April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Feasibility of using OpenEyes to identify potentially eligible patients for clinical research
Author Affiliations & Notes
  • Annelie Small
    NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Bill Aylward
    NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Ratna Khan
    NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Carlos E Pavesio
    NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Maria Pefkianaki
    NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Praveen J Patel
    NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 5591. doi:
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      Annelie Small, Bill Aylward, Ratna Khan, Carlos E Pavesio, Maria Pefkianaki, Praveen J Patel; Feasibility of using OpenEyes to identify potentially eligible patients for clinical research. Invest. Ophthalmol. Vis. Sci. 2014;55(13):5591.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: Identification of potentially eligible patients for clinical trials is vital for the success of undertaking clinical research and to ensure the widest possible access to new and advanced therapies through research. A new electronic patient record for ophthalmology (OpenEyes), which is modular and searchable has recently been developed and introduced at Moorfields Eye Hospital. One of the key strength of the software is in the clinical research arena where it can be used to identify patients who may be eligible for clinical trials therefore potentially reducing the time taken and resource deployed in meeting recruitment goals for clinical trials while also enabling the widest possible access of clinical trials to potentially eligible patients.

Methods: In this feasibility analysis, we identified two clinical trials for the treatment of rare retinal conditions: one trial for patients with multifocal choroiditis and panuveitis patients and the other for patients with Behςet’s disease patients who are taking 20mg of Prednisolone orally. Secondly several search items mapped to the inclusion criteria of the trials were identified plus a time frame for the search period. OpenEyes was then used to search the ophthalmology patient record database for patients at Moorfields Eye Hospital who meet the search criteria. Finally, a sub-investigator applied the inclusion criteria and exclusion criteria from the clinical trial protocols to the electronic patient record to confirm potential eligibility.

Results: A list of 58 patients for the Behςet’s disease trial [search time frame = 4 months] of which 5 are eligible for the trial and a list of 33 patients for the multifocal choroiditis trial [search time frame = 2 months] of which 1 is eligible for the trial was generated. The time spent on generating the lists was ≤ 3 minutes in total, including inputting search items and the system search.

Conclusions: This confirms the feasibility of using OpenEyes successfully to identify patients who may be eligible for clinical trials. This novel, searchable system of the ophthalmology database has great potential to rapidly identify patients who may be eligible for clinical trials at Moorfields Eye Hospital thereby enabling more patients to access new therapies through clinical research while potentially reducing the time and resource needed to complete clinical trial recruitment.

Keywords: 468 clinical research methodology  
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