The power and potential of data cannot be overstated. It’s the building block of our work here at Think Research (and our modern society as a whole). With rapidly increasing amounts and sources of personal health data, the future of our healthcare system truly lies in appropriately harnessing the transformative potential of data and analytics.
Wanting to learn more about this vital resource, we recently sat down with Allan Brand, our Senior Data Specialist at Think Research. Allan has spent his career working with data and analytics, from publishing research to supporting foundational data collection and analytics programs. His current role at Think Research is to help manage and leverage data to support our partners through improved system integration, data delivery, or insightful analytics and reporting to drive evidence-based decisions.
Why is data so fundamental to healthcare?
AB: Healthcare data can impact multiple dimensions of patient care from personalized medicine and clinical decision support to operational and strategic planning. Using the right data to deliver the best practice for patients, and iterating off that data to maintain quality delivery is rapidly becoming the new standard.
As data utilization becomes commonplace across both private and public sectors, leveraging evidence-based health analytics for strategic decision making is quickly becoming a multi-billion dollar industry.
What’s a common challenge that organizations face when it comes to leveraging data?
AB: With so much data being created across fragmented systems, companies are seeing the value of their data lost due to system fragmentation, a lack of resources, and poor data quality. With advanced methodology, ‘black box’ solutions that take in messy, low-quality data and provide a result with no justification will never have complete buy in. These kinds of solutions cannot be a substitute for effective data management and analytics storytelling. Understanding why decisions are made, at least at a broad level, will always need to be a part of any solution.
Helping get our partners up to analytics speed is a key objective of ours. Rising healthcare costs, increased patient needs and shrinking budgets cut into already stretched analytics resources. While meaningful data can help these systems more effectively optimize their resources, the time and effort to develop these systems must be similarly meted out of an already strained budget. Part of our work is to make sure they are getting the most out of their collected information.
In your experience, what is required to fully take harness the data that your organization generates?
AB: Managing and interpreting data requires integrated dedicated clinical and data expertise to build meaningful stories out of meaningful data. Many companies are willing to help provide analytics platforms, but providing comprehensive solutions means leveraging multiple types of expertise to derive the most value from those platforms. It also means fostering partnerships to share data and skillsets where possible, and creating the space for meaningful impact.
Managing and interpreting that data, particularly in the context of big data assets, presents its own challenges. The potential impact of clinical data capture and use in our Canadian healthcare ecosystem has already been well described and delivering actionable data to patients and healthcare partners should be a cornerstone of any data-based healthcare partner.
What’s a useful way to measure your organization’s data proficiency?
Analytics can be measured against system maturity scales, but users should be not be stymied or feel like they are incapable of doing amazing work if they “score too low”.
Analytics maturity measured through data comprehensiveness will always be a moving target, and cannot be used as the metric to capture what useful data looks like. Useful data cannot be a hypothetical construct, but must be based on what is available and in use now, keeping in mind what’s coming down the road. That does not mean that better data should not be strived for, but only that it should not be used as an excuse to limit what is possible now.
I would say it’s more important to have good governance and maintain good data quality to maximizing data value instead of being overly preoccupied with vying for a score through using low quality data to maximize an analytics score as opposed to deliver the best value from your data.
What are some tools that can help with leveraging data-driven insight?
AB: There are a variety of tools to manage and build analytics solutions available to consumers, and at Think Research, we have tools that we use here for data management, data science, and dashboarding. Each company is different, and it’s about understanding what drives your data needs to determine what tools you would use.
I’m obviously a big proponent of our Spotlight analytics platform, as it’s something we’ve worked hard to develop, and something that I think really helps our users. We work hard to provide the knowledge to make our health system better, and Spotlight is our way of monitoring and providing that feedback in real time, helping clinicians, hospitals, and users understand what’s happening at a glance.
It will be fascinating to see how this interesting field evolves over time. Stay tuned as we share more perspectives on data and analytics in further blog posts.