Healthcare professionals with engineering backgrounds are about as rare as the Knicks winning an NBA championship. Tech engineering and development teams tend to move at warp speed, whereas mature healthcare systems overall operate at a more deliberate, measured pace.
But that pace no longer works in the digital era, where innovations like AI are making it necessary to refresh operational thinking. With this in mind, I believe adopting a tech engineering mindset offers a framework that can help you align with today’s technological advancements and the way patients live and work.
Siloed point thinking creates waste and errors, while systems thinking aligns with value-based care—where coordination, prevention and efficiency improve outcomes and reduce costs. Engineers can play a pivotal role in accelerating healthcare’s shift from reactive, point-of-care thinking to proactive, systematic care, ensuring that efficiency, safety and patient outcomes advance together.
Systematic Thinking
Systematic thinking in healthcare means seeing the big picture and understanding how all elements, including telemedicine, work together to improve care. By assessing a patient’s full needs—whether through virtual consults to address specialist shortages, remote monitoring or post-surgical follow-up—this approach leads to better outcomes. Healthcare systems still struggle with siloed departments, making full care integration a persistent challenge.
Additionally, failure to look outside the internal structure can have negative consequences. For example, if a new manufacturing facility is bringing more employees to the region, is your healthcare system equipped to manage the uptick in pediatric or urgent care services? Is there a telemedicine provider in place to support the increased patient load? Keeping patients local is a key revenue source, but it requires examining all these interconnected elements to be successful.
Systematic thinking is making some headway. The American Medical Association (AMA) recognizes its value and includes the topic as one of its learning modules, encouraging professionals to adopt practices that recognize the circular nature of cause-and-effect relationships.
Adaptability
Having a systematic framework is essential to being able to adapt to external and internal changes. Compared to engineering or tech product development, which can revise code and iterate a product, it’s a tougher hurdle for healthcare systems.
Changes in services or new software do not follow the “move fast and break things” style of some tech leaders. That being said, healthcare and telemedicine providers can serve their patients well by being able to adapt effectively as unforeseen changes occur.
For example, a large regional health system we worked with specialized in pediatric services—including an emergency department, NICU, PICU and inpatient rehabilitation unit. It faced a major challenge when a long-standing neurology partner shifted entirely to outpatient care, leaving the hospital without inpatient pediatric neurology coverage.
It adapted by introducing pediatric neurology telemedicine care, but found medical staff and families initially resistant; however, by allowing the children to stay in the hospital and receive the array of specialty services, families and staff quickly became convinced that telemedicine was an asset.
When unforeseen challenges arise, the key is to think in systems, iterating your systems quickly but safely. In this case, instead of viewing the loss as an isolated staffing issue, the health system applied systematic thinking, introducing telemedicine as a modular solution, similar to how engineers iterate on components. The overall key is to make sure you build adaptable frameworks rather than rigid plans.
Applied Science
Healthcare systems are making progress in applied science applications like AI, machine learning and predictive analytics. An AMA survey found physician use of AI jumped from 38% in 2023 to 66% in 2024. Billing codes, visit notes, care plans and assistive diagnosis are some of the uses.
To increase AI adoption, the AMA survey noted physicians want to see certain needs addressed, notably increased regulatory oversight, data privacy assurance and seamless workflow integration. Adequate training and education in the use of AI was also cited by physicians as important.
In telemedicine, AI enables remote diagnostics and analytics to customize consultations based on individual patients’ data. It can promote better patient outcomes and support much-needed specialty care in rural communities.
But achieving AI adoption and meeting physician needs will require a non-siloed, systematic framework in which healthcare administrators, tech staff and physicians work together to develop and implement an integration strategy and data privacy protection remedies.
Blending Tech And Telemedicine
Among other phenomena, AI has compelled legacy healthcare systems to quickly develop a point of view about GenAI technology. The question is: Who should lead the charge for AI adoption?
A Bessemer Venture Partners analysis of healthcare AI adoption indicates new technology investments are solidly the C-suite’s domain. Of those surveyed, 68% say IT staff’s role now is to validate, but decision making power is in the hands of tech-focused CEOs and CXOs.
Healthcare system’s executive suite will need to drive further adoption, all while finding solutions to the issues of data privacy and system integration. They will increasingly require an AI component in a technology budget request.
As AI gains more widespread applications across healthcare, it underscores a critical reality: The future of care delivery cannot succeed without systematic thinking, engineering-driven solutions and the ability to adapt quickly. Those who embrace this approach will lead the next era of healthcare innovation, while those who resist risk being left behind.
Jason Povio, Chief Executive Officer for Eagle Telemedicine
Original Article published in Forbes.
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