2020
DOI: 10.1111/nep.13761
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Funnel plots of patient‐reported outcomes to evaluate health‐care quality: Basic principles, pitfalls and considerations

Abstract: A funnel plot is a graphical method to evaluate health‐care quality by comparing hospital performances on certain outcomes. So far, in nephrology, this method has been applied to clinical outcomes like mortality and complications. However, patient‐reported outcomes (PROs; eg, health‐related quality of life [HRQOL]) are becoming increasingly important and should be incorporated into this quality assessment. Using funnel plots has several advantages, including clearly visualized precision, detection of volume‐ef… Show more

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Cited by 16 publications
(12 citation statements)
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“…After this, we mainly used three methods to test the sensitivity of the results of our MR analysis. We tested the heterogeneity of SNPs using IVW and MR-Egger methods, and used funnel plots as validation (23,24). We apply the MR-Egger method to evaluate whether there is horizontal pleiotropy in SNPs (25).…”
Section: Discussionmentioning
confidence: 99%
“…After this, we mainly used three methods to test the sensitivity of the results of our MR analysis. We tested the heterogeneity of SNPs using IVW and MR-Egger methods, and used funnel plots as validation (23,24). We apply the MR-Egger method to evaluate whether there is horizontal pleiotropy in SNPs (25).…”
Section: Discussionmentioning
confidence: 99%
“…The use of aggregated PROM data as a benchmark for quality of care was questioned by doctors due to the large case-mix differences between centres. Recent research in a dialysis setting indeed suggests that case-mix adjustments have to be made [ 60 ], as has also been illustrated in stroke care [ 61 ]. In addition, doctors indicate that it is difficult, if not impossible, to interpret aggregated PROM results without knowing the patient, their comorbidity, their history and their personality.…”
Section: Discussionmentioning
confidence: 99%
“…The indirectly standardized ratios for different sites were described in the funnel plot with 95% and 99.8% Poisson limits. [ 16 , 17 ] All the analysis was performed in SAS, version 9.4 (SAS Institute, Cary, North Carolina, USA) and R 3.6.1. A two-sided P value of 0.05 was used to determine the statistical significance.…”
Section: Methodsmentioning
confidence: 99%
“…Then, the indirectly standardized ratio for each site was calculated as the observed amount of ACS usage divided by the expected number of ACS usage. The indirectly standardized ratios for different sites were described in the funnel plot with 95% and 99.8% Poisson limits [16,17] . All the analysis was performed in SAS, version 9.4 (SAS Institute, Cary, North Carolina, USA) and R 3.6.1.…”
Section: Methodsmentioning
confidence: 99%