Successful healthcare data strategies are no longer built around a single vendor, nor on standalone or on-premise solutions. To maximize the return on their data, organizations must leverage new standards and best practices. Simply having more data is not good enough.
Healthcare enterprise buyers: payers, providers, pharma, and digital leaders at those organizations, find themselves in a world of cloud transformation, interoperability, data exchanges, and data breaches. In their efforts to remain relevant and deliver top-notch solutions, these organizations often grapple with a bewildering array of buzzwords and high cost “digital transformation” initiatives that forget to meaningfully transform anything.
Many healthcare organizations are adopting strategies to stay abreast of the true trends beyond the buzzwords, but few are doing it right.
You Need a Healthcare Data Strategy.
A comprehensive data strategy is essential. Without one, organizations risk perpetuating technical debt and falling into the sunk cost fallacy. How can an organization shed unprofitable investments, abandon detrimental habits, and transform their healthcare data strategy into a successful Healthcare Data Value Chain?
It begins with intentional system architecture. Untangle Health excels in crafting healthcare data strategies that fulfill organizational and financial objectives. We identify unmet needs and market opportunities and translate them into actionable strategies and solutions for enterprise buyers.
When you architect with intent, you align your systems and data infrastructure to your key business objectives: ensuring no technology exists for its own sake. Additionally, you implement stronger data protection measures, better safeguard health information, and ensure a safer and more transparent healthcare ecosystem.
What is a Healthcare Data Value Chain?
A Healthcare Data Value Chain is an intentionally-designed and objective-aligned way of wrapping your arms around data infrastructure. While market terms such as “data fabric” and “data platform” encompass many key technical requirements of an effective Healthcare Data Value Chain, they do not focus on the value provided. Data infrastructure is a means to an end, not the end.
The Healthcare Data Value Chain translates data into actionable information and high-value outputs. While the specific components and vendors may change among organizations, the Healthcare Data Value Chain is foundational to operating a data-related business.
While helpful to view as a sequential chain as per Figure 1, in practice this functions more as a continuous cycle within an organization that is part of a connected ecosystem. (See Figure 2)
For the most part, healthcare no longer operates in a nightly or monthly batched cadence. Instead, you find real-time access and queries requiring low latency and highly usable systems. After all, as the heart of a technical organization, the data value chain does more than just connect that organization’s systems, it powers the flow of data within the connected healthcare ecosystem.
As we support organizations moving through their healthcare data strategies, we help them move from a focus on “taking” and “getting” data to instead focus on the value that should be returned to the market. This builds long term defensibility, with other market players depending on your outputs.
To accommodate this more holistic perspective, we compiled our Healthcare Data Value Chain in an ecosystem view by adding additional encompassing layers to include “Market Engagement” by healthcare stakeholders and “Customer Engagement Layer” for patients, members, and other customer types.
Components of a Healthcare Data Value Chain.
Get Data
You cannot have a data value chain without inbound and outbound data. Whether based on compliance drivers, business drivers, or visibility drivers, receiving and sharing data is a modern healthcare must. To prevent waste, each of these system-to-system connections, participation in HIEs or interoperative networks, and additional data partners must ultimately be grounded in the organizational data strategy.
Compile Data
With the volume of data available, the market’s current concerns and priorities are centered on data quality, cleansing, and uplift. Due to the complexity of the healthcare ecosystem, most modern organizations exchange data with thousands of partners. Compiling data transforms formats (HL7, FHIR, API, x12, XML, JSON, CCDA, CSV), unifies leveraging identity tools (EMPI, HMDM), and finally enriches utilizing outside sources.
Compilation ensures data from outside sources match internal standards and synchronize with internal databases for seamless reporting, analytics, and workflows.
Store Data
Healthcare organizations now understand they are not cloud service providers. We see this as many organizations transition away from on premise and self-hosted systems. The cloud models allow them to avoid playing the capital expense hardware game, instead opting for consumption-based operating expenses. However, there are still significant choices to be made for how and where data are stored.
Highly accessible data needs a low latency, high-performance cloud infrastructure to prevent read/writes and data exchange from getting in the way of a business’ needs. The database schema and format are foundational choices. Many of our partners are building with Fast Healthcare Interoperability Resources (FHIR) in mind, but there are still different approaches, with FHIR-first or a FHIR-facade being two common examples. But which is better for your organization? Consider first how your partners send and receive data. This will help determine the most appropriate data structure to align with your and your customers’ objectives.
Analyze Data
The goal of analyzing data is to translate them into insights, not just make more reports. Healthcare is filled with analytics, AI, machine learning, reports, dashboards, visualizations, and other tools that enable organizations to summarize their data. It’s crucial for organizations to focus on “why” they are analyzing data to not get stuck on the “what,” which can result in analysis paralysis or just analysis for analysis’ sake.
Why are you storing these data and how are you measuring impact?
The “what” focus also results from when an organization is stuck on their own key performance indicators (KPIs) without considering their customers. Instead, consider looking at customer performance indicators (CPIs).
Solely focusing on KPIs can lead to further disconnects between an organization and its customers. Incorporating CPIs, such as patient wait time, prior authorization turnaround time, claim filed to patient payment requested time, and referral to scheduling time, ensure insight into the metrics patients and members truly care about.
Deploy Data & Insights
Your organization’s value and differentiation are derived from the data and insights you share with your partners. These demonstrate your unique perspective and contributions to the healthcare ecosystem.
As the market transitions away from dashboards and reports and heads towards embedded insights and automation, valuable data are ingestible data. Ingesting data requires the right partnerships to summarize and incorporate those data directly into processes or decisions. This is another area our partners get stuck – understanding why partners are requesting data can lead to visibility into new opportunities to work together. Effectively deploying data and insights can deepen partnerships, improve care delivery, improve patient outcomes, retain customers, and help defend your market position.
Secure & Protect Data
Data breaches are costly, cause a loss of efficiency, and damage your brand. They can also greatly impact patient care. Securing and protecting data is the foundation of the health data value chain: without a secure system any data strategy will ultimately fail.
When thinking about protecting data, ensure you are covering your data both in transit and at rest. Don’t rest assured that yesterday’s best practices are still good enough. For example, a two-legged token strategy could lead to exposure points; our successful partners recognize that role-based access control ensures both AuthoriZation and AuthenticatioN, ideally configured to the individual or role. You also need a resilient infrastructure surrounding your cloud environments and web applications.
The Market Engagement Layer
The market engagement layer surrounds an organization’s Healthcare Data Value Chain to provide the context and reminder that it lives within a connected ecosystem. Every healthcare organization is part of this ecosystem, and data received from partners often come with an expectation of something in return.
When defining a data strategy and implementing a Healthcare Data Value Chain to execute that strategy, the market-oriented approach ensures we do not stray from market needs and requests.
When organizations operate in an insular way, with internal product and technology teams defining roadmaps without market input, we see those organizations lose product market fit, increase churn, and struggle with sales. Instead, organizations that digest market feedback (directly, from sales, and from customer success) and constantly realign products and services to meet market needs (at least on a quarterly basis) retain or grow their market position by continually ensuring their infrastructure provides “Value.”
The Customer Engagement Layer
Ultimately, we surround our Healthcare Data Value Chain with the Customer Engagement Layer. This layer encourages organizations to deepen their understanding of their customers, whether patients, members, consumers, clinicians, or other stakeholders. Unsurprisingly, this enables organizations to better serve their needs. No organization can exist without customers, and this ensures end-customers are placed in priority determination.
As alluded to earlier, here is where the CPIs or Customer Performance Indicators come into play. Instead of organizations focusing on how they evaluate themselves (KPIs), how would those organizations’ customers evaluate them? For example, prioritizing cost savings (a potential KPI) could conflict with patient scheduling satisfaction (a potential CPI) if the cost savings were achieved by reducing the refresh rate of open appointment slots from hourly to weekly in order to save on cloud expenses. The reduction in refresh rate could directly impact customers, as savvy patients may learn to log in first thing Monday morning to grab optimal slots, which could affect overall patient satisfaction with the scheduling options.
The Customer Engagement Layer ensures organizations do not lose track of the customers they serve.
Our Role in this Space
Untangle Health developed the Healthcare Data Value Chain to enable healthcare organizations to visualize the systems and processes that will better serve their customers. By understanding and investing in mastery of the individual components, enterprise healthcare organizations can avoid the pull of monolithic partners and platforms which claim mastery over each component, despite not excelling across the full spectrum. On the flip side of that, Untangle Health serves market share and capability-leading software companies across the individual categories to better fulfill a true healthcare data value chain for their customers.
As experts in assessing data ecosystems, rearchitecting platforms, evaluating partners, and navigating the complexity of today’s healthcare market, we know how tangled these layers can get. Our role is to untangle the difficulty of navigating the healthcare industry, separating the marketers from the executors who can actually deliver what they sell.
Our company “untangles” healthcare and technology, ensuring sellers effectively communicate the value of their products and services, and enabling buyers to develop the optimized healthcare data strategies that yield better clinical, operational, and financial outcomes.
