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Do expert assessments converge? An exploratory case study of evaluating and managing a blood supply risk.

ABSTRACT: BACKGROUND: Examining professional assessments of a blood product recall/withdrawal and its implications for risk and public health, the paper introduces ideas about perceptions of minimal risk and its management. It also describes the context of publicly funded blood transfusion in Canada and the withdrawal event that is the basis of this study. METHODS: Interviews with 45 experts from administration, medicine, blood supply, laboratory services and risk assessment took place using a multi-level sampling framework in the aftermath of the recall. These experts either directly dealt with the withdrawal or were involved in the management of the blood supply at the national level. Data from these interviews were coded in NVivo for analysis and interpretation. Analytically, data were interpreted to derive typifications to relate interview responses to risk management heuristics. RESULTS: While all those interviewed agreed on the importance of patient safety, differences in the ways in which the risk was contextualized and explicated were discerned. Risk was seen in terms of patient safety, liability or precaution. These different risk logics are illustrated by selected quotations. CONCLUSIONS: Expert assessments did not fully converge and it is possible that these different risk logics and discourses may affect the risk management process more generally, although not necessarily in a negative way. Patient safety is not to be compromised but management of blood risk in publicly funded systems may vary. We suggest ways of managing blood risk using formal and safety case approaches.

SUBMITTER: Eyles J

PROVIDER: S-EPMC3223866 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Do expert assessments converge? An exploratory case study of evaluating and managing a blood supply risk.

Eyles John J Heddle Nancy N Webert Kathryn K Arnold Emmy E McCurdy Bronwen B

BMC public health 20110824

<h4>Background</h4>Examining professional assessments of a blood product recall/withdrawal and its implications for risk and public health, the paper introduces ideas about perceptions of minimal risk and its management. It also describes the context of publicly funded blood transfusion in Canada and the withdrawal event that is the basis of this study.<h4>Methods</h4>Interviews with 45 experts from administration, medicine, blood supply, laboratory services and risk assessment took place using ...[more]

PMID: 21864330

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Project description:BackgroundThe quantification of uncertainty and variability is a key component of quantitative risk analysis. Recent advances in Bayesian statistics make it ideal for integrating multiple sources of information, of different types and quality, and providing a realistic estimate of the combined uncertainty in the final risk estimates.MethodsWe present two case studies related to foodborne microbial risks. In the first, we combine models to describe the sequence of events resulting in illness from consumption of milk contaminated with VTEC O157. We used Monte Carlo simulation to propagate uncertainty in some of the inputs to computer models describing the farm and pasteurisation process. Resulting simulated contamination levels were then assigned to consumption events from a dietary survey. Finally we accounted for uncertainty in the dose-response relationship and uncertainty due to limited incidence data to derive uncertainty about yearly incidences of illness in young children. Options for altering the risk were considered by running the model with different hypothetical policy-driven exposure scenarios. In the second case study we illustrate an efficient Bayesian sensitivity analysis for identifying the most important parameters of a complex computer code that simulated VTEC O157 prevalence within a managed dairy herd. This was carried out in 2 stages, first to screen out the unimportant inputs, then to perform a more detailed analysis on the remaining inputs. The method works by building a Bayesian statistical approximation to the computer code using a number of known code input/output pairs (training runs).ResultsWe estimated that the expected total number of children aged 1.5-4.5 who become ill due to VTEC O157 in milk is 8.6 per year, with 95% uncertainty interval (0,11.5). The most extreme policy we considered was banning on-farm pasteurisation of milk, which reduced the estimate to 6.4 with 95% interval (0,11). In the second case study the effective number of inputs was reduced from 30 to 7 in the screening stage, and just 2 inputs were found to explain 82.8% of the output variance. A combined total of 500 runs of the computer code were used.ConclusionThese case studies illustrate the use of Bayesian statistics to perform detailed uncertainty and sensitivity analyses, integrating multiple information sources in a way that is both rigorous and efficient.

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Do expert assessments converge? An exploratory case study of evaluating and managing a blood supply risk.

Publications

Do expert assessments converge? An exploratory case study of evaluating and managing a blood supply risk.

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