CTO: I Negotiate Change

Digital transformation in a hospital is a continuous struggle to balance quality of care goals, healthcare professionals’ well-being and expectations, patients’ needs, financial constraints, and technology. What does this work look like behind the scenes? An Interview with Dr. Anke Diehl, Chief Transformation Officer (CTO) at University Hospital Essen (Germany).

Let’s start with clarifying your role. What’s the difference between a Chief Information Officer, Chief Digital Officer, and Chief Digital Transformation Officer?

No, there’s a significant difference. Chief Information or Digital Officers are typically more technical, often with backgrounds in IT or medical informatics. A Chief Transformation Officer, however, is usually someone from the medical field who recognizes that digitalization changes the entire culture of a hospital.

This role requires collaborating across disciplines — IT specialists, medical technologists, nurses, therapists, and patients — to find innovative solutions. That’s why my title is Chief Transformation Officer, not just an IT or digital role.

You were a physician before transitioning into digital transformation. What led to that change?

It’s been part of my personal journey. After medical school and training in neurology, I spent a year in neuroradiology and was fascinated by imaging technology. I ended up staying in radiology for 11 years, learning the importance of teamwork with technicians and other staff.

Later, I shifted to healthcare services research, focusing on telemedicine and health technologies. Eventually, I was invited back to the University Hospital, where I became Germany’s first digital change manager. After a few years, I became the Chief Transformation Officer and now lead our digital transformation unit.

Do all hospitals need a digital transformation officer, or can they wait for change to happen?

Hospitals that want to survive need to take proactive steps. They must appoint someone — either a transformation officer or a change manager — to drive the process. This person doesn’t need to be a doctor but should have both technical training and healthcare management experience. They must also be open-minded and capable of advising hospital leadership on the best strategies.

In your role, you have to manage many conflicts, for example, between hospital managers, who want smooth digital transformation, and medical staff, who often find IT systems frustrating and inefficient.

Hospital managers are under pressure to implement digital systems that improve efficiency and reduce costs, but many healthcare professionals, particularly doctors and nurses, struggle with the systems we have today. Managers are focused on long-term transformation, but doctors and nurses are dealing with the immediate challenges — IT systems that are often slow, clunky, or require them to spend more time on administrative tasks than with patients.

For example, electronic patient records (EPR) were introduced with the goal of improving patient care through better data management. However, many doctors feel that the current EPR systems take too much time to update and don’t provide enough immediate value. Instead of spending time with patients, they’re spending time inputting data, often across multiple systems that aren’t well-integrated. Nurses face similar challenges, and frustration builds when the technology is perceived as more of a burden than a tool.

In my role, I need to act as a bridge between these two perspectives. On one side, hospital administrators expect the digital transformation to be seamless, but on the other, medical staff are struggling with systems that don’t always meet their needs. We try to approach digitalization incrementally, introducing systems in ways that don’t overwhelm staff and allowing for plenty of feedback so we can make adjustments based on their experiences. This is crucial because if we don’t get the buy-in from healthcare providers — the people using the technology — the transformation can’t succeed.

It’s important to understand that digital transformation isn’t just about introducing new technology; it’s about changing the entire workflow. This means rethinking how doctors and nurses interact with patients, each other, and the systems they use. For managers, the focus is often on the big picture — improving outcomes and efficiency — but for staff on the ground, it’s about how these changes affect their day-to-day work. That’s where conflicts can arise, and it’s my responsibility to ensure that we find common ground.

At the University Hospital in Essen, we’re fortunate to have a robust digital infrastructure, with over 300 IT professionals supporting us. The Governing Council is very forward-thinking, which makes a big difference. However, even with that support, we still face the same frustrations that other healthcare systems experience. Interoperability, for instance, is a massive challenge. Systems don’t always communicate well with each other, leading to delays and inefficiencies that frustrate medical staff.

Another factor is that healthcare professionals are not free to decide what technology they will use. A doctor can’t just choose to use a speech recognition tool if the hospital doesn’t have the budget to implement it. This lack of flexibility is a significant pain point. Doctors and nurses often have excellent ideas about how technology could improve their work, but without the proper IT systems, they’re stuck with whatever the hospital provides.

At Universitätsmedizin Essen, we’ve tried to eliminate as many of these barriers as possible. We’ve invested in a FHIR-based data lake, the largest in Europe. This allows us to develop and test new AI algorithms, providing staff with tools that genuinely help their work. But even with this, conflicts still arise. The key is open communication, active listening, and ensuring that digital solutions are developed with the end-user — the doctors and nurses — in mind. If we can bridge the gap between management’s vision for the future and the immediate needs of healthcare providers, digital transformation becomes a collaborative effort rather than a source of frustration.

You mentioned that openness to change didn’t happen overnight. How was this shift in mindset and readiness for transformation achieved?

Achieving this transformation involved several vital steps. First, it required strong leadership and strategic decisions from the top. When Professor Jochen Werner joined the governing board in 2015, he introduced the concept of a “smart hospital.” Initially, there was some resistance and skepticism among staff, with some questioning whether this concept was suitable for a university clinic. However, Professor Werner’s vision proved to be transformative.

He made it clear that digitalization and AI were critical for the “future hospital.” Then, Prof. Werner mandated that all new staff, regardless of their position, be prepared for these changes. This approach ensured that everyone in the organization, from the highest levels of management to recruits, was aligned with the digital transformation goals.

Over the next few years, it became evident that collaboration was essential for success. In a university setting, there is often competition between clinical departments, but the realization grew that working together on digital processes would be more beneficial. Departments began to see the advantages of adopting the same systems and strategies, which led to greater efficiency and integration.

Moreover, engaging with younger staff who were more familiar with digital tools and fostering a culture of open dialogue was crucial. The hospital encouraged collaboration and innovation, recognizing that valuable ideas could come from any level of the organization. This inclusive approach helped to overcome resistance and build a unified effort toward achieving their digital transformation goals.

What does a typical day look like for you as a Chief Transformation Officer?

My day is all about communication. I start by checking emails and then spend most of the day talking to people — on the phone, in meetings, or through video calls — to solve problems and connect with the right teams.

My main task is processing information and ensuring the right people are involved in addressing issues. The pandemic shifted many of our meetings to virtual, but the focus on communication remains the same.

With so many AI solutions on the market, how do you decide if a new system is worth implementing?

I have to find a balance between potential benefits, costs, and practical feasibility. At the University Hospital Essen, we’re fortunate since we do much of our research in digitalization and AI. We develop and test many systems internally. We have access to large, high-quality clinical datasets, which allow us to validate the AI tools we create, ensuring they’re accurate and fit for purpose.

When considering external AI solutions, the evaluation becomes more complex. Many AI systems developed outside the hospital environment lack access to clinical data during their development. This often leads to tools that are impressive on paper but struggle when applied to real-world medical settings. Hospitals are unique environments — workflows are complex, patient needs vary significantly, and data must be handled with the utmost security and privacy. Many developers don’t fully understand these dynamics, which can create a disconnect between what the AI solution promises and what it can deliver in practice.

We always assess whether the AI system will integrate smoothly into our existing IT ecosystem. If it can’t, that’s often a deal-breaker, regardless of how innovative or beneficial the technology appears. Most hospitals are not fully integrated with the FHIR standard, which ensures that different systems can “talk” to each other and share data seamlessly. If an AI solution isn’t compatible with the FHIR standard or other core infrastructure, implementing it becomes a major challenge. Integration requires extensive coordination across departments and systems, and it can become expensive and time-consuming.

On top of that, we’re a public institution that adds layers of regulation and bureaucracy to the decision-making process. We can’t just decide to adopt a technology because we like it. All purchases must go through strict procurement processes designed to ensure that taxpayer money is spent wisely. This often means we are less flexible compared to private industry, where equity funds or venture capital can be quickly invested into promising startups. In healthcare, even if a tool shows promise, we must carefully evaluate the needs within our hospital, submit proposals, and adhere to state and national regulations before moving forward.

AI systems can be costly, not just in terms of the initial purchase but also in maintenance, training, and ongoing updates. Any new system must offer tangible benefits that justify the investment. We look closely at the projected outcomes — will this AI improve patient care? Will it streamline operations, reduce workload, and free up time for healthcare professionals? Will it help us lower costs in the long run? If the answers aren’t clear, we typically move cautiously, especially given the financial pressures many hospitals are under.

One more thing: Many systems are overhyped and developed with great ambition but little understanding of the complexities of medical environments. What looks revolutionary in a demo might not work in a hospital setting, where data is messier, workflows are less predictable, and decisions must be made under pressure.

For instance, we’ve seen AI tools that promise to diagnose diseases faster or help manage patient flow more effectively. While those solutions are exciting, the practical question is whether the tool can integrate into the daily routine of medical staff without adding to their workload or complicating processes. If a tool takes more time to use than the existing system or demands more training than we can realistically provide, it won’t be adopted, no matter how advanced it is.

We involve healthcare professionals in the evaluation process. Their insights help us understand if a system is practical, easy to use, and genuinely beneficial. Without their input, it’s easy to make decisions based solely on technical specifications and overlook the reality of day-to-day clinical work.

We also consider scalability. An AI solution might work well in one department or for a small set of patients, but we need systems that can scale across our entire hospital, covering thousands of patients and multiple specialties. If a system can’t handle that scale or requires too many customizations, it can be more trouble than it’s worth.

What are the most promising AI systems for healthcare facilities on the market right now?

Large language models and speech recognition. In the past, we focused on structured data entry, but now, speech technology can capture information more efficiently. For example, a speech recognition system could collect patient-reported outcomes, allowing doctors to focus on specialized care.

AI can provide insights from multiple data collected within the hospital and outside the system, like wearables. No doctor has time to analyze them, but AI systems are capable of checking on the go to see if there are new alarming trends to be further examined. 

There are so many biomarkers that could help to take care of patients better, spot diseases earlier, and monitor health. I believe AI will make use of them. What excites me is including patient-reported outcomes in the electronic patient records. With a layer of AI, we can better understand patient’s health without being overloaded by data.

Regarding policy, what needs to change to make digital transformation in healthcare easier?

The existing regulations are too rigid and often slow down innovation. Many good ideas are stifled by overly complex approval processes and outdated rules that don’t account for the fast pace of digital advancement. We must rethink how we regulate health technologies, especially data protection and interoperability. The balance between ensuring patient safety and enabling innovation is delicate — the barriers are too high for new solutions to be implemented quickly.

We also need a more flexible approach to how patients engage with their health. The current system is designed around traditional, reactive healthcare models, where the patient comes to the hospital or doctor only when something goes wrong. But with digital tools, we have the opportunity to shift toward a more proactive, preventative model. Younger generations are embracing wearables, fitness trackers, and personalized health apps. They’re monitoring their health in real-time, which could help detect issues early. If we could integrate that data more seamlessly into the healthcare system, doctors could have a more complete picture of a patient’s health over time rather than just episodic snapshots.

We can’t rely on the belief that insurance will cover everything anymore and that the doctor is the sole authority on health.

Let’s be honest: Digital healthcare needs financial incentives. Digitalization often requires upfront investment, whether it’s in equipment, software, or training, but the long-term gains — better patient outcomes, more efficient workflows, and reduced errors — aren’t reflected in current reimbursement models. If we want hospitals to fully embrace digital transformation, the financial frameworks must evolve to support that investment.

Digitalization isn’t just about making healthcare more efficient; it’s about improving healthcare for everyone involved.

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