Over the past twenty years, clinical decision support systems have significantly expanded and are now commonplace across many medical fields. These tools have aided many disciplines within medicine to provide greater efficiency and accuracy. However, in the field of optometry and specifically for glaucoma, such support systems are not yet available. In many optometric settings, OCT devices are used to screen for eye disease. Often, the OCT alone lacks specificity and ends up falsely flagging patients who have a problem. This results in an overload of patients, and referrals of patients, who do not need to be treated nor to see a specialist.  

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As clinical optometrists, the amount of data we interact with grows every year. The key is in refining the data points to what is clinically significant.  With an aging population, the demand for care will continue to outpace the supply of optometrists (and ophthalmologists).  Clinical decision support systems are an additional diagnostic tool for optometrists. When they are developed with greater sensitivity and specificity, there can be more accurate patient management. This leads to fewer patient referrals for those who don’t need high-level secondary or tertiary care. This helps to ensure we have more time for patients who truly require our care. To address this gap, we have collaborated with research scientists at Topcon and several large academic institutions to develop a model that meets these goals for accurately diagnosing glaucoma in screening settings.

Using optic nerve photographs, OCT imaging, visual field testing, eye pressure, and corneal thickness measurements, we have created a Glaucoma Health Score metric, where each patient receives a score between 0 and 100. The higher the number is the more likely glaucoma is present. Thus, providing a much clearer assessment of whether a patient has glaucoma or is at risk of developing it.

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We are able to actively participate in this research thanks to the extensive data available to us at the IEI. In the past year alone, ICO treated over 4,400 glaucoma patients, spanning all stages of the disease. In addition to our current patients, we have incorporated historical data into our analysis, enabling us to categorize glaucoma by stages.

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This approach not only helps tailor treatment to individual needs but also assists in identifying cases where more intensive monitoring or treatment may be necessary to prevent progression. With patient data spanning years, advanced diagnostic technology, strong partnerships, and expert faculty, ICO brings together all the essential elements to drive our research forward. We’ve established ourselves as a strong industry partner, delivering high-quality results on time.

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We are still in the early validation phase, gathering data from a range of patients, including those with glaucoma, glaucoma suspects, and a control population. So far, we have run dozens of individuals through the simulator and validated them based on years of clinical experience, ensuring the metric’s accuracy with appropriate controls and statistical validations.

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Through this initial analysis, we have demonstrated the feasibility of developing a multi-risk factor glaucoma health score.

Having worked in this field for the past three decades, I have witnessed significant improvements in diagnostic accuracy as technology advances. I am particularly excited to see how this data driven approach for new tools can guide optometrists to make the best diagnosis for their glaucoma suspects and patients. This project has been a deeply rewarding extension of my clinical work over the last 30 years. 

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Chaglasian, M.; Nishida, T.; Moghimi, S.; Speilburg, A.; Durbin, M.K.; Hou, H.; El-Nimri, N.W.; Lee, C.K.; Guzman, A.; Arias, J.D.; et al.  The Development and Validation of a Glaucoma Health Score for Glaucoma Screening Based on Clinical Parameters and Optical Coherence Tomography Metrics. J. Clin. Med. 2024, 13, 6728. https://doi.org/10.3390/jcm13226728