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Decision curve analysis as a framework to estimate the potential value of screening or other decision-making aids.

ABSTRACT: OBJECTIVES:There is an increasing debate about the impact of mental health screening. We illustrate the use of a decision making framework that can be applied when there is no sufficient data to support a traditional cost-benefit analysis. METHODS:We conducted secondary analyses of data from 459 male prisoners who were screened upon intake. We compared the potential benefit of different approaches (screening, history taking, and universal interventions) to allocating treatment resources using decision curve analysis. RESULTS:Screening prisoners for distress at typical levels of sensitivity (75%) and specificity (71%) were estimated to provide the greatest net benefit if between 2 and 5 false positives per detected illness are tolerable. History taking and self-harm screening provide the largest net benefit when only 1 or 2 false positives per detected illness would be tolerable. The benefits of screening were less among those without a recent psychiatric history, ethnic minorities, and those with fewer psychosocial needs. CONCLUSIONS:Although screening has potential to increase detection of treatment, important subgroup differences exist. Greater consideration of responses to positive screens or alternatives to screening are needed to maximize the impact of efforts to improve detection and treatment of mental illness.

SUBMITTER: Martin MS

PROVIDER: S-EPMC6877186 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Decision curve analysis as a framework to estimate the potential value of screening or other decision-making aids.

Martin Michael S MS Wells George A GA Crocker Anne G AG Potter Beth K BK Colman Ian I

International journal of methods in psychiatric research 20171228 1

<h4>Objectives</h4>There is an increasing debate about the impact of mental health screening. We illustrate the use of a decision making framework that can be applied when there is no sufficient data to support a traditional cost-benefit analysis.<h4>Methods</h4>We conducted secondary analyses of data from 459 male prisoners who were screened upon intake. We compared the potential benefit of different approaches (screening, history taking, and universal interventions) to allocating treatment res ...[more]

PMID: 29282797

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Project description:IntroductionAlthough systematic reviews have shown how decision aids about cancer-related clinical decisions improve selection of key options and shared decision-making, whether or not particular decision aids, defined by their specific presentation formats, delivery methods and other attributes, can perform better than others in the context of cancer-screening decisions is uncertain. Therefore, we planned an overview to address this issue by using standard umbrella review methods to repurpose existing systematic reviews and their component comparative studies.Methods and analysisWe will search PubMed, Embase, the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effects from inception through 31 December 2021 with no language restriction and perform full-text evaluation of potentially relevant articles. We will include systematic reviews of randomised controlled trials or non-randomised studies of interventions that assessed a decision aid about cancer-screening decisions and compared it with an alternative tool or conventional management in healthy average-risk adults. Two reviewers will extract data and rate the study validity according to standard quality assessment measures. Our primary outcome will be intended and actual choice and adherence to selected options. The secondary outcomes will include attributes of the option-selection process, achieving shared decision-making and preference-linked psychosocial outcomes. We will qualitatively assess study, patient and intervention characteristics and outcomes. We will also take special care to investigate the presentation format, delivery methods and quality of the included decision aids and assess the degree to which the decision aid was delivered and used as intended. If appropriate, we will perform random-effects model meta-analyses to quantitatively synthesise the results.Ethics and disseminationEthics approval is not applicable as this is a secondary analysis of publicly available data. The review results will be submitted for publication in a peer-reviewed journal.Prospero registration numberCRD42021235957.

Project description:The conflicting recommendations for prostate cancer (PCa) screening and the mixed messages communicated to the public about screening effectiveness make it critical to assist men in making informed decisions.To assess the effectiveness of 2 decision aids in helping men make informed PCa screening decisions.A racially diverse group of male outpatients aged 45 to 70 years from 3 sites were interviewed by telephone at baseline, 1 month, and 13 months, from 2007 through 2011. We conducted intention-to-treat univariate analyses and multivariable linear and logistic regression analyses, adjusting for baseline outcome measures.Random assignment to print-based decision aid (n?=?628), web-based interactive decision aid (n?=?625), or usual care (UC) (n?=?626).Prostate cancer knowledge, decisional conflict, decisional satisfaction, and whether participants underwent PCa screening.Of 4794 eligible men approached, 1893 were randomized. At each follow-up assessment, univariate and multivariable analyses indicated that both decision aids resulted in significantly improved PCa knowledge and reduced decisional conflict compared with UC (all P <.001). At 1 month, the standardized mean difference (Cohen’s d) in knowledge for the web group vs UC was 0.74, and in the print group vs UC, 0.73. Decisional conflict was significantly lower for web vs UC (d?=?0.33) and print vs UC (d?=?0.36). At 13 months, these differences were smaller but remained significant. At 1 month, high satisfaction was reported by significantly more print (60.4%) than web participants (52.2%; P?=?.009) and significantly more web (P?=?.001) and print (P?=?.03) than UC participants (45.5%). At 13 months, differences in the proportion reporting high satisfaction among print (55.7%) compared with UC (49.8%; P?=?.06) and web participants (50.4%; P?=?.10) were not significant. Screening rates at 13 months did not differ significantly among groups.Both decision aids improved participants’ informed decision making about PCa screening up to 13 months later but did not affect actual screening rates. Dissemination of these decision aids may be a valuable public health tool.clinicaltrials.gov Identifier: NCT00196807.

Project description:BackgroundScientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation.ResultsSidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick.ConclusionsSidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that traditional single gene lists do not, particularly in areas such as interaction discovery.

Project description:Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches.

Project description:Shared decision making (SDM) is important in achieving patient-centered care. SDM tools such as decision aids are intended to inform the patient. When used to assist in decision making between treatments, decision aids have been shown to reduce decisional conflict, increase ease of decision making, and increase modification of previous decisions.The purpose of this systematic review is to assess the impact of computerized decision aids on patient-centered outcomes related to SDM for seriously ill patients.PubMed and Scopus databases were searched to identify randomized controlled trials (RCTs) that assessed the impact of computerized decision aids on patient-centered outcomes and SDM in serious illness. Six RCTs were identified and data were extracted on study population, design, and results. Risk of bias was assessed by a modified Cochrane Risk of Bias Tool for Quality Assessment of Randomized Controlled Trials.Six RCTs tested decision tools in varying serious illnesses. Three studies compared different computerized decision aids against each other and a control. All but one study demonstrated improvement in at least one patient-centered outcome. Computerized decision tools may reduce unnecessary treatment in patients with low disease severity in comparison with informational pamphlets. Additionally, electronic health record (EHR) portals may provide the opportunity to manage care from the home for individuals affected by illness. The quality of decision aids is of great importance. Furthermore, satisfaction with the use of tools is associated with increased patient satisfaction and reduced decisional conflict. Finally, patients may benefit from computerized decision tools without the need for increased physician involvement.Most computerized decision aids improved at least one patient-centered outcome. All RCTs identified were at a High Risk of Bias or Unclear Risk of Bias. Effort should be made to improve the quality of RCTs testing SDM aids in serious illness.

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Decision curve analysis as a framework to estimate the potential value of screening or other decision-making aids.

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Decision curve analysis as a framework to estimate the potential value of screening or other decision-making aids.

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