0.001) such that, while HIV-status and Black race were independently associated with decreased waitlisting, the interaction of Black race and HIV-status exacerbated those disparities. While limited by lack of HIV-specific data that may impact inferences with respect to race, additional studies are urgently needed to understand the interplay between HIV risk factors, HIV-stigma, and racism, and how intersectionality may exacerbate disparities in transplantation among PWH.

Background: State-level nursing workforce data are important because national-level data cannot account for the local condi-tions that affect workforce distributions across states. The Alabama Board of Nursing collects licensure and survey data that inform registered nurse (RN) supply. However, little is known about the demand for acute care RNs in the state. Purpose: The purpose of this study was to characterize the demand for acute care RNs in Alabama. Methods: An exploratory, descriptive design was employed. Demand for acute care RNs was determined using a voluntary Survey of Acute Care Registered Nurse Employers in Alabama 2019. Chief nursing officers (CNOs) in Alabama were invited to complete the survey between July 2019 and April 2020. Results: Twenty-five CNOs representing Alabama's acute care hospitals completed the survey, 68% of whom reported an overall high demand with difficulty filling open acute care RN positions. That proportion increased to 80% when CNOs were queried about the demand for experienced RNs. Conclusion: This study provides evidence of the increasing demand for acute care RNs in Alabama even prior to the COVID-19 pandemic. To ensure patient safety and quality care in Alabama, the development of structures and processes for ongoing data collection regarding Alabama's acute care RN workforce supply and demand should be a legislative and regulatory priority.

Well-child visits focus on health promotion and disease detection and are critical to the appropriate provision of care. Evidence has shown that participation in well-child visits is associated with various patient-level factors; however, there has been an increasing focus on the influence of community-level social determinants of health (SDoH). This study explored associations between well-child visits and community-level SDoH at the census tract level among children enrolled in Alabama Medicaid. Through this analysis, it is possible to understand the distribution of care among this underserved population in different geographic settings, thus identifying potential disparities and areas for targeted intervention. Using administrative data from 2015 to 2017 enrollees in Alabama Medicaid that have been geographically linked to information on urbanicity and poverty, logistic regressions (both in total and stratified by age group) were estimated with separate community-level urbanicity, poverty variables, and individual characteristics. The regressions were repeated using a combined urbanicity/poverty variable. Looking at urbanicity and poverty together, with the exception of the least urban areas, it was those living in census tracts where there was discordance in urbanicity and poverty that had the highest likelihood of receiving well-child visits compared with those in census tracts classified as medium poverty (all urbanicity levels). There is a positive effect for Medicaid enrollees in the middle tertile of urbanicity in areas of low and high poverty and in wealthier more urban areas. If poverty and urbanicity were explored separately, some of the nuances would not have been apparent.

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, P < 0.01; OR: 0.68, P < 0.01) and higher odds of no medical claims (OR: 1.11, P < 0.05; OR: 1.73, P < 0.05) than non-Hispanic White children. Rural residents had lower odds of telehealth use than urban residents. Those in the highest family income-based fee group had higher odds of telehealth use than the lowest family income-based fee group. As telehealth will likely continue to play an important role in health care delivery, additional efforts/investments are required to ensure telehealth does not further exacerbate inequities in pediatric health care access.

Abstract PURPOSE To examine whether trends in new-onset pediatric type 2 diabetes (T2D) -- inclusive of patients requiring hospitalization and patients managed outpatient -- were impacted during the COVID-19 pandemic, and to compare patient characteristics prior to and during COVID-19. METHODS A retrospective single-center medical-record review was conducted in a hospital which cares for 90% of Alabama’s pediatric T2D patients. Patients with new-onset T2D referred from March 2017-March 2021 were included. Counts of patients presenting per month (“monthly rates”) were computed. Linear regression models were estimated for the full sample and stratified by Medicaid and non-Medicaid insurance status. Patient characteristics prior to versus during COVID-19 were compared. RESULTS 642 patients presented with new-onset T2D over this period. Monthly rates were 11.1 ± 3.8 prior to COVID-19,19.3 ± 7.8 during COVID-19 (p=0.004). Monthly rates for Medicaid patients differed prior to and during COVID-19 (7.9 ± 3.4 vs 15.3 ± 6.6, p = 0.003) but not for non-Medicaid patients (3.3 ± 1.7 vs 4.0 ± 2.4, p=0.33). Regression results showed significant increases in monthly rates during COVID-19 for the full sample (β=, p<0.05) and for Medicaid enrollees (β=, p<0.05) Hospitalization-rate, severity of obesity, and hemoglobin A1c remained similar prior to and during COVID-19, though the proportion of male patients increased from 36.8% to 46.1% (p=0.021). CONCLUSIONS A rise in new-onset T2D was observed among Alabama’s youth during the COVID-19 pandemic, a burden that disproportionately affected Medicaid enrollees and males. Future research should explore the pathways through which the pandemic impacted pediatric T2D.

OBJECTIVE:We investigated asthma quality measures to understand patient characteristics associated with non-attainment of quality care and measure the association with asthma-related emergency department (ED) visits or inpatient hospitalizations (IPs).METHODS:Using administrative data from ALL Kids, Alabama's Children's Health Insurance Program, from 2013 to 2019 we calculated non-attainment of the Medication Management for Asthma (MMA) and Asthma Medication Ratio (AMR) quality measures. Patient characteristics and asthma-related ED visits and IPs associated with non-attainment of the MMA and AMR measures were assessed using logit regression models and Marginal effects at the mean.RESULTS:Among 2528 children with asthma, 53.2% failed to attain the MMA measure and 8.5% the AMR measure. Prior asthma-related ED visits or IP stays increased likelihood of non-attainment by 14.8 percentage points (95% CI 8.6-20.9) for MMA and 7.3 percentage points (95% CI 2.8-11.8) for AMR. Among 868 children (34.3%) with three years of continuous enrollment, AMR non-attainment was associated with a 6.1 percentage point increase in ED or IP utilization (95% CI 1.3-10.9), however MMA non-attainment was not associated with either outcome. Prior ED visit/IP stay was associated with a 17.2 percentage point (95% CI 8.3-26.1) increase in the likelihood of a subsequent ED visit/IP stay among those with non-attainment MMA and a 15.5 percentage point increase (95% CI 6.9-24.2) for non-attainment AMR.CONCLUSIONS:Patient characteristics associated with non-attainment of asthma quality measures presents actionable evidence to guide improvement efforts as non-attainment AMR increases the risk of subsequent ED visits and IP stays.