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.

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 18th-November 24th, 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.

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.

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.

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.

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.

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.

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.

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.

Quantifying and explaining accessibility with application to the 2009 H1N1 vaccination campaign.

Accessibility and equity across populations are important measures in public health. This paper is specifically concerned with potential spatial accessibility, or the opportunity to receive care as moderated by geographic factors, and with horizontal equity, or fairness across populations regardless of need. Both accessibility and equity were goals of the 2009 vaccination campaign for the novel H1N1a influenza virus, including during the period when demand for vaccine exceeded supply. Distribution system design can influence equity and accessibility at the local level. We develop a general methodology that integrates optimization, game theory, and spatial statistics to measure potential spatial accessibility across a network, where we quantify spatial accessibility by travel distance and scarcity. We estimate and make inference on local (census-tract level) associations between accessibility and geographic, socioeconomic, and health care infrastructure factors to identify potential inequities in vaccine accessibility during the 2009 H1N1 vaccination campaign in the U.S. We find that there were inequities in access to vaccine at the local level and that these were associated with factors including population density and health care infrastructure. Our methodology for measuring and explaining accessibility leads to policy recommendations for federal, state, and local public health officials. The spatial-specific results inform the development of equitable distribution plans for future public health efforts.

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.

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.

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.

Small-Area Estimation of Spatial Access to Care and Its Implications for Policy.

Local or small-area estimates to capture emerging trends across large geographic regions are critical in identifying and addressing community-level health interventions. However, they are often unavailable due to lack of analytic capabilities in compiling and integrating extensive datasets and complementing them with the knowledge about variations in state-level health policies. This study introduces a modeling approach for small-area estimation of spatial access to pediatric primary care that is data "rich" and mathematically rigorous, integrating data and health policy in a systematic way. We illustrate the sensitivity of the model to policy decision making across large geographic regions by performing a systematic comparison of the estimates at the census tract and county levels for Georgia and California. Our results show the proposed approach is able to overcome limitations of other existing models by capturing patient and provider preferences and by incorporating possible changes in health policies. The primary finding is systematic underestimation of spatial access, and inaccurate estimates of disparities across population and across geography at the county level with respect to those at the census tract level with implications on where to focus and which type of interventions to consider.

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.

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.

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.

Dental care access for children in the United States.

OBJECTIVES: To evaluate access to dental care for children in the United States. METHODS: The study population included children in 48 states and the District of Columbia. Using multiple data sources, dental care access was estimated at the community level by matching dental care supply and demand using mathematical modeling accounting for access constraints. Outcome measures included percent-met demand, travel distance, and percentage of underserved and unserved communities. Multiple scenarios to improve Medicaid/CHIP participation of dentists were evaluated. RESULTS: Medicaid-insured and CHIP-insured children exhibited lower access compared to those privately insured. The percent-met demand was lower than 50% for Medicaid-insured children and CHIP-insured children for 42 and 34 states, respectively. Percent-met demand was higher than 50% for private-insured children except for Texas and West Virginia. Increasing Medicaid/CHIP participation of dentists resulted in improving access for public-insured children. At 100% Medicaid/CHIP participation, all states exhibited different degrees of percent-met demand increase for publicly insured children, from 7% to 46%. The percent-met demand across all children ranged in 23.8%-82.9% under 70% participation rate versus 22%-83% under 100% participation rate. No single participation rate improved access for all children uniformly across all states. CONCLUSIONS: This study found that dental care access was lower for children with public insurance than those with private access across all states, although states responded differently to changes in Medicaid/CHIP participation. Increasing access for children with public insurance would reduce disparities, but overall children's access to dental care would be better improved by expanding the oral health workforce.

Consensus-based recommendations for diagnosis and surgical management of cranioplasty and post-traumatic hydrocephalus from a European panel.

Introduction: Planning cranioplasty (CPL) in patients with suspected or proven post-traumatic hydrocephalus (PTH) poses a significant management challenge due to a lack of clear guidance. Research question: This project aims to create a European document to improve adherence and adapt to local protocols based on available resources and national health systems. Methods: After a thorough non-systematic review, a steering committee (SC) formed a European expert panel (EP) for a two-round questionnaire using the Delphi method. The questionnaire employed a 9-point Likert scale to assess the appropriateness of statements inherent to two sections: "Diagnostic criteria for PTH" and "Surgical strategies for PTH and cranial reconstruction." Results: The panel reached a consensus on 29 statements. In the "Diagnostic criteria for PTH" section, five statements were deemed "appropriate" (consensus 74.2-90.3 %), two were labeled "inappropriate," and seven were marked as "uncertain."In the "Surgical strategies for PTH and cranial reconstruction" section, four statements were considered "appropriate" (consensus 74.2-90.4 %), six were "inappropriate," and five were "uncertain." Discussion and conclusion: Planning a cranioplasty alongside hydrocephalus remains a significant challenge in neurosurgery. Our consensus conference suggests that, in patients with cranial decompression and suspected hydrocephalus, the most suitable diagnostic approach involves a combination of evolving clinical conditions and neuroradiological imaging. The recommended management sequence prioritizes cranial reconstruction, with the option of a ventriculoperitoneal shunt when needed, preferably with a programmable valve. We strongly recommend to adopt local protocols based on expert consensus, such as this, to guide patient care.

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.