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Can Public Health Risk Assessment Using Risk Matrices Be Misleading?

Vatanpour S, Hrudey SE, Dinu I - Int J Environ Res Public Health (2015)

Bottom Line: We estimated the risk from the experiential data and compared these estimates with those provided by the risk assessment matrix.Although we validated the theoretical concern, for these authentic experiential data, the practical scope of the problem was limited.This method should not be abandoned wholesale, but users must address the source of the problem, apply the risk matrix with a full understanding of this problem and use matrix predictions to inform, but not drive decision-making.

View Article: PubMed Central - PubMed

Affiliation: School of Public Health, University of Alberta, Edmonton, AB T6G 1C9, Canada. vatanpour@ualberta.ca.

ABSTRACT
The risk assessment matrix is a widely accepted, semi-quantitative tool for assessing risks, and setting priorities in risk management. Although the method can be useful to promote discussion to distinguish high risks from low risks, a published critique described a problem when the frequency and severity of risks are negatively correlated. A theoretical analysis showed that risk predictions could be misleading. We evaluated a practical public health example because it provided experiential risk data that allowed us to assess the practical implications of the published concern that risk matrices would make predictions that are worse than random. We explored this predicted problem by constructing a risk assessment matrix using a public health risk scenario-Tainted blood transfusion infection risk-That provides negative correlation between harm frequency and severity. We estimated the risk from the experiential data and compared these estimates with those provided by the risk assessment matrix. Although we validated the theoretical concern, for these authentic experiential data, the practical scope of the problem was limited. The risk matrix has been widely used in risk assessment. This method should not be abandoned wholesale, but users must address the source of the problem, apply the risk matrix with a full understanding of this problem and use matrix predictions to inform, but not drive decision-making.

No MeSH data available.


Related in: MedlinePlus

Risk estimation according to log-Risk = log-Frequency + log-Severity.
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ijerph-12-09575-f003: Risk estimation according to log-Risk = log-Frequency + log-Severity.

Mentions: The relationship between this empirical function and the observed estimates of risk derived from Table 2 is shown in Figure 3.


Can Public Health Risk Assessment Using Risk Matrices Be Misleading?

Vatanpour S, Hrudey SE, Dinu I - Int J Environ Res Public Health (2015)

Risk estimation according to log-Risk = log-Frequency + log-Severity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4555299&req=5

ijerph-12-09575-f003: Risk estimation according to log-Risk = log-Frequency + log-Severity.
Mentions: The relationship between this empirical function and the observed estimates of risk derived from Table 2 is shown in Figure 3.

Bottom Line: We estimated the risk from the experiential data and compared these estimates with those provided by the risk assessment matrix.Although we validated the theoretical concern, for these authentic experiential data, the practical scope of the problem was limited.This method should not be abandoned wholesale, but users must address the source of the problem, apply the risk matrix with a full understanding of this problem and use matrix predictions to inform, but not drive decision-making.

View Article: PubMed Central - PubMed

Affiliation: School of Public Health, University of Alberta, Edmonton, AB T6G 1C9, Canada. vatanpour@ualberta.ca.

ABSTRACT
The risk assessment matrix is a widely accepted, semi-quantitative tool for assessing risks, and setting priorities in risk management. Although the method can be useful to promote discussion to distinguish high risks from low risks, a published critique described a problem when the frequency and severity of risks are negatively correlated. A theoretical analysis showed that risk predictions could be misleading. We evaluated a practical public health example because it provided experiential risk data that allowed us to assess the practical implications of the published concern that risk matrices would make predictions that are worse than random. We explored this predicted problem by constructing a risk assessment matrix using a public health risk scenario-Tainted blood transfusion infection risk-That provides negative correlation between harm frequency and severity. We estimated the risk from the experiential data and compared these estimates with those provided by the risk assessment matrix. Although we validated the theoretical concern, for these authentic experiential data, the practical scope of the problem was limited. The risk matrix has been widely used in risk assessment. This method should not be abandoned wholesale, but users must address the source of the problem, apply the risk matrix with a full understanding of this problem and use matrix predictions to inform, but not drive decision-making.

No MeSH data available.


Related in: MedlinePlus