Care Decision Making (care + decision_making)

Distribution by Scientific Domains

Selected Abstracts

Health Care Decision Making for Reproductive Care

Article first published online: 6 NOV 200
No abstract is available for this article. [source]

Whither trial-based economic evaluation for health care decision making?

Mark J. Sculpher
Abstract The randomised controlled trial (RCT) has developed a central role in applied cost-effectiveness studies in health care as the vehicle for analysis. This paper considers the role of trial-based economic evaluation in this era of explicit decision making. It is argued that any framework for economic analysis can only be judged insofar as it can inform two key decisions and be consistent with the objectives of a health care system subject to its resource constraints. The two decisions are, firstly, whether to adopt a health technology given existing evidence and, secondly, an assessment of whether more evidence is required to support this decision in the future. It is argued that a framework of economic analysis is needed which can estimate costs and effects, based on all the available evidence, relating to the full range of possible alternative interventions and clinical strategies, over an appropriate time horizon and for specific patient groups. It must also enable the accumulated evidence to be synthesised in an explicit and transparent way in order to fully represent the decision uncertainty. These requirements suggest that, in most circumstances, the use of a single RCT as a vehicle for economic analysis will be an inadequate and partial basis for decision making. It is argued that RCT evidence, with or without economic content, should be viewed as simply one of the sources of evidence, which must be placed in a broader framework of evidence synthesis and decision analysis. Copyright 2006 John Wiley & Sons, Ltd. [source]

Mapping the Cochrane evidence for decision making in health care

Regina P. El Dib PhD
Abstract Rationale and aim, Over the past 12 years, thousands of authors working with the Cochrane Collaboration around the world have produced systematic reviews to reduce uncertainty in health care decision making. We evaluated the conclusions from Cochrane systematic reviews of randomized controlled trials in terms of their recommendations for clinical practice and research. Methods, In our cross-sectional study of systematic reviews published in the Cochrane Library, we randomly selected and analysed completed systematic reviews published across all 50 Cochrane Collaborative Review Groups. Results, We analysed 1016 completed systematic reviews. Of these, 44% concluded that the interventions studied were likely to be beneficial, of which 1% recommended no further research and 43% recommended additional research. Also, 7% of the reviews concluded that the interventions were likely to be harmful, of which 2% did not recommend further studies and 5% recommended additional studies. In total, 49% of the reviews reported that the evidence did not support either benefit or harm, of which 1% did not recommend further studies and 48% recommended additional studies. Overall, 96% of the reviews recommended further research. Conclusions, Cochrane systematic reviews were about evenly split between those in which the authors concluded that at least one of the interventions was beneficial and those in which the evidence neither supported nor refuted the intervention tested. The Cochrane Collaboration needs to include clinical trial protocol summaries with a study design optimized to answer the relevant research questions. [source]

Critical care nurse practitioners and clinical nurse specialists interface patterns with computer-based decision support systems

APRN (Assistant Professor of Health, Community Systems, Coordinator of the Nursing Education Graduate Program), PhD(c), Scott Weber EdD
Abstract Purpose: The purposes of this review are to examine the types of clinical decision support systems in use and to identify patterns of how critical care advanced practice nurses (APNs) have integrated these systems into their nursing care patient management practices. The decision-making process itself is analyzed with a focus on how automated systems attempt to capture and reflect human decisional processes in critical care nursing, including how systems actually organize and process information to create outcome estimations based on patient clinical indicators and prognosis logarithms. Characteristics of APN clinicians and implications of these characteristics on decision system use, based on the body of decision system user research, are introduced. Data sources: A review of the Medline, Ovid, CINAHL, and PubMed literature databases was conducted using "clinical decision support systems,""computerized clinical decision making," and "APNs"; an examination of components of several major clinical decision systems was also undertaken. Conclusions: Use patterns among APNs and other clinicians appear to vary; there is a need for original research to examine how APNs actually use these systems in their practices in critical care settings. Because APNs are increasingly responsible for admission to, and transfer from, critical care settings, more understanding is needed on how they interact with this technology and how they see automated decision systems impacting their practices. Implications for practice: APNs who practice in critical care settings vary significantly in how they use the clinical decision systems that are in operation in their practice settings. These APNs must have an understanding of their use patterns with these systems and should critically assess whether their patient care decision making is affected by the technology. [source]