Opinion: Data Driven Decision Making in Healthcare, Quantity vs Quality
Eugenio Zuccarelli • February 6, 2023
2.5 quintillion. That’s the truly astonishing number of bytes (i.e., information) that is generated every day around the world. 2.5 followed by 18 zeros, is a number that most people would have a hard time comprehending.
And every day we generate it faster.
In fact, 90% of all the data we have has been generated in the past two years, meaning that we don’t just have more data than ever, but we keep generating it at a faster rate, generating an amount of data that is almost overwhelming. This is especially true for the Healthcare sector, which accounts for approximately 30% of all the data. It is not difficult to understand why we are at the point where most organizations are confronted with a new problem – how to handle such a large amount of data.
Until a few years ago, one of the major issues faced by companies, and especially executives, was the lack of information. Now we are facing the opposite problem, the information is there but it’s all about how to use it effectively. Knowing how to go from data to decisions, what is usually called “data-driven decision-making”, has become one of the main differentiators of success.
In the twenty-first century, being a leader who knows how to use data to get to the right conclusions is one of the most elusive, but at the same time powerful, concepts in any sector. Even more so in the healthcare sector, where decisions not only affect the health of the business but also affect the health of the people.
As a sector, we have now reached a point when all the necessary components have aligned in our society to better tackle such large amount of data. As such we several essential things in front of us:
- huge amounts of data
- the tools to analyse them (computers with sufficient computing capacity)
- and experts with the right technical knowledge (data scientists)
Despite this, leaders in the healthcare sector are still struggling to move from a mostly qualitative to a quantitative approach. So, what are the main obstacles companies are dealing with?
- Access. Interoperability is one of the most complex issues in the digital health industry. Even though large quantities of data are generated each day, accessing that information easily, quickly and across systems is still extremely complex.
- Information Overload. At times, there is simply too much data and decision-makers have a lot to consider, so they often end up in what’s usually called “analysis paralysis”, preventing them from making an informed decision and ending up relying mostly on their experience.
- Trust. Finally, sometimes, leaders do not have a complete overview of how the data was generated, analysed and the insights produced. They do not fully know if the sources are reliable and if the technical team has a deep understanding of the domain knowledge.
These situations are more common than they might seem. During the pandemic, getting access to data about hospitalizations and deaths was extremely tricky; luckily for these situations panned out. However, to many papers were published every single day, often with conflicting information, resulting in little trust overall in the quality of the reporting and the approaches used to get to the insights.
What is certain, and has been studied for years, is that organizations that are used to leveraging data to drive decisions are on average more successful (measured in profits) than those that mainly make decisions based on intuition.
So, what can we do to transform a company’s executives into data-driven decision-makers? We need to intervene on the culture of the company, trying to profoundly change the organization’s philosophy. This can be done, for example, through courses, especially those aimed at executives. We can educate them on how to go from data to decisions and what the benefits are.
Another technique, which is borrowed from Pharma and Tech companies, is the concept of RCT or A / B Testing. That is the philosophy that every action must be tested first and based on the feedback a decision can be made. This should not just be applied to drugs or tech products but should become more of a high-level approach to prioritize decisions based on feedback.
Finally, one of the most powerful approaches is to favour solutions that are simple and easy to explain, solutions that can be easily interpreted by anyone, because when solutions are understood easily, they have a higher likelihood of being accepted and trusted. Only once we manage to deeply change the philosophy of a company, can we bring it to be a true source of innovation.
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