25 November 2020

Clinical decision support for prostate cancer care in the age of information overload

Philipp Grätzel von Grätz, MD speaks to Professor Helge Seifert, MD, Head of the Department of Urology at University Hospital Basel (USB) and Christian Wetterauer, MD, urologist at USB about how they are using Artificial Intelligence and smart data integration as a solution to the challenge of providing evidence-based prostate cancer treatment in an age of multidisciplinary care and accelerating data accumulation.

“Every patient has the right to be treated according to the most recent evidence-based recommendations,” says Professor Helge Seifert, head of the Department of Urology at University Hospital Basel (USB). However, this is a challenge in an age of exponentially accelerating data accumulation, resulting in an overload of information for doctors. In an effort to provide a solution to this challenge, USB has recently established a pilot project to evaluate a clinical decision support system from Siemens Healthineers to provide assistance with prostate cancer care. This is enabling urologists at USB to live up to the dictum of providing the best evidence-based care for their prostate cancer patients.

Urologists at USB treat around 200 patients with newly diagnosed prostate cancer each year. They also assess hundreds more cases presented at multidisciplinary tumour boards (MTB) by colleagues from other hospitals nearby and by ambulatory urologists from both Switzerland and Germany.

Offering evidence-based treatment to every prostate cancer patient may sound straight-forward, but in reality, it is not, according to Prof. Seifert.

“We see big differences in care standards in different institutions,” he says.

An important reason for these variations in clinical practice is information overload, says Christian Wetterauer, MD, senior urologist at USB: “The amount of data that we have to take into account for our clinical decisions in prostate cancer patients is increasing exponentially. This makes it very difficult for many urologists to stay up to date.”

Information overload can be especially difficult to handle for smaller institutions with fewer staff than university hospitals. It is also a challenge for a centre of expertise like USB, says Prof. Seifert, since the weekly MTB conferences take longer and longer, and preparing patients for the MTB becomes ever more time-consuming. “Our MTBs take place once a week, and they exceed core working time regularly. We discuss on average 15 to 20 patients.”

Evidence-based, patient-specific support

To address the challenges posed by complex and, at times, overwhelming amounts of data, urologists and IT specialists at USB have entered into cooperation with Siemens Healthineers to become the global pilot site of the first CE-certified decision support solution for clinicians. AI-Pathway Companion Prostate Cancer aggregates and integrates individual patient data from various sources and creates a personalized disease-specific model for each patient. With the help of Artificial Intelligence (AI) techniques, the digital solution also provides state-of-the-art decision support along the clinical pathway in accordance with the evidence-based guidelines of either the European Association of Urology (EAU) or the National Comprehensive Cancer Network (NCCN). For example, thanks to AI techniques, radiology and pathology results are correlated and visualized. A patient-specific risk assessment is provided according to guideline recommendations. The patient is mapped along the clinical pathway and, according to the individual situation, relevant diagnostic steps or recommended treatment options are provided. All this is presented in a way that is intuitive to practicing clinicians.

“A big strength of this project is that clinicians have been involved in the development very early on. The software really mirrors the specific requirements of routine clinical users,” explains Dr Wetterauer.

Use case: Multidisciplinary tumour board

An important use case for the new solution at USB is the aforementioned MTB. Until now, it has taken between 5 and 12 minutes to prepare a patient for the MTB. Discussing each individual case in the MTB takes about 5 minutes on average. Using AI-Pathway Companion both for patient preparation before the MTB and for patient presentation during the MTB, much time will likely be saved.

“We don’t have to put together the information we need manually before an MTB anymore, because data aggregation for each patient happens automatically. This should reduce preparation time considerably, ideally to close to zero,” says Dr Wetterauer.

Ultimately, tailored recommendations for individual patients based on the most recent guidelines and clinical trial results will translate into improved outcomes.

“A solution like this will lead to better quality of care,” says Prof Seifert. “It will be especially valuable in peripheral hospitals and smaller medical institutions with a high case load.”

He adds: “We won’t be able to offer patient care in the future without integrating evidence-based knowledge and patient data.”

The urologist in the driving seat

At USB, AI-Pathway Companion will soon be used and evaluated during the MTB.

“Colleagues are really excited when they see the new software solution for the first time,” says Dr Wetterauer. “Something like this has not been available so far.”

What urologists like about the approach, apart from the clearly arranged user interface, is that it is not about replacing doctors.

“The solution uses data integration and AI tools to give doctors a helping hand and relieve them of routine tasks. This is much appreciated,” he adds.

“It is also what patients expect when they come to be treated for prostate cancer,” says to Prof Seifert. “Patients want to be treated in line with available standards, but they also want individual recommendations by their doctor, and they want them face to face. Software definitely won’t replace the doctor. But it helps to make well-informed, evidence-based recommendations, and it can make different treatment options more transparent.”

The author
Philipp Grätzel von Grätz is a medical doctor
and journalist specializing in healthcare, science,
and technology. He is based in Berlin.