The electronic Adrenal Incidentaloma Management System; “eAIMS”

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Case Study Summary
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Overview summary:
Adrenal incidentalomas (AI) are lesions found whilst patients undergo radiological scans for other conditions. Most are benign and hormonally non-functional. However, 20% are malignant and/or produce excess hormones. Malignant lesions require rapid treatment as tumours can be aggressive and life-threatening.

This project based at University Hospitals of North Midlands and University Hospital of South Manchester aimed to establish effective management of patients with AIs, minimising delays in diagnosis/treatment and reducing patient distress.
Challenge identified and actions taken :
  1. We did not develop consensus guidelines - these became redundant following publication of 2016 guidelines.
  2. How to make the system utilisable with different centres IT systems within our pilot work’s limited budget.
  3. We identified the importance of incorporating an MDT outcome letter into eAIMS to save time and reduce errors. Ultimately, this will positively impact on uptake by other centres.
Actions:
  1. The system is aligned with the newly published European Guidelines for AI (2016).
  2. In collaboration with Trust IT, we developed a web-based embedded electronic management system (the electronic Adrenal Incidentaloma Management System; “eAIMS”). Use of a web-based system improves ability of other centres to uptake eAIMS, even if they utilise different IT systems.
  3. The system captures key information on AI cases and generates a pre-populated MDT outcome letter, saving clinical and administrative time whilst ensuring timely management with enhanced safety (reduced need to re-dictate and type results, minimising transcription errors). We also developed a prioritisation strategy, in collaboration with MDT members, which ensured that high risk individuals are prioritised for prompt discussion and decisions.
Impacts / outcomes:

There are many positives outcomes from the eAIMS project. It has made a positive impact within the healthcare industry and helped to improve patient safety, reduced the time from AI identification to MDT decision and much more. The impact that eAIMS has made is discussed in more detail below:
  1. By using the newly published European guidelines, we developed a novel, web-based eAIMS that links the clinical, biochemical and radiological data necessary for assessing and managing AI patients.
  2. Implementation of eAIMS, along with improvements in the prioritisation strategy, resulted in:
    • A 78% reduction in the time from AI identification to MDT decision (vs. our original primary objective of 20%). This significantly reduced delay, which will result in less patient anxiety.
    • A 49% reduction in staff hands-on time.
    • Improved patient safety:
      • A reduction in the risk of transcription errors, given the in-built error validation of entered data and the automatic generation of the MDT outcome letter as opposed to repeated human-instigated steps.
      • Our analysis identified that 70% of AIs were not being followed-up, and hence we are now developing the next stage of the programme to proactively identify all new AI cases, thereby avoiding missing cases (work in progress).
    • A 28% reduction in costs (from an independent health economics analysis).
  3. Links outside UHNM: Built-in the project is the partnership with UHSM to explore the generalisability and utility of the system. The system was conceived as web-based from the outset to facilitate wider adoption. We have also established dialogue with the Association of British Clinical Diabetologists to showcase our work.
Which local or national clinical or policy priorities does this innovation address:
Firstly, the eAIMS system has improved the prioritisation strategy of AI patients, which has led to a reduction in the time from AI identification to MDT decisions. It has optimised the likelihood of tumour treatments from earlier identification and enhanced digital health. • The eAIMS system is already in place and has become the default at UHNM (University Hospitals of North Midlands). • The web-based system has also already been adopted by University Hospital of South Manchester and is fully functional. This will demonstrate the adoptability by other Trusts.
Plans for the future:
Our plan for the future is to spread the innovation:
  • One of the ways we will spread the innovation is by offering the system to selected Trusts across the UK. By doing this we hope that the system will be adopted by other Trusts.
  • We also would like to further develop the eAIMS system to ensure that it is more user-friendly and less time-consuming (e.g. a paper form to be scanned to allow data entry).
  • Furthermore, another plan for us is that the data management infra-structure (e.g. system administrator) to manage the core system, ensuring data quality, managing enquires, facilitating audits and more.
  • Moreover, we would like to explore other options to enhance and evaluate cost-effectiveness, patient benefit (as measured by changes in anxiety levels).
Tips for adoption:
System is web-based making it very easy for other centres to adopt the system. This has already been demonstrated through University Hospital of South Manchester, who operate on a different base IT system to UHNM, and have successfully adopted and utilised the eAIMS system.
Contact for further information:
For more information contact: Simon.Lea@uhnm.nhs.uk
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