Digital Slit Lamps: Workflow, AI and Clinical Adoption

Abstract

Digital slit-lamp technology connects a familiar examination with new possibilities: structured image capture, remote review, quantitative measurement and AI-supported documentation. My central proposition is that adoption will depend on the complete clinical workflow. A useful system must deliver trustworthy information to the right person, reduce avoidable work and support an appropriate next decision. This perspective reviews selected approaches and proposes how clinic leaders and developers can assess their practical value.

Introduction

Through my involvement with Pallas and Swiss Vision Group, I have come to see slit-lamp examination as one of the less digitized parts of our clinic workflows. This is a personal observation, not a measured comparison across clinics. It raises a practical question: why should an examination rich in visual information so often end with a manually written description?

A photograph alone does not solve the problem. Someone must identify the patient, acquire the relevant views, assess image quality, interpret the findings and place them in the clinical record. If digitization adds tasks without removing friction elsewhere, its clinical and commercial value will be difficult to sustain.

Methods reviewed

This is a focused narrative perspective, not a systematic review or a head-to-head device evaluation. Public manufacturer descriptions and selected primary studies were reviewed on 9 October 2026 to illustrate different approaches. Inclusion does not imply endorsement, completeness or equivalent regulatory status. The following examples solve different parts of the workflow.

1. Digitizing an established examination

Topcon describes its DC-4 camera attachment for compatible slit lamps and transfer of captured images to IMAGEnet 6. The emphasis is on adding documentation to an established examination.¹ The implementation question is whether capture, patient matching and retrieval fit the existing clinical record without repeated manual entry.

2. Separating the examiner from the instrument

Eyoto describes Aetheia:Remote for clinician-controlled examination with local assistance and Aetheia:Auto for automated or assisted acquisition. These are manufacturer descriptions, not independent evidence of equivalent outcomes or improved throughput.² The distinguishing opportunity is to reorganize where and by whom acquisition and review occur; the evaluation must include failed acquisitions, escalation and local staffing.

3. Portable acquisition

A 2021 study of the Remidio PSL D20 reported optical characterization and a nine-subject pilot demonstrating photodocumentation and teleophthalmology feasibility.³ This supports feasibility in a limited setting. It does not establish broad diagnostic equivalence or the economics of routine deployment. Portability should be evaluated alongside repeatability, training and the ability to capture clinically necessary views.

4. AI-supported measurement

A study published online in 2025, in the January 2026 issue of Ophthalmology Science, evaluated AI-based anterior chamber depth estimation using smartphone-compatible Smart Eye Camera images against anterior-segment OCT at a separate institution.⁴ This illustrates a specific measurement task. It should not be interpreted as validation of autonomous diagnosis across anterior-segment disease.

Key learnings

Acquisition, measurement and diagnosis are distinct tasks. A workflow may separate acquisition from later clinical interpretation. AI may assist selected measurements or documentation, but responsibility for clinical decisions, uncertain findings and escalation must be explicit.

Image quality is a workflow requirement. Before interpretation, the system should establish whether the required anatomy and views were captured adequately. A technically successful upload can still be clinically insufficient.

Interoperability determines everyday usefulness. Patient identity, laterality, acquisition settings, timestamps and findings need to travel with the record. Buyers should request a demonstration in their actual practice-management and clinical-record environment, including retrieval at a later visit.

Efficiency needs an end-to-end denominator. Faster capture has limited value if review, transcription or repeat acquisition consumes the time saved. Measure staff time and clinician time separately, from patient identification through a completed and reviewed record.

Opportunities and threats

For clinic groups, a promising opportunity is a more consistent record across visits and locations, with specialist review directed toward cases that need it. For developers, standardized acquisition can provide a foundation for narrowly defined AI tasks. For patients, the potential benefit is a clearer journey with fewer avoidable handoffs. These are opportunities to test, not outcomes established by this review.

The main threats are incomplete examinations, inappropriate confidence in an algorithm, extra documentation work, fragmented records and business cases based on capacity that is never used. An algorithm validated on one device, population or acquisition protocol may require further evaluation elsewhere. Buyers should verify the intended use and current local regulatory status of the exact hardware–software combination with the supplier.

The commercial question is who benefits enough to pay. A clinic may value reduced clinician time, improved record quality, access to expertise or additional completed visits. Each value proposition requires a different pilot and a different economic model. Subscription fees, integration, training, support and rework belong in that model alongside the instrument price.

Discussion

I would begin a pilot with one clinical pathway and a defined comparison against current practice. Before installation, agree what a complete examination record requires, who reviews it and when an in-person assessment is needed. Avoid combining a new instrument, an untested AI model and a redesigned staffing model into one undifferentiated claim of success.

Record acquisition success, repeat capture, documentation completeness, time by staff role, time to clinical decision, escalation and patient experience. Where measurement or diagnostic performance is claimed, use an appropriate reference standard and independent evaluation. Report difficult and ungradable cases, not only successful acquisitions.

Then calculate cost per completed, clinically usable examination and test whether released capacity is actually used. The strongest evidence for adoption would connect reliable clinical information with a workflow improvement that persists after the initial enthusiasm and training period.

Conclusion

The digital slit lamp has the potential to connect examination, measurement and documentation more effectively. The decisive innovation may be the organization of the work around it. For an ophthalmic company, the challenge is to build that workflow into the product. For a clinic, it is to demand evidence that the complete process improves.

Efficient and effective workflow is king. The instrument earns its place when the whole clinical process works better.

Developing a digital ophthalmic technology or planning adoption across clinics? Explore innovation and commercialization advisory or the clinic-group perspective.

Discuss a digital ophthalmology workflow decision

Author perspective informed by work in ophthalmic research, company building and governance. This article contains no new clinical dataset or company ranking. Manufacturer descriptions are identified separately from research evidence. See Michael’s leadership and board roles.

Efficient and effective workflow is king.