Dataset Information

A personalised screening strategy for diabetic retinopathy: a cost-effectiveness perspective.

ABSTRACT: AIMS/HYPOTHESIS:In this study we examined the cost-effectiveness of three different screening strategies for diabetic retinopathy: using a personalised adaptive model, annual screening (fixed intervals), and the current Dutch guideline (stratified based on previous retinopathy grade). METHODS:For each individual, optimal diabetic retinopathy screening intervals were determined, using a validated risk prediction model. Observational data (1998-2017) from the Hoorn Diabetes Care System cohort of people with type 2 diabetes were used (n?=?5514). The missing values of retinopathy grades were imputed using two scenarios of slow and fast sight-threatening retinopathy (STR) progression. By comparing the model-based screening intervals to observed time to develop STR, the number of delayed STR diagnoses was determined. Costs were calculated using the healthcare perspective and the societal perspective. Finally, outcomes and costs were compared for the different screening strategies. RESULTS:For the fast STR progression scenario, personalised screening resulted in 11.6% more delayed STR diagnoses and €11.4 less costs per patient compared to annual screening from a healthcare perspective. The personalised screening model performed better in terms of timely diagnosis of STR (8.8% less delayed STR diagnosis) but it was slightly more expensive (€1.8 per patient from a healthcare perspective) than the Dutch guideline strategy. CONCLUSIONS/INTERPRETATION:The personalised diabetic retinopathy screening model is more cost-effective than the Dutch guideline screening strategy. Although the personalised screening strategy was less effective, in terms of timely diagnosis of STR patients, than annual screening, the number of delayed STR diagnoses is low and the cost saving is considerable. With around one million people with type 2 diabetes in the Netherlands, implementing this personalised model could save €11.4 million per year compared with annual screening, at the cost of 658 delayed STR diagnoses with a maximum delayed time to diagnosis of 48 months.

SUBMITTER: Emamipour S

PROVIDER: S-EPMC7527375 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A personalised screening strategy for diabetic retinopathy: a cost-effectiveness perspective.

Emamipour Sajad S van der Heijden Amber A W A AAWA Nijpels Giel G Elders Petra P Beulens Joline W J JWJ Postma Maarten J MJ van Boven Job F M JFM Feenstra Talitha L TL

Diabetologia 20200731 11

<h4>Aims/hypothesis</h4>In this study we examined the cost-effectiveness of three different screening strategies for diabetic retinopathy: using a personalised adaptive model, annual screening (fixed intervals), and the current Dutch guideline (stratified based on previous retinopathy grade).<h4>Methods</h4>For each individual, optimal diabetic retinopathy screening intervals were determined, using a validated risk prediction model. Observational data (1998-2017) from the Hoorn Diabetes Care Sys ...[more]

PMID: 32734441

Similar Datasets

Project description:BackgroundDiabetic retinopathy (DR) is a significant global public health and economic burden. DR accounts for approximately 15-17% of all cases of total blindness in the USA and Europe. Telemedicine is a new intervention for DR screening, however, there is not enough evidence to support its cost-effectiveness. The aim of this study is to review the most recent published literature on economic evaluations of telemedicine in DR screening and summarize the evidence on the cost-effectiveness of this technology.MethodsA systematic search of PubMed, Embase and Google Scholar for relevant articles published between January 2010 and January 2020. Studies were included if they met the following criteria: (1) recruited subjects with either type 1, type 2 diabetes (2) evaluated telemedicine technology (3) patients underwent primary screening for DR (4) compared a telemedicine-based intervention with standard care (5) performed an economic evaluation or provided sufficient data for evaluating the cost-effectiveness of the technology used.ResultsOf 2238 articles screened, seven studies were included. Four of the studies were conducted in developed countries: The United States, Singapore and two studies in Canada. Three studies were conducted in developing countries: India, Brazil and South Africa. The patient populations in all studies were diabetic patients over the age of 18, previously not screened for DR. All seven studies used a telemedicine program which included capturing a retinal image and subsequently transmitting it to an ocular imaging center to assess the severity of DR. All studies compared telemedicine to a standard screening method for DR, including the option of no screening as standard of care. Although telemedicine requires initial and maintenance costs, it has the potential to provide significant cost savings by increasing patients' working ability, increasing independent living ability, increasing quality of life and reducing travel costs.ConclusionsDiabetic retinopathy telemedicine technology has the potential to provide significant cost savings, especially in low-income populations and rural patients with high transportation costs.

Project description:BackgroundRetinopathy is a common complication of diabetes mellitus that if detected early by regular retinal examinations can be treated; thus, blindness can be delayed or prevented. Providing high-quality retinal screening is difficult, especially in rural and remote areas. Canada's First Nations population has a higher prevalence of diabetes and is, in general, more geographically isolated than the broader Canadian population. We modelled the cost-effectiveness of retinopathy screening by travelling retina specialists versus retinal photography with a portable digital camera in an isolated First Nations cohort with diabetes.MethodsThe 2 screening programs were modelled to run concurrently for 5 years, with outcomes evaluated over 10 years. To construct economic models for the population of Cree individuals living in the western James Bay area of northern Ontario, we used available data on the prevalence of diabetes in the area and estimates of the incidence of retinopathy derived from the published literature. We compared the screening models and calculated total costs, visual outcome, costs per sight-year saved and costs per quality-adjusted life year (QALY). We also estimated the costs of implementing a screening program for all First Nations individuals in Ontario with diabetes and no access to an ophthalmologist.ResultsFrom the perspective of the health care system the camera program was preferable to the specialist-based program. Over 10 years, 67 v. 56 sight years were saved, compared with no screening, at costs of 3900 Canadian dollars v. 9800 Canadian dollars per sight year and 15,000 Canadian dollars v. 37,000 Canadian dollars per QALY. Generalizing these results to the province of Ontario, the camera system could allow most isolated First Nations people with diabetes to be screened for 5 years for approximately 1.2 million Canadian dollars.InterpretationA portable retinal camera is a cost-effective means of screening for diabetic retinopathy in isolated communities of at-risk individuals.

Project description:BackgroundDiabetic eye complications are the leading cause of visual loss among working-aged people. Pharmacy-based teleophthalmology has emerged as a possible alternative to in-person examination that may facilitate compliance with evidence-based recommendations and reduce barriers to specialized eye care. The objective of this study was to estimate the cost-effectiveness of mobile teleophthalmology screening compared with in-person examination (primary care) for the diabetic population residing in semiurban areas of southwestern Ontario.MethodsA decision tree was constructed to compare in-person examination (comparator program) versus pharmacy-based teleophthalmology (intervention program). The economic model was designed to identify patients with more than minimal diabetic retinopathy, manifested by at least 1 microaneurysm at examination (modified Airlie House classification grade of ≥ 20). Cost-effectiveness was assessed as cost per case detected (true-positive result) and cost per case correctly diagnosed (including true-positive and true-negative results).ResultsThe cost per case detected was $510 with in-person examination and $478 with teleophthalmology, and the cost per case correctly diagnosed was $107 and $102 respectively. The incremental cost-effectiveness ratio was $314 per additional case detected and $73 per additional case correctly diagnosed. Use of pharmacologic dilation and health care specialists' fees were the most important cost drivers.InterpretationThe study showed that a compound teleophthalmology program in a semiurban community would be more effective but more costly than in-person examination. The findings raise the question of whether the benefits of pharmacy-based teleophthalmology in semiurban areas, where in-person examination is still available, are equivalent to those observed in remote communities. Further study is needed to investigate the impact of this program on the prevention of severe vision loss and quality of life in a semiurban setting.

Project description:ImportanceScreening for diabetic retinopathy is recommended for children with type 1 diabetes (T1D) and type 2 diabetes (T2D), yet screening rates remain low. Point-of-care diabetic retinopathy screening using autonomous artificial intelligence (AI) has become available, providing immediate results in the clinic setting, but the cost-effectiveness of this strategy compared with standard examination is unknown.ObjectiveTo assess the cost-effectiveness of detecting and treating diabetic retinopathy and its sequelae among children with T1D and T2D using AI diabetic retinopathy screening vs standard screening by an eye care professional (ECP).Design, setting, and participantsIn this economic evaluation, parameter estimates were obtained from the literature from 1994 to 2019 and assessed from March 2019 to January 2020. Parameters included out-of-pocket cost for autonomous AI screening, ophthalmology visits, and treating diabetic retinopathy; probability of undergoing standard retinal examination; relative odds of undergoing screening; and sensitivity, specificity, and diagnosability of the ECP screening examination and autonomous AI screening.Main outcomes and measuresCosts or savings to the patient based on mean patient payment for diabetic retinopathy screening examination and cost-effectiveness based on costs or savings associated with the number of true-positive results identified by diabetic retinopathy screening.ResultsIn this study, the expected true-positive proportions for standard ophthalmologic screening by an ECP were 0.006 for T1D and 0.01 for T2D, and the expected true-positive proportions for autonomous AI were 0.03 for T1D and 0.04 for T2D. The base case scenario of 20% adherence estimated that use of autonomous AI would result in a higher mean patient payment ($8.52 for T1D and $10.85 for T2D) than conventional ECP screening ($7.91 for T1D and $8.20 for T2D). However, autonomous AI screening was the preferred strategy when at least 23% of patients adhered to diabetic retinopathy screening.Conclusions and relevanceThese results suggest that point-of-care diabetic retinopathy screening using autonomous AI systems is effective and cost saving for children with diabetes and their caregivers at recommended adherence rates.

Project description:Aims/hypothesis: Using variable diabetic retinopathy screening intervals, informed by personal risk levels, offers improved engagement of people with diabetes and reallocation of resources to high-risk groups, while addressing the increasing prevalence of diabetes. However, safety data on extending screening intervals are minimal. The aim of this study was to evaluate the safety and cost-effectiveness of individualised, variable-interval, risk-based population screening compared with usual care, with wide-ranging input from individuals with diabetes.Methods: This was a two-arm, parallel-assignment, equivalence RCT (minimum 2 year follow-up) in individuals with diabetes aged 12 years or older registered with a single English screening programme. Participants were randomly allocated 1:1 at baseline to individualised screening at 6, 12 or 24 months for those at high, medium and low risk, respectively, as determined at each screening episode by a risk-calculation engine using local demographic, screening and clinical data, or to annual screening (control group). Screening staff and investigators were observer-masked to allocation and interval. Data were collected within the screening programme. The primary outcome was attendance (safety). A secondary safety outcome was the development of sight-threatening diabetic retinopathy. Cost-effectiveness was evaluated within a 2 year time horizon from National Health Service and societal perspectives.Results: A total of 4534 participants were randomised. After withdrawals, there were 2097 participants in the individualised screening arm and 2224 in the control arm. Attendance rates at first follow-up were equivalent between the two arms (individualised screening 83.6%; control arm 84.7%; difference -1.0 [95% CI -3.2, 1.2]), while sight-threatening diabetic retinopathy detection rates were non-inferior in the individualised screening arm (individualised screening 1.4%, control arm 1.7%; difference -0.3 [95% CI -1.1, 0.5]). Sensitivity analyses confirmed these findings. No important adverse events were observed. Mean differences in complete case quality-adjusted life-years (EuroQol Five-Dimension Questionnaire, Health Utilities Index Mark 3) did not significantly differ from zero; multiple imputation supported the dominance of individualised screening. Incremental cost savings per person with individualised screening were £17.34 (95% CI 17.02, 17.67) from the National Health Service perspective and £23.11 (95% CI 22.73, 23.53) from the societal perspective, representing a 21% reduction in overall programme costs. Overall, 43.2% fewer screening appointments were required in the individualised arm.Conclusions/interpretation: Stakeholders involved in diabetes care can be reassured by this study, which is the largest ophthalmic RCT in diabetic retinopathy screening to date, that extended and individualised, variable-interval, risk-based screening is feasible and can be safely and cost-effectively introduced in established systematic programmes. Because of the 2 year time horizon of the trial and the long time frame of the disease, robust monitoring of attendance and retinopathy rates should be included in any future implementation.Trial registration: ISRCTN 87561257 FUNDING: The study was funded by the UK National Institute for Health Research. Graphical abstract.

Project description:BackgroundWe aimed to evaluate the cost-effectiveness of an artificial intelligence-(AI) based diabetic retinopathy (DR) screening system in the primary care setting for both non-Indigenous and Indigenous people living with diabetes in Australia.MethodsWe performed a cost-effectiveness analysis between January 01, 2022 and August 01, 2023. A decision-analytic Markov model was constructed to simulate DR progression in a population of 1,197,818 non-Indigenous and 65,160 Indigenous Australians living with diabetes aged ≥20 years over 40 years. From a healthcare provider's perspective, we compared current practice to three primary care AI-based screening scenarios-(A) substitution of current manual grading, (B) scaling up to patient acceptance level, and (C) achieving universal screening. Study results were presented as incremental cost-effectiveness ratio (ICER), benefit-cost ratio (BCR), and net monetary benefits (NMB). A Willingness-to-pay (WTP) threshold of AU$50,000 per quality-adjusted life year (QALY) and a discount rate of 3.5% were adopted in this study.FindingsWith the status quo, the non-Indigenous diabetic population was projected to develop 96,269 blindness cases, resulting in AU$13,039.6 m spending on DR screening and treatment during 2020-2060. In comparison, all three intervention scenarios were effective and cost-saving. In particular, if a universal screening program was to be implemented (Scenario C), it would prevent 38,347 blindness cases, gain 172,090 QALYs and save AU$595.8 m, leading to a BCR of 3.96 and NMB of AU$9,200 m. Similar findings were also reported in the Indigenous population. With the status quo, 3,396 Indigenous individuals would develop blindness, which would cost the health system AU$796.0 m during 2020-2060. All three intervention scenarios were cost-saving for the Indigenous population. Notably, universal AI-based DR screening (Scenario C) would prevent 1,211 blindness cases and gain 9,800 QALYs in the Indigenous population, leading to a saving of AU$19.2 m with a BCR of 1.62 and NMB of AU$509 m.InterpretationOur findings suggest that implementing AI-based DR screening in primary care is highly effective and cost-saving in both Indigenous and non-Indigenous populations.FundingThis project received grant funding from the Australian Government: the National Critical Research Infrastructure Initiative, Medical Research Future Fund (MRFAI00035) and the NHMRC Investigator Grant (APP1175405). The contents of the published material are solely the responsibility of the Administering Institution, a participating institution or individual authors and do not reflect the views of the NHMRC. This work was supported by the Global STEM Professorship Scheme (P0046113), the Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075). The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian State Government. W.H. is supported by the Melbourne Research Scholarship established by the University of Melbourne. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Project description:BackgroundCommunity-based telemedicine screening for diabetic retinopathy (DR) has been highly recommended worldwide. However, evidence from low- and middle-income countries (LMICs) on the choice between artificial intelligence (AI)-based and manual grading-based telemedicine screening is inadequate for policy making.ObjectiveThe aim of this study was to test whether the AI model is more worthwhile than manual grading in community-based telemedicine screening for DR in the context of labor costs in urban China.MethodsWe conducted cost-effectiveness and cost-utility analyses by using decision-analytic Markov models with 30 one-year cycles from a societal perspective to compare the cost, effectiveness, and utility of 2 scenarios in telemedicine screening for DR: manual grading and an AI model. Sensitivity analyses were performed. Real-world data were obtained mainly from the Shanghai Digital Eye Disease Screening Program. The main outcomes were the incremental cost-effectiveness ratio (ICER) and the incremental cost-utility ratio (ICUR). The ICUR thresholds were set as 1 and 3 times the local gross domestic product per capita.ResultsThe total expected costs for a 65-year-old resident were US $3182.50 and US $3265.40, while the total expected years without blindness were 9.80 years and 9.83 years, and the utilities were 6.748 quality-adjusted life years (QALYs) and 6.753 QALYs in the AI model and manual grading, respectively. The ICER for the AI-assisted model was US $2553.39 per year without blindness, and the ICUR was US $15,216.96 per QALY, which indicated that AI-assisted model was not cost-effective. The sensitivity analysis suggested that if there is an increase in compliance with referrals after the adoption of AI by 7.5%, an increase in on-site screening costs in manual grading by 50%, or a decrease in on-site screening costs in the AI model by 50%, then the AI model could be the dominant strategy.ConclusionsOur study may provide a reference for policy making in planning community-based telemedicine screening for DR in LMICs. Our findings indicate that unless the referral compliance of patients with suspected DR increases, the adoption of the AI model may not improve the value of telemedicine screening compared to that of manual grading in LMICs. The main reason is that in the context of the low labor costs in LMICs, the direct health care costs saved by replacing manual grading with AI are less, and the screening effectiveness (QALYs and years without blindness) decreases. Our study suggests that the magnitude of the value generated by this technology replacement depends primarily on 2 aspects. The first is the extent of direct health care costs reduced by AI, and the second is the change in health care service utilization caused by AI. Therefore, our research can also provide analytical ideas for other health care sectors in their decision to use AI.

Dataset Information

A personalised screening strategy for diabetic retinopathy: a cost-effectiveness perspective.

Publications

A personalised screening strategy for diabetic retinopathy: a cost-effectiveness perspective.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets