Literature DB >> 18633418

How to interpret your dot: decoding the message of clinical performance indicators.

J Schulman1, D J Spiegelhalter, G Parry.   

Abstract

Comparative performance reports continue to proliferate, so it is increasingly important that healthcare workers can interpret the graphically displayed results correctly. This article acquaints readers with key concepts for thinking clearly and critically about such displays: (1) articulating the question a display answers, along with reflecting on questions the display might appear to, but does not, answer; (2) establishing that provider comparisons are made fairly, ever mindful of methodological assumptions and limitations; (3) accounting for systematic differences among performers that are unexplained by specified predictors, that is, random effect methods that yield 'shrunken' estimates; (4) understanding funnel plots used to summarize complex analyses and how one may vary the interrogative focus so that 'outlier' values most likely signal extraordinary performance. Finally, these concepts are given broader context in a view of the ultimate aim of the evaluative enterprise.

Mesh:

Year:  2008        PMID: 18633418     DOI: 10.1038/jp.2008.67

Source DB:  PubMed          Journal:  J Perinatol        ISSN: 0743-8346            Impact factor:   2.521


  5 in total

1.  Perils and opportunities of comparative performance measurement.

Authors:  Jochen Profit; LeChauncy D Woodard
Journal:  Arch Pediatr Adolesc Med       Date:  2012-02

2.  Impact of guideline-recommended dietitian assessments on weight gain in infants with cystic fibrosis.

Authors:  Thida Ong; Frankline M Onchiri; Maria T Britto; Sonya L Heltshe; Larry G Kessler; Michael Seid; Bonnie W Ramsey
Journal:  J Cyst Fibros       Date:  2021-08-26       Impact factor: 5.482

3.  Hospital variation in admissions for low back pain following an emergency department presentation: a retrospective study.

Authors:  Giovanni Ferreira; Marina Lobo; Bethan Richards; Michael Dinh; Chris Maher
Journal:  BMC Health Serv Res       Date:  2022-07-12       Impact factor: 2.908

4.  The probability of being identified as an outlier with commonly used funnel plot control limits for the standardised mortality ratio.

Authors:  Sarah E Seaton; Bradley N Manktelow
Journal:  BMC Med Res Methodol       Date:  2012-07-16       Impact factor: 4.615

5.  The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

Authors:  Anita Lindmark; Bart van Rompaye; Els Goetghebeur; Eva-Lotta Glader; Marie Eriksson
Journal:  PLoS One       Date:  2016-04-07       Impact factor: 3.240

  5 in total

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