Christian CK, Gustafson ML, Betensky RA, et al. The volume-outcome relationship: don't believe everything you see

Harvard University, Cambridge, Massachusetts, United States
World Journal of Surgery (Impact Factor: 2.35). 11/2005; 29(10):1241-4. DOI: 10.1007/s00268-005-7993-8
Source: PubMed

ABSTRACT This paper investigates methodological limitations of the volume-outcome relationship. A brief overview of quality measurement is followed by a discussion of two important aspects of the relationship.

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    • "The majority of studies have analysed and displayed volume as a categorical variable and, although it is statistically inferior to handling it as a continuous variable, it does overcome difficulties of visual interpretation of potential correlations along a volume gradient that are subsequently not proven to be statistically significant [3]. However, it has the disadvantage of suggesting absolute cut-off values, which may not be appropriate or indeed intended. "
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    ABSTRACT: There has been much interest in the volume–outcome relationship within surgical specialities and the potential impact on service reconfiguration. Recent research has raised questions about the validity of the methodology used in existing volume–outcome studies. This review explores a methodological framework for assessing the volume–outcome relationship and discusses limitations of previous research. In particular reference is made to the existing urological literature in this field. Areas for improvement and the potential for future research are considered.
    British Journal of Medical and Surgical Urology 09/2008; 1(2):50-57. DOI:10.1016/j.bjmsu.2008.06.004
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    • "Various approaches to determine such a cutpoint have been used, for example, external standards, the median volume, or choice of an ''optimal'' cutpoint, which minimizes the P-value relating volume to outcome [25] [26]. The disadvantages of categorizing a continuous covariate , especially by choosing a data-dependent ''optimal'' cutpoint, have been discussed and such a proceeding has been cautioned against [4] [6] [27]. "
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    ABSTRACT: The aim was to review different approaches for the derivation of threshold values and to discuss their strengths and limitations in the context of minimum provider volumes. The following methods for the calculation of threshold values are compared and discussed: The value of acceptable risk limit, the value of acceptable risk gradient, the benchmark value proposed by Budtz-Jørgensen and Ulm's breakpoint model. The latter is extended to account for two different breakpoints. The methods are applied to German quality assurance data concerning total knee replacement. The discussed methods for calculating threshold values differ in the kind of information that has to be specified beforehand. For the value of acceptable risk limit approach an absolute number, the acceptable risk, has to be predetermined. The value of acceptable risk gradient approach and the method of Budtz-Jørgensen require the specification of a relative change expressed in gradient and in odds, respectively. On the other hand, the threshold value according to the method of Ulm is defined as a parameter of a statistical model and no a priori specification is required. Each of the proposed methods has benefits and drawbacks. The choice of the most appropriate approach depends on the specific problem and the available data.
    Journal of clinical epidemiology 07/2008; 61(11):1125-31. DOI:10.1016/j.jclinepi.2007.11.020 · 5.48 Impact Factor
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