Data has become the cornerstone of decision-making and organizational growth. The ability to harness and analyze vast amounts of data has the potential to revolutionize patient care, streamline operations, and enhance the overall performance of healthcare organizations. However, achieving this potential requires more than just having access to advanced data analytics platforms. It demands a well-structured approach to data governance and a clear understanding of the specific needs of each stakeholder in the healthcare ecosystem.
This article explores key insights from Unlocking Big Data, Episode 5 by industry experts Chad Konchak, AVP of Clinical Analytics at NorthShore University HealthSystem, and Michael Meucci, CEO of Arcadia. They share their perspectives on the critical functionalities required for healthcare organizations to achieve very satisfied ratings from their analytics platforms.
Data analytics in healthcare serves a diverse range of stakeholders, including financial personnel, clinical staff, researchers, and partners. As Michael Meucci points out, the challenge lies in catering to the needs of this wide array of users and connecting the various analytics efforts cohesively.
To achieve this, healthcare organizations must adopt a comprehensive data governance framework that spans across the entire organization. Without a single definition of data governance, analytics efforts may become disjointed, leading to suboptimal outcomes and dissatisfaction with the platform's performance.
Meucci emphasizes, "You need to be able to evaluate each of those use cases and think about how you create that end-to-end vision of how you use analytics to drive the business forward and connect the different analytics efforts. If you don't have a single definition of data governance across the organization, you're going to create a bunch of swirl."
This lack of unified data governance is a significant contributing factor to the dissatisfaction experienced by users with their analytics platforms. Chad Konchak highlights the importance of providing quick and accurate answers to users' questions. In a complex healthcare setting, stakeholders often require timely information to make informed decisions.
However, the lack of centralized data and standardized governance can lead to disparate answers from different teams, causing confusion and a lack of trust in the data. Therefore, the ideal data analytics platform should enable users to access information swiftly and consistently, empowering them to drive data-driven business decisions with confidence.
Konchak further explains, "They ask one group in one area and it doesn't happen very fast, they don't like the answer, or it's not very good. So then they ask a different group, and now they get different answers." The lack of a cohesive and reliable analytics platform leads to uncertainty and dissatisfaction among users.
The conversation between Meucci and Konchak emphasizes that the problem with analytics platforms isn't solely rooted in technology; it's about people and processes within healthcare organizations. Just like health literacy is essential for patients, data literacy is critical for healthcare professionals to make the most of analytics solutions. Establishing a common data governance structure across the organization becomes vital to ensure the accuracy and reliability of data-driven insights.
As Meucci suggests, vendors must go beyond promoting their technology and invest time in understanding their customers' data governance structures, analytics team configurations, and insights dissemination processes. This approach will foster a supportive relationship between vendors and healthcare organizations, avoiding conflicts that may hinder the platform's effectiveness.
Meucci emphasizes, "We need to improve data literacy. Just like we need healthcare consumers to improve health literacy, we need folks to understand that you need a common structure for data governance across an organization." This emphasis on data literacy and governance demonstrates the importance of a collaborative approach in healthcare analytics.
Konchak reinforces this perspective by emphasizing the importance of centralizing data and governance while building skilled teams before implementing sophisticated technology. Even the most advanced analytics platforms may fall short if the organization lacks a robust governance program and competent personnel. To achieve successful outcomes, healthcare organizations must focus on aligning technology, people, and processes effectively.
Konchak adds, "I don't think the problem is with the technology and the platform. There are so many great platforms out there. There's incredible technology. It's with in organizations not having the other, right, people and process." This acknowledgment highlights the need for organizations to prioritize foundational elements before investing in advanced analytics technology.
The quest for the holy grail of data analytics in healthcare begins with prioritizing process and people over technology. Konchak stresses that successful analytics programs involve translating business problems into meaningful questions that can be addressed by data scientists or analysts. The conventional method of submitting requests to IT and waiting for data to be returned is no longer sufficient for the complex challenges healthcare organizations face.
To succeed, vendors should move away from pushing their technology and instead engage in conversations centered on solving specific problems. By understanding the unique challenges of each healthcare organization, vendors can tailor their offerings to deliver more effective and meaningful analytics solutions.
Meucci adds, "If Chad calls me and says, 'I want to talk to you about analytics solutions,' I'm excited. I want to have a conversation with NorthShore. I want to talk about how we can help them. But it doesn't start with me coming in saying, 'OK, here's who we are. This is what we do, and this is what we can do for you.' It needs to start with, 'Tell me where your opportunities are. Where are your challenges?'" This collaborative approach puts problem-solving at the forefront of the conversation, ensuring that analytics solutions are tailored to the organization's specific needs.
Healthcare data governance plays a pivotal role in determining the success of data analytics platforms. The ideal solution involves creating an end-to-end vision of analytics usage, standardizing data governance, and fostering data literacy within healthcare organizations. By prioritizing people and processes over technology, organizations can unlock the full potential of data analytics and drive positive change in the healthcare ecosystem. Vendors, on the other hand, should actively engage with their customers to understand their specific challenges and tailor their offerings accordingly. The holy grail of data analytics is within reach, and it starts with a data-driven, collaborative approach between all stakeholders in the healthcare industry.
View more of the Unlocking Big Data series presented by HIMSS.
Check out the Unlocking Big Data companion podcast below or on Apple, Spotify, and Google.