Healthcare leaders face increasingly complex data needs—driven by both recent legislation and their own goals to improve outcomes. And requirements for reacting to these needs are coming quickly.
Current timelines and business intelligence and analytics (BI&A) strategies of many organizations are not aligned to support the increasing needs of population health management, value-based care, enhanced patient experience, and data collaboration and portability. These initiatives demand that data accuracy, accessibility, usability and governance be in place.
Despite the intensifying need, analytics has usually taken longer, been more costly to sustain than executives expect, while delivering less. In addition, many organizations are jumping ahead to develop analytics programs without having the basics in place. This can actually undermine analytics efforts—even doom them to failure.
New care delivery models such as ACOs are increasingly pressured to start delivering meaningful insights immediately. Healthcare organizations that ignore data management basics when building a strategy will struggle to succeed. Fortunately, BI&A technology is catching up with healthcare’s unique needs and can quickly advance an organization’s ability to capture, consolidate and utilize the abundance of available electronic health records (EHR), health plan data, and other data.
Still, 70 to 80 percent of BI initiatives fail to produce promised results. That’s because organizations struggle to acknowledge the role that effective data management plays in their organization’s own transformation. For example, a large health system has seven different definitions of an admission, causing great churn and manual processing. Effective master data management enables a common language without changing proprietary source systems.
An effective BI&A strategy considers much more than just data and technology. It requires a candid look at the operational processes and people, along with a willingness to take a few steps back if needed.
Healthcare organizations should begin by evaluating themselves against a maturity model continuum. It is worth asking a few critical questions at the start.
- Who has ultimate accountability for the organization’s data?
- Is data governance in place?
- Is your data accurate?
- Do you have a common set of business rules around the problem list?
After your organization understands the current state, you can articulate a plan in common terms to move closer to the desired maturity level. Whether you’re working toward more self-serve analytics or basic data warehouse functions, a few basic rules will set the stage for success.
Here are some steps to help you develop a strong BI&A model that meets your current needs and allows for the constant changes in healthcare.
Establish a clear vision that aligns to business objectives. Know where you want to go by developing a vision that has measurable outcomes. For example, say the chief safety and quality officer needs to reduce re-admissions to less than 7 percent across all hospitals within the system. Identify and align your organization’s objectives and the information required to achieve them. Explicitly communicate the connection between business and information strategies so that staff understands, for example, how data gathering affects personalized patient care. Organizations that skip or do not thoroughly complete this step are at risk for expensive delays or rework.
Get and keep executives involved. It’s not enough to have general support from the executive team. You need the active, committed involvement of key stakeholders in such areas as clinical, informatics, technology, operations, research and finance. Clinicians who are already stretched thin will need to be able to commit time to this. The probability of success is high when leaders rally around the cause, anchor it in business objectives, and make it part of everyday conversations. Convince them you can keep working on any immediate pain points if you adjust the current strategy back to the basics. You can do this by incorporating the short-term needs into your roadmap and broadly publicizing the outcomes.
Strike a balance of people, process, technology and data. Don’t underestimate the impact that changes will have on your culture. Include change management in your plan. Appoint a strong, visible leader. If front-line providers are not entering data completely, show them where the analytics fail upstream in the EHR. Guiding processes—from data governance and user support to program management and quality oversight—are essential. It takes good processes and the right people to deliver on your technology investment.
Know your value proposition and priorities. When BI&A strategies lack a consistent basis for priorities, they’re prone to failure. Define your value proposition and integrate it as criteria into a prioritization model to avoid straying from what matters most.
Develop a BI&A program roadmap. Shed light on obstacles and constraints, such as interoperability standardization, and provide solutions for removing them. Define a repeatable development and delivery model for new capabilities. Deliver early and measure progress, either by tying your first project to an existing major initiative such as population health, or by selecting a high-impact project that demonstrates immediate results.
Create a framework for evolving technology solutions. Preparing for a strong BI&A program includes integrating multiple interconnected components that deliver timely, trusted and actionable information. Examples include integration between systems by, for example, getting home health data back into the acute or ambulatory EHR, and vice versa. Deploy shared risk health plans and health information exchanges. Whether leveraging internal tools or new technology purchases, base your selection on defined business and technology criteria across all of the options being assessed.
The bottom line: rather than a sprint to the finish line, your BI&A program is a long-term investment that includes virtually everything. Know your environment and develop a strong foundation by leveraging the basics and keeping it as simple as possible. Remember that many adoption barriers to implementing a BI strategy are managerial and cultural rather than data- or technology-related. Following the steps above will strengthen your organization’s ability to implement a meaningful, actionable BI&A program and strategically position you for the ongoing transformation of healthcare.
Tomorrow: Successful Healthcare Analytics: Data Liquidity
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