IT-based Patient Interventions for Opioid Abuse: Evaluation using Analytical Model

The number of people in the US with opioid abuse exceeds 2 million and the total cost is approximately $100B per year. In this study, we focus on patient-level interventions and present three IT-based interventions: (a) mobile reminders, (b) electronic monitoring, and (c) composite intervention. We have developed an analytical model for evaluating interventions using Return-on-Investment (ROI). The interventions are cost-effective for higher values of intervention effectiveness, hospital, and emergency room cost. However, with QoL improvement, cost-effectiveness improves significantly. We also explored the use of financial incentives for increasing the adoption of interventions. These results will help patients, healthcare professionals, decision-makers, and family members to choose the most suitable intervention to address opioid abuse

Opioid Use Disorder: Decision Support for Healthcare Professionals

Opioid Use Disorder (OUD) is defined as deviating from the physician’s prescription of a specific opioid. The OUD patients will require expensive inpatient treatment followed by a long-term outpatient treatment. We present a decision support system for opioid prescriptions, inpatient treatment (detoxification), and outpatient treatment by healthcare professionals. We analyzed the impact of inaccuracy in PDMP, decision scenarios, and effectiveness of decisions in outpatient scenarios on the opioid resource requirements. The proposed DSS will lead to better decision making using both the risk score and patient’s condition

Opioid Use Disorder: Studying Quality of Life with IT-based Interventions

Opioid Use Disorder (OUD) has become a major public health challenge. There have been several interventions, including those based on health-IT, proposed recently. There is a major need to study these interventions. We are interested in exploring how different IT-based interventions impact opioid related Quality of Life. We developed a model using Markov chain for three different states in OUD. The model and results can lead to better decision making by healthcare professionals, patients and insurance companies. More specifically, the proposed model and results can help in (a) whether to prescribe opioids to different types of patients, (b) what IT-based interventions are suitable with an opioid prescription, and (c) how patients and healthcare professionals can select an intervention out of multiple available interventions

Patient Generated Health Data: Framework for Decision Making

Patient information is a major part of healthcare decision making. Although currently scattered due to multiple sources and diverse formats, decision making can be improved if the patient information is readily available in a unified manner. Mobile technologies can improve decision making by integrating patient information from multiple sources. This study explores how patient generated health data (PGHD) from multiple sources can lead to improved healthcare decision making. A semi-systematic review is conducted to analyze research articles for transparency, clarity, and complete reporting. We conceptualize the data generated by healthcare professional as primarily from EHR/EMR and the data generated by patient as primarily from mobile apps and wearables. Eight themes led to the development of Convergence Model for Patient Data (CMPD). A framework was developed to illustrate several scenarios, to identify quality and timeliness requirements in mobile healthcare environment, and to provide necessary decision support

pyParaOcean: A System for Visual Analysis of Ocean Data

Visual analysis is well adopted within the field of oceanography for the analysis of model simulations, detection of different phenomena and events, and tracking of dynamic processes. With increasing data sizes and the availability of multivariate dynamic data, there is a growing need for scalable and extensible tools for visualization and interactive exploration. We describe pyParaOcean, a visualization system that supports several tasks routinely used in the visual analysis of ocean data. The system is available as a plugin to Paraview and is hence able to leverage its distributed computing capabilities and its rich set of generic analysis and visualization functionalities. pyParaOcean provides modules to support different visual analysis tasks specific to ocean data, such as eddy identification and salinity movement tracking. These modules are available as Paraview filters and this seamless integration results in a system that is easy to install and use. A case study on the Bay of Bengal illustrates the utility of the system for the study of ocean phenomena and processes.Comment: 8 pages, EnvirVis202

Up-regulation of a death receptor renders antiviral T cells susceptible to NK cell-mediated deletion

This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 3.0 Unported license, as described at http://creativecommons.org/licenses/by-nc-sa/3.0/).This work was funded by the Medical Research Council (Clinical Research Training Fellowship to DP and grant G0801213 to M.K. Maini)

The third signal cytokine IL-12 rescues the anti-viral function of exhausted HBV-specific CD8 T cells.

Optimal immune activation of naïve CD8 T cells requires signal 1 mediated by the T cell receptor, signal 2 mediated by co-stimulation and signal 3 provided by pro-inflammatory cytokines. However, the potential for signal 3 cytokines to rescue anti-viral responses in functionally exhausted T cells has not been defined. We investigated the effect of using third signal cytokines IL-12 or IFN-α to rescue the exhausted CD8 T cell response characteristic of patients persistently infected with hepatitis B virus (HBV). We found that IL-12, but not IFN-α, potently augmented the capacity of HBV-specific CD8 T cells to produce effector cytokines upon stimulation by cognate antigen. Functional recovery mediated by IL-12 was accompanied by down-modulation of the hallmark inhibitory receptor PD-1 and an increase in the transcription factor T-bet. PD-1 down-regulation was observed in HBV but not CMV-specific T cells, in line with our finding that the highly functional CMV response was not further enhanced by IL-12. IL-12 enhanced a number of characteristics of HBV-specific T cells important for viral control: cytotoxicity, polyfunctionality and multispecificity. Furthermore, IL-12 significantly decreased the pro-apoptotic molecule Bim, which is capable of mediating premature attrition of HBV-specific CD8 T cells. Combining IL-12 with blockade of the PD-1 pathway further increased CD8 functionality in the majority of patients. These data provide new insights into the distinct signalling requirements of exhausted T cells and the potential to recover responses optimised to control persistent viral infections

Opioid Use Disorder: IT-based Interventions

Opioid Use Disorder (OUD) is a problematic pattern of opioid use leading to problems or distress. It can lead to higher healthcare costs and serious harm to patients. Patients have vulnerability to OUD based on their history, genetic makeup, current environment and stressors, medical condition and type of opioid prescribed. The number of people in the US with OUD exceeds 2 million and the total cost is approximately $100B/year. In this study, we present a theory-based design approach and three interventions for OUD. More specifically, we present the following techno-behavioural interventions: (a) decision support for healthcare professionals, (b) reminders, monitoring, and interventions for patients and (c) group support for patients. We have developed an analytical model which can be used to study cost of healthcare and interventions, and preferences of patients using utilities. We also explore the use of financial incentives for increasing the adoption of interventions. We found that interventions can lead to considerable cost savings even for mild to moderate OUD and these savings can translate into significant incentives for patients to continue the interventions. These results will help healthcare professionals, decision-makers, and researchers to explore various interventions for different patients with OUD

Integration of Mobile Health and EHR

The goal of EHR is to integrate and access patient’s information digitally to improve healthcare efficiency and decision making. Mobile health extends the coverage and quality of healthcare to anyone anytime anywhere by getting current information about patient’s activities. We are interested in exploring the integration of EHR and mobile health and how it can improve healthcare decision making. The integration will lead to more detailed and current information from mobile applications, sensors and other devices being combined with EHR information. This will allow the healthcare professionals to be anywhere with mobile access, empower patients by access to the latest information, result in effective medical research, and reach patients quickly for necessary interventions. From the literature, we observe that there is considerable interest in mobile health and EHR, but several challenges have not been addressed. The challenges identified in this study, including seamless access, data integration, speed and quality of decision making, and outcomes, need to be addressed by IS/IT research community in the near future