Helping oncologists manage complexity

Clinical decision support tools will help oncologists manage complexity

Making treatment decisions is a tough choice for oncologists: a therapy might save or significantly extend one patient’s life but not deliver the desired outcome for another patient. Reaching this decision involves weighing a variety of data – from clinical trials to the patient’s medical background – and with the advent of more personalised oncology, the sheer volume of data that needs to be considered is growing exponentially.

When we speak to oncologists, the most consistent feedback we hear is that the complexity of information is increasing and we need support to access it faster, more efficiently and in a more targeted manner.

Consider how precision oncology will fundamentally change the way cancer patients are treated. First, instead of looking at the organ of the cancer’s origin only, doctors are going to pay more attention to the patient’s genomic characteristics and the medical history when deciding on the most effective cancer therapy. With next-generation sequencing technologies now broadly available, it is easier than ever before to understand the genomic variants of a cancer. We expect many new therapies based on the molecular profile of a tumour to come to the market in the next three to five years; for some indications it could be two or three times as many therapies compared to today.

All the ‘new’ data that is becoming available is driving therapeutic decisions in oncology.

It is therefore legitimate to ask: could oncologists be overwhelmed by the amount of data available to them? The short answer is: if limited to only today’s standard tools and practices, if they aren’t already, they will be very soon.

In the near future, oncologists will need to embrace digital solutions, such as Clinical Decision Support (CDS) systems, to manage the complexity. Based on algorithms and extensive computing power, CDS tools can structure and filter clinical data to help physicians make more informed treatment decisions faster.

However, according to our recent research with 130 oncologists from the US and Europe, only one fifth of oncologists routinely use CDS tools today. We expect that number to significantly increase and CDS to become a standard tool for tumour diagnosis in the coming years. Furthermore, we believe that these tools will contribute to the breakthrough of precision oncology as they help physicians choose individual therapies for patients over standard treatments and do so with a reduced margin of error.

The main objective of CDS tools is to structure and filter information so the physician will only have to analyse data relevant to a specific case. Depending on the task – either diagnosis or assisting in treatment decisions – the way the CDS tool supports the physician is different. In the first case, CDS are significantly reducing the risk of human error by ‘spotting’ things even the most experienced oncologists might overlook or at least need a second opinion for.

When it comes to deciding on the right treatment, CDS is not replacing the physician’s authority but rather provides and classifies relevant information that allows the specialist to make an even better and more informed decision. For example, CDS tools display the appropriate clinical evidence. As a medical director at a breast cancer centre points out: “These recommendations solicit our thoughts and I feel like we can be better doctors and can deliver better, more precise care.”

This feature becomes even more important as the number of possible therapy options increases once oncologists start considering genomic profiling for their patients. One medical centre assistant professor argues that, as treatment options are “going to get more granular and more detailed, it’s good to have a lot of treatment support”. This allows oncologists to use non-standard treatments with more confidence or focus on the findings of a clinical trial for a particular sub-population.

So why isn’t it used more now?

The complaint we’ve heard from physicians is that too much useless data is thrown at them and that CDS tools aren’t always very good at understanding the context in which decisions need to be made by physicians. A lung cancer specialist illustrates this perfectly: “If you have a patient who’s a smoker, I get a pop up saying ‘Did you screen them for lung cancer?‘ I am a lung cancer doctor. All my patients have lung cancer.”

One-size-fits-all CDS tools simply ask too many questions or require too much effort by the physicians to get the user experience right. Instead of reducing complexity and saving time for the physician, one-size-fits-all CDS tools have the opposite effect in reality: they require physicians to filter much more information themselves as they need to carefully consider which click is important and which is not. The more the physician has a role in triggering the right information, the less likely the physician will use the tool – it needs to happen in the background.

But it will – with improved algorithms and more real-world data being fed into these tools, CDS will become even more accurate in the future. Consequently, CDS tools will become the standard application in diagnostics. They are more likely to get the diagnosis 100% right compared to even the most experienced oncologist who might only be at 99%. CDS tools need to improve by requiring less front-end physician input than they do now.

To be clear, CDS systems are in the end just tools. The most effective therapy might not always be the best treatment option for the patient. Quality of life, for example, is a dimension that is hardly considered by algorithms although it is a very important aspect for patients who are going through cancer therapy. It is the patient and the doctor deciding together what the right approach is in an individual situation. But arming both the patient and physician with the best possible information to help make that decision is crucial.

To learn more about what oncologists say they need, read our full research report The Future Is now: How to Drive Precision Oncology

Boris

Dr Boris Bogdan, medical doctor by training, is a partner at Accenture Switzerland and globally leads Accenture’s Precision Oncology and Personalised Healthcare Practice. His passion is to envision the future of healthcare. Prior to joining Accenture, Dr Bogdan was an entrepreneur and part of McKinsey. He has published numerous publications on the pharmaceutical industry and is author of the books Valuation in Life Sciences and Medrevolution.

Dr Sandra Dietschy-Künzle is a senior principal in Accenture’s Life Sciences practice with more than 10 years of experience in the healthcare industry and in-depth expertise on drug development in the field of oncology. Prior to joining Accenture, Dr Dietschy-Künzle held positions at a biotech company and has worked as an equity analyst for the healthcare sector. She has supported the development of oncology assets from early research into late clinical development. She holds a PhD in Natural Sciences from the University of Zurich.

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. We combine unmatched experience and specialised capabilities across more than 40 industries — powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. With 509,000 people serving clients in more than 120 countries, Accenture brings continuous innovation to help clients improve their performance and create lasting value across their enterprises. Visit us at www.accenture.com

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Clinical decision support tools will help oncologists manage complexity

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