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Empowering Precision Oncology: Leveraging digital solutions to facilitate molecular tumour board meetings and patient care management

 

Dr. Huey-En Tzeng shares her experience setting up a Molecular Tumour Board (MTB) at Taichung Veterans General Hospital (VGH), and the advantages of using digital solutions to faciliate the MTB meetings

Introduction

My name is Dr. Huey-En Tzeng and I am a medical oncologist at Taichung Veterans General Hospital. I also serve as the CEO of the Precision Medicine Center, where I oversee precision oncology and lead the MTB. My journey with the MTB started in 2017 at Taipei Medical University Hospital, where Professor Yen Yun established Taiwan’s first MTB, and I was a key member. In 2022, I moved to Taichung Veterans General Hospital. With the support of the superintendent Professor Shih-Ann Chen, I established the MTB at this hospital as well.

What is the vision of cancer care at Taichung VGH?

Taichung Veterans General Hospital is the National Medical Center in Taiwan, treating five to six thousand newly diagnosed cancer patients each year. In 2019, the hospital established the Precision Medicine Center, which integrates clinical practice, tumor biology and bioinformatics to offer the latest in cancer NGS testing. In 2022, we joined the National Health Research Institutes’ Precision Oncology Demonstration Project, providing comprehensive genomic profiling (CGP) testing for 2,000 cancers patients across Taiwan. As of April 2024, we have already enrolled 440 cases. We have also assembled a team of molecule experts and hold MTB meetings every two weeks to explore and discuss the optimal treatment plan which can benefit the most to our patients. Additionally, we aim to build a robust database to accumulate real-world data and establish a large-scale precision medicine repository.

What are the challenges encountered in precision oncology diagnosis, treatment decision making and progression monitoring in your country/your institution?

Starting in May this year, the government began to reimburse NGS testing, including CGP. Additionally, hospitals are now required to establish MTB and have to submit relevant data reports to national health insurance database. CGP provides a comprehensive analysis of cancer genes, but it brings significant challenges because of the large and complicated number of the mutation variants. These different mutation variants need input from multidisciplinary experts. However, for hospitals without experts, this is a new and difficult area. Especially in terms of data management, there is an urgent need to use standard data formats and build systems that can effectively use cancer database for clinical decisions and patient outcome monitoring.

Why were MTBs important in your institution? What were the challenges you encountered in conducting oncology MTBs in your institution?

There are four objectives to set up MTB in our hospital. First, it provides consultations, including testing options, hereditary cancer tests, and report interpretation. Second, it discusses the treatment plans. Third, it refers patients to clinical trials. Lastly, the MTB plays an educational role. However, traditional MTBs rely heavily on manual effort to collect data from various sources. When we review cases, we need to look at both the genetic test mutation variants and the patient’s clinical data. This data is stored in different HIS systems, making it difficult to keep everyone on the same page. As a result, we spend a lot of time organizing discussion materials, and the conclusions from these discussions are hard to store in the HIS for the attending physicians to refer at any time. In addition, we follow up with patients every six months, so managing the MTB patient list is also very important to us.

How have digital MTBs been implemented into your institution for cancer management?

After adopting MTB digital platforms, both genetic and clinical data can be stored in the same platform. In terms of workflow, physicians just simply need to fill in the patient’s medical record number and submit it, and I will receive the submission. At the same time, the platform will initiate automated data entry. Therefore, I can quickly review the cases that need to be discussed in the MTB on the digital platform and further schedule dates for MTB discussion. Even if the MTB members are in different locations, they can edit discussion data on the platform at any time before the MTB. In the discussions of the MTB clinical trials are important information. The platform integrates external clinical trial information and can match possible clinical trials and the latest journal literature based on the patient’s genomic profiling. In addition, the decision-making process of the discussions can also be stored completely on the platform, assisting us in cancer patients management and follow up.

What is your experience using digital MTB platforms? How have digital MTB platforms streamline your process?

Using a digital MTB platform, the biggest benefit is that it automates the collection of genetic and clinical data. MTB members can look at patient level data simultaneously, making preparation faster. It also improves patient management and follow –up across specialties. In the past, the information for each step, from physicians requesting case discussions, to reviewing cases, to preparing slides, and writing discussion records – was scattered. The digital MTB platform not only helps us digitize the process but also streamlines it. I can say it saves us a lot of time and workload.

What advice would you give your fellow colleagues to incorporate digital MTB platforms into their clinical or institutional practice?

Implementing the digital MTB platform requires effective change management and the ability to endure initial challenges. I would say it requires top-down decision support to sustain it. Once we overcome this phase, we can fully appreciate the value the MTB platform brings. Additionally, during the implementation phase, integrating clinical and IT capabilities is crucial. While IT skills are fundamental, understanding clinical processes and needs is indispensable. Last but not the least, automating data integration isn’t something that happens overnight; it should align with clinical milestones and be completed by phases.

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