Going paperless: improved cataract surgery outcome data quality in a new fully electronic unit

A. Z. Nghiem, C. Canning, J. Eason, John Sparrow, T. H. Flynn

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)
87 Downloads (Pure)

Abstract

Objectives: To report outcome data on the first 5000 consecutive cataract cases at a new paperless eye unit and benchmark against the Royal College of Ophthalmologists’ National Ophthalmology Database (RCOphth NOD). Methods: Using the in-built audit tool of the electronic medical records system, data from all cataract operations performed between 1 April 2014 and 13 January 2017 were compiled. Results: Five thousand and eight cases were recorded of which the overall intra-operative complication rate was 2.4%, the most common being posterior capsular rupture—1.14%. Follow-up data on post-operative complications were recorded in 98.6% of cases. Pre- and post-operative visual acuities was measured in 98.0% of cases. In all, 40.8% of eyes achieved a visual acuity of 6/6 or better and 90.7% achieved 6/12 or better. Conclusions: A data set of >5000 consecutive cataract operations was obtained in this eye department. The recording of pre- and post-operative visual acuity in 98% of cases compare very favourably to the RCOphth NOD Audit Report 2017 where pre- and post-operative visual acuities were recorded in only 57.1% of operations. Despite this difference, the outcome measures from this unit and RCOphth NOD were very similar, validating the results of the RCOphth NOD audit reports. Significantly, when applying the RCOphth NOD audit criteria for measuring post-operative visual acuity, approximately 15% of cases were excluded from the data set, reducing the completeness of the data set. Paperless ophthalmology units are feasible in today’s NHS and can produce near complete cataract data sets; this can ultimately lead to more comprehensive and reliable aggregate cataract outcome data.

Original languageEnglish
Pages (from-to)948-952
Number of pages5
JournalEye
Volume33
Issue number6
Early online date11 Feb 2019
DOIs
Publication statusPublished - 1 Jun 2019

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