Introduction 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.
Methods 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.
Results 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.
Conclusions 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.
- continuous quality improvement
- Decision support, computerised
- Diagnostic errors
- Healthcare quality improvement
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Contributors FFWH: project originator, project (clinical) lead (University Hospitals of North Midlands) and contributed to writing the paper. AAF: project (Clinical biochemistry) lead (University Hospitals of North Midlands) and contributed to writing the paper. SCL: project manager and contributed to writing the paper. BGI: project (clinical) lead (University Hospital of South Manchester) and contributed to writing the paper. MF: quality improvement contribution. JS: statistics and methodology. RF and GX: health economics. CG and AG: clinical management of AI cases and membership of the multidisciplinary team. EM: IT management and Trust adoption. SO supported the work in his capacity as a primary care clinician and also providing a commissioner’s perspective. All authors reviewed the manuscript.
Funding This study was support by a grant from the Health Foundation (GIFTS 7555: CRM 2216).
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the article.
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