Practice Development, Digital Operating Room, Artificial Intelligence
Smoothing the Way for High Tech Adoption
What is the best way to integrate new technology into the office?

Timothy Norris
Published: Monday, September 2, 2024
In the digital era, integrating new technology into everyday clinical practice can be challenging. What could be considered a boon for workflow and performance can instead have the opposite effect if the integration process is not optimal, said Kristine Morrill at a recent high tech adoption workshop.
While the clinician may be very enthusiastic about some new tech acquisition, this does not always transmit to the whole clinic team, who might struggle due to a lack of training and support from the manufacturer, she noted.
Morrill added many of the failures in introducing new technology in the field could also be attributed to the industry, from unrealistic expectations regarding clinician needs to proper lack of funding and commercialisation errors. Successfully integrating new technology in clinical practice requires staff engagement and patient communication.
“What is your current situation? What do you want to achieve?”
Adopting a new technology is always gradual: of all the clinicians, only 2.5% will immediately try and adopt an innovation, followed by 13.5% of what are called early innovators. “So, what is stopping a clinician from becoming an early innovator?” asked Carl Zeiss Meditech’s Head of AI, Georgy Shakirin. Surely it is not an easy task—going through all the available evidence just to understand what really works and what does not, he observed.
According to Shakirin, to make it worthwhile both in terms of time and money, it is important first to assess the new technology’s integration and interoperability—asking peers for feedback and trying to understand how much the workflow can be affected.
A key point is the presence and quality of service and support—which may be essential to guarantee a good integration—and improvement of the clinical ecosystem, Shakirin underlined. Integrating a technology such as AI is especially sensible for these different aspects. It is necessary to understand what kind of data is used, how the model is trained, and if the available computational power is enough. Available cloud storage and all the regulatory aspects also need consideration, he added.
A decision in the making
Patients, regulators, funders, policymakers, and clinicians may all have the best intentions when considering adding a new technology to a practice. This generates a whole ecosystem, with different decision processes that often are poorly coordinated, leading to confusion and lack of decision, Joaquín Fernández Pérez MD, PhD told the workshop.
Adapting to every scenario is then vital to improve this decision-making process. It starts with a Feasible, Interesting, Novel, Ethical, and Relevant (FINER) research question, he observed. Moreover, the question must be based on the PICO-S/T, considering the Patient, Intervention, Control, Outcome, Study Design, and Timeline. Finally, to convert the level of evidence into recommendations, Dr Fernández suggested the GRADE system, a systematic review based on literature. A high level of evidence and randomised controlled trials independent from bias are needed.
Dr Fernández also stressed an evaluation of cost-benefit and cost-consequence as key for a successful health-technology assessment, which he said could improve collaboration and transparency in healthcare decision-making for more inclusive policy development.
ESCRS: monitoring healthcare
When it comes to gathering and analysing data to monitor the quality of European healthcare systems, ESCRS is on the front line—collecting data and analysing and reporting outcomes to identify benchmarks and significant variants, which it hopes will lead to improvements in healthcare quality, Anders Behndig MD, PhD told the workshop.
“We are facing the same problem,” he said. So far, ESCRS has collected data on 4 million cataract surgeries and 13,000 corneal and cell transplantations through different registries, such as EUREQUO and EURECCA, from several EU member states.
“We want to achieve EMR-registry interoperability, to export data from electronic medical records, and cut down the workload,” Dr Behndig said.
The workshop was held at the 2024 ESCRS Winter Meeting in Frankfurt.
Kristine Morrill is Co-founder and President of Medevise Consulting, Strasbourg, France. kristine.morrill@research.escrs.org
Georgy Shakirin is Head of AI of Carl Zeiss Meditech.
Joaquín Fernández Pérez MD, PhD is CEO and Medical Director of the Ophthalmology Department at Qvisión in Vithas Virgen del Mar Hospital, Almería, Spain. JoaquinFernandezoft@Qvision.es
Anders Behndig MD, PhD is President of the Swedish Ophthalmological Society and Professor at Umeå University Hospital, Sweden. anders.behndig@umu.se
Tags: practice management, leadership, panel, digital, digital ophthalmology, Kris Morrill, Georgy Shakirin, Anders Behndig, Joaquin Fernandez Perez, AI, artificial intelligence, technology, high tech, practice development, streamline processes, tech acquisition
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