Adrenal lesions found incidentally: how to improve clinical and cost-effectiveness.


Journal

BMJ open quality
ISSN: 2399-6641
Titre abrégé: BMJ Open Qual
Pays: England
ID NLM: 101710381

Informations de publication

Date de publication:
02 2020
Historique:
received: 01 11 2018
revised: 21 10 2019
accepted: 22 10 2019
entrez: 15 2 2020
pubmed: 15 2 2020
medline: 31 10 2020
Statut: ppublish

Résumé

Adrenal incidentalomas are lesions that are incidentally identified while scanning for other conditions. While most are benign and hormonally non-functional, around 20% are malignant and/or hormonally active, requiring prompt intervention. Malignant lesions can be aggressive and life-threatening, while hormonally active tumours cause various endocrine disorders, with significant morbidity and mortality. Despite this, management of patients with adrenal incidentalomas is variable, with no robust evidence base. This project aimed to establish more effective and timely management of these patients. We developed a web-based, electronic Adrenal Incidentaloma Management System (eAIMS), which incorporated the evidence-based and National Health Service-aligned 2016 European guidelines. The system captures key clinical, biochemical and radiological information necessary for adrenal incidentaloma patient management and generates a pre-populated outcome letter, saving clinical and administrative time while ensuring timely management plans with enhanced safety. Furthermore, we developed a prioritisation strategy, with members of the multidisciplinary team, which prioritised high-risk individuals for detailed discussion and management. Patient focus groups informed process-mapping and multidisciplinary team process re-design and patient information leaflet development. The project was partnered by University Hospital of South Manchester to maximise generalisability. Implementation of eAIMS, along with improvements in the prioritisation strategy, resulted in a 49% reduction in staff hands-on time, as well as a 78% reduction in the time from adrenal incidentaloma identification to multidisciplinary team decision. A health economic analysis identified a 28% reduction in costs. The system's in-built data validation and the automatic generation of the multidisciplinary team outcome letter improved patient safety through a reduction in transcription errors. We are currently developing the next stage of the programme to proactively identify all new adrenal incidentaloma cases.

Identifiants

pubmed: 32054639
pii: bmjoq-2018-000572
doi: 10.1136/bmjoq-2018-000572
pmc: PMC7047483
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Fahmy W F Hanna (FWF)

Department of Diabetes and Endocrinology, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK fahmy.hanna@uhnm.nhs.uk.
Centre for Health and Development, Staffordshire University, Stoke-on-Trent, UK.

Basil G Issa (BG)

Department of Diabetes and Endocrinology, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK.

Simon C Lea (SC)

Research and Innovation Directorate, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK.

Cherian George (C)

Imaging, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, Staffordshire, UK.

Anurag Golash (A)

Department of Urology, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK.

Mike Firn (M)

Springfield Consultancy, South West London and Saint George's Mental Health NHS Trust, London, UK.

Seyi Ogunmekan (S)

Furlong Medical Centre, Stoke-on-Trent, UK.

Elloise Maddock (E)

Department of Information and Communications Technology, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK.

Julius Sim (J)

School of Primary, Community and Social Care, Keele University, Keele, UK.

Georgios Xydopoulos (G)

Department of Health Economics, University of East Anglia, Norwich, UK.

Richard Fordham (R)

Department of Health Economics, University of East Anglia, Norwich, UK.

Anthony A Fryer (AA)

Department of Clinical Biochemistry, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK.

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