Browsing by Subject "monitoring"
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Item Achieving Multiple Conservation Goals with Satellite-Based Monitoring and Alert Systems(2023-01-01) Tabor, Karyn Marie; Holland, Margaret B; Geography and Environmental Systems; Geography and Environmental SystemsConservation early warning and alert systems (CEAS) provide substantial opportunities to improve awareness of global change and deliver time-sensitive information to users taking measures to avert the loss of ecosystems that provide critical services to support human well-being. In recent years, the conservation community has fostered a proliferation of CEAS that utilize the near real-time capabilities of Earth observation satellites to monitor global changes and inform strategic and effective responses to emerging ecosystem threats. While scrutiny of the effectiveness of conservation interventions by researchers, practitioners, and funders has boosted more rigorous evaluations of conservation interventions in the past decade, assessments of how technologies like CEAS enable conservation actions are scarce. In this doctoral research, I reviewed the current suite of CEAS and highlighted gaps in the literature to describe or evaluate their applications. I collected users? and developers? experiences with CEAS across several countries and identified differential barriers to using CEAS for different populations while sourcing recommendations for improving design and access. Finally, I focused on the development of CEAS for tropical land management in Colombia and analyzed how institutions integrate CEAS into national decision-making frameworks. The overall results from this work suggest that dozens of CEAS provide cost-effective approaches for achieving multiple conservation goals. While some users are overwhelmed by the variety of systems available, many users, particularly those on the front lines of conservation, face numerous barriers preventing access to and effective use of satellite-based monitoring information. Funders should prioritize support for disseminating technology and alert information uptake over building more systems. Improvements in coordination, collaboration, and adequate resources to support technology use are required to increase CEAS use for diverse applications. The power of surveillance technologies like CEAS may also have unintended social and environmental consequences. Therefore, system developers and proponents of CEAS must understand the risks and follow guidelines to minimize further marginalizing vulnerable groups. Designing proxy measures for outcomes can enable rapid system adjustments to reduce risks and better connect the information to action. This research aims to improve the design and implementation of CEAS to fully realize the potential role of these systems in supporting global sustainability.Item Are Prescription Drug Monitoring Programs Effective? An Analysis of the Impact of Prescription Drug Monitoring Programs (PDMPs) Operational Variation on Prescription Opioid Misuse and Abuse(2020-01-01) Guggino, Kathy Michele; Miller, Nancy; School of Public Policy; Public PolicyABSTRACT Title of dissertations: Are Prescription Drug Monitoring Programs (PDMPs) Effective? An Analysis of the Impact of Prescription Drug Monitoring Programs (PDMPs) Operational Variation on Prescription Opioid Misuse and Abuse Kathy Guggino-Easterling, Doctor of Philosophy, 2021 dissertations directed by: Nancy A. Miller. Ph.D., Professor, Public Policy BackgroundAccording to the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics (NCHS), the third leading cause of accidental death in the U.S. in 2018 was narcotic overdoses. According to Healthcare Cost and Utilization Project (HCUP) data, the rate of opioid-related inpatient stays per 100,000 population in 2017 was 299.7, compared to 189.2 in 2010. The prescription drug abuse epidemic is intricate and multi-faceted. State prescription monitoring programs (PMPs) or prescription drug monitoring programs (PDMPs) have been described as a potentially impactful clinical tool to prevent prescription drug abuse. However, it is important to account for operational variations when studying the effectiveness of PDMPs in order to determine which programs are most successful, to determine best practices, to inform policy decisions and to justify PDMP funding. Objective The goal of this research was to determine the extent to which variation in state PDMP operational characteristics affects PDMP effectiveness in decreasing opioid abuse, as measured by state level opioid inpatient discharges. This study also examined whether PDMPs have the unintended consequence of increasing heroin use. Methods I conducted a state-level analysis with state-level data acquired from publicly available sources, using a cross-sectional time series model with adjustments for state and year fixed effects. Data were analyzed for 23 states with available HCUPnet opioid inpatient discharge data for the period 2001 through 2014. I examined four PDMP characteristics: proactive PDMP, frequency of data reporting requirements, mandatory query and mandatory enrollment. To deal with potential endogeneity, I explored possible instrumental variables. Although the three I tested were weak instruments across most of my analyses, I was able to use an instrumental variable related to the Affordable Care Act state marketplace exchanges to test whether state implementation of a PDMP was endogenous (See Appendix II). Using the Hausman test for endogeneity, I determined that presence of a PDMP was not endogenous (See Appendix III). Main Findings Overall, the results do not support the hypothesis that having an operational PDMP, measured simply by the presence of a PDMP, would decrease opioid related discharges. However, statistically significant results were found for states with a more frequent data reporting interval, mandatory enrollment, and, although marginally significant, mandatory query. Both a mandatory enrollment and mandatory query requirement were associated with a reduction in opioid inpatient discharges, while less frequent reporting was associated with an increase in opioid discharges over the study period. Although reduced inpatient discharges could result from fewer admissions, greater inpatient mortality, or both, research finds inpatient mortality for opioid misuse declined between 2001 and 2012 (Douglas et al., 2017), suggesting the discharge reduction is associated with fewer admissions for opioid misuse. Another variable which had a consistent statistically significant effect was a state Naloxone access law; these laws were associated with a decrease of between .029 and .037 inpatient opioid discharges per 1,000 state population over the study time period. I found limited spillover effects of PDMP operational characteristics on poisoning by heroin inpatient discharges. Heroin poisoning frequently happens when a person overdoses on heroin unintentionally. Conclusions/implicationsBased on these findings, more states should explore the implementation of a more frequent data reporting interval, and mandatory enrollment and query requirements. This will promote greater utilization of PDMP systems as a clinical decision support tool. In addition, more states may want to consider adopting naloxone overdose prevention laws. State policymakers should invest funds for research by partners, such as local universities, for ongoing PDMP evaluations to build evidence which can guide policy implementation. In addition, major recent federal opioid laws that include federal funding for PDMPs will be very helpful in advancing PDMPS and increasing PDMP use by providers, Medicaid providers and managed care entities. ?Item Board Independence and Credit Ratings(2010) Bradley, Michael; Chen, DongUsing Sarbanes-Oxley Act (SOX) as a natural experiment, we find evidence consistent with an optimal level of board independence for credit ratings. We test two hypotheses that could explain this optimality: information cost hypothesis (ICH) that the effectiveness of independent boards increases with the private benefits of the management, and decreases with the cost of monitoring and advising, and the shareholder empowering hypothesis (SEH) that the empowering of shareholders through stronger board independence reduces the agency cost of equity but exacerbates the agency cost of debt. We find mixed evidence supporting ICH, and stronger evidence supporting SEH.Item Clustering for Monitoring Distributed Data Streams(2016-01-01) Barouti, Maria; Kogan, Jacob; Malinovsky, Yaakov; Mathematics and Statistics; Mathematics, AppliedData mining is a challenging research area of computer science with profound applications in database industries and resulting market needs. Data mining is the computational process of discovering patterns in big data sets. This process enables us to extract valuable information from large data by involving methods at the intersection of different topics such as machine learning, statistics, and artificial intelligence. Over the last years there has been a growing interest in data analysis research by monitoring data streams in a distributed system. In this study we propose to monitor arbitrary threshold functions over distributed data streams while minimizing communication overhead. To illustrate this further, assume that we have a number of sensors that are spread in the space and we would like to monitor the average of their measurements while minimizing communication between the sensors. Each sensor represents a node that produces time varying vectors derived from the stream of measurements. Thus we are interested to check if a function evaluated at the vectors' average at each time is greater than zero while communication between the nodes is minimized. Motivated by recent contributions based on geometric ideas, and after reviewing some well known clustering algorithms we present an alternative approach that combines system theory techniques, clustering and statistical approaches. Our approach enables monitoring values of an arbitrary threshold function over distributed data streams through a set of constraints applied independently on each stream and/or clusters of streams. The clusters are designed to evolve in time and to adapt themselves to the data stream. A correct choice of clusters yields a reduction in communication load. Unlike many clustering algorithms that attempt to collect together similar data items, monitoring requires clusters with dissimilar vectors canceling each other as much as possible. In particular, subclusters of a good cluster do not have to be good. This novel type of clustering dictated by the problem at hand requires development of new algorithms and/or modification of the existing ones, and this thesis is a step in this direction. We report experiments on real-world data with a newly devised clustering algorithm. The experiments detect instances where communication between nodes is required, and show that the clustering approach reduces communication load. Last but not least, we indicate new future directions and discuss possible methodologies that can be involved into my future research agenda.Item Earth Observation to Address Inequities in Post-Flood Recovery(AGU, 2024-02-22) Friedrich, H. K.; Tellman, B.; Sullivan, J. A.; Saunders, A.; Zuniga-Teran, A. A.; Bakkensen, L. A.; Cawley, M.; Dolk, M.; Emberson, Robert; Forrest, S. A.; Gupta, N.; Gyawali, N.; Hall, C. A.; Kettner, A. J.; Lozano, J. L. Sanchez; Bola, G. B.Floods impact communities worldwide, resulting in loss of life, damaged infrastructure and natural assets, and threatened livelihoods. Climate change and urban development in flood-prone areas will continue to worsen flood-related losses, increasing the urgency for effective tools to monitor recovery. Many Earth Observation (EO) applications exist for flood-hazard monitoring and provide insights on location, timing, and extent in near real-time and historically to estimate flood risk. Less attention has been paid to flood recovery, even though differing recovery rates and outcomes can have immediate and enduring distributional effects within communities. EO data are uniquely positioned to monitor post-flood recovery and inform policy on hazard mitigation and adaptation but remain underutilized. We encourage the EO and flood research community to refocus on developing flood recovery applications to address growing risk. Translation of EO insights on flood recovery among flood-affected communities and decision-makers is necessary to address underlying social vulnerabilities that exacerbate inequitable recovery outcomes and advocate for redressing injustices where disparate recovery is observed. We identify an unequivocal need for EO to move beyond mapping flood hazard and exposure toward post-flood recovery monitoring to inform recovery across geographic contexts. This commentary proposes a framework for remote sensing scientists to engage community-based partners to integrate EO with non-EO data to advance flood recovery monitoring, characterize inequitable recovery, redistribute resources to mitigate inequities, and support risk reduction of future floods.Item The Non-Monotonic Effect of Board Independence on Credit Ratings(2012) Chen, DongUsing Sarbanes-Oxley Act (SOX) as a natural experiment, we find evidence consistent with an optimal level of board independence for credit ratings. We test two hypotheses that could explain this optimality: information cost hypothesis (ICH) that the effectiveness of independent boards increases with the private benefits of the management, and decreases with the cost of monitoring and advising, and the shareholder empowering hypothesis (SEH) that the empowering of shareholders through stronger board independence reduces the agency cost of equity but exacerbates the agency cost of debt. We find mixed evidence supporting ICH, and stronger evidence supporting SEH.Item Real-Time Direct Measurement of Human Liver Allograft Temperature from Recovery to Transplantation(Wolters Kluwer Health, 2006-02-15) Villa, Rosa; Fondevila, Constantino; Erill, Ivan; Guimera, Anton; Bombuy, Ernest; Gomez-Suarez, Cristina; Sacristan, Juan Carlos; Garcıa-Valdecasas, Juan CarlosTemperature is a key parameter in organ preservation that has been consistently linked to primary nonfunction (PNF). In this communication, and for the first time anywhere, continued and direct measurements of human liver intraparenchymal temperatures are reported in six clinical cases of orthotopic liver transplantations (OLT). These measurements cover the entire transplantation procedure and include the full transport phase. In contrast with long-held beliefs, these data demonstrate that liver allograft temperatures reach and stabilize at near 0°C, instead of 4°C, during transport using standard protocols. Furthermore, these low temperatures do not appear to contribute to graft failure when negative factors such as long preservation, the presence of hepatic steatosis, or advanced donor age are present. The clinical and experimental implications of these findings, together with other relevant elements derived from the direct and continuous monitoring of human liver allograft intraparenchymal temperatures, are discussed.