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In 2018, the National Center for Healthcare Leadership (NCHL) published a new version of its health leadership competency model (v.3.0). Accredited graduate programs interested in transitioning to the new model will need to map this model to the Commission on Accreditation of Healthcare Management Education (CAHME) domains as part of their self-study process. The present study was pursued to ensure consistency in mapping the new NCHL competencies to the CAHME domains, and to offer guidance on the mapping process for future model users. To accomplish this, faculty from three different CAHME-accredited graduate programs, each familiar with the NCHL model through their own work, conducted independent crosswalks of each of the new NCHL competencies and the CAHME domains. We then compared results, and any resolved discrepancies through a consensus discussion. Through this exercise, we found that human raters were able to reliably match NCHL competencies to the CAHME domains. A table of our results is provided as a resource for program directors for the CAHME self-study process.

In 2018, the National Center for Healthcare Leadership (NCHL) published a new version of its health leadership competency model (v.3.0). Accredited graduate programs interested in transitioning to the new model will need to map this model to the Commission on Accreditation of Healthcare Management Education (CAHME) domains as part of their self-study process. The present study was pursued to ensure consistency in mapping the new NCHL competencies to the CAHME domains, and to offer guidance on the mapping process for future model users. To accomplish this, faculty from three different CAHME-accredited graduate programs, each familiar with the NCHL model through their own work, conducted independent crosswalks of each of the new NCHL competencies and the CAHME domains. We then compared results, and any resolved discrepancies through a consensus discussion. Through this exercise, we found that human raters were able to reliably match NCHL competencies to the CAHME domains. A table of our results is provided as a resource for program directors for the CAHME self-study process.

Although informatics trainees and practitioners who assume operational computing roles in their organization may have reasonably advanced understanding of theoretical informatics, many are unfamiliar with the practical topics - such as downtime procedures, interface engines, user support, JCAHO compliance, and budgets - which will become.

There are three forces behind the sea change in adoption of health information technology (HIT). The inciting event was the 2007 global economic recession. This led to passage of ARRA, the American Recovery and Reinvestment Act in 2009. The second driving force from a legislative perspective is PPACA, the Patient Protection and Affordable Care Act (aka “Obamacare”). The third driver of the rapid adoption of HIT involves both the nature of information and communication technology itself as well as how people are choosing to use these tools. One core theme is the movement towards “mobile health.” Smartphones and connected tablets are increasingly supplanting desktop and laptop computers as the device of choice for both consumers and providers of healthcare. The remainder of this chapter proposes several sets of lenses through which you might look at how to best develop those opportunities. We’ll begin with an update to what we know about the current and future state of the workforce and then review a range of resources you might explore, including educational programs, competencies, certifications, and professional organizations.

Public Health Informatics (PHI) education began at the University of Washington (UW) with a Summer Institute in 1995. The Biomedical and Health Informatics graduate program, which is housed in the School of Medicine, is an interdisciplinary, multi-school program. It demonstrates the UW's cooperative efforts in advancing informatics, encompassing the schools of public health, medicine, nursing, dentistry, pharmacy, information and graduate schools in computer science. This article provides an overview of the developmental milestones related to activities in PHI and describes the evaluation strategy and assessment plan for PHI training at the UW (http://phig.Washington.edu).

In an interim analysis of this phase 3 trial, the addition of pembrolizumab to chemotherapy resulted in longer progression-free survival than chemotherapy alone among patients with advanced triple-negative breast cancer whose tumors expressed programmed death ligand 1 (PD-L1) with a combined positive score (CPS; the number of PD-L1-staining tumor cells, lymphocytes, and macrophages, divided by the total number of viable tumor cells, multiplied by 100) of 10 or more. The results of the final analysis of overall survival have not been reported. We randomly assigned patients with previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer in a 2:1 ratio to receive pembrolizumab (200 mg) every 3 weeks plus the investigator's choice of chemotherapy (nanoparticle albumin-bound paclitaxel, paclitaxel, or gemcitabine-carboplatin) or placebo plus chemotherapy. The primary end points were progression-free survival (reported previously) and overall survival among patients whose tumors expressed PD-L1 with a CPS of 10 or more (the CPS-10 subgroup), among patients whose tumors expressed PD-L1 with a CPS of 1 or more (the CPS-1 subgroup), and in the intention-to-treat population. Safety was also assessed. A total of 847 patients underwent randomization: 566 were assigned to the pembrolizumab-chemotherapy group, and 281 to the placebo-chemotherapy group. The median follow-up was 44.1 months. In the CPS-10 subgroup, the median overall survival was 23.0 months in the pembrolizumab-chemotherapy group and 16.1 months in the placebo-chemotherapy group (hazard ratio for death, 0.73; 95% confidence interval [CI], 0.55 to 0.95; two-sided P = 0.0185 [criterion for significance met]); in the CPS-1 subgroup, the median overall survival was 17.6 and 16.0 months in the two groups, respectively (hazard ratio, 0.86; 95% CI, 0.72 to 1.04; two-sided P = 0.1125 [not significant]); and in the intention-to-treat population, the median overall survival was 17.2 and 15.5 months, respectively (hazard ratio, 0.89; 95% CI, 0.76 to 1.05 [significance not tested]). Adverse events of grade 3, 4, or 5 that were related to the trial regimen occurred in 68.1% of the patients in the pembrolizumab-chemotherapy group and in 66.9% in the placebo-chemotherapy group, including death in 0.4% of the patients in the pembrolizumab-chemotherapy group and in no patients in the placebo-chemotherapy group. Among patients with advanced triple-negative breast cancer whose tumors expressed PD-L1 with a CPS of 10 or more, the addition of pembrolizumab to chemotherapy resulted in significantly longer overall survival than chemotherapy alone. (Funded by Merck Sharp and Dohme; KEYNOTE-355 ClinicalTrials.gov number, NCT02819518.).

Molecular docking computationally predicts the conformation of a small molecule when binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline as they determine the fitness of sampled poses. Here we describe and evaluate the 1.0 release of the Gnina docking software, which utilizes an ensemble of convolutional neural networks (CNNs) as a scoring function. We also explore an array of parameter values for Gnina 1.0 to optimize docking performance and computational cost. Docking performance, as evaluated by the percentage of targets where the top pose is better than 2Å root mean square deviation (Top1), is compared to AutoDock Vina scoring when utilizing explicitly defined binding pockets or whole protein docking. Gnina , utilizing a CNN scoring function to rescore the output poses, outperforms AutoDock Vina scoring on redocking and cross-docking tasks when the binding pocket is defined (Top1 increases from 58% to 73% and from 27% to 37%, respectively) and when the whole protein defines the binding pocket (Top1 increases from 31% to 38% and from 12% to 16%, respectively). The derived ensemble of CNNs generalizes to unseen proteins and ligands and produces scores that correlate well with the root mean square deviation to the known binding pose. We provide the 1.0 version of Gnina under an open source license for use as a molecular docking tool at https://github.com/gnina/gnina .

Chemical doping is one of the most important strategies for tuning electrical properties of semiconductors, particularly thermoelectric materials. Generally, the main role of chemical doping lies in optimizing the carrier concentration, but there can potentially be other important effects. Here, we show that chemical doping plays multiple roles for both electron and phonon transport properties in half-Heusler thermoelectric materials. With ZrNiSn-based half-Heusler materials as an example, we use high-quality single and polycrystalline crystals, various probes, including electrical transport measurements, inelastic neutron scattering measurement, and first-principles calculations, to investigate the underlying electron-phonon interaction. We find that chemical doping brings strong screening effects to ionized impurities, grain boundary, and polar optical phonon scattering, but has negligible influence on lattice thermal conductivity. Furthermore, it is possible to establish a carrier scattering phase diagram, which can be used to select reasonable strategies for optimization of the thermoelectric performance. Chemical doping plays an important role in tuning carrier concentration of materials, but its influence on other aspects of electrical properties is less known. Here, the authors find that chemical doping brings strong screening effects to ionized impurities, grain boundary, and polar optical phonon scattering.

Accelerating deforestation rates in Earth's tropical rainforests have dramatic impacts on local public health, agricultural productivity, and global climate change. We used satellite observations to quantify the local temperature changes in deforested patches of rainforests across the tropics and found local warming larger than that predicted from more than a century of climate change under a worst-case emissions scenario. We show that the most extreme warming is typically found in large patches of deforestation; the combined effects of deforestation and climate change on tropical temperatures present a uniquely difficult challenge to the long term public health, occupational safety, and economic security of tropical populations.