Validation of a Virtual Model of Service Delivery for Choroidal Nevi

December 7, 2018 updated by: Manchester University NHS Foundation Trust

Validation of a Virtual Clinic for Choroidal Nevomelanocytic Lesions: Safety, Patient Acceptability and Health Economics Analysis

Choroidal nevomelanocytic lesions have a high prevalence affecting up to 7% of the entire population and are increasingly incidentally identified during routine eye check- ups in community optometry services. Given the tendency to err on the side of caution, there is evidence of excessive referrals challenging service delivery in both tertiary eye units and specialist ocular oncology services. Although previous studies have examined the natural history and risk factors for growth of choroidal nevomelanocytic lesions, optimal delivery of management remains uncertain. Management approaches display diversity with respect to the number and type of baseline investigations, the duration and frequency of monitoring of relevant patients. Utilisation of the skills of allied health professionals in appropriate cases would allow streamlining service delivery in a socialised healthcare system, maximise capacity, and allow community services to play an enhanced role. However, the evidence for this model of delivery is lacking. Within existing models of care for these lesions, patients are faced with delays, need for more than one attendances to the hospital and increased anxiety around prognosis.

This project aims to answer the question of whether these low-risk, bland incidental findings might possibly be managed by allied health professionals with the use of clinical imaging and specific algorithms to make appropriate management decisions. We aim to validate a model of service delivery on a virtual basis that will accommodate for capacity pressures to accept all relevant referrals, while offering a safe service and optimising patient experience of care. We will thus validate the setting up of a virtual choroidal nevomelanocytic clinic in terms of safety and patient acceptability. More specifically, the degree of agreement between management decisions made by non-medical graders on the basis of imaging data alone as opposed to gold standard decisions (clinical and imaging tests combined) is examined. Health economics analysis of the proposed service delivery model will be undertaken to demonstrate cost-effectiveness.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

199

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

14 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients under the care of MREH and MEH for ocular nevomelanocytic lesions (CNL) will be recruited prospectively into the study.

Description

All patients attending the CNL clinics of MREH/MEH who have offered informed consent will be included in the study. Patients who are then diagnosed with alternate pathologies other than CNL (erroneous referrals) will be excluded from agreement analysis. Recognition of alternate pathologies by non-medical graders will, however, be an additional outcome measure for this project. Cases of Congenital Hypertrophy of the Retinal Pigment Epithelium (CHRPE) will be classified as 'alternate pathology' for the purposes of this study. Exclusion criteria will be media opacities (cornea, lens, vitreous body) precluding adequate visualisation of fundus and incomplete set of imaging data.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Degree of agreement (kappa co-efficient) between management decisions reached clinically as opposed to those reached on the basis of imaging tests alone (virtual model)
Time Frame: 18 months
Validation of the virtual model of service delivery will be sought by calculating the degree of agreement (kappa co-efficient) between management decisions (Discharge, Review or Refer patients) reached by direct clinical examination as opposed to decisions reached through assessing imaging tests only.
18 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 8, 2016

Primary Completion (Actual)

March 31, 2018

Study Completion (Actual)

March 31, 2018

Study Registration Dates

First Submitted

March 3, 2016

First Submitted That Met QC Criteria

March 8, 2016

First Posted (Estimate)

March 14, 2016

Study Record Updates

Last Update Posted (Actual)

December 11, 2018

Last Update Submitted That Met QC Criteria

December 7, 2018

Last Verified

December 1, 2018

More Information

Terms related to this study

Other Study ID Numbers

  • Nevus Protocol v1.0

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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