Modeling Tool for Decision Support during Early Days of an Anthrax Event.
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SUBMITTER: Rainisch G
PROVIDER: S-EPMC5176207 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPalliative chemotherapy is often administered to terminally ill cancer patients to relieve symptoms. Yet, unnecessary use of chemotherapy can worsen patients' quality of life due to treatment-related toxicities. Thus, accurate prediction of survival in terminally ill patients can help clinicians decide on the most appropriate palliative care for these patients. However, studies have shown that clinicians often make imprecise predictions of survival in cancer patients. Hence, the purpose of this study was to create a clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy.Materials and methodsData were obtained from a retrospective study of 400 randomly selected terminally ill cancer patients in the National Cancer Centre Singapore (NCCS) from 2008 to 2009. After removing patients with missing data, there were 325 patients remaining for model development. Three classification algorithms, naive Bayes (NB), neural network (NN), and support vector machine (SVM) were used to create the models. A final model with the best prediction performance was then selected to develop the tool.ResultsThe NN model had the best prediction performance. The accuracy, specificity, sensitivity, and area under the curve (AUC) of this model were 78%, 82%, 74%, and 0.857, respectively. Five patient attributes (albumin level, alanine transaminase level (ATL), absolute neutrophil count, Eastern Cooperative Oncology Group (ECOG) status, and number of metastatic sites) were included in the model.ConclusionsA decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy was created. With further validation, this tool coupled with the professional judgment of clinicians can help improve patient care.
| S-EPMC3396145 | biostudies-literature
Project description:Objective The aim of the study is to identify and prioritize early intervention (EI) stakeholders' perspectives of supports and barriers to implementing the Young Children's Participation and Environment Measure (YC-PEM), an electronic patient-reported outcome (e-PRO) tool, for scaling its implementation across multiple local and state EI programs.Methods An explanatory sequential (quan > QUAL) mixed-methods study was conducted with EI families (n = 6), service coordinators (n = 9), and program leadership (n = 7). Semi-structured interviews and focus groups were used to share select quantitative pragmatic trial results (e.g., percentages for perceived helpfulness of implementation strategies) and elicit stakeholder perspectives to contextualize these results. Three study staff deductively coded transcripts to constructs in the Consolidated Framework for Implementation Research (CFIR). Data within CFIR constructs were inductively analyzed to generate themes that were rated by national early childhood advisors for their relevance to longer term implementation.Results All three stakeholder groups (i.e., families, service coordinators, program leadership) identified thematic supports and barriers across multiple constructs within each of four CFIR domains: (1) Six themes for "intervention characteristics," (2) Six themes for "process," (3) three themes for "inner setting," and (4) four themes for "outer setting." For example, all stakeholder groups described the value of the YC-PEM e-PRO in forging connections and eliciting meaningful information about family priorities for efficient service plan development ("intervention characteristics"). Stakeholders prioritized reaching families with diverse linguistic preferences and user navigation needs, further tailoring its interface with automated data capture and exchange processes ("process"); and fostering a positive implementation climate ("inner setting"). Service coordinators and program leadership further articulated the value of YC-PEM e-PRO results for improving EI access ("outer setting").Conclusion Results demonstrate the YC-PEM e-PRO is an evidence-based intervention that is viable for implementation. Optimizations to its interface are needed before undertaking hybrid type-2 and 3 multisite trials to test these implementation strategies across state and local EI programs with electronic data capture capabilities and diverse levels of organizational readiness and resources for implementation.
| S-EPMC9891850 | biostudies-literature
Project description:A strengthened evidence base and earmarked federal funding have spurred the implementation of coordinated specialty care (CSC) for people experiencing early psychosis. However, existing funding mechanisms are insufficient and unsustainable to support population-wide deployment of CSC. This article describes the design framework of an innovative payment model for CSC that includes a bundled case rate payment and an optional outcome-based payment. To assist CSC payer and provider organizations in designing payment systems tailored to local preferences and circumstances, the research team is developing a decision-support tool that allows users to define design choices and provide input. The authors document the analytical algorithms underlying the tool and discuss how it could be further developed or expanded for CSC and other behavioral health interventions that feature an interdisciplinary team of clinicians and nonclinical professionals, public education and outreach, patient centeredness, and a recovery orientation.
| S-EPMC8317229 | biostudies-literature
Project description:Appropriate thromboprophylaxis for patients with atrial fibrillation or atrial flutter (AF) remains a national challenge. The recent availability of direct oral anticoagulants (DOACs) with comparable efficacy and improved safety compared with warfarin alters the balance between risk factors for stroke and benefit of anticoagulation. Our objective was to examine the impact of DOACs as an alternative to warfarin on the net benefit of oral anticoagulant therapy (OAT) in a real-world population of AF patients.This is a retrospective cohort study of patients with paroxysmal or persistent nonvalvular AF. We updated an Atrial Fibrillation Decision Support Tool (AFDST) to include DOACs as treatment options. The tool generates patient-specific recommendations based upon individual patient risk factor profiles for stroke and major bleeding using quality-adjusted life-years (QALYs) calculated for each treatment strategy by a decision analytic model. The setting included inpatient and ambulatory sites in an academic health center in the midwestern United States. The study involved 5,121 adults with nonvalvular AF seen for any ambulatory visit or inpatient hospitalization over the 1-year period (January through December 2016). Outcome measure was net clinical benefit in QALYs.When DOACs are a therapeutic option, the AFDST recommends OAT for 4,134 (81%) patients and no antithrombotic therapy or aspirin for 489 (9%). A strong recommendation for OAT could not be made in 498 (10%) patients. When warfarin is the only option, OAT is recommended for 3,228 (63%) patients and no antithrombotic therapy or aspirin for 973 (19%). A strong recommendation for OAT could not be made in 920 (18%) patients. In total, 1,508 QALYs could be gained if treatment were changed to that recommended by the AFDST.Availability of DOACs increases the proportion of patients for whom oral anticoagulation therapy is recommended in a real-world cohort of AF patients and increased projected QALYs by more than 1,500 when all patients are receiving thromboprophylaxis as recommended by the AFDST compared with current treatment.
| S-EPMC5726779 | biostudies-literature
Project description:BackgroundReporting of adverse events (AEs) following vaccination can help identify rare or unexpected complications of immunizations and aid in characterizing potential vaccine safety signals. We developed an open-source, generalizable clinical decision support system called Electronic Support for Public Health-Vaccine Adverse Event Reporting System (ESP-VAERS) to assist clinicians with AE detection and reporting.MethodsESP-VAERS monitors patients' electronic health records for new diagnoses, changes in laboratory values, and new allergies following vaccinations. When suggestive events are found, ESP-VAERS sends the patient's clinician a secure electronic message with an invitation to affirm or refute the message, add comments, and submit an automated, prepopulated electronic report to VAERS. High-probability AEs are reported automatically if the clinician does not respond. We implemented ESP-VAERS in December 2012 throughout the MetroHealth System, an integrated healthcare system in Ohio. We queried the VAERS database to determine MetroHealth's baseline reporting rates from January 2009 to March 2012 and then assessed changes in reporting rates with ESP-VAERS.ResultsIn the 8 months following implementation, 91 622 vaccinations were given. ESP-VAERS sent 1385 messages to responsible clinicians describing potential AEs. Clinicians opened 1304 (94.2%) messages, responded to 209 (15.1%), and confirmed 16 for transmission to VAERS. An additional 16 high-probability AEs were sent automatically. Reported events included seizure, pleural effusion, and lymphocytopenia. The odds of a VAERS report submission during the implementation period were 30.2 (95% confidence interval, 9.52-95.5) times greater than the odds during the comparable preimplementation period.ConclusionsAn open-source, electronic health record-based clinical decision support system can increase AE detection and reporting rates in VAERS.
| S-EPMC6642796 | biostudies-literature
Project description:ObjectivesImmunization programs in low-income and middle-income countries (LMICs) are faced with an ever-growing number of vaccines of public health importance recommended by the World Health Organization, while also financing a greater proportion of the program through domestic resources. More than ever, national immunization programs must be equipped to contextualize global guidance and make choices that are best suited to their setting. The CAPACITI decision-support tool has been developed in collaboration with national immunization program decision makers in LMICs to structure and document an evidence-based, context-specific process for prioritizing or selecting among multiple vaccination products, services, or strategies.MethodsThe CAPACITI decision-support tool is based on multi-criteria decision analysis, as a structured way to incorporate multiple sources of evidence and stakeholder perspectives. The tool has been developed iteratively in consultation with 12 countries across Africa, Asia, and the Americas.ResultsThe tool is flexible to existing country processes and can follow any type of multi-criteria decision analysis or a hybrid approach. It is structured into 5 sections: decision question, criteria for decision making, evidence assessment, appraisal, and recommendation. The Excel-based tool guides the user through the steps and document discussions in a transparent manner, with an emphasis on stakeholder engagement and country ownership.ConclusionsPilot countries valued the CAPACITI decision-support tool as a means to consider multiple criteria and stakeholder perspectives and to evaluate trade-offs and the impact of data quality. With use, it is expected that LMICs will tailor steps to their context and streamline the tool for decision making.
| S-EPMC10563585 | biostudies-literature
Project description:In the field of forestry, one of the most economically important ecosystem service is the provision of timber. The need to calculate the economic effects of forest management in the short, medium, and long term is increasing. Forest operations or timber harvesting, which comprises felling, processing, and transport of trees or timber, are responsible for a large part of the costs and environmental impacts associated to forest management or enterprises. From a decision maker's perspective, it is essential to estimate working productivity and production costs under given operating conditions before any operation is conducted. This work addresses the lack of a valid collection of models that allows estimating time, productivities, and costs of labor and machinery for the most important forest operations in forest stands under Central European conditions. To create such models, we used data from forest enterprises, manual time studies, and the literature. This work presents a decision support tool that estimates the wood harvesting productivities of 12 different kinds of forest operations under Central European conditions. It includes forest operations using chainsaws, harvesters, skidders, forwarders, chippers, cable and tower yarders, and helicopters. In addition, the tool covers three models for wood volume estimation. The tool is written in Java and available open-source under the Apache License. This work shows how the tool can be used by describing its graphical user interface (GUI) and its application programming interface (API) that facilitates bulk processing of scientific data. Carefully selected default values allow estimations without knowing all input variables in detail. Each model is accompanied by an in-depth documentation where the forest operation, input variables, formulas, and statistical background are given. We conclude that HeProMo is a very useful tool for applications in forest practice, research, and teaching.
| S-EPMC7774941 | biostudies-literature
Project description:Heat poses an urgent threat to public health in cities, as the urban heat island (UHI) effect can amplify exposures, contributing to high heat-related mortality and morbidity. Urban trees have the potential to mitigate heat by providing substantial cooling, as well as co-benefits such as reductions in energy consumption. The City of Boston has attempted to expand its urban canopy, yet maintenance costs and high tree mortality have hindered successful canopy expansion. Here, we present an interactive web application called Right Place, Right Tree-Boston that aims to support informed decision-making for planting new trees. To highlight priority regions for canopy expansion, we developed a Boston-specific Heat Vulnerability Index (HVI) and present this alongside maps of summer daytime land surface temperatures. We also provide information about tree pests and diseases, suitability of species for various conditions, land ownership, maintenance tips, and alternatives to tree planting. This web application is designed to support decision-making at multiple spatial scales, to assist city officials as well as residents who are interested in expanding or maintaining Boston's urban forest.
| S-EPMC7544061 | biostudies-literature
Project description:Newly recognized as natural nanocarriers that deliver biological information between cells, extracellular vesicles (EVs), including exosomes and microvesicles, provide unprecedented therapeutic opportunities. Large-scale and cost-effective manufacturing is imperative for EV products to meet commercial and clinical demands; successful translation requires careful decisions that minimize financial and technological risks. Here, we develop a decision support tool (DST) that computes the most cost-effective technologies for manufacturing EVs at different scales, by examining the costs of goods associated with using published protocols. The DST identifies costs of labor and consumables during EV harvest as key cost drivers, substantiating a need for larger-scale, higher-throughput, and automated technologies for harvesting EVs. Importantly, we highlight a lack of appropriate technologies for meeting clinical demands, and propose a potentially cost-effective solution. This DST can facilitate decision-making very early on in development and be used to predict, and better manage, the risk of process changes when commercializing EV products.
| S-EPMC6322973 | biostudies-literature
Project description:BackgroundPromising health interventions tested in pilot studies will only achieve population-wide impact if they are implemented at scale across communities and health systems. Scaling up effective health interventions is vital as not doing so denies the community the most effective services and programmes. However, there remains a paucity of practical tools to assess the suitability of health interventions for scale-up. The Intervention Scalability Assessment Tool (ISAT) was developed to support policy-makers and practitioners to make systematic assessments of the suitability of health interventions for scale-up.MethodsThe ISAT was developed over three stages; the first stage involved a literature review to identify similar tools and frameworks that could be used to guide scalability assessments, and expert input to develop draft ISAT content. In the second stage, the draft ISAT tool was tested with end users. The third stage involved revising and re-testing the ISAT with end users to further refine the language and structure of the final ISAT.ResultsA variety of information and sources of evidence should be used to complete the ISAT. The ISAT consists of three parts. Part A: 'setting the scene' requires consideration of the context in which the intervention is being considered for scale-up and consists of five domains, as follows: (1) the problem; (2) the intervention; (3) strategic/political context; (4) evidence of effectiveness; and (5) intervention costs and benefits. Part B asks users to assess the potential implementation and scale-up requirements within five domains, namely (1) fidelity and adaptation; (2) reach and acceptability; (3) delivery setting and workforce; (4) implementation infrastructure; and (5) sustainability. Part C generates a graphical representation of the strengths and weaknesses of the readiness of the proposed intervention for scale-up. Users are also prompted for a recommendation as to whether the intervention (1) is recommended for scale-up, (2) is promising but needs further information before scaling up, or (3) does not yet merit scale-up.ConclusionThe ISAT fills an important gap in applied scalability assessment and can become a critical decision support tool for policy-makers and practitioners when selecting health interventions for scale-up. Although the ISAT is designed to be a health policy and practitioner tool, it can also be used by researchers in the design of research to fill important evidence gaps.
| S-EPMC6942323 | biostudies-literature