- •Foreword
- •Preface
- •Contents
- •1.1 Introduction
- •1.2 Method
- •1.2.1 Databases
- •1.2.2 Dates
- •1.2.3 Keywords
- •1.2.4 Criteria for Inclusion
- •1.2.5 Criteria for Exclusion
- •1.2.6 Selection of Papers
- •1.3 Results
- •1.3.1 Subspecialty
- •1.3.2 Type of Telemedicine
- •1.3.3 Study Design
- •1.3.4 Final Conclusions of Papers
- •1.4 Discussion
- •References
- •2.1 Introduction
- •2.2 The Need for Diabetic Retinopathy Screening Programs
- •2.4 Guidelines for Referring Patients
- •2.7 Program Models for Diabetic Retinopathy Screening
- •2.9 Program Personnel and Operations
- •2.9.1 Primary Care Providers
- •2.9.2 Photographers
- •2.9.3 Clinical Consultants
- •2.9.4 Administrators
- •2.9.5 A Note to CEOs, Operations Directors, and Clinic Managers
- •2.10 Policies and Procedures
- •2.10.1 Sample Protocol 1
- •2.10.1.1 Diabetic Retinopathy Screening Services
- •Policy
- •Background
- •Procedure
- •2.10.2 Sample Protocol 2
- •2.10.2.1 Pupil Dilation Before Diabetic Retinopathy Photography
- •Policy
- •Background
- •Procedure
- •2.10.3 Sample Protocol 3
- •2.10.3.1 Diabetic Retinopathy Photography Review
- •Policy
- •Background
- •Procedure
- •2.11 Technical Requirements
- •2.11.1 Connectivity
- •2.11.2 Resolution
- •2.11.3 Color
- •2.11.4 Stereopsis
- •2.11.5 Compression
- •2.11.6 Enhancement
- •2.11.7 Pupil Dilation
- •2.11.8 Early California Telemedicine Initiatives Diabetic Retinopathy Screening
- •2.11.9 The American Indian Diabetes Teleophthalmology Grant Program
- •2.11.10 Central Valley EyePACS Diabetic Retinopathy Screening Project
- •2.12.1 Diabetic Retinopathy
- •2.12.1.1 ADA Guidelines Terms
- •2.12.1.2 Vitrectomy
- •References
- •3: Stereopsis and Teleophthalmology
- •3.1 Introduction
- •3.2 History of Stereopsis and Stereopsis in Ophthalmology
- •3.3 Technology and Photography
- •3.3.3 Imaging Fields
- •3.3.4 Image Viewing Techniques
- •3.3.5 Image Compression
- •3.4 Stereoscopic Teleophthalmology Systems
- •3.4.1 University of Alberta
- •3.4.4 Joslin Vision Network
- •3.5 Conclusion
- •References
- •4.1 Introduction
- •4.2 Methods
- •4.2.1 Main Outcome Measures
- •4.3 Results
- •4.3.1 Retinal Video Recording Versus Retinal Still Photography
- •4.3.2 Video Compression Analysis
- •4.4 Discussion
- •References
- •5.1 Introduction
- •5.1.1 Automated, Remote Image Analysis of Retinal Diseases
- •5.1.2 Telehealth
- •5.2 Design Requirements
- •5.2.1 Telehealth Network Architecture
- •5.2.2 Work Flow
- •5.2.3 Performance Evaluation of the Network
- •5.3 Automated Image Analysis Overview
- •5.3.1 Quality Assessment Module
- •5.3.2 Vascular Tree Segmentation
- •5.3.3 Quality Evaluation
- •5.4 Anatomic Structure Segmentation
- •5.4.1 Optic Nerve Detection
- •5.4.2 Macula
- •5.4.3 Lesion Segmentation
- •5.4.4 Lesion Population Description
- •5.4.5 Image Query
- •5.5 Summary
- •References
- •6.1 Introduction
- •6.3 Optical Coherence Tomography to Detect Leakage
- •References
- •7.1 Introduction
- •7.2 Patients and Methods
- •7.2.1 Participants
- •7.2.2 Methods
- •7.2.3 Statistics
- •7.3 Results
- •7.3.1 Reliability of Image Evaluation
- •7.3.2 Prevalence of Glaucomatous Optic Nerve Atrophy
- •7.4 Discussion
- •7.5 Perspectives
- •References
- •8.1 Introduction
- •8.1.2 Homology Between Retinal and Systemic Microvasculature
- •8.1.3 Need for More Precise CVD Risk Prediction
- •8.2.1 Retinal Microvascular Signs
- •8.2.2 Retinal Vessel Biometry
- •8.2.3 Newer Retinal Imaging for Morphologic Features of Retinal Vasculature
- •8.3 Associations of Retinal Imaging and CVD Risk
- •8.3.1.1 Risk of Pre-clinical CVD
- •8.3.1.2 Risk of Stroke
- •8.3.1.3 Risk of Coronary Heart Disease
- •8.3.2.1 Risk of Hypertension
- •8.3.2.2 Risk of Stroke
- •8.3.2.3 Risk of Coronary Heart Disease
- •8.3.2.4 Risk of Peripheral Artery Disease
- •8.3.3 Newer Morphologic Features of Retinal Vasculature
- •8.4 Retinal Imaging and Its Potential as a Tool for CVD Risk Prediction
- •References
- •9.1 Alzheimer’s Disease
- •9.2 Treatments
- •9.3 Diagnosis
- •9.6 Conclusions
- •References
- •10.1 Introduction
- •10.1.1 Stroke
- •10.1.2 Heart Disease
- •10.1.3 Arteriovenous Ratio
- •10.2 Purpose
- •10.3 Method
- •10.3.1 Medical Approach
- •10.3.2 Technical Approach
- •10.3.3 Output of Medical Data
- •10.4 Patients
- •10.5 Results
- •10.5.1 Medical History
- •10.5.2 Telemedical Evaluation of Retinal Vessels
- •10.5.2.1 Prevalence of Retinal Microangiopathy
- •10.5.2.2 Arteriovenous Ratio
- •10.5.2.3 PROCAM-Index
- •10.6 Discussion and Perceptive
- •10.6.1 Estimation of “Stroke Risk” Estimated by the Stage of Retinal Microangiopathy
- •References
- •11.1 Introduction
- •11.2 System Requirements
- •11.3 Fundus Camera
- •11.4 Imaging Procedure
- •11.4.1 Reading Center Procedure
- •11.5 Detection of Macular Edema
- •11.6 Implementation
- •11.7 Unreadable Images
- •11.7.1 Impact on Overall Diabetic Retinopathy Assessment Rates
- •11.7.2 Compliance with Recommendations
- •11.7.3 Challenges
- •11.7.4 Summary
- •References
- •12.1 Screening
- •12.2 Background
- •12.3 Historical Perspective in England
- •12.4 Methodology
- •12.4.1 The Aim of the Programme
- •12.5 Systematic DR Screening
- •12.6 Cameras for Use in the English Screening Programme
- •12.7 Software for Use in the English Screening Programme
- •12.9 Implementation in England
- •12.11 Quality Assurance
- •12.12 The Development of External Quality Assurance in the English Screening Programme
- •12.13 Information Technology (IT) Developments for the English Screening Programme
- •12.14 Dataset Development
- •12.15 The Development of External Quality Assurance Test Set for the English Screening Programme
- •12.16 Failsafe
- •12.17 The Epidemic of Diabetes
- •References
- •13.1 Introduction
- •13.2 Burden of Diabetes and Diabetic Retinopathy in India
- •13.3 Diabetic Retinopathy Screening Models
- •13.4 Need for Telescreening
- •13.5 Guidelines for Telescreening
- •13.6 ATA Categories of DR Telescreening Validation
- •13.7 Yield of Diabetic Retinopathy in a Telescreening Model
- •13.8 How Are Images Transferred
- •13.10 How Many Fields Are Enough for Diabetic Retinopathy Screening
- •13.11 Is Mydriasis Needed While Using Nonmydriatic Camera?
- •13.12 Validation Studies on Telescreening
- •13.12.1 Accuracy of Telescreening
- •13.12.2 Patient Satisfaction in Telescreening
- •13.12.3 Cost Effectivity
- •13.12.4 Telescreening for Diabetic Retinopathy: Our Experience
- •13.13 Future of Diabetic Retinopathy Screening
- •References
- •14.1 Introduction
- •14.2 Methods
- •14.3 Discussion
- •14.4 Conclusion
- •References
- •15.1 Introduction
- •15.1.1 Description of the EADRSI
- •15.5 State Support of Screening in the Safety Net
- •15.7 Screening Economics for Providers
- •15.8 Patient Sensitivity to Fees
- •15.9 Conclusion
- •References
- •16.1 Introduction
- •16.2 Setting Up the New Screening Model
- •16.2.1 Phase 1: Training
- •16.2.2 Phase 2: Evaluation of Agreement
- •16.2.3 Phase 3: Implementation of the Screening Model
- •16.3 Technologic Requirements
- •16.3.1 Data Management
- •16.3.2 Data Models
- •16.3.2.1 Data Scheme for Patient-Related Information
- •16.3.2.2 Data Scheme for Images
- •Fundus Camera VISUCAM Pro NM
- •PACS Server
- •ClearCanvas DICOM Visualizer
- •16.4 Results
- •16.4.1 Phase 2: Agreement Evaluation
- •16.4.2 Phase 3: Implementation of the Screening Model
- •16.5 Discussion
- •16.5.1 Evaluation of the Screening Model
- •16.5.2 Prevalence of DR
- •16.5.3 Quality Evaluation
- •16.6 Conclusion
- •References
- •17.1.3 Examination and Treatment
- •17.1.4 Limitations of Current Care
- •17.2 Telemedicine and ROP
- •17.2.2 Accuracy and Reliability of Telemedicine for ROP Diagnosis
- •17.2.3 Operational ROP Telemedicine Systems
- •17.2.4 Potential Barriers
- •17.3 Closing Remarks
- •17.3.1 Future Directions
- •References
- •18.1 Introduction
- •18.2 Neonatal Stress and Pain
- •18.3 ROP Screening Technique
- •18.4 Effect of Different Examination Techniques on Stress
- •18.5 Future of Retinal Imaging in Babies
- •References
- •19.1 Introduction
- •19.2 History of the Program
- •19.3 Telehealth Technologies
- •19.4 Impact of the Program
- •Selected References
- •Preamble
- •Introduction
- •Background
- •The Diabetic Retinopathy Study (DRS)
- •Mission
- •Vision
- •Goals
- •Guiding Principles
- •Ethics
- •Clinical Validation
- •Category 1
- •Category 2
- •Category 3
- •Category 4
- •Communication
- •Medical Care Supervision
- •Patient Care Coordinator
- •Image Acquisition
- •Image Review and Evaluation
- •Information Systems
- •Interoperability
- •Image Acquisition
- •Compression
- •Data Communication and Transmission
- •Computer Display
- •Archiving and Retrieval
- •Security
- •Reliability and Redundancy
- •Documentation
- •Image Analysis
- •Legal Requirements
- •Facility Accreditation
- •Privileging and Credentialing
- •Stark Act and Self-referrals
- •State Medical Practice Acts/Licensure
- •Tort Liability
- •Duty
- •Standards of Care
- •Consent
- •Quality Control
- •Operations
- •Customer Support
- •Originating Site
- •Transmission
- •Distant Site
- •Financial Factors
- •Reimbursement
- •Grants
- •Federal Programs
- •Other Financial Factors
- •Equipment Cost
- •Summary
- •Abbreviations
- •Appendices
- •Appendix A: Interoperability
- •Appendix B: DICOM Metadata
- •Appendix C: Computer-Aided Detection
- •Appendix D: Health Insurance Portability and Accountability Act (HIPAA)
- •Appendix F: Quality Control
- •Appendix H: Customer Support
- •Level 1
- •Level 2
- •Level 3
- •Appendix I: Reimbursement
- •Medicare
- •Medicaid
- •Commercial Insurance Carrier Reimbursement
- •Other Financial Factors
- •Disease Prevention
- •Resource Utilization
- •American Telemedicine Association’s Telehealth Practice Recommendations for Diabetic Retinopathy
- •Conclusion
- •References
- •Contributors
- •Second Edition
- •First Edition
- •Index
Economics of Screening for Diabetic 15 Retinopathy Using Telemedicine in California’s Safety Net
Robert Quade and Veenu Aulakh
15.1Introduction
The cost-effectiveness of screening for diabetic retinopathy has been well documented, with studies repeatedly concluding that this approach to screening results in improved access and substantial savings compared with a lack of screening [1–6]. In addition to the benefit of preserved vision realized by individual patients who complete the process, there exists solid evidence that society itself gains from additional resources devoted to retinopathy screening and the resulting reduction in costs associated with vision loss.
Typically, telemedicine programs are funded by grants as demonstration projects through introduction and development stages, with evaluations documenting clinical outcomes, costs and benefits, and participant satisfaction. Sustainability after the grant period requires that other resources be found to replace the grant funding, and so the long-term economics of the program must also be a consideration in an economic evaluation. The
R. Quade ( )
Quade and Associates,
Sacramento, CA, USA
e-mail: bobquade@surewest.net
V. Aulakh
Innovations for the Underserved, California HealthCare Foundation,
1438 Webster Street, Suite 400, Oakland, CA 94612, USA
most likely resources for sustainability come through public health insurance coverage of specific services provided through telemedicine or in large vertically integrated health programs in which both costs and benefits are captured.
This chapter provides an overview of the economic aspects of the evaluation of one large telemedicine program designed to deliver screening for diabetic retinopathy at scale in California’s health safety net.
15.1.1 Description of the EADRSI
The California HealthCare Foundation launched the Expanding Access to Diabetic Retinopathy Screening Initiative (EADRSI) in 2007 to use telemedicine to address patient barriers to diabetic eye care by reducing the cost to the patient and eliminating the need to travel, get a separate appointment, and go to an unfamiliar place for care. The EADRSI grew out of a pilot project involving 13 safety-net clinics begun in 2005 under the direction of Dr. Jorge Cuadros of the UC Berkeley School of Optometry. That pilot project was designed to reduce screening costs by the use of open-source software developed for the project (EyePACS) and the use of specially certified optometrists as consulting readers. The fee for reading a case within the EyePACS network was set at $15, well below the cost of most alternatives. The EADRSI was designed to take this screening to scale and establish a sustainable reading network.
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In the EADRSI, screening for retinopathy is integrated into normal patient care in the safety-net setting in order to address directly barriers associated with patient travel and scheduling of additional appointments. Patients who have been screened through the program had limited access to diabetic eye care prior to the EADRSI and represented a substantial reservoir of undiagnosed pathology. Nearly two-thirds of all patients screened were uninsured. More than 25% of the screens were for patients whose last exam had been at least 2 years prior to the screen, and an additional 20% had never had a diabetic eye exam. On average, providers reported that 26% of diabetic patients had received diabetic eye exams in the year before screening began, with most having referred patients to eye specialists at other locations. There was often poor communication between providers and specialists, and in some cases the provider had no way of knowing if a patient had kept an appointment with a specialist. The standard barriers to access applied to these off-site referrals: patient travel, fees charged by specialists, and scheduling and wait times for appointments all contributed to low diabetic eye exam rates.
Within EADRSI, the safety-net provider initiates screening cases. Clinic personnel capture a set of three retinal images and one external image of each eye using a fundus camera, and then upload those images with appropriate patient information to the Internet using EyePACS software. Photographers are typically medical assistants, but providers also employed a range of technicians, case managers, and nurses in this role. Each screening site was recommended to have between two and four trained photographers to provide backup and consistency in the case of staff turnover. All photographers were trained and certified by UC Berkeley prior to screening patients, and UC Berkeley has been providing refresher training for photographers when requested.
Once the patient information and images are uploaded, a consulting reader examines the images and information. The reader then uses EyePACS to upload findings and any appropriate referral to follow-up care to the Internet. UC Berkeley recruited, trained, and certified each reader prior to that specialist reading any cases, with 55 individuals reading at least one case in the EADRSI. Most of these readers are optometrists, but not all
Table 15.1 Most significant finding by case
|
Proportion |
Most significant finding |
of cases (%) |
Clinically significant macular edema |
5 |
Proliferative diabetic retinopathy |
2 |
Severe nonproliferative diabetic |
2 |
retinopathy |
|
Moderate nonproliferative diabetic |
12 |
retinopathy |
|
Mild nonproliferative diabetic |
11 |
retinopathy |
|
“Other” pathology, with no |
7 |
retinopathy |
|
No pathology |
61 |
operate within the EyePACS network of readers: some clinics have staff optometrists certified to read cases, and others have opted to contract with local ophthalmologists for reads to enhance relationships that could help with patient access to treatment.
The screen is completed as clinic personnel access these findings on the Internet and route them through the clinic, notifying patients of the findings and initiating the process of getting the patient into follow-up care as necessary. Increasingly, EyePACS is being integrated with EHRs that automate some of the information flow.
As of the end of 2010, more than 53,000 cases have been screened, with nearly 11,000 people referred to a specialist for follow-up care for a specific condition. Another 7% of all cases resulted in a referral for general eye care. Pathology has been discovered for nearly 40% of all patients screened. Many patients were found to have more than one pathology, with the most significant findings listed in Table 15.1.
15.2Cost-Effectiveness of Telemedicine for Screening for Diabetic Retinopathy in the Safety Net
The health-care safety net in California is a diverse group of providers delivering a broad range of health-care services to medically underserved and uninsured populations. The safety net is subject to varied definitions because it lacks a formal
15 Economics of Screening for Diabetic Retinopathy Using Telemedicine in California’s Safety Net |
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Table 15.2 Costs and benefits of EADRSI from different perspectives |
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Probable long-term |
|
Perspective |
Benefits |
Costs |
balance |
|
State |
Future savings on support services |
Current reimbursements to |
Net benefit |
|
|
associated with vision loss |
providers for screening |
|
|
Patient |
Vision preserved |
Co-payments, time |
Net benefit |
|
Provider/clinic |
Reimbursements for screening, |
Screening costs, administrative |
Net cost |
|
|
co-payments from patients |
costs |
|
|
Screening network |
Read fees |
Read costs, administrative |
Benefits = costs |
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|
|
costs |
|
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structure and its components have diverse licensing, funding, missions, and relationships [7]. About 7.6 million Californians relied on safetynet providers for health care in 2006 [8]. Safetynet providers are caught between rising costs, a trend toward declining reimbursements, and increased demand for services. At the same time, safety-net providers are working to keep up with technological change while controlling costs.
Many studies have found screening for diabetic retinopathy to be cost effective [1] and even cost saving [2]. Screening using telemedicine has been found to be the dominant strategy when compared with conventional clinic-based ophthalmology [3] and the less costly alternative in a similar comparison [4]. Systematic delivery of screening has been found to be more cost effective than opportunistic delivery and results in more pathology being discovered. This finding is sensitive to screening volume and compliance, with increases in either leading to greater cost-effectiveness [5]. The cost-effective- ness advantage of telemedicine over conventional clinic-based ophthalmology is also subject to economies of scale, with telemedicine becoming more affordable at higher volumes [6].
While screening for retinopathy has been demonstrated to lead to great savings for society, it remains underfunded and underutilized, at least partially due to mismatches between the parties receiving benefits and those providing resources. An economic evaluation should assess costs and benefits from multiple perspectives, including the patient, the provider, and society or the state [9]. In cases in which the provision of services depends on a telemedicine network, an additional analysis should be conducted from the perspective of the network.
The safety net exists because market forces would underallocate resources to the care of people without the ability to pay privately for healthcare services. Especially in the safety net, patients do not, and cannot, bear all of the costs of the services they consume. Without resources from government sources, cost and benefit analysis is likely to reveal mismatches between those who benefit and those who bear the costs. Benefits accrue to patients, society, and the state, while most costs are borne by safety-net providers (Table 15.2).
Costs and benefits for the provider and the network are easily observed and quantified. Safety-net providers undertake the normal transaction of providing a service and receiving reimbursements for services provided to patients covered by public insurance. Since nearly twothirds of patients screened through EADRSI had no health insurance coverage, some providers asked uninsured patients for co-payments to partially cover costs of screening.
The screening network provides infrastructure and training and connects screening sites with the eye consultants who read the images and complete the screens. To achieve sustainability, the network is run as a business with revenues from read fees charged to providers covering the costs of reading images and administering the program. Any surplus revenue goes into a fund to replace fundus cameras and grow the network. The volume of screens read within the network has to meet or exceed the break-even point for the network to be sustainable without grant support.
Benefits to the state and the patient will be realized in the future and will occur in the form of avoided costs. From the perspective of the patient, the benefit is uncertain, and education may be necessary to improve patient compliance with
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screening recommendations. From the perspective of the state, immediate budget concerns complicate the issue with a short-term focus on cost cutting, but a current investment in retinopathy screening is likely to pay off with substantial cost savings in future budget years.
15.3Increasing Benefit by Improving Access to Necessary Follow-up Care
Realizing the full benefit of screening requires that patients found to have diabetic retinopathy receive effective and timely treatment, but the same barriers to access have been found to exist. Patients still need to take time from work, arrange travel, schedule appointments with an unfamiliar provider, and pay for an initial confirmatory exam, monitoring visits, and ultimately a series of treatments. In some areas of the state, wait times for appointments with specialists were found to exceed 7 months, furthering discouraging patients from accessing follow-up care. A lack of obvious symptoms may contribute to a lack of patient urgency in seeking this care, but some providers are reporting success by showing the patient their own retinal images as part of an educational approach to addressing this barrier.
Even so, most patients referred to a specialist did not get to a first appointment for follow-up care in a timely manner. A study of 417 patients referred to a specialist for vision-threatening diabetic retinopathy in the first year of the EADRSI found that only 119 (28.5%) accessed any followup care, and at least two of these patients refused treatment when told how much it would cost. Losses occurred at all stages of the referral process. The biggest loss (31% of all referrals) was patients who received appointments but either canceled or did not keep them. Another 25% of patients were notified of the referral, but failed to get an appointment, although some appointments were still “pending” more than 1 year after the screen. Poorer access to follow-up care was associated with having no health insurance, living in Los Angeles County, and Hispanic ethnicity. The average length of time between the screen and the
first follow-up appointment was just over 7 months, and patients who had to wait longer for an appointment were less likely to keep that appointment.
15.4Benefits to the State
Timely detection of retinopathy facilitates preservation of vision and allows the state to avoid costs associated with that loss of vision. In early 2009, CHCF commissioned a study of the benefits that would accrue to the state of California from EADRSI screening activities. This study used a Markov model and data from the first 15 months of screening to find the present value of the expected benefit to the state was in excess of $2,500 per screen over the lifetime of the patient [10]. The study made the case for more support for this approach to vision preservation strictly on an economic basis, although ideally that support should cover not just screening, but also should cover treatment: follow-up care has to be completed for the state to benefit.
These findings have been updated based upon new data, but without changing the findings. The sample size has increased from 5,864 cases to over 50,000 cases. Prevalences have changed since the original study was completed, at least partially in response to UC Berkeley working with readers to further refine protocols. Prevalence figures from cases with the refined protocol were used to reestimate savings with the belief that these data more accurately represent the actual disease burden in the safety-net population. More significantly, however, the results were updated to reflect poor access to follow-up care. Only cases that actually got to the follow-up appointment realized any benefit from screening, while screening costs were incurred for all patients.
Combining these changes and using Newman’s Markov model, the expected benefit falls to a more modest $768 per patient screened. This still represents a benefit of more than $39 million to date even when most of the benefit is lost to fol- low-up and represents an excellent return on CHCF’s $2.7 million investment. Screening costs are still incurred for all patients, but the benefit of
