The impact of alternative pricing methods for drugs in California Workers’ Compensation System: fee-schedule pricing

Introduction California’s Workers’ Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. Objectives To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Methods Claims transaction-level data (2011–2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman’s Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Results Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M;$63.9M, $47.9M, and$40.6M in 2011–2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. Conclusions CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all reimbursement approaches would require combinations of pricing benchmarks. We suggest keeping primary reimbursement at 100% of Medi-Cal and for drugs without a primary Medi-Cal price calculating the maximum fee as 60% of AWP and then 97% of WAC. Alternatively, we suggest using NADAC as a primary fee-schedule followed by either 60% AWP and 97% WAC or AWP-40% for drugs with no NADAC price. Fee-schedules may not offer the best price and a formulary approach may provide more flexibility

An appropriate verbal probability lexicon for communicating surgical risks is unlikely to exist

Effective risk communication about medical procedures is critical to ethical shared decision-making. Here, we explore the potential for development of an evidence-based lexicon for verbal communication of surgical risk. We found that Ear, Nose and Throat (ENT) surgeons expressed a preference for communicating such risks using verbal probability expressions (VPEs; e.g., “high risk”). However, there was considerable heterogeneity in the expressions they reported using (Study 1). Study 2 compared ENT surgeons’ and laypeople’s (i.e., potential patients) interpretations of the ten most frequent VPEs listed in Study 1. While both groups displayed considerable variability in interpretations, lay participants demonstrated more, as well as providing systematically higher interpretations than those of surgeons. Study 3 found that lay participants were typically unable to provide unique VPEs to differentiate between the ranges of (low) probabilities required. Taken together, these results add to arguments that reliance on VPEs for surgical risk communication is ill-advised. Not only are there systematic interpretational differences between surgeons and potential patients, but the coarse granularity of VPEs raises severe challenges for developing an appropriate evidence-based lexicon for surgical risk communication. We caution against the use of VPEs in any risk context characterized by low, but very different, probabilities. (PsycInfo Database Record (c) 2022 APA, all rights reserved

EXTENSIBLE DATABASE FRAMEWORK FOR MANAGEMENT OF UNSTRUCTURED AND SEMI-STRUCTURED DOCUMENTS

Method and system for querying a collection of Unstructured or semi-structured documents to identify presence of, and provide context and/or content for, keywords and/or keyphrases. The documents are analyzed and assigned a node structure, including an ordered sequence of mutually exclusive node segments or strings. Each node has an associated set of at least four, five or six attributes with node information and can represent a format marker or text, with the last node in any node segment usually being a text node. A keyword (or keyphrase) is specified. and the last node in each node segment is searched for a match with the keyword. When a match is found at a query node, or at a node determined with reference to a query node, the system displays the context andor the content of the query node

Adding Hierarchical Objects to Relational Database General-Purpose XML-Based Information Managements

NETMARK is a flexible, high-throughput software system for managing, storing, and rapid searching of unstructured and semi-structured documents. NETMARK transforms such documents from their original highly complex, constantly changing, heterogeneous data formats into well-structured, common data formats in using Hypertext Markup Language (HTML) and/or Extensible Markup Language (XML). The software implements an object-relational database system that combines the best practices of the relational model utilizing Structured Query Language (SQL) with those of the object-oriented, semantic database model for creating complex data. In particular, NETMARK takes advantage of the Oracle 8i object-relational database model using physical-address data types for very efficient keyword searches of records across both context and content. NETMARK also supports multiple international standards such as WEBDAV for drag-and-drop file management and SOAP for integrated information management using Web services. The document-organization and -searching capabilities afforded by NETMARK are likely to make this software attractive for use in disciplines as diverse as science, auditing, and law enforcement

Semaphorin 3A Contributes to Distal Pulmonary Epithelial Cell Differentiation and Lung Morphogenesis

altered distal lung structure.) littermate controls. mice that survived the immediate perinatal period. Furthermore, Sema3A deletion was linked with enhanced postnatal alveolar septal cell death.These data suggest that Sema3A modulates distal pulmonary epithelial cell development and alveolar septation. Defining how Sema3A influences structural plasticity of the developing lung is a critical first step for determining if this pathway can be exploited to develop innovative strategies for repair after acute or chronic lung injury

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems.Comment: Presented at NeurIPS 2019 Workshop "Machine Learning and the Physical Sciences

CD44 Promotes Intoxication by the Clostridial Iota-Family Toxins

International audienceVarious pathogenic clostridia produce binary protein toxins associated with enteric diseases of humans and animals. Separate binding/translocation (B) components bind to a protein receptor on the cell surface, assemble with enzymatic (A) component(s), and mediate endocytosis of the toxin complex. Ultimately there is translocation of A component(s) from acidified endosomes into the cytosol, leading to destruction of the actin cytoskeleton. Our results revealed that CD44, a multifunctional surface protein of mammalian cells, facilitates intoxication by the iota family of clostridial binary toxins. Specific antibody against CD44 inhibited cytotoxicity of the prototypical Clostridium perfringens iota toxin. Versus CD44(+) melanoma cells, those lacking CD44 bound less toxin and were dose-dependently resistant to C. perfringens iota, as well as Clostridium difficile and Clostridium spiroforme iota-like, toxins. Purified CD44 specifically interacted in vitro with iota and iota-like, but not related Clostridium botulinum C2, toxins. Furthermore, CD44 knockout mice were resistant to iota toxin lethality. Collective data reveal an important role for CD44 during intoxication by a family of clostridial binary toxins

Neuropilin 2/Plexin-A3 receptors regulate the functional connectivity and the excitability in the layers 4 and 5 of the cerebral cortex

The functions of cortical networks are progressively established during development by series of events shaping the neuronal connectivity. Synaptic elimination, which consists of removing the supernumerary connections generated during the earlier stages of cortical development, is one of the latest stages in neuronal network maturation. The semaphorin 3F coreceptors neuropilin 2 (Nrp2) and plexin-A3 (PlxnA3) may play an important role in the functional maturation of the cerebral cortex by regulating the excess dendritic spines on cortical excitatory neurons. Yet, the identity of the connections eliminated under the control of Nrp2/PlxnA3 signaling is debated, and the importance of this synaptic refinement for cortical functions remains poorly understood. Here, we show that Nrp2/PlxnA3 controls the spine densities in layer 4 (L4) and on the apical dendrite of L5 neurons of the sensory and motor cortices. Using a combination of neuroanatomical, ex vivo electrophysiology, and in vivo functional imaging techniques in Nrp2 and PlxnA3 KO mice of both sexes, we disprove the hypothesis that Nrp2/PlxnA3 signaling is required to maintain the ectopic thalamocortical connections observed during embryonic development. We also show that the absence of Nrp2/PlxnA3 signaling leads to the hyperexcitability and excessive synchronization of the neuronal activity in L5 and L4 neuronal networks, suggesting that this system could participate in the refinement of the recurrent corticocortical connectivity in those layers. Altogether, our results argue for a role of semaphorin–Nrp2/PlxnA3 signaling in the proper maturation and functional connectivity of the cerebral cortex, likely by controlling the refinement of recurrent corticocortical connections