Comparison of two propensity score-based methods for balancing covariates: the overlap weighting and fine stratification methods in real-world claims data.

BACKGROUND: Two propensity score (PS) based balancing covariate methods, the overlap weighting method (OW) and the fine stratification method (FS), produce superb covariate balance. OW has been compared with various weighting methods while FS has been compared with the traditional stratification method and various matching methods. However, no study has yet compared OW and FS. In addition, OW has not yet been evaluated in large claims data with low prevalence exposure and with low frequency outcomes, a context in which optimal use of balancing methods is critical. In the study, we aimed to compare OW and FS using real-world data and simulations with low prevalence exposure and with low frequency outcomes. METHODS: We used the Texas State Medicaid claims data on adult beneficiaries with diabetes in 2012 as an empirical example (N = 42,628). Based on its real-world research question, we estimated an average treatment effect of health center vs. non-health center attendance in the total population. We also performed simulations to evaluate their relative performance. To preserve associations between covariates, we used the plasmode approach to simulate outcomes and/or exposures with N = 4,000. We simulated both homogeneous and heterogeneous treatment effects with various outcome risks (1-30% or observed: 27.75%) and/or exposure prevalence (2.5-30% or observed:10.55%). We used a weighted generalized linear model to estimate the exposure effect and the cluster-robust standard error (SE) method to estimate its SE. RESULTS: In the empirical example, we found that OW had smaller standardized mean differences in all covariates (range: OW: 0.0-0.02 vs. FS: 0.22-3.26) and Mahalanobis balance distance (MB) (< 0.001 vs. > 0.049) than FS. In simulations, OW also achieved smaller MB (homogeneity: <0.04 vs. > 0.04; heterogeneity: 0.0-0.11 vs. 0.07-0.29), relative bias (homogeneity: 4.04-56.20 vs. 20-61.63; heterogeneity: 7.85-57.6 vs. 15.0-60.4), square root of mean squared error (homogeneity: 0.332-1.308 vs. 0.385-1.365; heterogeneity: 0.263-0.526 vs 0.313-0.620), and coverage probability (homogeneity: 0.0-80.4% vs. 0.0-69.8%; heterogeneity: 0.0-97.6% vs. 0.0-92.8%), than FS, in most cases. CONCLUSIONS: These findings suggest that OW can yield nearly perfect covariate balance and therefore enhance the accuracy of average treatment effect estimation in the total population.

Utilization, quality, and spending for pediatric Medicaid enrollees with primary care in health centers vs non-health centers.

BACKGROUND: Limited research has explored the performance of health centers (HCs) compared to other primary care settings among children in the United States. We evaluated utilization, quality, and expenditures for pediatric Medicaid enrollees receiving care in HCs versus non-HCs. METHODS: This national cross-sectional study utilized 2012 Medicaid Analytic eXtract (MAX) claims to examine children 0-17 years with a primary care visit, stratified by whether majority (> 50%) of primary care visits were at HCs or non-HCs. Outcome measures include utilization (primary care visits, non-primary care outpatient visits, prescription claims, Emergency Department (ED) visits, hospitalizations) and quality (well-child visits, avoidable ED visits, avoidable hospitalizations). For children enrolled in fee-for-service Medicaid, we also measured expenditures. Propensity score-based overlap weighting was used to balance covariates. RESULTS: A total of 2,383,270 Medicaid-enrolled children received the majority of their primary care at HCs, while 18,540,743 did at non-HCs. In adjusted analyses, HC patients had 20% more primary care visits, 15% less non-primary care outpatient visits, and 21% less prescription claims than non-HC patients. ED visits were similar across the two groups, while HC patients had 7% lower chance of hospitalization than non-HC. Quality of care outcomes favored HC patients in main analyses, but results were less robust when excluding managed care beneficiaries. Total expenditures among the fee-for-service subpopulation were lower by $239 (8%) for HC patients. CONCLUSIONS: In this study of nationwide claims data to evaluate healthcare utilization, quality, and spending among Medicaid-enrolled children who receive primary care at HCs versus non-HCs, findings suggest primary care delivery in HCs may be associated with a more cost-effective model of healthcare for children.

Racial and ethnic disparities in short interval pregnancy following delivery in Catholic vs non-Catholic hospitals among California Medicaid enrollees.

OBJECTIVES: We examined the impact of Catholic hospital delivery on short interval pregnancy in the California 2010-2014 Medicaid population. STUDY DESIGN: We used Cox regression to estimate the association between hospital affiliation and short interval pregnancy, adjusting for patient factors. RESULTS: Catholic hospital delivery had increased the risk of pregnancy within 6 months for Black (hazard ratio [HR] 1.11, 95% CI 1.06, 1.17) and Hispanic (HR 1.07, 95% CI 1.05, 1.09) but not for White women (HR 1.02, 95% CI 0.98, 1.05). CONCLUSIONS: Among California women with Medicaid, Catholic hospital delivery was associated with short interval pregnancy only among women of color.

Association of Health Insurance Status With Severity and Treatment Among Infants With Retinopathy of Prematurity.

This study describes retinopathy of prematurity treatment practices using Medicaid and commercial claims databases. Infants with Medicaid tend to be sicker overall and have higher rates of retinopathy of prematurity requiring treatment than those with commercial insurance. Among patients who required treatment, those with Medicaid were more likely to receive anti-vascular endothelial growth factor than laser treatment. [J Pediatr Ophthalmol Strabismus. 2023;60(6):e75-e78.].

Health care use and spending for Medicaid patients diagnosed with opioid use disorder receiving primary care in Federally Qualified Health Centers and other primary care settings.

INTRODUCTION: This nationwide study builds on prior research, which suggests that Federally Qualified Health Centers (FQHCs) and other primary care providers are associated with increased access to opioid use disorder (OUD) treatment. We compare health care utilization, spending, and quality for Medicaid patients diagnosed with OUD who receive primary care at FQHCs and Medicaid patients who receive most primary care in other settings, such as physician offices (non-FQHCs). We hypothesized that the integrated care model of FQHCs would be associated with greater access to medication for opioid use disorder (MOUD) and/or behavioral health therapy and lower rates of potentially inappropriate co-prescribing. METHODS: This cross-sectional study examined 2012 Medicaid Analytic eXtract files for patients diagnosed with OUD receiving most (>50%) primary care at FQHCs (N = 37,142) versus non-FQHCs (N = 196,712) in all 50 states and Washington DC. We used propensity score overlap weighting to adjust for measurable confounding between patients who received care at FQHCs versus non-FQHCs and increase generalizability of findings given variation in Medicaid programs and substance use policies across states. RESULTS: FQHC patients displayed higher primary care utilization and fee-for-service spending, and similar or lower utilization and fee-for-service spending for other health service categories. Contrary to our hypotheses, non-FQHC patients were more likely to receive timely (≤90 days) MOUD (buprenorphine, methadone, naltrexone, or suboxone) (Relative Risk [RR] = 1.10, 95% CI: 1.07, 1.12) and more likely be retained in medication treatment (>180 days) (RR = 1.12, 95% CI: 1.09, 1.14). However, non-FQHC patients were less likely to receive behavioral health therapy (mental health or substance use therapy) (RR = 0.90, 95% CI: 0.88, 0.92) and less likely to remain in behavioral health treatment (RR = 0.92, 95% CI: 0.89, 0.94). Non-FQHC patients were more likely to fill potentially inappropriate prescriptions of benzodiazepines and opioids after OUD diagnosis (RR = 1.35, 95% CI: 1.30, 1.40). CONCLUSIONS: Observed patterns suggest that Medicaid patients diagnosed with OUD who obtained primary care at FQHCs received more integrated care compared to non-FQHC patients. Greater care integration may be associated with increased access to behavioral health therapy and quality of care (lower potentially inappropriate co-prescribing) but not necessarily greater access to MOUD.

Quality of Care for US Adults With Medicaid Insurance and Type 2 Diabetes in Federally Qualified Health Centers Compared With Other Primary Care Settings.

OBJECTIVE: The objective of this study was to evaluate indicators of diabetes quality of care for US nonelderly, adult Medicaid enrollees with type 2 diabetes and compare federally qualified health centers (FQHCs) versus non-FQHCs. RESEARCH DESIGN AND METHODS: We analyzed diabetes process measures and acute health services utilization with 2012 US fee-for-service and managed care Medicaid claims in all 50 states and DC. We compared FQHC (N=121,977) to non-FQHC patients (N=700,401) using propensity scores to balance covariates and generalized estimating equation models. RESULTS: Overall, laboratory-based process measures occurred more frequently (range, 65.7%-76.6%) than measures requiring specialty referrals (retinal examinations, 33.3%; diabetes education, 3.4%). Compared with non-FQHC patients, FQHC patients had about 3 percentage point lower rates of each process measure, except for higher rates of diabetes education [relative risk=1.09, 95% confidence interval (CI): 1.03-1.16]. FQHC patients had fewer overall [incident rate ratio (IRR)=0.87, 95% CI: 0.86-0.88] and diabetes-related hospitalizations (IRR=0.79, 95% CI: 0.77-0.81), but more overall (IRR=1.06, 95% CI: 1.05-1.07) and diabetes-related emergency department visits (IRR=1.10, 95% CI: 1.08-1.13). CONCLUSIONS: This national analysis identified opportunities to improve diabetes management among Medicaid enrollees with type 2 diabetes, especially for retinal examinations or diabetes education. Overall, we found slightly lower rates of most diabetes care process measures for FQHC patients versus non-FQHC patients. Despite having higher rates of emergency department visits, FQHC patients were significantly less likely to be hospitalized than non-FQHC patients. These findings emphasize the need to identify innovative, effective approaches to improve diabetes care for Medicaid enrollees, especially in FQHC settings.

Short-interval pregnancy in the Illinois Medicaid population following delivery in Catholic vs non-Catholic hospitals.

OBJECTIVE: Catholic hospitals restrict access to comprehensive reproductive health services that could impact patient outcomes. We sought to determine whether delivery at a Catholic hospital is associated with shorter pregnancy intervals among patients insured by Medicaid in Illinois. STUDY DESIGN: We used Illinois Medicaid data files to conduct a retrospective cohort study. We used billing codes to identify deliveries in 2010 and 2011 and classified each by a hospital of delivery, maternal age, race/ethnicity, and residential zip code. We calculated the interval from index birth to subsequent conception using an established method and used Cox proportional hazards regression to compare the rate of subsequent pregnancy between enrollees who delivered in Catholic vs non-Catholic hospitals, adjusting for individual characteristics. We also computed differences in the rates of conception within 6-, 12-, and 18-month intervals. RESULTS: We identified 96,293 index births and 18,627 subsequent conceptions. Twenty-eight percent (26,775) of index births occurred in a Catholic hospital. Women who delivered in a Catholic hospital had a 12% greater risk of conception in the following 18 months (HR 1.12, 95% CI 1.09-1.16) after adjusting for age, race/ethnicity, and rural residence. At 18 months, 23.9% of enrollees delivering in a Catholic hospital had become pregnant as compared to 21.2% for enrollees delivering in a non-Catholic hospital (difference of 2.6%, 95% CI 1.8-3.6). CONCLUSION: Illinois Medicaid enrollees who deliver at Catholic hospitals have an increased risk of short-interval pregnancy. As the market share of Catholic hospitals grows, providers must work with patients to acknowledge and address these potential impacts on reproductive health outcomes and policies must change to promote equitable access. IMPLICATIONS: Delivery at a Catholic hospital is associated with an increased risk of short-interval pregnancy. Further attention from providers, researchers, and policymakers alike, is necessary to identify the mechanisms through which these differences manifest such that effective interventions can be developed.

Preconception care and severe maternal morbidity in the United States.

BACKGROUND: In the United States, approximately 52,000 women per year (accounting for 1.46% of births) experience severe maternal morbidity, which is defined as a complication that causes significant maternal harm or risk of death. It disproportionately affects women from racial or ethnic minorities, people with chronic diseases, and those with Medicaid or no insurance. Preconception care has been hailed as a strategy to improve pregnancy outcomes and reduce disparities, but its broad benefits for maternal outcomes have not been demonstrated. OBJECTIVE: Our objective was to measure the association between preconception care and the odds of severe maternal morbidity among women with Medicaid. STUDY DESIGN: This is a secondary analysis of Medicaid claims using the Medicaid Analytic Extract files (2010-2012). We used the International Classification of Diseases, Ninth Revision codes, published by the US Office of Population Affairs' Quality Family Planning program to define 7 domains of preconception care. The primary outcome was maternal death within 12 weeks of delivery or severe maternal morbidity during birth hospitalization, defined by the presence of any diagnosis or procedure on the severe maternal morbidity International Classification of Diseases, Ninth Revision code list from the Centers for Disease Control and Prevention. Because this list may overestimate severe maternal morbidity by counting any blood transfusion, our secondary outcome used the same code list but without transfusion. We reviewed care in the year before conception and used logistic regression to estimate the association between each domain and severe maternal morbidity for all births to women enrolled in Medicaid and aged 15 to 45 years with births during 2012. We performed a subgroup analysis for women with chronic disease (kidney disease, hypertension, or diabetes). RESULTS: Severe maternal morbidity or death occurred in 26,285 births (1.74%) when including blood transfusions and 9,481 births (0.63%) when excluding transfusions. Receiving contraceptive services in the year before conception was associated with decreased odds of severe maternal morbidity (adjusted odds ratio, 0.92; 95% confidence interval, 0.88-0.95) and pregnancy test services were associated with increased odds (adjusted odds ratio, 1.08; 95% confidence interval, 1.01-1.14). In the primary analysis, no significant associations were observed for other preconception care domains. Among those women with at least 1 chronic disease, contraceptive care (adjusted odds ratio, 0.84; 95% confidence interval, 0.75-0.95) and routine physical or gynecologic exams (adjusted odds ratio, 0.79; 95% confidence interval, 0.71-0.88) were associated with decreased odds of severe maternal morbidity. Similar associations were found for severe maternal morbidity when excluding blood transfusion. CONCLUSIONS: Contraceptive services in the year before conception and routine exams for women with chronic disease are associated with decreased odds of severe maternal morbidity or death for Medicaid enrollees.

Global initiative for congenital toxoplasmosis: an observational and international comparative clinical analysis.

Globally, congenital toxoplasmosis remains a significant cause of morbidity and mortality, and outbreaks of infection with T. gondii represent a significant, emerging public health burden, especially in the developing world. This parasite is a threat to public health. Disease often is not recognized and is inadequately managed. Herein, we analyze the status of congenital toxoplasmosis in Morocco, Colombia, the United States, and France. We identify the unique challenges faced by each nation in the implementation of optimal approaches to congenital toxoplasmosis as a public health problem. We suggest that developed and developing countries use a multipronged approach, modeling their public health management protocols after those in France. We conclude that education, screening, appropriate treatment, and the development of novel modalities will be required to intervene successfully in caring for individuals with this infection. Gestational screening has been demonstrated to be cost-effective, morbidity-sparing, and life-saving. Recognition of the value and promise of public health interventions to prevent human suffering from this emerging infection will facilitate better patient and societal outcomes.

Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain.

BACKGROUND: Street imagery is a promising and growing big data source providing current and historical images in more than 100 countries. Studies have reported using this data to audit road infrastructure and other built environment features. Here we explore a novel application, using Google Street View (GSV) to predict travel patterns at the city level. METHODS: We sampled 34 cities in Great Britain. In each city, we accessed 2000 GSV images from 1000 random locations. We selected archived images from time periods overlapping with the 2011 Census and the 2011-2013 Active People Survey (APS). We manually annotated the images into seven categories of road users. We developed regression models with the counts of images of road users as predictors. The outcomes included Census-reported commute shares of four modes (combined walking plus public transport, cycling, motorcycle, and car), as well as APS-reported past-month participation in walking and cycling. RESULTS: We found high correlations between GSV counts of cyclists ('GSV-cyclists') and cycle commute mode share (r = 0.92)/past-month cycling (r = 0.90). Likewise, GSV-pedestrians was moderately correlated with past-month walking for transport (r = 0.46), GSV-motorcycles was moderately correlated with commute share of motorcycles (r = 0.44), and GSV-buses was highly correlated with commute share of walking plus public transport (r = 0.81). GSV-car was not correlated with car commute mode share (r = -0.12). However, in multivariable regression models, all outcomes were predicted well, except past-month walking. The prediction performance was measured using cross-validation analyses. GSV-buses and GSV-cyclists are the strongest predictors for most outcomes. CONCLUSIONS: GSV images are a promising new big data source to predict urban mobility patterns. Predictive power was the greatest for those modes that varied the most (cycle and bus). With its ability to identify mode of travel and capture street activity often excluded in routinely carried out surveys, GSV has the potential to be complementary to new and traditional data. With half the world's population covered by street imagery, and with up to 10 years historical data available in GSV, further testing across multiple settings is warranted both for cross-sectional and longitudinal assessments.