Closing the gap: Improving access to trauma care in New Mexico (2007-2017).

BACKGROUND: Trauma is a major cause of death and disability in the United States, and significant disparities exist in access to care, especially in non-urban settings. From 2007 to 2017 New Mexico expanded its trauma system by focusing on building capacity at the hospital level. METHODS: We conducted a geospatial analysis at the census block level of access to a trauma center in New Mexico within 1 h by ground or air transportation for the years 2007 and 2017. We then examined the characteristics of the population with access to care. A multiple logistic regression model assessed for remaining disparities in access to trauma centers in 2017. RESULTS: The proportion of the population in New Mexico with access to a trauma center within 1 h increased from 73.8% in 2007 to 94.8% in 2017. The largest increases in access to trauma care within 1 h were found among American Indian/Alaska Native populations (AI/AN) (35.2%) and people living in suburban areas (62.9%). In 2017, the most rural communities (aOR 58.0), communities on an AI/AN reservation (aOR 25.6), communities with a high proportion of Hispanic/Latino persons (aOR 8.4), and a high proportion of elderly persons (aOR 3.2) were more likely to lack access to a trauma center within 1 h. CONCLUSION: The New Mexico trauma system expansion significantly increased access to trauma care within 1 h for most of New Mexico, but some notable disparities remain. Barriers persist for very rural parts of the state and for its sizable American Indian community.

Transcranial Electrical Neuromodulation Based on the Reciprocity Principle.

A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.