Opioid utilization after orthopaedic trauma hospitalization among Medicaid-insured adults

Opioids are vital to pain management and sedation after trauma-related hospitalization. However, there are many confounding clinical, social, and environmental factors that exacerbate pain, post-injury care needs, and receipt of opioid prescriptions following orthopaedic trauma. This retrospective study sought to characterize differences in opioid prescribing and dosing in a national Medicaid eligible sample from 2010-2018. The study population included adults, discharged after orthopaedic trauma hospitalization, and receiving an opioid prescription within 30 days of discharge. Patients were identified using the International Classification of Diseases (ICD-9; ICD-10) codes for inpatient diagnosis and procedure. Filled opioid prescriptions were identified from National Drug Codes and converted to morphine milligram equivalents (MME). Opioid receipt and dosage (e.g., morphine milligram equivalents [MME]) were examined as the main outcomes using regressions and analyzed by year, sex, race/ethnicity, residence rurality-urbanicity, and geographic region. The study population consisted of 86,091 injured Medicaid-enrolled adults; 35.3% received an opioid prescription within 30 days of discharge. Male patients (OR = 1.12, 95% CI: 1.07-1.18) and those between 31-50 years of age (OR = 1.15, 95% CI: 1.08-1.22) were found to have increased odds ratio of receiving an opioid within 30 days of discharge, compared to female and younger patients, respectively. Patients with disabilities (OR = 0.75, 95% CI: 0.71-0.80), prolonged hospitalizations, and both Black (OR = 0.87, 95% CI: 0.83-0.92) and Hispanic patients (OR = 0.72, 95% CI: 0.66-0.77), relative to white patients, had lower odds ratio of receiving an opioid prescription following trauma. Additionally, Black and Hispanic patients received lower prescription doses compared to white patients. Individuals hospitalized in the Southeastern United States and those between the ages of 51-65 age group were found to be prescribed lower average daily MME. There were significant variations in opioid prescribing practices by race, sex, and region. National guidelines for use of opioids and other pain management interventions in adults after trauma hospitalization may help limit practice variation and reduce implicit bias and potential harms in outpatient opioid usage.

Opioid Utilization after Cardiac Surgery in the Pediatric Medicaid-Insured Population

OBJECTIVE

To determine the variation of outpatient opioid prescribing across the US in postoperative pediatric cardiac patients.

STUDY DESIGN

Retrospective, cross-sectional study using a concatenated database of Medicaid claims between from 2016 through 2018 of children 0-17 years, discharged after cardiac surgery and receiving an opioid prescription within 30 days. Filled prescriptions were identified and converted to morphine milligram equivalents (MME). Use, duration, and dose were analyzed by sex, race, ethnicity, residence urbanicity, and region.

RESULTS

Among 17 186 Medicaid-enrolled children after cardiac surgery, 2129 received opioids within 30 days of discharge. Females received lower doses than males (coefficient -0.17, P = .022). Hispanic individuals were less likely to receive opioids (coefficient 0.53, P < .05, 95% CI: 0.38-0.71) and for shorter periods (coefficient 0.83, P < .001). Midwest (MW) (OR 0.61, 95% P-values < 0.05, 95% CI: 0.46-0.80) and Northeast (NE) (OR 0.43, 95% P-values < 0.05, 95% CI: 0.30-0.61) regions were less likely to receive opioids but used higher doses compared with the Southeast (SE) (MW coefficient 0.41, Southwest (SW) coefficient 0.18, NE coefficient 0.32, West (W) coefficient 0.19, P < .05).

CONCLUSIONS

There were significant variations in opioid prescribing after cardiac surgery by race, ethnicity, sex, and region. National guidelines for outpatient use of opioids in children after cardiac surgery may help limit practice variation and reduce potential harms in outpatient opioid usage.

The impact of dentists' availability in delivering dental care in Florida Elementary Schools

OBJECTIVE

This study evaluates the dentists' availability to deliver preventive dental care to children in schools and the impact of school-based programs on access.

METHODS

The study population included Florida elementary-school children, differentiated by dental insurance (Medicaid, CHIP, private, or none). We considered the implementation of school-based programs using optimization modeling to (re)allocate the dentists' caseload to schools to meet demand for preventive care under resource constraints. We considered multiple settings for school-based program implementation: (i) school prioritization; and (ii) dentists' participation in public insurance. Statistical inference was used to identify communities to improve access and reduce disparities.

RESULTS

School-based programs reduced unmet demand (3%-12%), being more efficient if prioritizing schools in communities targeted to improve access. The access improvement varied by insurance status and geography. Uninsured urban children benefited most from school-based programs, with 15%-75% unmet need reduction. The percentage of urban communities targeted to improve access decreased by 12% against no-school program. Such percentage remained large for suburban (15%-100%) and rural (50%-100%) communities. Disparity in access for public-insured vs. private-insured children persisted under school-based programs (32%-84% identified communities).

CONCLUSION

School-based programs improve dental care access; the improvement was however different by insurance status, with uninsured children benefiting the most. Accounting to the dentists' availability in prioritizing schools resulted in effective resource allocation to school-based programs. Access disparities between public and private-insured children did not improve; school-based programs shifted resources from public-insured to uninsured. School-based programs are effective in addressing access barriers to those children experiencing them most.

Association Between In-Home Treatment and Engagement in Psychosocial Services Among Medicaid-Enrolled Youth

OBJECTIVE

Prior studies have identified low rates of engagement in mental health (MH) services in clinic settings among children enrolled in Medicaid. Yet, little is known about whether the delivery of in-home MH treatment (in which the clinician travels to the child's home) improves engagement for this population. This study examines the association between the delivery of in-home psychosocial treatment and engagement in services among Medicaid-enrolled youth.

METHOD

We used 2010 to 2014 Georgia Medicaid claims data to identify 53,508 children and adolescents (aged 5-17 years) with a MH diagnosis that initiated new psychosocial treatment. We estimated regression models controlling for covariates to examine the relationship of the receipt of any in-home psychosocial treatment in the home setting with 3 outcome measures of engagement: receipt of at least 4 psychosocial visits during the first 12 weeks; total number of psychosocial visits during the first 12 weeks; and total duration of service use.

RESULTS

Those who received any in-home psychosocial treatment (compared to those who did not) had 4.3 times the odds (odds ratio = 4.3, 95% CI = 4.0, 4.7) of receiving at least 4 visits during the first 12 weeks, had 4.5 (95% CI = 4.3, 4.7) more predicted visits during the first 12 weeks, and had a longer treatment episode duration (mean rate ratio = 1.54, 95% CI = 1.48,1.59).

CONCLUSION

Although many Medicaid-enrolled youth do not receive a sufficient number of MH services to achieve positive outcomes, our findings suggest that providing in-home psychosocial treatment can improve service engagement and potentially help address this challenge.

Assessment of Dentist Participation in Public Insurance Programs for Children in the US

Importance

Evaluating the availability of dentists to provide dental care services to children is important for identifying interventions for improving access.

Objective

To assess dental care availability for children in the US by public insurance participation, rural-urban setting, and dentist taxonomy (general, pediatric, or specialized).

Design, Setting, and Participants

This cross-sectional study analyzed the availability of dentists from matching 3 data sets: the 2020 National Plan and Provider Enumeration System, the 2019-2020 State Board of Dentistry information acquired from each state, and the 2019 InsureKidsNow.org database. Data on active dentists in most states (including the District of Columbia [combined hereinafter with states] and excluding Hawaii and Washington) were included in the analysis. The study was conducted from January 2019 to March 2022.

Main Outcomes and Measures

The number and percentage of dentists participating in public insurance programs (Medicaid and/or Children's Health Insurance Program [CHIP]) were aggregated at the dental office and stratified by the rurality of their practice and taxonomy. State-level comparisons were derived between this study and reports from the Health Policy Institute of the American Dental Association, along with maps and summary statistics disseminated through a data portal and state reports.

Results

Among 204 279 active dentists, participation in public insurance varied widely across states, especially for the states that manage the Medicaid and CHIP programs separately. Participation rates in Medicaid and CHIP varied substantially from those of the Health Policy Institute of the American Dental Association. Participation in Medicaid and CHIP was lowest among urban dentists (Medicaid, 26%; CHIP, 29%) and highest among rural dentists (Medicaid, 39%; CHIP, 40%), while urban dentists accounted for most of the dentist population (urban, 84%; rural, 5%). Similarly, participation in Medicaid and CHIP was substantially lower among general dentists (Medicaid, 28%; CHIP, 29%) vs pediatric dentists (57% in both programs), while each state's dentist population consisted of notably more general (84%) than pediatric (3%) dentists. Nearly half of the states revealed wide variations in Medicaid and CHIP participation between counties, ranging from no participation (21 states) to full participation (22 states).

Conclusions and Relevance

The findings of this study suggest that disparities in the availability of dentists for pediatric dental care are extensive, particularly for Medicaid- and CHIP-insured children, those living in rural communities, and those receiving specialized care. Lack of dentist availability for Medicaid- and CHIP-insured children appears to deter access to receiving dental care.

Parallel Subgradient Algorithm with Block Dual Decomposition for Large-scale Optimization

This paper studies computational approaches for solving large-scale optimization problems using a Lagrangian dual reformulation, solved by parallel sub-gradient methods. Since there are many possible reformulations for a given problem, an important question is: Which reformulation leads to the fastest solution time? One approach is to detect a block diagonal structure in the constraint matrix, and reformulate the problem by dualizing the constraints outside of the blocks; the approach is defined herein as block dual decomposition. Main advantage of such a reformulation is that the Lagrangian relaxation has a block diagonal constraint matrix, thus decomposable into smaller sub-problems that can solved in parallel. We show that the block decomposition can critically affect convergence rate of the sub-gradient method. We propose various decomposition methods that use domain knowledge or apply algorithms using knowledge about the structure in the constraint matrix or the dependence in the decision variables, towards reducing the computational effort to solve large-scale optimization problems. In particular, we introduce a block decomposition approach that reduces the number of dualized constraints by utilizing a community detection algorithm. We present empirical experiments on an extensive set of problem instances including a real application. We illustrate that if the number of the dualized constraints in the decomposition increases, the computational effort within each iteration of the sub-gradient method decreases while the number of iterations required for convergence increases. The key message is that it is crucial to employ prior knowledge about the structure of the problem when solving large scale optimization problems using dual decomposition.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Evaluating scenarios for school reopening under COVID19

BACKGROUND

Thousands of school systems have struggled with the decisions about how to deliver education safely and effectively amid the COVID19 pandemic. This study evaluates the public health impact of various school reopening scenarios (when, and how to return to in-person instruction) on the spread of COVID19.

METHODS

An agent-based simulation model was adapted and used to project the impact of various school reopening strategies on the number of infections, hospitalizations, and deaths in the state of Georgia during the study period, i.e., February 18^th-November 24^th, 2020. The tested strategies include (i) schools closed, i.e., all students receive online instruction, (ii) alternating school day, i.e., half of the students receive in-person instruction on Mondays and Wednesdays and the other half on Tuesdays and Thursdays, (iii) alternating school day for children, i.e., half of the children (ages 0-9) receive in-person instruction on Mondays and Wednesdays and the other half on Tuesdays and Thursdays, (iv) children only, i.e., only children receive in-person instruction, (v) regular, i.e., all students return to in-person instruction. We also tested the impact of universal masking in schools.

RESULTS

Across all scenarios, the number of COVID19-related deaths ranged from approximately 8.8 to 9.9 thousand, the number of cumulative infections ranged from 1.76 to 1.96 million for adults and 625 to 771 thousand for children and youth, and the number of COVID19-related hospitalizations ranged from approximately 71 to 80 thousand during the study period. Compared to schools reopening August 10 with a regular reopening strategy, the percentage of the population infected reduced by 13%, 11%, 9%, and 6% in the schools closed, alternating school day for children, children only, and alternating school day reopening strategies, respectively. Universal masking in schools for all students further reduced outcome measures.

CONCLUSIONS

Reopening schools following a regular reopening strategy would lead to higher deaths, hospitalizations, and infections. Hybrid in-person and online reopening strategies, especially if offered as an option to families and teachers who prefer to opt-in, provide a good balance in reducing the infection spread compared to the regular reopening strategy, while ensuring access to in-person education.

Evaluating access to pediatric oral health care in the southeastern states

BACKGROUND

In this article, the authors addressed shortcomings in existing research on pediatric oral health care access using rigorous data and methods for identifying statistically significant disparities in oral health care access for children.

METHODS

The study population included children, differentiated by insurance status (Medicaid, Children's Health Insurance Program, private, none). The authors measured provider-level supply as the number of oral health care visits, stratified by provider type and urbanicity-rurality. The authors defined demand as the number of dental visits for children and derived demand and supply mainly from 2019 and 2020 data. Using statistical modeling, the authors evaluated where disparities in travel distance across communities or by insurance status were statistically significant.

RESULTS

Although Dental Health Professional Shortage Areas are primarily rural, this study found that the proportions of rural, suburban, and urban communities identified for access interventions ranged from 24% through 66% and from 8% through 86%, respectively. For some states (Florida, Louisiana, Texas), rural and suburban communities showed a need for interventions for all children, whereas in the remaining states, the lack of Medicaid and Children's Health Insurance Program access mainly contributed to these disparities. Variations in access disparities with respect to insurance status across states or by urbanicity-rurality were extensive, with the rate of communities identified for reducing disparities ranging from 1% through 100%.

CONCLUSIONS

All states showed a need for access interventions and for reducing disparities due to geographic location or insurance status. The sources of disparities were different across states, suggesting need for different policies and interventions across the 10 states.

PRACTICAL IMPLICATIONS

The study findings support the need for policies toward reducing disparities in oral health care access.

Global Sensitivity Analysis via a Statistical Tolerance Approach

Sensitivity analysis and multiparametric programming in optimization modeling study variations of optimal value and solutions in the presence of uncertain input parameters. In this paper, we consider simultaneous variations in the inputs of the objective and constraint (jointly called the RIM parameters), where the uncertainty is represented as a multivariate probability distribution. We introduce a tolerance approach based on principal component analysis, which obtains a tolerance region that is suited to the given distribution and can be considered a confidence set for the random input parameters. Since a tolerance region may contain parameters with different optimal bases, we extend the tolerance approach to the case where multiple optimal bases cover the tolerance region, by studying theoretical properties of critical regions (defined as the set of input parameters having the same optimal basis). We also propose a computational algorithm to find critical regions covering a given tolerance region in the RIM parameter space. Our theoretical results on geometric properties of critical regions contribute to the existing theory of parametric programming with an emphasis on the case where RIM parameters vary jointly, and provide deeper geometric understanding of critical regions. We evaluate the proposed framework using a series of experiments for sensitivity analysis, for model predictive control of an inventory management problem, and for large optimization problem instances.

Assessing Health and Wellness Outcomes of Medicaid-Enrolled Infants Born to Adolescent Mothers

OBJECTIVE

To assess the effect of adolescent birth on the health and wellness of these infants within their first year of life.

METHODS

Our study focused on 2011 Medicaid births nationwide. The study group (infants born to adolescents, aged 10 to 19 at time of birth) was matched with infants born to adults (aged 20 to 44 at time of birth), based on demographics. Statistical tests (proportion test and Poisson test) were used to compare the outcomes of these two groups to determine if differences were significant.

RESULTS

The outcomes assessed were: low birth weight (LBW), substance exposure, foster care, health status, infant mortality, emergency department (ED) visits, and wellness visits. Of the 68,562 infant pairs included in the study, we found statistically significant higher rates of LBW (P ≤ 0·005), infant mortality (P = 0·05), and ED visits (P ≤ 0·005) for infants born to adolescents at the 95% confidence interval. The rate of wellness visits for all infants was well below the recommended amount. Additional differences were found at the race/ethnicity and urbanicity levels.

CONCLUSION FOR PRACTICE

Infants born to adolescents had a higher rate of ED visits within the first year of life, however, the increased rates of LBW and mortality for the Medicaid population are not as significant as previous national studies suggest. Analysis of outcomes across stratification helped identify vulnerable populations (i.e. urban infants). Public health programs are urged to examine ED visits in infants born to adolescents among the Medicaid population. Improved health education or phone-based resources could help reduce unnecessary visits and reduce cost.

Homebound by COVID19: the benefits and consequences of non-pharmaceutical intervention strategies

BACKGROUND

Recent research has been conducted by various countries and regions on the impact of non-pharmaceutical interventions (NPIs) on reducing the spread of COVID19. This study evaluates the tradeoffs between potential benefits (e.g., reduction in infection spread and deaths) of NPIs for COVID19 and being homebound (i.e., refraining from interactions outside of the household).

METHODS

An agent-based simulation model, which captures the natural history of the disease at the individual level, and the infection spread via a contact network assuming heterogeneous population mixing in households, peer groups (workplaces, schools), and communities, is adapted to project the disease spread and estimate the number of homebound people and person-days under multiple scenarios, including combinations of shelter-in-place, voluntary quarantine, and school closure in Georgia from March 1 to September 1, 2020.

RESULTS

Compared to no intervention, under voluntary quarantine, voluntary quarantine with school closure, and shelter-in-place with school closure scenarios 4.5, 23.1, and 200+ homebound adult-days were required to prevent one infection, with the maximum number of adults homebound on a given day in the range of 119 K-248 K, 465 K-499 K, 5388 K-5389 K, respectively. Compared to no intervention, school closure only reduced the percentage of the population infected by less than 16% while more than doubling the peak number of adults homebound.

CONCLUSIONS

Voluntary quarantine combined with school closure significantly reduced the number of infections and deaths with a considerably smaller number of homebound person-days compared to shelter-in-place.

Accounting for uncertainty in policy decision making: Improving access to pediatric dental care

OBJECTIVE

To introduce a statistical inference framework for policy decision making on access to pediatric dental care.

DATA SOURCES

Secondary data were collected for the state of Colorado for year 2019.

STUDY DESIGN

The access model was an optimization model, matching the demand (patients) and supply (providers) of dental care. Sampling distributions of model inputs were specified using hierarchical Bayesian models, with hyperparameters informed by prior information derived from multiple data sources. Simultaneous inference was applied to identify areas for access improvement. The model was applied to make inference on the pediatric dental care in Colorado, accounting for financial access, differentiated into public (Medicaid and CHIP), private (commercial and out-of-pocket), and without financial access.

DATA COLLECTION/EXTRACTION METHODS

Multiple data sources informed the access measurement approach including: 2017 American Community Survey, 2019 Colorado Dental Board, and 2019 National Provider Plan and Enumeration System, 2019 InsureKidsNow.gov among others.

PRINCIPAL FINDINGS

The median access measure (travel distance) was greater than the Colorado access standards in 16.9% and 65.1% of census tracts for children with private financial access and publicly insured, respectively. Accounting for uncertainty (confidence level 99%), these percentages decreased to 14.6% and 25.6%, respectively, with mostly suburban and rural tracts failing to meet the standards. The median disparity for Medicaid and CHIP versus private financial access was greater than 5 miles in 84.5% and 81.6% of census tracts, respectively. Accounting for uncertainty (confidence level 99%), these percentages declined to 19.5% and 10.5%, respectively, with significant disparities around the metropolitan areas.

CONCLUSIONS

While many communities failed to meet access standards, when accounting for uncertainty, most urban ones did not fail. Disparities in spatial access between publicly and privately insured were most acute in urban communities. Medicaid insured experienced higher disparities than CHIP insured; those differences were not identified when not accounting for uncertainty.

Reflecting on prediction strategies for epidemics: Preparedness and public health response

Objective

To provide an overview of the literature on respiratory infectious disease epidemic prediction, preparedness, and response (including pharmaceutical and nonpharmaceutical interventions) and their impact on public health, with a focus on respiratory conditions such as asthma.

Data Sources

Published literature obtained through PubMed database searches.

Study Selections

Studies relevant to infectious epidemics, asthma, modeling approaches, health care access, and data analytics related to intervention strategies.

Results

Prediction, prevention, and response strategies for infectious disease epidemics use extensive data sources and analytics, addressing many areas including testing and early diagnosis, identifying populations at risk of severe outcomes such as hospitalizations or deaths, monitoring and understanding transmission and spread patterns by age group, social interactions geographically and over time, evaluating the effectiveness of pharmaceutical and nonpharmaceutical interventions, and understanding prioritization of and access to treatment or preventive measures (eg, vaccination, masks), given limited resources and system constraints.

Conclusion

Previous epidemics and pandemics have revealed the importance of effective preparedness and response. Further research and implementation need to be performed to emphasize timely and actionable strategies, including for populations with particular health conditions (eg, chronic respiratory diseases) at risk for severe outcomes.

The impact of social distancing on COVID19 spread: State of Georgia case study

As the spread of COVID19 in the US continues to grow, local and state officials face difficult decisions about when and how to transition to a "new normal." The goal of this study is to project the number of COVID19 infections and resulting severe outcomes, and the need for hospital capacity under social distancing, particularly, shelter-in-place and voluntary quarantine for the State of Georgia. We developed an agent-based simulation model to project the infection spread. The model utilizes COVID19-specific parameters and data from Georgia on population interactions and demographics. The simulation study covered a seven and a half-month period, testing different social distancing scenarios, including baselines (no-intervention or school closure only) and combinations of shelter-in-place and voluntary quarantine with different timelines and compliance levels. The following outcomes are compared at the state and community levels: the number and percentage of cumulative and daily new symptomatic and asymptomatic infections, hospitalizations, and deaths; COVID19-related demand for hospital beds, ICU beds, and ventilators. The results suggest that shelter-in-place followed by voluntary quarantine reduced peak infections from approximately 180K under no intervention and 113K under school closure, respectively, to below 53K, and delayed the peak from April to July or later. Increasing shelter-in-place duration from four to five weeks yielded 2-9% and 3-11% decrease in cumulative infection and deaths, respectively. Regardless of the shelter-in-place duration, increasing voluntary quarantine compliance decreased daily new infections from almost 53K to 25K, and decreased cumulative infections by about 50%. The cumulative number of deaths ranged from 6,660 to 19,430 under different scenarios. Peak infection date varied across scenarios and counties; on average, increasing shelter-in-place duration delayed the peak day by 6 days. Overall, shelter-in-place followed by voluntary quarantine substantially reduced COVID19 infections, healthcare resource needs, and severe outcomes.

Provider-Level Caseload of Psychosocial Services for Medicaid-Insured Children

OBJECTIVE

We estimated the caseload of providers, practices, and clinics for psychosocial services (including psychotherapy) to Medicaid-insured children to improve the understanding of the current supply of such services and to inform opportunities to increase their accessibility.

METHODS

We used 2012-2013 Medicaid claims data and data from the 2013 National Plan and Provider Enumeration System to identify and locate therapists, psychiatrists, and mental health centers along with primary, rehabilitative, and developmental care providers in the United States who provided psychosocial services to Medicaid-insured children. We estimated the per-provider, per-location, and state-level caseloads of providers offering these services to Medicaid-insured children in 34 states with sufficiently complete data to perform this analysis, by using the most recent year of Medicaid claims data available for each state. We measured caseload by calculating the number of psychosocial visits delivered by each provider in the selected year. We compared caseloads across states, urbanicity, provider specialty (eg, psychiatry, psychology, primary care), and practice setting (eg, mental health center, single practitioner).

RESULTS

We identified 63 314 providers, practices, or centers in the Medicaid claims data that provided psychosocial services to Medicaid-insured children in either 2012 or 2013. The median provider-level per-year caseload was <25 children and <250 visits across all provider types. Providers with a mental health center-related taxonomy accounted for >40% of visits for >30% of patients. Fewer than 10% of providers and locations accounted for >50% of patients and visits.

CONCLUSIONS

Psychosocial services are concentrated in a few locations, thereby reducing geographic accessibility of providers. Providers should be incentivized to offer care in more locations and to accept more Medicaid-insured patients.

An Economic Analysis of Intensive Multidisciplinary Interventions for Treating Medicaid-Insured Children with Pediatric Feeding Disorders

Background. Intensive multidisciplinary intervention (IMI) represents a well-established treatment for pediatric feeding disorders (PFDs), but program availability represents an access care barrier. We develop an economic analysis of IMI for weaning from gastronomy tube (G-tube) treatment for children diagnosed with PFDs from the Medicaid programs' perspective, where Medicaid programs refer to both fee-for-service and managed care programs. Methods. The 2010-2012 Medicaid Analytic eXtract claims provided health care data for children aged 13 to 72 months. An IMI program provided data on average admission costs. We employed a finite-horizon Markov model to simulate PFD treatment progression assuming 2 treatment arms: G-tube only v. IMI targeting G-tube weaning. We compared the expenditure differential between the 2 arms under varying time horizons and treatment effectiveness. Results. Overall Medicaid expenditure per member per month was $6814, $2846, and $1550 for the study population of children with PFDs and G-tube treatment, the control population with PFDs without G-tube treatment, and the no-PFD control population, respectively. The PFD-diagnosed children with G-tube treatment only had the highest overall expenditures across all health care settings except psychological services. The expenditure at the end of the 8-year time horizon was $405,525 and $208,218 per child for the G-tube treatment only and IMI arms, respectively. Median Medicaid expenditure was between 1.7 and 2.2 times higher for the G-tube treatment arm than for the IMI treatment arm. Limitations. Data quality issues could cause overestimates or underestimates of Medicaid expenditure. Conclusions. This study demonstrated the economic benefits of IMI to treat complex PFDs from the perspective of Medicaid programs, indicating this model of care not only holds benefit in terms of improving overall quality of life but also brings significant expenditure savings in the short and long term.

Medicaid caseload for pediatric oral health care

BACKGROUND

The authors' aims were to compare, according to strata, dentists' participation in Medicaid and Medicaid provider-level caseload measured as the number of patients or visits for preventive or restorative care for 2 comparison years.

METHODS

The data sources were the 2012-2013 Medicaid Analytic eXtract claims and 2013 National Plan and Provider Enumeration System data sets. The authors measured Medicaid participation as the proportion of dentists participating in Medicaid among those in the National Plan and Provider Enumeration System. The authors measured provider-level caseload according to the number of patients or visits. The authors stratified oral health care providers according to state; whether practicing in rural, suburban, or urban communities; and provider type.

RESULTS

The differences in participation rates for rural versus suburban and versus urban communities ranged from -4% through 27% and -6% through 37%, respectively. The 2012 state median number of patients per provider for preventive care ranged from 99 through 358. The provider-level caseload increased from rural to urban and from other provider to general dentist to pediatric dentist. The difference in caseload from 2012 to 2013 was not statistically significant except for the pediatric dentist type.

CONCLUSIONS

This study's results suggest that the realized caseload for children enrolled in Medicaid varies according to provider type and urbanicity. The state median caseload for preventive care is lower than the 500:1 patient to provider ratio used as the minimum caseload in access estimates from other studies.

PRACTICAL IMPLICATIONS

This study's results can assist states in gauging the level of oral health care provided to children insured by Medicaid compared with that in other states, with implications for the specification of oral health policies.

Projecting the economic impact of silver diamine fluoride on caries treatment expenditures and outcomes in young U.S. children

OBJECTIVE

To quantify the economic impact of using silver diamine fluoride (SDF) to arrest the progression of dental caries in Medicaid-enrolled children (aged 1-5 years) relative to the standard restorative treatment from the Medicaid programs' perspective.

METHODS

We used Monte Carlo simulation to estimate averted restorative visits and associated expenditures for varying SDF effectiveness and intervention penetration levels. We compared the current standard of care for treating caries to applying SDF. We estimated expenditures from the 2010-2012 Medicaid Analytic Extract files for seven US states and the incremental cost effectiveness ratio for SDF application on averted restorative visits.

RESULTS

Across the seven states, averted restorative visits ranged from 2,049 (Vermont) to 60,542 (North Carolina), assuming an SDF penetration level of 50%. Averted per-restorative visit costs ranged from $100 to $350 per-visit. There were higher averted per-restorative visit costs in nonmetropolitan counties than metropolitan counties.

CONCLUSIONS

Providing SDF as a caries management strategy can reduce Medicaid program dental care expenditures by averting expensive caries treatment options. It could also prevent stressful restorative procedures. State Medicaid programs should consider reimbursing for SDF to arrest the progression of dental caries in young children.

Medicaid Claims for Contraception Among Women With Medical Conditions After Release of the US Medical Eligibility Criteria for Contraceptive Use

INTRODUCTION

The US Medical Eligibility Criteria for Contraceptive Use (MEC) identified 20 medical conditions that increase a woman's risk for adverse outcomes in pregnancy. MEC recommends that women with these conditions use long-acting, highly effective contraceptive methods. The objective of our study was to examine provision of contraception to women enrolled in Medicaid who had 1 or more of these 20 medical conditions METHODS: We used Medicaid Analytic Extract claims data to study Medicaid-enrolled women who were of reproductive age in the 2-year period before MEC's release (2008 and 2009) (N = 442,424) and the 2-year period after its release (2011 and 2012) (N = 533,619) for 14 states. We assessed 2 outcomes: provision of family planning management (FPM) and provision of highest efficacy methods (HEMs) for the entire study population and by health condition. The ratio of the after-MEC rate to the before-MEC rate was used to determine significance in MEC's uptake.

RESULTS

Outcomes increased significantly from the before-MEC period to the after-MEC period for both FPM (1.06; lower bound confidence interval [CI], 1.05) and HEM (1.37; lower bound CI, 1.36) for a 1-sided hypothesis test. For the 19 of 20 conditions we were able to test for FPM, contraceptive use increased significantly for 12 conditions, with ratios ranging from 1.05 to 2.14. For the 16 of 20 conditions tested for HEM, contraception use increased significantly for all conditions, with ratios ranging from 1.19 to 2.80.

CONCLUSION

Provision of both FPM and HEM increased significantly among women with high-risk health conditions from the before-MEC period (2008 and 2009) to the after-MEC period (2011 and 2012). Health policy makers and clinicians need to continue promotion of effective family planning management for women with high-risk conditions.

Adherence to Recommended Care Guidelines in the Treatment of Preschool-Age Medicaid-Enrolled Children With a Diagnosis of ADHD

OBJECTIVE

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood. Clinical guidelines recommend behavior therapy as the first-line treatment for preschool-age children with ADHD. This study evaluated longitudinal patterns of services received by Medicaid-enrolled children ages 2 to 5 with ADHD in seven southeastern states (Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, and South Carolina).

METHODS

A discrete sequence clustering analysis was used with 2005-2012 Medicaid Analytic eXtract data to profile patient-level utilization for each state, with a focus on receipt of psychological services and medication. The model output was used to assess utilization behaviors longitudinally relative to recommended care guidelines and to characterize sources of variation in utilization patterns by demographic and ecological factors.

RESULTS

Five states had a utilization profile with a high probability of receipt of psychological services before medication among children with ADHD, covering 16% of the total study population. Most young children's ADHD care experience in the seven states (65%) fit utilization profiles characterized by a high probability of receiving any ADHD medication. Black race was significantly associated with higher utilization of psychological services in three states.

CONCLUSIONS

About 16% of Medicaid-enrolled preschool-age children with ADHD received care during 2005-2012 that appeared to be consistent with 2011 recommended care guidelines. State-level and subpopulation variations in utilization for ADHD-related clinical care were found. The findings indicate that there were major gaps in treatment for ADHD among young children and that the gaps are wider for some states and subpopulations of children.

Asthma Prevalence Among Medicaid-Enrolled Children

BACKGROUND

Small-area asthma prevalence measures, which are crucial for targeting interventions, are currently sparsely available for children.

OBJECTIVE

To provide measures of in-contact asthma prevalence for the 2012 Medicaid child population so as to highlight areas in need of targeted asthma interventions.

METHODS

Using the 2012 Medicaid Analytic eXtract claims files, we developed 2 prevalence metrics differentiated by persistent and diagnosed asthma. We developed prevalence measures at the state, county, and census tract levels, with statistical inferences to highlight areas of high prevalence where interventions should be focused. We compared the measures with asthma prevalence estimates derived from a sample of the child population that self-reported whether they have been diagnosed with asthma regardless of in-contact asthma.

RESULTS

A total of 1.98 million (8.1%) and 1.71 million (6.9%) Medicaid-enrolled children were identified with in-contact asthma diagnosis and persistent asthma, respectively. Among 40 states, 17 had lower prevalence estimates for the Medicaid-enrolled children compared with similar child asthma self-reported prevalence estimates from the Centers for Disease Control and Prevention. High-prevalence regions spanned primarily in the southern Midwest region, from Texas to West Virginia and from Illinois to north Florida.

CONCLUSION

There are large variations in the differences between the self-reported estimates from the Centers for Disease Control and Prevention for the general population and the in-contact estimates for the Medicaid-enrolled children, highlighting potential asthma misdiagnosis in the Medicaid population in many states. Small-area estimates point to areas of high prevalence, consistently throughout the south and southeast.

Estimating the Cost Savings of Preventive Dental Services Delivered to Medicaid-Enrolled Children in Six Southeastern States

OBJECTIVE

To quantify the impact of multiyear utilization of preventive dental services on downstream dental care utilization and expenditures for children.

DATA SOURCES/STUDY SETTING

We followed 0.93 million Medicaid-enrolled children who were 3-6 years old in 2005 from 2005 to 2011. We used Medicaid claims data of Alabama, Georgia, Mississippi, North Carolina, South Carolina, and Texas.

STUDY DESIGN

We clustered each state's study population into four groups based on utilization of topical fluoride and dental sealants before caries-related treatment using machine learning algorithms. We evaluated utilization rates and expenditures across the four groups and quantified cost savings of preventive care for different levels of penetration.

DATA EXTRACTION METHOD

We extracted all dental-related claims using CDT codes.

PRINCIPAL FINDINGS

In all states, Medicaid expenditures were much lower for children who received topical fluoride and dental sealants before caries development than for all other children, with a per-member per-year difference ranging from $88 for Alabama to $156 for Mississippi.

CONCLUSIONS

The cost savings from topical fluoride and sealants across the six states ranged from $1.1M/year in Mississippi to $12.9M/year in Texas at a 10 percent penetration level. Preventive dental care for children not only improves oral health outcomes but is also cost saving.

ADA Health Policy Institute's methodology overestimates spatial access to dental care for publicly insured children

OBJECTIVE

This article discusses the sources of overestimation of spatial access as recently provided by the Health Policy Institute (HPI) of the American Dental Association.

METHODS

Sources of overestimation of access included estimation of Medicaid participation and capacity and limitations of the access measurement approach.

RESULTS

While the HPI analysis used a 30% Medicaid acceptance rate for Florida, 10.2% of dentists accepted ≥100 Medicaid patients in 2015. The nationwide median number of Medicaid-enrolled children per provider ranges from 36 (Nebraska) to 265 (Florida). HPI estimated that 94% of publicly insured children in Georgia lived within 15 minutes of participating dentists. More rigorous modeling for access estimated that 23% of the total child population do not have access within the state access standards in Georgia.

CONCLUSIONS

The estimates provided by HPI substantially overestimate access for children with public insurance. The overestimation comes from both the data limitations and the shortcomings of the methodology employed.

High-dimensional multivariate additive regression for uncovering contributing factors to healthcare expenditure

Many studies in health services research rely on regression models with a large number of covariates or predictors. In this article, we introduce novel methodology to estimate and perform model selection for high-dimensional non-parametric multivariate regression problems, with application to many healthcare studies. We particularly focus on multi-responses or multi-task regression models. Because of the complexity of the dependence between predictors and the multiple responses, we exploit model selection approaches that consider various level of groupings between and within responses. The novelty of the method lies in its ability to account simultaneously for between and within group sparsity in the presence of non-linear effects. We also propose a new set of algorithms that can identify inactive and active predictors that are common to all responses or to a subset of responses. Our modeling approach is applied to uncover factors that impact healthcare expenditure for children insured through the Medicaid benefits program. We provide important findings on the association between healthcare expenditure and a large number of well-cited factors for two neighboring states, Georgia and North Carolina, which have similar demographics but different Medicaid systems. We also validate our methods with a benchmark cancer data set and simulated data examples.

Quantifying Disparities in Accessibility and Availability of Pediatric Primary Care across Multiple States with Implications for Targeted Interventions

OBJECTIVE

To quantify disparities in accessibility and availability of pediatric primary care by modeling interventions across multiple states that compare publicly insured versus privately insured children, and urban versus rural communities.

DATA SOURCES

Secondary data sources include 2013 National Plan and Provider Enumeration System, 2009 MAX Medicaid claims, 2012 American Community Survey.

STUDY DESIGN

The study models accessibility and availability of care for all children in seven states.

METHODS

Optimization modeling with access constraints is used to estimate access. Statistical hypothesis testing is used to quantify systematic disparities.

PRINCIPAL FINDINGS

California has the best accessibility for privately insured children and Minnesota for publicly insured children. Mississippi has the lowest availability for both populations. Overall, the disparities in availability for pediatric primary care are not as significant as in accessibility. Both rural and urban communities are in need of improvement in accessibility to primary care for publicly insured children, although at varying levels across states.

CONCLUSIONS

Disparities in availability are not as significant as disparities in accessibility. Opportunities to improve access to pediatric primary care vary by state. Generating specific recommendations for small areas is critical to enabling health policy decision makers to improvement access.

Does distance to a cystic fibrosis center impact health outcomes?

INTRODUCTION

This paper considers the impact of geographic distance from cystic fibrosis centers on lung function in children, young adults, and adults with cystic fibrosis.

METHODS

Clinical patient-level data on 20 351 patients from 1986 to 2011 were evaluated from the Cystic Fibrosis Foundation National Patient Registry. We measure distance using a patient's zip code centroid to the center where they received care. A heteroscedastic mixed effects model was used to capture the association of distance with longitudinal variation in patients' lung function.

RESULTS

Children, young adults, and adults in lower socioeconomic categories had a %FEV₁ between 3 and 10 percentage-points lower than those living in higher income areas and those privately insured. For patients who changed distance categories, high distance was associated with lower lung function in young adults (P-value <0.001). For older patients we observed the reverse, suggesting that the choice to move farther away is associated with better health (P-value <0.001). For patients who did not change distance categories, only medium distance in children was significant (P-value = 0.01). Known confounding factors including age and CFTR mutation class were statistically significantly associated to health outcomes (P-value <0.001).

CONCLUSIONS

This study shows distance is not found to be associated with health lung function among patients whose distance category remained unchanged during the analysis. For patients who move, the association of health with distance depends on the age of the patient; adult patients further from their care center are healthier. Overall, we find that socioeconomic and genetic factors appear to impact health outcomes to a greater extent.

Uncovering Longitudinal Health Care Behaviors for Millions of Medicaid Enrollees: A Multistate Comparison of Pediatric Asthma Utilization

BACKGROUND

This study introduces a framework for analyzing and visualizing health care utilization for millions of children, with a focus on pediatric asthma, one of the major chronic respiratory conditions.

METHODS

The data source is the 2005 to 2012 Medicaid Analytic Extract claims for 10 Southeast states. The study population consists of Medicaid-enrolled children with persistent asthma. We translate multiyear, individual-level medical claims into sequences of discrete utilization events, which are modeled using Markov renewal processes and model-based clustering. Network analysis is used to visualize utilization profiles. The method is general, allowing the study of other chronic conditions.

RESULTS

The study population consists of 1.5 million children with persistent asthma. All states have profiles with high probability of asthma controller medication, as large as 60.6% to 90.2% of the state study population. The probability of consecutive asthma controller prescriptions ranges between 0.75 and 0.95. All states have utilization profiles with uncontrolled asthma with 4.5% to 22.9% of the state study population. The probability for controller medication is larger than for short-term medication after a physician visit but not after an emergency department (ED) visit or hospitalization. Transitions from ED or hospitalization generally have a lower probability into physician office (between 0.11 and 0.38) than into ED or hospitalization (between 0.20 and 0.59).

CONCLUSIONS

In most profiles, children who take asthma controller medication do so regularly. Follow-up physician office visits after an ED encounter or hospitalization are observed at a low rate across all states. Finally, all states have a proportion of children who have uncontrolled asthma, meaning they do not take controller medication while they have severe outcomes.

Disparities in Preventive Dental Care Among Children in Georgia

INTRODUCTION

We compared access to preventive dental care among low-income children eligible for public dental insurance to access among children with private dental insurance and/or high family income (>400% of the federal poverty level) in Georgia, and the effect of policies toward increasing access to dental care for low-income children.

METHODS

We used multiple sources of data (eg, US Census, Georgia Board of Dentistry) to estimate, by census tract, measures of preventive dental care access in 2015 for children aged 0 to 18 years. Measures were percentage of met need, 1-way travel distance to a dentist, and scarcity of dentists. We used an optimization model to estimate access, quantify disparities, and evaluate policies.

RESULTS

About 1.5 million children were eligible for public insurance; 600,000 had private insurance and/or high family income. Across census tracts, average met need was 59% for low-income children and 96% for high-income children; for rural census tracts, these values were 33% and 84%, respectively. The average 1-way travel distance for all census tracts was 3.7 miles for high-income and/or privately insured children and 17.2 miles for low-income children; for rural census tracts, these values were 11.6 and 32.9 miles, respectively. Increasing dentists' acceptance of public insurance-eligible children increased met need more in rural areas than in urban areas. To achieve 100% met need in rural tracts, however, an 80% participation rate among dentists would be required.

CONCLUSION

Across census tracts, high-income children had better access to preventive dental care than low-income children had. Identifying tracts with disparities in access could result in more efficient allocation of public health dental resources.

Modeling Heterogeneity in Healthcare Utilization Using Massive Medical Claims Data

We introduce a modeling approach for characterizing heterogeneity in healthcare utilization using massive medical claims data. We first translate the medical claims observed for a large study population and across five years into individual-level discrete events of care called utilization sequences. We model the utilization sequences using an exponential proportional hazards mixture model to capture heterogeneous behaviors in patients' healthcare utilization. The objective is to cluster patients according to their longitudinal utilization behaviors and to determine the main drivers of variation in healthcare utilization while controlling for the demographic, geographic, and health characteristics of the patients. Due to the computational infeasibility of fitting a parametric proportional hazards model for high-dimensional, large sample size data we use an iterative one-step procedure to estimate the model parameters and impute the cluster membership. The approach is used to draw inferences on utilization behaviors of children in the Medicaid system with persistent asthma across six states. We conclude with policy implications for targeted interventions to improve adherence to recommended care practices for pediatric asthma.

The cost-effectiveness of three interventions for providing preventive services to low-income children

OBJECTIVE

We evaluated the impact of loan repayment programmes, revising Medicaid fee-for-service rates, and changing dental hygienist supervision requirements on access to preventive dental care for children in Georgia.

METHODS

We estimated cost savings from the three interventions of preventive care for young children after netting out the intervention cost. We used a regression model to evaluate the impact of changing the Medicaid reimbursement rates. The impact of supervision was evaluated by comparing general and direct supervision in school-based dental sealant programmes.

RESULTS

Federal loan repayments to dentists and school-based sealant programmes (SBSPs) had lower intervention costs (with higher potential cost savings) than raising the Medicaid reimbursement rate. General supervision had costs 56% lower than direct supervision of dental hygienists for implementing a SBSP. Raising the Medicaid reimbursement rate by 10 percentage points would improve utilization by <1% and cost over $38 million. Given one parameter set, SBSPs could serve over 27 000 children with an intervention cost between $500 000 and $1.3 million with a potential cost saving of $1.1 million. Loan repayment could serve almost 13 000 children for a cost of $400 000 and a potential cost saving of $176 000.

CONCLUSIONS

The three interventions all improved met need for preventive dental care. Raising the reimbursement rate alone would marginally affect utilization of Medicaid services but would not substantially increase acceptance of Medicaid by providers. Both loan repayment programmes and amending supervision requirements are potentially cost-saving interventions. Loan repayment programmes provide complete care to targeted areas, while amending supervision requirements of dental hygienists could provide preventive care across the state.

Estimating Demand for and Supply of Pediatric Preventive Dental Care for Children and Identifying Dental Care Shortage Areas, Georgia, 2015

OBJECTIVES

Demand for dental care is expected to outpace supply through 2025. The objectives of this study were to determine the extent of pediatric dental care shortages in Georgia and to develop a general method for estimation that can be applied to other states.

METHODS

We estimated supply and demand for pediatric preventive dental care for the 159 counties in Georgia in 2015. We compared pediatric preventive dental care shortage areas (where demand exceeded twice the supply) designated by our methods with dental health professional shortage areas designated by the Health Resources & Services Administration. We estimated caries risk from a multivariate analysis of National Health and Nutrition Examination Survey data and national census data. We estimated county-level demand based on the time needed to perform preventive dental care services and the proportion of time that dentists spend on pediatric preventive dental care services from the Medical Expenditure Panel Survey.

RESULTS

Pediatric preventive dental care supply exceeded demand in Georgia in 75 counties: the average annual county-level pediatric preventive dental care demand was 16 866 hours, and the supply was 32 969 hours. We identified 41 counties as pediatric dental care shortage areas, 14 of which had not been designated by the Health Resources & Services Administration.

CONCLUSIONS

Age- and service-specific information on dental care shortage areas could result in more efficient provider staffing and geographic targeting.

Projecting the Impact of the Affordable Care Act Provisions on Accessibility and Availability of Primary Care Providers for the Adult Population in Georgia

OBJECTIVES

To evaluate how met need for accessibility and availability of primary care among nonelderly individuals in Georgia will be affected by the Patient Protection and Affordable Care Act (ACA) over the next 10 years.

METHODS

We used a stock-and-flow model to predict the number of available visits from 2013 to 2025, regression models to project needed visits, and an optimization model to estimate met need. The outputs of these models were used to estimate unmet need and the availability and accessibility of primary care.

RESULTS

Our findings showed that the number of primary care providers will increase by 9.2% to 11.7% by 2025 and that the number of needed visits will increase by 20%. Under Medicaid expansion, the percentage of met need will increase from 67% to 80%. Accessibility will improve by 20% under expansion, and availability will decrease by 13% to 19% under expansion.

CONCLUSIONS

The ACAs' provisions will reduce unmet need and positively affect accessibility while reducing availability in some communities. Increased need because of a larger Medicaid population under Medicaid expansion will not be a significant burden on the privately insured population.

An optimization framework for measuring spatial access over healthcare networks

BACKGROUND

Measurement of healthcare spatial access over a network involves accounting for demand, supply, and network structure. Popular approaches are based on floating catchment areas; however the methods can overestimate demand over the network and fail to capture cascading effects across the system.

METHODS

Optimization is presented as a framework to measure spatial access. Questions related to when and why optimization should be used are addressed. The accuracy of the optimization models compared to the two-step floating catchment area method and its variations is analytically demonstrated, and a case study of specialty care for Cystic Fibrosis over the continental United States is used to compare these approaches.

RESULTS

The optimization models capture a patient's experience rather than their opportunities and avoid overestimating patient demand. They can also capture system effects due to change based on congestion. Furthermore, the optimization models provide more elements of access than traditional catchment methods.

CONCLUSIONS

Optimization models can incorporate user choice and other variations, and they can be useful towards targeting interventions to improve access. They can be easily adapted to measure access for different types of patients, over different provider types, or with capacity constraints in the network. Moreover, optimization models allow differences in access in rural and urban areas.

The effect of geographic access on severe health outcomes for pediatric asthma

BACKGROUND

Access to medical care and severe pediatric asthma outcomes vary with geography, but the relationship between them has not been studied.

OBJECTIVE

We sought to evaluate the relationship between geographic access and health outcomes for pediatric asthma.

METHODS

The severe outcome measures include emergency department (ED) visits and hospitalizations for children with an asthma diagnosis in Georgia and North Carolina. We quantify asthma prevalence, outcome measures, and factors included in the statistical model using multiple data sources. We calculate geographic access to primary and asthma specialist care using optimization models. We estimate the association between outcomes and geographic access in the presence of other factors using logistic regression. The model is used to project the reduction in severe outcomes with improvement in access.

RESULTS

The association between access and outcomes for pediatric asthma depends on the type of outcome measure, type of care, and variations in other factors. The expression of this association is also different for the 2 states. Access to primary care plays a larger role than access to specialist care in explaining Georgia ED visits, whereas the reverse applies for hospitalizations. In North Carolina access to both primary and specialist care are statistically significant in explaining the variability in ED visits.

CONCLUSIONS

The variation in the association between estimated access and outcomes affects the projected reductions of severe outcomes with access improvement. Thus applying one intervention would not have the same level of improvement across geography. Interventions must be tailored to target regions with the potential to deliver the highest effect to gain maximum benefit.

Estimating prevalence of overweight or obese children and adolescents in small geographic areas using publicly available data

Introduction

Interventions for pediatric obesity can be geographically targeted if high-risk populations can be identified. We developed an approach to estimate the percentage of overweight or obese children aged 2 to 17 years in small geographic areas using publicly available data. We piloted our approach for Georgia.

Methods

We created a logistic regression model to estimate the individual probability of high body mass index (BMI), given data on the characteristics of the survey participants. We combined the regression model with a simulation to sample subpopulations and obtain prevalence estimates. The models used information from the 2001–2010 National Health and Nutrition Examination Survey, the 2010 Census, and the 2010 American Community Survey. We validated our results by comparing 1) estimates for adults in Georgia produced by using our approach with estimates from the Centers for Disease Control and Prevention (CDC) and 2) estimates for children in Arkansas produced by using our approach with school examination data. We generated prevalence estimates for census tracts in Georgia and prioritized areas for interventions.

Results

In DeKalb County, the mean prevalence among census tracts varied from 27% to 40%. For adults, the median difference between our estimates and CDC estimates was 1.3 percentage points; for Arkansas children, the median difference between our estimates and examination-based estimates data was 1.7 percentage points.

Conclusion

Prevalence estimates for census tracts can be different from estimates for the county, so small-area estimates are crucial for designing effective interventions. Our approach validates well against external data, and it can be a relevant aid for planning local interventions for children.

Understanding variations in pediatric asthma care processes in the emergency department using visual analytics

Health care delivery processes consist of complex activity sequences spanning organizational, spatial, and temporal boundaries. Care is human-directed so these processes can have wide variations in cost, quality, and outcome making systemic care process analysis, conformance testing, and improvement challenging. We designed and developed an interactive visual analytic process exploration and discovery tool and used it to explore clinical data from 5784 pediatric asthma emergency department patients.

Multilevel cross-dependent binary longitudinal data

We provide insights into new methodology for the analysis of multilevel binary data observed longitudinally, when the repeated longitudinal measurements are correlated. The proposed model is logistic functional regression conditioned on three latent processes describing the within- and between-variability, and describing the cross-dependence of the repeated longitudinal measurements. We estimate the model components without employing mixed-effects modeling but assuming an approximation to the logistic link function. The primary objectives of this article are to highlight the challenges in the estimation of the model components, to compare two approximations to the logistic regression function, linear and exponential, and to discuss their advantages and limitations. The linear approximation is computationally efficient whereas the exponential approximation applies for rare events functional data. Our methods are inspired by and applied to a scientific experiment on spectral backscatter from long range infrared light detection and ranging (LIDAR) data. The models are general and relevant to many new binary functional data sets, with or without dependence between repeated functional measurements.

Evaluation of telemedicine for screening of diabetic retinopathy in the Veterans Health Administration

OBJECTIVE

To explore the cost-effectiveness of telemedicine for the screening of diabetic retinopathy (DR) and identify changes within the demographics of a patient population after telemedicine implementation.

DESIGN

A retrospective medical chart review (cohort study) was conducted.

PARTICIPANTS

A total of 900 type 1 and type 2 diabetic patients enrolled in a medical system with a telemedicine screening program for DR.

METHODS

The cost-effectiveness of the DR telemedicine program was determined by using a finite-horizon, discrete time, discounted Markov decision process model populated by parameters and testing frequency obtained from patient records. The model estimated the progression of DR and determined average quality-adjusted life years (QALYs) saved and average additional cost incurred by the telemedicine screening program.

MAIN OUTCOME MEASURES

Diabetic retinopathy, macular edema, blindness, and associated QALYs.

RESULTS

The results indicate that telemedicine screening is cost-effective for DR under most conditions. On average, it is cost-effective for patient populations of >3500, patients aged <80 years, and all racial groups. Observable trends were identified in the screening population since the implementation of telemedicine screening: the number of known DR cases has increased, the overall age of patients receiving screenings has decreased, the percentage of nonwhites receiving screenings has increased, the average number of miles traveled by a patient to receive a screening has decreased, and the teleretinal screening participation is increasing.

CONCLUSIONS

The current teleretinal screening program is effective in terms of being cost-effective and increasing population reach. Future screening policies should give consideration to the age of patients receiving screenings and the system's patient pool size because our results indicate it is not cost-effective to screen patients aged older than 80 years or in populations with <3500 patients.