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Using knowledge discovery through data mining to gain intelligence from routinely collected incident reporting in an acute English hospital

Alison Leary (School of Health and Social Care, London South Bank University, London, UK) (School of Health, University of South Eastern Norway, Oslo, Norway)
Robert Cook (School of Health, Birmingham City University - Bournville Campus, Birmingham, UK)
Sarahjane Jones (School of Health and Social Care, Staffordshire University, Stoke-on-Trent, UK)
Mark Radford (Chief Nurse, Health Education England and Deputy Chief Nursing Officer, NHS England)
Judtih Smith (University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK)
Malcolm Gough (University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK)
Geoffrey Punshon (Department of Health and Social Care, London South Bank University School of Health and Social Care, London, UK)

International Journal of Health Care Quality Assurance

ISSN: 0952-6862

Article publication date: 21 February 2020

Issue publication date: 31 March 2020

Abstract

Purpose

Incident reporting systems are commonly deployed in healthcare but resulting datasets are largely warehoused. This study explores if intelligence from such datasets could be used to improve quality, efficiency, and safety.

Design/methodology/approach

Incident reporting data recorded in one NHS acute Trust was mined for insight (n = 133,893 April 2005–July 2016 across 201 fields, 26,912,493 items). An a priori dataset was overlaid consisting of staffing, vital signs, and national safety indicators such as falls. Analysis was primarily nonlinear statistical approaches using Mathematica V11.

Findings

The organization developed a deeper understanding of the use of incident reporting systems both in terms of usability and possible reflection of culture. Signals emerged which focused areas of improvement or risk. An example of this is a deeper understanding of the timing and staffing levels associated with falls. Insight into the nature and grading of reporting was also gained.

Practical implications

Healthcare incident reporting data is underused and with a small amount of analysis can provide real insight and application to patient safety.

Originality/value

This study shows that insight can be gained by mining incident reporting datasets, particularly when integrated with other routinely collected data.

Keywords

Citation

Leary, A., Cook, R., Jones, S., Radford, M., Smith, J., Gough, M. and Punshon, G. (2020), "Using knowledge discovery through data mining to gain intelligence from routinely collected incident reporting in an acute English hospital", International Journal of Health Care Quality Assurance, Vol. 33 No. 2, pp. 221-234. https://doi.org/10.1108/IJHCQA-08-2018-0209

Publisher

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Emerald Publishing Limited

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