AIMS: To develop a methodology for case-mix adjustment of surgical outcomes for individual cataract surgeons using electronically collected multi-centre data conforming to the cataract national data set (CND). METHODS: Routinely collected anonymised data were remotely extracted from electronic patient record (EPR) systems in 12 participating NHS Trusts undertaking cataract surgery. Following data checks and cleaning, analyses were carried out to risk adjust outcomes for posterior capsule rupture rates for individual surgeons, with stratification by surgical grade. RESULTS: A total of 406 surgeons from 12 NHS Trusts submitted data on 55,567 cataract operations between November 2001 and July 2006 (86% from January 2004). In all, 283 surgeons contributed data on >25 cases, providing 54,319 operations suitable for detailed analysis. Case-mix adjusted results of individual surgeons are presented as funnel plots for all surgeons together, and separately for three different grades of surgeon. Plots include 95 and 99.8% confidence limits around the case-mix adjusted outcomes for detection of surgical outliers. CONCLUSIONS: Routinely collected electronic data conforming to the CND provides sufficient detail for case-mix adjustment of cataract surgical outcomes. The validation of these risk indicators should be carried out using fresh data to confirm the validity of the risk model. Once validated this model should provide an equitable approach for peer-to-peer comparisons in the context of revalidation.
AIMS: To develop a methodology for case-mix adjustment of surgical outcomes for individual cataract surgeons using electronically collected multi-centre data conforming to the cataract national data set (CND). METHODS: Routinely collected anonymised data were remotely extracted from electronic patient record (EPR) systems in 12 participating NHS Trusts undertaking cataract surgery. Following data checks and cleaning, analyses were carried out to risk adjust outcomes for posterior capsule rupture rates for individual surgeons, with stratification by surgical grade. RESULTS: A total of 406 surgeons from 12 NHS Trusts submitted data on 55,567 cataract operations between November 2001 and July 2006 (86% from January 2004). In all, 283 surgeons contributed data on >25 cases, providing 54,319 operations suitable for detailed analysis. Case-mix adjusted results of individual surgeons are presented as funnel plots for all surgeons together, and separately for three different grades of surgeon. Plots include 95 and 99.8% confidence limits around the case-mix adjusted outcomes for detection of surgical outliers. CONCLUSIONS: Routinely collected electronic data conforming to the CND provides sufficient detail for case-mix adjustment of cataract surgical outcomes. The validation of these risk indicators should be carried out using fresh data to confirm the validity of the risk model. Once validated this model should provide an equitable approach for peer-to-peer comparisons in the context of revalidation.
Authors: N El-Hindy; R L Johnston; P Jaycock; T Eke; A J Braga; D M Tole; P Galloway; J M Sparrow Journal: Eye (Lond) Date: 2008-03-14 Impact factor: 3.775
Authors: P Jaycock; R L Johnston; H Taylor; M Adams; D M Tole; P Galloway; C Canning; J M Sparrow Journal: Eye (Lond) Date: 2007-11-23 Impact factor: 3.775
Authors: N Narendran; P Jaycock; R L Johnston; H Taylor; M Adams; D M Tole; R H Asaria; P Galloway; J M Sparrow Journal: Eye (Lond) Date: 2008-03-07 Impact factor: 3.775
Authors: J D Benzimra; R L Johnston; P Jaycock; P H Galloway; G Lambert; A K K Chung; T Eke; J M Sparrow Journal: Eye (Lond) Date: 2008-02-08 Impact factor: 3.775
Authors: Tiarnan D L Keenan; Qingyu Chen; Elvira Agrón; Yih-Chung Tham; Jocelyn Hui Lin Goh; Xiaofeng Lei; Yi Pin Ng; Yong Liu; Xinxing Xu; Ching-Yu Cheng; Mukharram M Bikbov; Jost B Jonas; Sanjeeb Bhandari; Geoffrey K Broadhead; Marcus H Colyer; Jonathan Corsini; Chantal Cousineau-Krieger; William Gensheimer; David Grasic; Tania Lamba; M Teresa Magone; Michele Maiberger; Arnold Oshinsky; Boonkit Purt; Soo Y Shin; Alisa T Thavikulwat; Zhiyong Lu; Emily Y Chew Journal: Ophthalmology Date: 2022-01-03 Impact factor: 14.277