Using medico-legal claims for quality improvement in maternity care: application and revision of an NHSLA coding taxonomy.

BJOG

Department of Obstetrics and Gynaecology, School of Clinical Sciences, The Ritchie Centre, Monash University, Clayton, Vic., Australia.

Published: November 2019

Objective: To validate the NHSLA maternity claims taxonomy at the level of a single maternity service and assess its ability to direct quality improvement.

Design: Qualitative descriptive study.

Setting: Medico-legal claims between 1 January 2000 and 31 December 2016 from a maternity service in metropolitan Melbourne, Australia.

Population: All obstetric claims and incident notifications occurring within the date range were included for analysis.

Methods: De-identified claims and notifications data were derived from the files of the insurer of Victorian public health services. Data included claim date, incident date and summary, and claim cost. All reported issues were coded using the NHSLA taxonomy and the lead issue identified.

Main Outcome Measures: Rate of claims and notifications, relative frequency of issues, a revised taxonomy.

Results: A combined total of 265 claims and incidents were reported during the 6 years. Of these 59 were excluded, leaving 198 medico-legal events for analysis (1.66 events/1000 births). The costs for all claims was $46.7 million. The most common claim issues were related to management of labour (n = 63, $17.7 million), cardiotocographic interpretation (n = 43, $24.4 million), and stillbirth (n = 35, $656,750). The original NHSLA classification was not sufficiently detailed to inform care improvement programmes. A revised taxonomy and coding flowchart is presented.

Conclusions: Systematic analysis of obstetric medico-legal claims data can potentially be used to inform quality and safety improvement.

Tweetable Abstract: New taxonomy to target health improvement from maternity claims based on NHSLA Ten Years of Maternity Claims.

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Source
http://dx.doi.org/10.1111/1471-0528.15823DOI Listing

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