Impact of the Affordable Care Act on Insurance Status of Spine Patients Presenting to the Emergency Department.

Although the Affordable Care Act (ACA) has been shown to broadly affect access to care, there is little data examining the change in insurance status with regard to nonelective spinal trauma, infection, and tumor patients. The purpose of this study is to evaluate the changes in insurance status before and after implementation of the ACA in patients who present to the emergency room of a single, level 1 trauma and regional spinal cord injury center. Patient demographic and hospital course information were derived from consult notes and electronic medical record review. Spinal consults between January 1, 2013, and December 31, 2015, were initially included. Consults between January 1 and December 31, 2014, were subsequently removed to obtain two separate cohorts reflecting one calendar year prior to ("pre-ACA") and following ("post-ACA") the effective date of implementation of the ACA on January 1, 2014. Compared with the pre-ACA cohort, the post-ACA cohort had a significant increase in insurance coverage (95.0% versus 83.9%, P < 0.001). Post-ACA consults had a significantly shorter length of stay compared with pre-ACA consults (7.94 versus 9.19, P < 0.001). A significantly greater percentage of the post-ACA cohort appeared for clinical follow-up subsequent to their initial consultation compared to the pre-ACA cohort (49.5% versus 35.3%, P < 0.001). Spinal consultation after the implementation of the ACA was found to be a significant positive predictor of Medicaid coverage (odds ratio = 1.96 [1.05, 3.82], P = 0.04) and a significant negative predictor of uninsured status (odds ratio = 0.28 [0.16, 0.47], P < 0.001). Increase in overall insurance coverage, increase in patient follow-up after initial consultation, and decrease in hospital length of stay were all noted after the implementation of the ACA for spinal consultation patients presenting to the emergency department.

On collaborative reinforcement learning to optimize the redistribution of critical medical supplies throughout the COVID-19 pandemic.

OBJECTIVE: This work investigates how reinforcement learning and deep learning models can facilitate the near-optimal redistribution of medical equipment in order to bolster public health responses to future crises similar to the COVID-19 pandemic. MATERIALS AND METHODS: The system presented is simulated with disease impact statistics from the Institute of Health Metrics, Centers for Disease Control and Prevention, and Census Bureau. We present a robust pipeline for data preprocessing, future demand inference, and a redistribution algorithm that can be adopted across broad scales and applications. RESULTS: The reinforcement learning redistribution algorithm demonstrates performance optimality ranging from 93% to 95%. Performance improves consistently with the number of random states participating in exchange, demonstrating average shortage reductions of 78.74 ± 30.8% in simulations with 5 states to 93.50 ± 0.003% with 50 states. CONCLUSIONS: These findings bolster confidence that reinforcement learning techniques can reliably guide resource allocation for future public health emergencies.

Life-cycle assessment of sewage sludge-based large-scale biogas plant.

The aim of this work was to study the life-cycle assessment (LCA) and impact of a biogas plant based on the municipal sewage sludge (6000 m3 capacity biogas plant at Wastewater Treatment Plant (WWTP), Delawas, Jaipur - Rajasthan, India), analyzing the environmental effects instigated due to basic systems of biogas production and also to examine the impact of using biogas as an alternate fuel using ReCiPe and midpoint methods. The results indicatedthat the construction of plant was insignificant to the whole life cycle impacts. Biogas plant showed negative GHG emissions (-0.2385 kg CO2 eq/m3) compared to coal-based electricity plants and digestate produced could be a good option to replace chemical fertilizer. Biogas production and agricultural spreading contributed -3.059E-08 kg CFC-11 eq/m3 towards beneficial effects which may be attributed to the avoidance of electricity and artificial fertilizers. The results indicated that sewage sludge-based biogas plant showed beneficial impact on the environment.

Mental Health Issues in Madhya Pradesh: Insights from National Mental Health Survey of India 2016.

BACKGROUND: About 14% of the global mental health burden is contributed by India. However, there exists a disparity in mental health patterns, utilization, and prioritization among various Indian states. The state of Madhya Pradesh is a low performer among Indian states, ranking lower than the national average on the Human Development Index, Hunger Index, and Gross Domestic Product (GDP). The state also performes poorly on other health-related indicators. Objectives of Study: To estimate the prevalence and patterns of mental illnesses in the state of Madhya Pradesh, India. MATERIAL AND METHODS: This study used the multistage, stratified, random cluster sampling technique, with selection probability proportionate to size at each stage. A total of 3240 individuals 18 years and older were interviewed. The mixed-method study that was employed had both quantitative and qualitative components. The Mini International Neuropsychiatric Interview along with 10 other instruments were used. RESULTS: The overall weighted prevalence for any mental illness was 13.9%, with 16.7% over the lifetime. The treatment gap for all of the mental health problems is very high (91%), along with high suicidal risk and substance use in the state. CONCLUSIONS: This study provides evidence of the huge burden of mental, behavioral, and substance use disorders as well as the treatment gap in Madhya Pradesh. This information is crucial for developing an effective prevention and control strategy. The high treatment gap in the state calls for coordinated efforts from all stakeholders, including policy makers, political leaders, health care professionals, and the society at large to give mental health care its due priority. These findings also highlight the need for multi-pronged interventions rooted in health policy directed at reducing the treatment gap in the short term and disease burden in the long run.

Isoniazid Preventive Therapy among Children Living with Tuberculosis Patients: Is It Working? A Mixed-Method Study from Bhopal, India.

Objective: We assessed uptake of isoniazid preventive therapy (IPT) among child contacts of smear-positive tuberculosis (TB) patients and its implementation challenges from healthcare providers' and parents' perspectives in Bhopal, India. Methods: A mixed-method study design: quantitative phase (review of programme records and house-to-house survey of smear-positive TB patients) followed by qualitative phase (interviews of healthcare providers and parents). Results: Of 59 child contacts (<6 years) of 129 index patients, 51 were contacted. Among them, 19 of 51 (37%) were screened for TB and one had TB. Only 11 of 50 (22%) children were started and 10 of 50 (20%) completed IPT. Content analysis of interviews revealed lack of awareness, risk perception among parents, cumbersome screening process, isoniazid stock-outs, inadequate knowledge among healthcare providers and poor programmatic monitoring as main barriers to IPT implementation. Conclusion: National TB programme should counsel parents, train healthcare providers, simplify screening procedures, ensure regular drug supply and introduce an indicator to strengthen monitoring and uptake of IPT.