Ophthalmic technicians comprise the backbone of ophthalmology practices by facilitating both direct patient care and indirect background clinic support. Not only do they obtain histories and testing data so doctors can focus on direct patient management but they also triage phone calls, refill medications, prepare minor procedures, and manage insurance preauthorizations, just to name a few responsibilities. Without them, the clinic’s flow and patient volume would be severely limited. Despite their importance, however, clinics increasingly contend with a nationwide technician shortage.
This shortage has been worsening as patient volume outpaces the supply of available staff. The number of ophthalmic training programs that offer the Certified Ophthalmic Technician certification—around 30—has not changed despite the rising demand.1,2 By 2021, there were < 60 000 technicians for > 19 000 ophthalmologists.3,4 The coronavirus disease 2019 pandemic accelerated shortages as clinics were initially forced to cut staff and then later deal with the quarantine-related patient backlog with already fewer technicians. The pandemic also caused long-term work culture paradigm shifts that spurred even higher turnover rates.5,6 Dubbed by the Harvard Business Review as the “Great Renegotiation,” this changing relationship between worker and employer is highlighted by a desire for purpose and flexibility, especially since many experienced what it was like to work from home.5 Exploring new ways to recruit and retain staff is now vital to clinic survival in this postpandemic era.
Ophthalmic technicians often leave because of job dissatisfaction, which is cited as the most influential cause of turnover by an International Joint Commission on Allied Health Personnel in Ophthalmology study.1 Harvard Business Review proposes that modern employees place high emphasis on engaging and meaningful work and opportunities for professional growth.5 Like doctors, technicians pursue health care for the rewarding patient interactions, which may be undermined by increasing busywork in a data-heavy, electronic, and bureaucratic medical system. The disproportionate and unfulfilling work that technicians take on when others leave only worsens this burden. To tackle this, Harvard Business Review recommends creating more flexible, engaging, and rewarding work environments to revive a sense of employee purpose and growth.7 We must do the same in our ophthalmology clinics if we wish to retain the best technicians.
Clinic flow inefficiencies undermine the technician’s job by creating friction points that compound throughout the day. Writers like Nordgren and Schonthal8 explore how reducing existing friction may be a more effective first step compared with adding fuel, which in our case, would be work incentives such as financial compensation, career advancement opportunities, and better benefits. For example, technicians waste time transferring data among systems and patients between examination rooms and testing devices. Addressing these areas of resistance using new technologies and workflow innovations may increase time for more rewarding aspects of the job, such as patient interaction, or challenging yet gratifying tasks, such as a difficult refraction. The time can even be used to show the technicians clinical and imaging findings that correspond to the patient history and testing they performed; this connection can provide more context and meaning to their work. Advances in technology can potentially augment the technician’s daily efforts, as represented by the last row of Figure 1 and further discussed below.
Figure 1.
General glaucoma clinic flow with potential technology assistance. AI = artificial intelligence; HPI = history of present illness; V/A = visual acuity; VF = visual field.
During clinic visits, technicians take the patient’s history, allowing for further questioning and possible tests. This can be time consuming, especially for technicians trying to confirm how elderly patients are using their eye drops. Preclinic surveys administered to patients before their clinic visit, either at home using the internet or in the office before the start of the visit, may reduce the time needed for technicians to take the patient history. In the future, preclinic information gathering could be augmented with artificial intelligence (AI). Doctor.ai, Ada Health, and Babylon Health are examples of medical AIs that try to fluidly converse with patients before clinic to create a preliminary diagnosis. It is important that all of these efforts for preclinic visit information gathering be usable and accessible for patients, especially for those with low computer literacy and vision impairment.
Next, the technician performs patient-specific testing, which can become a point of clinic bottleneck. New technologies may have the most impact in this area. Home-monitoring devices like Holter monitors and continuous glucose monitors have collected accurate data trends that obviate the need for a single in-clinic test. For ophthalmology, the iCare HOME2 Tonometry provides valuable insight into diurnal intraocular pressure fluctuations, whereas KeepYourSight’s web-based tools provide rudimentary screening for macular degeneration, glaucoma, and diabetic retinopathy. Although at-home testing is not yet widely adopted into clinical practice, these advancements paint a future in which this might be a reality. This opens the door to virtual visits for routine follow-up testing encounters that may decrease the in-person patient load so technicians can focus on more complex cases, though practical and legal issues, such as state licensure issues, need to be addressed to make this a reality.
Because at-home testing may not be practical for everyone, device advancements may improve the in-clinic experience for these patients. The common themes among these devices are automation, combination, and integration. An automated refractor (i.e., Chronos Automated Binocular Refraction System and Visionix EyeRefract) can take a subjective refraction, whereas virtual headsets (i.e., Radius XR) can obtain a subjective visual acuity without supervision. Some combine tests like the TONOREF III (i.e., visual acuity, refraction, tonometry, and pachymetry) and the Radius XR (i.e., visual acuity, color vision, and visual fields). Some integrate with the existing electronic medical records (i.e., Visionix EyeRefract with EPIC) or even with each other for seamless data transfer without the need for manual input (i.e., Zeiss Cataract Work Flow). Automation allows for decreased user time, whereas combination reduces movement between testing devices. Integration decreases manual data transfer, which can be not only tiresome work but also an opportunity for human error. Overall, these devices have the potential to significantly increase testing efficiency.
Lastly, technicians often function as scribes. That person must temporarily pass their responsibilities onto the other technicians during that clinic. AI scribes like Scribe.ai, Nuance, and Deepscribe.ai could fill the role of scribe and allow technicians who would usually be scribing to continue working up patients with the other technicians. Having just 1 more person to share the patient volume can lighten the overall workload. Although these AI scribes are in their infancy like the other technologies above, they suggest a future in which more robust models could accurately transcribe patient notes tailored to each physician’s style.
The traditional “patient-physician” relationship has now changed to a “patient—health care team” partnership as medicine increasingly recognizes the collective efforts of all team members. Because technicians spend significant time with patients—sometimes even more than the physicians—their interactions contribute greatly to the quality of care. The technological advancements previously discussed can collectively provide more time for these rewarding moments, ones that can make work more meaningful and exciting. However, new changes carry the risk of increasing user burden if they cause unintended and unforeseen inefficiencies in the existing system. These new technologies must not only be independently functional but also easily integrable into the clinic flow.
The need for usability necessitates careful design and rigorous evaluation of these technologies. A user-centered design process can first identify the need, then the technology to address it, and finally the feedback for further improvements.9 The user-centered design phases are outlined as specifying the context of use (who, when, and where of product usage), specifying requirements (user goals to be met for product success), creating design solutions (what technology to use), and evaluating designs (real-life testing and feedback). For example, the context is ophthalmology technicians in a clinic setting, the requirement is the need to improve clinic efficiency, the solution is 1 of the previously discussed technologies, and the evaluation is applying the intervention in real-time while evaluating if efficiency was improved without sacrificing quality. Clinics can internally evaluate these technologies by objectively measuring the time spent in each work-up step and subjectively interviewing technicians and patients on their experience working with the new technology. Success is ultimately increased usability for not only the technician but also the patients. Externally, formal studies can investigate the technology’s contribution in a practical setting, providing generalizable evidence for clinicians deciding whether to adopt these new technologies. These formal studies can also assess the financial cost of these tools so that clinics can make informed decisions on their purchase. In the end, a tool is only as good as its user and how it is applied.
Ophthalmology clinics depend on their high-quality technical staff. These employees deserve the utmost support, especially when they continue to work tirelessly despite challenging conditions. With the technological revolution in full swing, we hope to harness new advancements to create a more fulfilling experience for these vital employees.
Acknowledgments
This work was supported by the National Institutes of Health (K23EY032577 to B.C.S.) and an Unrestricted Grant from Research to Prevent Blindness, New York, to the Department of Ophthalmology & Visual Sciences, University of Utah. The sponsor or funding organization had no role in the design or conduct of this research.
Footnotes
Disclosure(s):
All authors have completed and submitted the ICMJE disclosures form.
The authors have no proprietary or commercial interest in any materials discussed in this article.
Barbara Wirostko, MD, an editor of this journal, was recused from the peer-review process of this article and had no access to information regarding its peer-review.
Contributor Information
Anthony P. Mai, Salt Lake City, Utah.
Barbara Wirostko, Salt Lake City, Utah.
Shannon Fitch, Salt Lake City, Utah.
Kari Hansen, Salt Lake City, Utah.
Wayne Imbrescia, Salt Lake City, Utah.
Brian C. Stagg, Salt Lake City, Utah.
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