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Impact of developing a multidisciplinary coded dataset standard on administrative data accuracy for septoplasty, septorhinoplasty and nasal trauma surgery

Published online by Cambridge University Press:  02 February 2017

S A R Nouraei*
Affiliation:
Department of ENT Surgery, Auckland City Hospital, Auckland, New Zealand
A Hudovsky
Affiliation:
Clinical Coding, Charing Cross Hospital, London, UK
J S Virk
Affiliation:
Department of ENT Surgery, Barts Health NHS Trust, London, UK
H A Saleh
Affiliation:
Department of ENT Surgery, Auckland City Hospital, Auckland, New Zealand
*
Address for correspondence: Mr S A R Nouraei, Department of ENT Surgery, Charing Cross Hospital, London W6 8RF, UK E-mail: RN@cantab.net
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Abstract

Objective:

This study aimed to develop a multidisciplinary coded dataset standard for nasal surgery and to assess its impact on data accuracy.

Method:

An audit of 528 patients undergoing septal and/or inferior turbinate surgery, rhinoplasty and/or septorhinoplasty, and nasal fracture surgery was undertaken.

Results:

A total of 200 septoplasties, 109 septorhinoplasties, 57 complex septorhinoplasties and 116 nasal fractures were analysed. There were 76 (14.4 per cent) changes to the primary diagnosis. Septorhinoplasties were the most commonly amended procedures. The overall audit-related income change for nasal surgery was £8.78 per patient. Use of a multidisciplinary coded dataset standard revealed that nasal diagnoses were under-coded; a significant proportion of patients received more precise diagnoses following the audit. There was also significant under-coding of both morbidities and revision surgery.

Conclusion:

The multidisciplinary coded dataset standard approach can improve the accuracy of both data capture and information flow, and, thus, ultimately create a more reliable dataset for use outcomes and health planning.

Information

Type
Main Articles
Copyright
Copyright © JLO (1984) Limited 2017 
Figure 0

Fig. 1 Diagram showing an example of nasal surgery coding which demonstrates the complexities of abstraction, which are strongly affected by the clarity and legibility of the primary documentation. PDS = polydioxanone

Figure 1

Fig. 2 Diagram showing the minimum coded dataset standard for nasal surgery.

Figure 2

Table I Audit using a nasal surgery minimum coded dataset standard: impact on coding accuracy and income

Figure 3

Table II Development of a minimum coded dataset standard: impact on the accuracy of nasal surgery coding