Visilant

There are 990 million people living with vision loss or blindness that is preventable or could be treated with access to eye care. 90% of these individuals live in low- and middle-income countries (LMICs). Vision loss is devastating for individuals, families, and communities, and leads to decreased quality of life, reduced economic productivity, and increased morbidity and mortality, which help perpetuate cycles of poverty. In rural LMIC settings, access to eye care is limited due to distance from eye care facilities, cost of travel, lack of trained ophthalmologists (1:91,000 patients in India), and community awareness, leading to disease progression and vision loss. Periodic “eye camp” screenings performed by trained ophthalmologists have long been the primary method for eye screening, but are limited by access to trained ophthalmologists, failure to reach the most remote communities, inconsistent calendar coverage, and high costs. A study conducted in rural South India showed that eye camps only reached 7% of patients with eye problems across a region and failed to reach patients who need care most. Across numerous LMIC surveys, women, older adults, and rural and poor patients are less likely to undergo eye camp screenings and receive eye care. To increase access, hospitals have established vision centers staffed by technicians to provide primary eye care. However, constraints such as lengthy training for technicians, limited capability to manage complex cases, and lack of imaging and telemedicine tools limit vision center scalability and result in unnecessary referrals to the base hospital.

Eye care systems in LMICs currently face a nearly insurmountable challenge: providing efficient, high quality, and low cost care to a large volume of patients who often present with complex, late stage symptoms, have limited ability to pay, and have minimal interaction with the eye care system. A platform for simple, accessible, ongoing screening of underserved patients has potential to enable earlier and equitable access to eye care to eliminate avoidable vision loss.

Visilant is a comprehensive technology platform developed at Johns Hopkins University (JHU) for eye hospitals, governments, and NGOs to provide decentralized eye screening, referral, and follow-up through telemedicine, artificial intelligence, and low-cost imaging hardware. This platform has been conceptualized and iteratively developed and validated in collaboration with the Aravind Eye Hospital (AEH) in Southern India to make sure it meets the needs of providers and patients in low resource settings. Visilant’s technology facilitates community-based screening, vision center teleconsultations, and referrals to tertiary care centers, ensuring sustainable integration of patients at all levels into care delivery systems. 

Our mobile telemedicine app enables community health workers (CHWs) and technicians with minimal ophthalmic training to conduct high volume eye screening. The mobile app guides CHWs through patient registration, collecting medical history, complaints, measuring visual acuity, and eye imaging in multiple local languages. The app operates asynchronously offline and uses low-bandwidth data transfer to enable screening in the most remote settings. The app is used with a novel, low-cost smartphone attachment to easily capture diagnostic-quality eye images. In pilot studies, we demonstrated that our imaging modality enables CHWs to achieve imaging proficiency in under 30 minutes and that remote ophthalmologist review of images taken by CHWs had greater than 90% diagnostic concordance with an in-person ophthalmologist exam.

Patient information and images are uploaded to a web portal to be reviewed by a trained ophthalmologist. Automated SMS follow-ups or phone calls are sent to patients regarding their diagnosis and next steps to promote follow-up. Program administrators can track key performance indicators through a simple data dashboard on the web portal, facilitating data-driven decision-making and outcome monitoring.

Visilant's back-end infrastructure seamlessly integrates with existing healthcare delivery systems, ensuring interoperability and scalability. The software and hardware have been advanced and validated through iterative development with AEH, including a pilot of 20 CHWs and 3,500 patients. In partnership with four hospitals across India, we have developed locally-hosted smartphone algorithms for preliminary diagnosis and referral of anterior segment conditions. Preliminary algorithms for diagnosing mature cataract, immature cataract, and clear lens achieved a 97.1% average precision. Deployment of these algorithms will enable near-real-time screening and referral to broaden access and alleviate strain on already overburdened ophthalmologists. This approach has potential to overcome longstanding geographic, financial, operational, and human resource constraints to eye screening while ensuring diagnostic validity, quality control, and interoperability with existing health system infrastructure. Our solution has been designed and tested in low resource settings and is positioned to transform eye care delivery globally. 

Our solutions support (1) patients in rural or underserved areas, (2) health care workers, and (3) eye care systems. 

For patients, Visilant ensures all patients can access essential eye care services close to their home, alleviating the burden and cost of travel. As a result, patients receive earlier detection and timely referral of eye disease which promotes better patient outcomes. Our solution overcomes traditional barriers to care, enhancing access for marginalized groups, including women, older adults, and rural and poor patients, fostering inclusivity in care delivery. Visilant’s community-driven approach increases community awareness about eye disease and creates a longitudinal eye care presence in the community. With restored vision, patients can regain their ability to perform tasks essential for high quality of life and economic productivity, such as reading, working, and participating in their communities, thus contributing to broader social and economic development goals.

For community health workers, our solution provides skilled employment opportunities, particularly for women, within their local communities. By equipping them with technological tools, such as our mobile telemedicine app, we empower them to conduct eye screenings accurately and efficiently, enhancing their effectiveness in delivering essential eye care services. This not only improves the health outcomes of the communities but also creates sustainable opportunities for economic empowerment and social development.

For eye care systems, we drive revenue through increasing volume of patients who receive reimbursable procedures, such as cataract surgery. Our solution shifts screening tasks to trained community health workers, enabling ophthalmologists to focus on treatment and complex cases, and reducing costs for the hospital. Traditional approaches to eye screening, such as eye camps, cost $5-8 per patient screened. Visilant reduces hospital costs through efficient human resource allocation. This helps promote financial sustainability for charitable eye hospitals so they can continue providing high-quality, low cost care. 

Visilant was originally conceptualized by collaborators at JHU and AEH, and the solution has been iteratively developed and tested alongside end users to ensure it meets the needs of health workers providing rural eye screening. We have conducted over 100 interviews with patients, health workers, technicians, ophthalmologists, hospital leadership, government representatives, NGOs, and more to understand stakeholder perspectives and incentives. Our team is partnered with the largest high-volume eye care systems globally that collectively serve over 12 million patients annually and are global leaders in eye care, enabling an accelerated pathway to scaling and broad adoption.

Visilant is led by a multidisciplinary team from diverse expertise in ophthalmology, biomedical engineering, artificial intelligence, and the development and commercialization of ophthalmic technologies for under-resourced settings. Visilant is led by Jordan Shuff (CEO), a biomedical engineer with 7 years of experience in global health and user-centered design. Dr. Nakul Shekhawat (Chief Medical Officer) is an ophthalmologist and epidemiologist with 18 years of experience with direct humanitarian care delivery, device development, and clinical and epidemiologic research in LMIC settings, including four culturally and geographically distinct regions of India. Dr. Kunal Parikh (President) is a biomedical engineer and serial social entrepreneur (Social Innovation Lab, Access HEARS, Global Institute for Vision Equity, and Eyedea Medical) with experience inventing, translating, and commercializing diagnostics, medical devices, and therapeutics. 

Visilant is enabled by proprietary user-centered technology developed at Johns Hopkins University that deskills eye screening and imaging, allowing for task shifting to a CHW while achieving diagnostic-quality. We have developed one of the world’s largest database of smartphone-based anterior segment eye disease images, which we used to develop the first portable combined telemedicine and automated diagnosis platforms for the leading causes of blindness.

Over the last 27 months, we developed our software and hardware platforms, developed partnerships with charitable, high volume eye care systems, and screened 3,500 patients. We recently completed a 1,000 patient validation study (funded by the National Eye Institute) of the hardware and software platform in collaboration with the world’s largest eye care system and have achieved a 97.1% average precision using AI to diagnose cataracts using our images. We are currently focused on design for manufacturing of the imaging hardware and software enhancements to ensure scalability and reliability of the telemedicine in high volume, low bandwidth settings across multiple partner hospitals globally. We are also conducting customer discovery interviews with small-to-mid sized eye hospitals to refine our business model for sustainability and scalability.

First, we are seeking mentorship to develop innovative, sustainable, and scalable business models that ensure our solution can reach as many people as possible while maintaining financial viability. We have identified numerous potential business models for a self-financing product that does not rely on patient payment and would benefit from support on evaluation and implementation.

Secondly, we are preparing for the commercial launch of our flagship product in Q1 2025 and are seeking rigorous evaluation of our implementation strategy, including regulatory compliance and go-to-market strategy. Through engagement with seasoned mentors provided by this program, we anticipate receiving invaluable feedback and guidance to identify potential pitfalls, mitigate risks, and avoid costly mistakes ahead of our product launch. 

Visilant is the only comprehensive solution for eye screening, referral, and management to ensure patients are integrated into existing care delivery systems to receive the treatment they need. 

Other companies offer portable anterior segment imaging devices. However, they were designed with ophthalmologists, not health workers as the end user. As a result, when we piloted these technologies with health workers, less than 33% of images were sufficient quality for diagnosis. By comparison, Visilant’s technology achieved 97% diagnostic quality images by health workers who received only 30 minutes of training. Additionally, the competitor devices on the market cost $2,000-4,500 which is not accessible or scalable in emerging markets. We worked closely with ophthalmologists and health workers to identify the most important functionalities in community and vision center settings and designed a simple, intuitive, low cost solution that meets the needs of patients and providers. 

Other solutions to this problem include visual acuity measurement applications, but these fail to provide a specific diagnosis and clear referral pathway for patients, which may cause increased referral burden. Many companies have developed algorithms for fundus imaging, which fails to address the leading causes of blindness (e.g., cataract). A few have developed algorithms using gold-standard, slit lamp images captured in a clinic, but these have limited utility in non-ideal field settings with affordable imaging devices. Visilant has developed one of the largest databases of smartphone-based anterior segment images, which enabled development of the first portable combined telemedicine and automated diagnosis platforms for anterior segment disorders. 

Visilant is the only platform that provides end-to-end patient care and integrates patients into the eye care system. Through customer discovery interviews, we recognized the administrative challenge of organizing screening and follow-up, managing health workers, and maintaining quality control, so we implemented automated follow-up, integration into existing EHR systems, and intelligent data dashboards to provide a comprehensive solution for hospitals. We offer training and implementation support to enable hospitals to implement a telemedicine outreach program in 2 weeks. Our innovation leverages our deep understanding of the needs of the patients, healthworkers, and hospital systems and advances in imaging, telemedicine, AI, and business models that collectively address the primary barriers to eye care access.

Our technology has been iteratively designed to meet the unique needs of the most underserved patients. Our novel imaging system enables community health workers to capture high quality eye images in a patient’s home or community. This is paired with our software platform, which provides an automated referrable decision, integrates the record into an electronic health system, and notifies the patient and hospital of follow up steps. This pathway enables decentralized eye screening at scale. We address the technical, geographic, and human resource constraints currently limiting access to eye care.

Additionally, we have developed a business model that drives hospital adoption and supports financial sustainability. We save hospitals money by reducing the cost of organizing large screening events, we increase revenue by increasing the volume of patients who are referred for reimbursed procedures, such as cataract, and we reduce the time ophthalmologists spend on patient screening so they can focus on treating patients.

We assess our organizational success by:

1. Number of patients served- we have impacted 3,500 patients during the development of Visilant. 

2. Number of hospital and community partnerships- we have piloted this technology with 3 eye hospital partners. These partners are the key to successful treatment of patients. 

3. Number of patients who follow up for care- we will track follow-up and evaluate methods  for improving follow-up to ensure patients receive the care they need.

4. Accuracy of ocular diagnoses and referrals- to ensure high quality care, we will evaluate accuracy of telemedicine diagnoses and referrals.

5. Cost for the patient- we will provide the screening for no cost to the patient. We are partnered with charitable eye hospitals who provide free or heavily subsidized eye care.

6. Cost effectiveness for the hospital- we will assess the cost of deployment at a new hospital to demonstrate cost effectiveness compared to current outreach strategies.

Our solution relies on digital health, imaging, and artificial intelligence technologies. We built the telemedicine platform on cloud services to make it easy to implement, scalable for high volume systems, and reliable. The system can operate offline asynchronously (data is stored and transmitted when internet is available) or over low bandwidth through image compression algorithms similar to WhatsApp. The mobile app guides health workers through complaint and medical history collection using adaptive questioning. The clinical protocols are easily modifiable without coding knowledge, so the screening can be easily customized to hospitals’ needs. 

The imaging attachment makes it simple for health workers to capture anterior segment images. The magnification system provides focused images across key ocular structures when the device is positioned against the patient’s face. The illumination system is optimized to visualize internal and surface structures of the eye for diagnosis of patients with all eye and skin tones. 

Our artificial intelligence algorithms are trained on images collected by community health workers from the target patient population on budget smartphones. Additional machine learning and image processing techniques are utilized to verify image quality and ensure quality control. The algorithms are lightweight and can be locally hosted on a smartphone without internet. 

2 full time, 10 part time

3.5 years

As a female-founded and led organization, we are committed to diversity, equity, and inclusion in our team. Our team is more than 60% women and more than 60% persons of color. Our advisory board is composed of individuals from the countries we work in so that our end user’s perspectives and needs are represented in all decisions. We work with hospitals to recruit community health workers from the local regions they serve because we recognize they are the ones best suited to care for people in their communities. We work to minimize barriers to opportunity for our staff by fostering an inclusive environment where everyone feels valued, respected, and empowered to contribute their unique insights and talents. This includes offering flexible or hybrid schedules to support team members with differing needs in their personal lives. Our CEO is passionate about mentoring young women in STEM, so we offer internships and learning experiences for high school girls interested in making an impact through science and technology.

We will leverage a software as a service (SaaS) business model with an annual subscription fee tiered by hospital size and a referral fee based on a percentage of hospital revenue for referred services. This will allow us to develop a scalable, high margin business model while enabling access. For example, cataract surgeries, which account for 20% of referrals, cost the hospital $15-20 per treatment. In India, the government may reimburse cataract surgery up to $90. Additionally, hospitals profit 50% off of provision of glasses, which typically cost $10-20. Use of Visilant’s technology will significantly increase the number of surgeries performed and glasses provided. Visilant will capture a small percentage of the profit for providing the referral, thus generating revenue as the hospital generates revenue. Through interviews with partner leadership and estimates of referral percentages and fees, we conservatively estimate an average revenue of $2 per person screened. Current eye camps cost $5-8 per patient, meaning Visilant reduces the cost of screening for the hospital while increasing the number of patients screened.

Additionally, we have identified opportunities to provide imaging hardware for screening and monitoring of patients in the US and during NGO medical missions. These earnings will subsidize broader utilization of the platform globally.

We have funded technology development and validation through non-dilutive grant funding, including funding from National Institutes of Health, Microsoft for Startups, National Academy of Medicine, and the Abell Foundation. Our team has a proven track record of success winning grants and completing grant milestones ahead of schedule. As a 501(c)(3), we will also leverage philanthropic funding for technical development and validation costs. 

As a SaaS company, our main costs are imaging hardware manufacturing, cloud architecture, and support staff. These costs will be covered through subscription and referral fees generated from hospitals. The imaging hardware is low cost to manufacture and will be recouped by a small subset of patient referrals. Our partners have in-country manufacturing facilities, enabling low cost, high quality device manufacturing locally, further reducing costs. We have conducted customer discovery interviews with hospitals to understand what they are willing to pay and what they pay for their existing electronic health record solutions. Based on the ability to pay, we worked with Cloud Engineers at Microsoft to develop a backend infrastructure that meets these cost constraints while achieving performance specifications. We conservatively estimate that hospital subscription fees will cover cloud computing costs. We will hire local and train project managers, implementation support, and technical support in-country, which will be more cost effective and ensure support is provided by people with local context knowledge. Staff will be supported by revenue generated through referral fees or other grant/philanthropic activities. Our low overhead costs and scalable business model will enable financial sustainability.