Abstract
Background
Many glaucoma referrals from the community to hospital eye services are unnecessary. Imaging technologies can potentially be useful to triage this population.
Objectives
To assess the diagnostic performance and cost-effectiveness of imaging technologies as triage tests for identifying people with glaucoma.
Design
Within-patient comparative diagnostic accuracy study. Markov economic model comparing the cost-effectiveness of a triage test with usual care.
Setting
Secondary care.
Participants
Adults referred from the community to hospital eye services for possible glaucoma.
Interventions
Heidelberg Retinal Tomography (HRT), including two diagnostic algorithms, glaucoma probability score (HRT-GPS) and Moorfields regression analysis (HRT-MRA); scanning laser polarimetry [glaucoma diagnostics (GDx)]; and optical coherence tomography (OCT). The reference standard was clinical examination by a consultant ophthalmologist with glaucoma expertise including visual field testing and intraocular pressure (IOP) measurement.
Main outcome measures
(1) Diagnostic performance of imaging, using data from the eye with most severe disease. (2) Composite triage test performance (imaging test, IOP measurement and visual acuity measurement), using data from both eyes, in correctly identifying clinical management decisions, that is ‘discharge’ or ‘do not discharge’. Outcome measures were sensitivity, specificity and incremental cost per quality-adjusted life-year (QALY).
Results
Data from 943 of 955 participants were included in the analysis. The average age was 60.5 years (standard deviation 13.8 years) and 51.1% were females. Glaucoma was diagnosed by the clinician in at least one eye in 16.8% of participants; 37.9% of participants were discharged after the first visit. Regarding diagnosing glaucoma, HRT-MRA had the highest sensitivity [87.0%, 95% confidence interval (CI) 80.2% to 92.1%] but the lowest specificity (63.9%, 95% CI 60.2% to 67.4%) and GDx had the lowest sensitivity (35.1%, 95% CI 27.0% to 43.8%) but the highest specificity (97.2%, 95% CI 95.6% to 98.3%). HRT-GPS had sensitivity of 81.5% (95% CI 73.9% to 87.6%) and specificity of 67.7% (95% CI 64.2% to 71.2%) and OCT had sensitivity of 76.9% (95% CI 69.2% to 83.4%) and specificity of 78.5% (95% CI 75.4% to 81.4%). Regarding triage accuracy, triage using HRT-GPS had the highest sensitivity (86.0%, 95% CI 82.8% to 88.7%) but the lowest specificity (39.1%, 95% CI 34.0% to 44.5%), GDx had the lowest sensitivity (64.7%, 95% CI 60.7% to 68.7%) but the highest specificity (53.6%, 95% CI 48.2% to 58.9%). Introducing a composite triage station into the referral pathway to identify appropriate referrals was cost-effective. All triage strategies resulted in a cost reduction compared with standard care (consultant-led diagnosis) but with an associated reduction in effectiveness. GDx was the least costly and least effective strategy. OCT and HRT-GPS were not cost-effective. Compared with GDx, the cost per QALY gained for HRT-MRA is £22,904. The cost per QALY gained with current practice is £156,985 compared with HRT-MRA. Large savings could be made by implementing HRT-MRA but some benefit to patients will be forgone. The results were sensitive to the triage costs.
Conclusions
Automated imaging can be effective to aid glaucoma diagnosis among individuals referred from the community to hospital eye services. A model of care using a triage composite test appears to be cost-effective.
Future work
There are uncertainties about glaucoma progression under routine care and the cost of providing health care. The acceptability of implementing a triage test needs to be explored.
Funding
The National Institute for Health Research Health Technology Assessment programme.
Many glaucoma referrals from the community to hospital eye services are unnecessary. Imaging technologies can potentially be useful to triage this population.
Objectives
To assess the diagnostic performance and cost-effectiveness of imaging technologies as triage tests for identifying people with glaucoma.
Design
Within-patient comparative diagnostic accuracy study. Markov economic model comparing the cost-effectiveness of a triage test with usual care.
Setting
Secondary care.
Participants
Adults referred from the community to hospital eye services for possible glaucoma.
Interventions
Heidelberg Retinal Tomography (HRT), including two diagnostic algorithms, glaucoma probability score (HRT-GPS) and Moorfields regression analysis (HRT-MRA); scanning laser polarimetry [glaucoma diagnostics (GDx)]; and optical coherence tomography (OCT). The reference standard was clinical examination by a consultant ophthalmologist with glaucoma expertise including visual field testing and intraocular pressure (IOP) measurement.
Main outcome measures
(1) Diagnostic performance of imaging, using data from the eye with most severe disease. (2) Composite triage test performance (imaging test, IOP measurement and visual acuity measurement), using data from both eyes, in correctly identifying clinical management decisions, that is ‘discharge’ or ‘do not discharge’. Outcome measures were sensitivity, specificity and incremental cost per quality-adjusted life-year (QALY).
Results
Data from 943 of 955 participants were included in the analysis. The average age was 60.5 years (standard deviation 13.8 years) and 51.1% were females. Glaucoma was diagnosed by the clinician in at least one eye in 16.8% of participants; 37.9% of participants were discharged after the first visit. Regarding diagnosing glaucoma, HRT-MRA had the highest sensitivity [87.0%, 95% confidence interval (CI) 80.2% to 92.1%] but the lowest specificity (63.9%, 95% CI 60.2% to 67.4%) and GDx had the lowest sensitivity (35.1%, 95% CI 27.0% to 43.8%) but the highest specificity (97.2%, 95% CI 95.6% to 98.3%). HRT-GPS had sensitivity of 81.5% (95% CI 73.9% to 87.6%) and specificity of 67.7% (95% CI 64.2% to 71.2%) and OCT had sensitivity of 76.9% (95% CI 69.2% to 83.4%) and specificity of 78.5% (95% CI 75.4% to 81.4%). Regarding triage accuracy, triage using HRT-GPS had the highest sensitivity (86.0%, 95% CI 82.8% to 88.7%) but the lowest specificity (39.1%, 95% CI 34.0% to 44.5%), GDx had the lowest sensitivity (64.7%, 95% CI 60.7% to 68.7%) but the highest specificity (53.6%, 95% CI 48.2% to 58.9%). Introducing a composite triage station into the referral pathway to identify appropriate referrals was cost-effective. All triage strategies resulted in a cost reduction compared with standard care (consultant-led diagnosis) but with an associated reduction in effectiveness. GDx was the least costly and least effective strategy. OCT and HRT-GPS were not cost-effective. Compared with GDx, the cost per QALY gained for HRT-MRA is £22,904. The cost per QALY gained with current practice is £156,985 compared with HRT-MRA. Large savings could be made by implementing HRT-MRA but some benefit to patients will be forgone. The results were sensitive to the triage costs.
Conclusions
Automated imaging can be effective to aid glaucoma diagnosis among individuals referred from the community to hospital eye services. A model of care using a triage composite test appears to be cost-effective.
Future work
There are uncertainties about glaucoma progression under routine care and the cost of providing health care. The acceptability of implementing a triage test needs to be explored.
Funding
The National Institute for Health Research Health Technology Assessment programme.
| Original language | English |
|---|---|
| Number of pages | 202 |
| Journal | Health Technology Assessment |
| Volume | 20 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - Jan 2016 |
Bibliographical note
FundingThe National Institute for Health Research Health Technology Assessment programme.
Acknowledgements
The authors would like to thank: Pauline Garden for her data management and secretarial support; Lara Kemp for secretarial support in producing the final report; Cynthia Fraser for literature searches and referencing the final report; Kirsty McCormack for support in setting up and initiating the study; Gladys McPherson and the programming team at the Centre for Healthcare Randomised Trials for providing and maintaining the study website; Luke Vale for invaluable advice and assistance in the development of the economic model; Ian Russell (user) and Russell Young (IGA representative) for reviewing the executive summary and lay summary; independent members of the steering committee, and research and development departments at each research centre. Particular thanks go to all the GATE study participants who gave of their time to take part in the study and staff who facilitated recruitment and data collection at Aberdeen Royal Infirmary, Bedford Hospital, Hinchingbrooke Hospital, Moorfields Eye Hospital and Royal Liverpool University Hospital.
Access to Document
- Automated imaging technologies for the diagnosis
© Queen’s Printer and Controller of HMSO 2016. This work was produced by Azuara-Blanco et al. under the terms of a commissioning contract issued by the Secretary of State for Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should be addressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK.
Fingerprint
Dive into the research topics of 'Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)'. Together they form a unique fingerprint.Profiles
-
Rodolfo Andrés Hernández
- School of Medicine, Medical Sciences & Nutrition, Health Economics Research Unit - Research Fellow
Person: Academic Related - Research
-
Craig Ramsay
- School of Medicine, Medical Sciences & Nutrition, Health Services Research Unit (HSRU) - Director of Health Services Research Unit
- Institute of Applied Health Sciences
Person: Academic