Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Was Rodney Ledward a statistical outlier? Retrospective analysis using hospital data to identify gynaecologists performance
Show others and affiliations
2005 (English)In: British Medical Journal, 2005, 330, 929Article in journal (Refereed)
Abstract [en]

Objectives: To investigate whether routinely collected data from hospital episode statistics could be used to identify the gynaecologist Rodney Ledward, who was suspended in 1966 and was the subject of the Ritchie inquiry into quality and practice within the NHS.

Design A mixed scanning approach was used to identify seven variables from hospital episode statistics that were likely to be associated with potentially poor performance. A blinded multivariate analysis was undertaken to determine the distance (known as the Mahalanobis distance) in the seven indicator multidimensional space that each consultant was from the average consultant in each year. The change in Mahalanobis distance over time was also investigated by using a mixed effects model.



Setting: NHS hospital trusts in two English regions, in the five years from 1991-2 to 1995-6.



Population: Gynaecology consultants (n = 143) and their hospital episode statistics data.



Main outcome measure Whether Ledward was a statistical outlier at the 95% level.



Results: The proportion of consultants who were outliers in any one year (at the 95% significance level) ranged from 9% to 20%. Ledward appeared as an outlier in three of the five years. Our mixed effects (multi-year) model identified nine high outlier consultants, including Ledward.



Conclusion: It was possible to identify Ledward as an outlier by using hospital episode statistics data. Although our method found other outlier consultants, we strongly caution that these outliers should not be overinterpreted as indicative of "poor" performance. Instead, a scientific search for a credible explanation should be undertaken, but this was outside the remit of our study. The set of indicators used means that cancer specialists, for example, are likely to have high values for several indicators, and the approach needs to be refined to deal with case mix variation. Even after allowing for that, the interpretation of outlier status is still as yet unclear. Further prospective evaluation of our method is warranted, but our overall approach may be potentially useful in other settings, especially where performance entails several indicator variables.

Place, publisher, year, edition, pages
2005.
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:kau:diva-25673OAI: oai:DiVA.org:kau-25673DiVA, id: diva2:599452
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2013-01-22

Open Access in DiVA

No full text in DiVA

Authority records BETA

Almasri, Abdullah

Search in DiVA

By author/editor
Almasri, Abdullah
By organisation
Department of Economics and Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 86 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf