The amount of healthcare data that exists has grown tremendously over the past 20 plus years due to the emergence of big data, and while its potential is seemingly limitless, data is useless if it’s not actionable. This begs the question: where do we, as an industry, begin? 

Data is a critical tool for healthcare professionals in the shift toward value-based care because it informs clinical and financial decisions that result in high-quality patient care and lower costs. It also enhances patient experience, empowering individuals to make more informed decisions about their health. 

In healthcare, separate from traditional medical records, big data is attributed in part to interoperability and collected from a broad spectrum of sources including wearable devices, smartphones, electronic health records and patient portals. Even social media is considered big data. And as you can imagine, there is a wealth of it. It’s estimated that by next year, every individual will generate roughly 1 gigabyte of healthcare data per day. With an estimated compound annual growth rate (CAGR) of 36 percent over the next five years, it’s nearly impossible to fully grasp the sheer volume of data that continues to be created and at our disposal. 

Volume and variety are characteristics by which big data is commonly measured. It’s also defined by velocity. The breakneck speed with which data is being created and flows necessitates it is processed quickly. Considering these three qualifiers in combination, the gargantuan task at hand begins to come into focus. 

In keeping with the theme of our series on how to make digital doable, we’ve established five pillars that enable data simplicity to help you and your organization understand how to approach your data journey. 

Before we dive in, it’s important to note that creating a data-driven culture begins with establishing and receiving buy in on your why. Before an organization conducts a deep dive on data, it needs to cement its business goals and determine how the use of data will add value and help achieve its desired outcomes. 

Architecture

Data moves around any given healthcare organization and its network of partners upwards, downwards, sideways and every which direction in between. While the visualization of the way data flows may resemble the board game Chutes and Ladders, in order for data to get to the appropriate individual or parties at the right time, there must be an infrastructure in place to control it. 

To create a roadmap for going forward, we must understand the current state. Organizations should assess the systems they have in place to determine if they interface and complement each other while having little or no capability overlap. This is an opportunity to identify inefficiencies and make system changes to fill gaps in information and ensure inbound data is robust. 

With the right tools in place, to eliminate silos and ensure data is easily accessed, the architecture should be established as a data lake. A data lake is a centralized storage point that pulls in analytics and data in real-time. To ensure the included unstructured data is searchable and the data lake is a help and not a hindrance in information retrieval, it should be organized before it’s filled. Establishing data categories, tags and characteristics for each at the outset will streamline file organization and prevent the lake from regressing into a black hole. 

Rapid And Scalable Ingestion

Data ingestion is the process of taking in data from internal and external sources. While the nature of some businesses only requires this be done in batches at established intervals, the urgency of decisions in healthcare, particularly those of a clinical nature, necessitates the immediate insights real-time data collection provides. 

One of the biggest challenges organizations face with data ingestion is speed because the data cleansing process is intricate and time and resource-intensive. Before it can be processed and eventually make its way to the data lake, disparate data must be converted to a common format. Then, as it flows, it must pass through a series of checkpoints including tests of its security. It must also be able to handle increasing amounts of data received from an innumerable number of sources. 

Governance

Simply stated, data governance is the management of data within an organization. With a strong data architecture in place, governance ensures a chain of trust is created so data producers and data consumers are confident it is handled and used appropriately. More specifically, the American Health Information Management Association’s (AHIMA) definition of data governance is an organization-wide framework for managing health information throughout its lifecycle. 

Putting a structure for data management in place assigns responsibility and creates accountability. When executed well, it gives providers and administrators the right information at the right time in the right format.

Establishing governance is arguably the most straightforward and easy to implement step in making data usable, but its significance cannot be overstated. You can read about emids’ approach to data governance, capabilities and expertise here

Technology

We’ve addressed the need to thoroughly assess data for its quality, completeness and compatibility, but not how to go about it. The answer lies in using a combination of proven technology and manpower. 

Data integration is a foundational step in making data useable. Before data is integrated, it must be standardized. Over the past two decades, emids has honed its unique approach to healthcare data standardization and helped countless organizations improve their processes. 

Using the right tools from an experienced partner with the oversight of skilled and experienced data professionals will help ensure you’re driving intended outcomes.

Skills And People

Picture a conveyor belt that continues to increase in speed, sending product down the line at an unrelenting rate. If healthcare data is the product, we must immediately become adept at how to efficiently and effectively collect, manage and store the data, and also how to staff the production line.

Harvard Business Review called data scientist the “sexiest job title of the 21st century” in 2012. At the time the proclamation was made, the profession was almost unheard of. Now, openings for data scientists and other mid and senior-level analytical roles are abundant and expected to continue to grow. The World Economic Forum’s 2018 Future of Jobs Report found 85 percent of the world’s largest companies plan to expand their use of big data analytics by 2022. 

While the desire for professionals who are able to monitor, analyze and validate data is high, the existence of individuals with the right skill set to fill vacant roles is comparatively low. The speed with which technology evolved and data became available surpassed available education, creating a significant gap between supply and demand.

Combined with the limited number of professionals equipped for data jobs, the integral role they play in data governance and organizational success must not be overlooked by hiring managers and administrators. 

The Bigger Picture

Harnessing data’s power to benefit your value-based care efforts and ultimately help achieve the Triple Aim may seem daunting, but the challenge is not insurmountable. Following and embracing these five easy-to-digest components will provide a clear path to success.

Keep an eye out for our final blog in this series where we’ll address convergence and connect the dots between strategy, design, experience and data. 

Nilesh Patil, chief data strategy officer, oversees Data Management and BI practice at emids. He is a focused business and technology expert with extensive experience developing enterprise information technology strategies and road maps, information architecture, standardized business metrics and analytical infrastructure. This comprehensive technology is designed to deliver vital information to industry organizations in innovative and insightful ways. Nilesh also serves as a valued advisor to multiple healthcare CIOs, CTOs and CAOs on their organizational initiatives, and plays a crucial role in assisting with developing actual blueprints and executing implementation. His skillset as a respected innovator and technology guru lends itself well in leading emids’ platform to help healthcare organizations realize their diverse analytics visions. Be sure to connect with Nilesh on LinkedIn.