As the digital trajectory of healthcare rises, health systems have an array of new resources available to make more effective and timely care decisions. However, to use these data analytics, machine learning, predictive analytics, and wellness applications to gain real-time, data-driven insight at the point of care, health systems must fully integrate the tools with their EHRs. Integration brings technical and administrative challenges, requiring organizations to coordinate around standards, administrative processes, regulatory principles, and functional integration, as well as develop compelling integration use cases that drive demand. When realized, full EHR integration will allow clinicians to leverage data from across the continuum of care (from health plan to patient-generated data) to improve patient diagnosis and treatment.
Interoperability in healthcare, despite frequent objections by EHR vendors and health systems (e.g. “EHR integration is too difficult to manage”), is integral to delivering high quality patient care.
Interoperability means different things to different health system stakeholders, from leaders seeing it as a purchase they must defend, to clinicians relying on it to get the information they need, when they need it. But it boils down to delivering the highest-quality, most effective, and most efficient care to patients—a goal that’s easier to define than achieve.
One of interoperability’s most important use cases, EHR integration, is challenged by EHR vendors and health systems worried about integration challenges, from HIT vendors wanting to integrate too many tools, to EHR access fears. Fortunately, objections are dissipating with the introduction of national interoperability policy and better cooperation among industry participants.
Amidst these distractions, health systems need to regain focus on interoperability’s top goal: improving patient care by making the best information available at the point of care.
Too much is at stake in value-based healthcare and the technology needed to provide it. When it comes to investing in the best healthcare analytics tools for delivering data-driven care management and outcomes improvement, executives should compare these seven points to determine whether an electronic health record or an enterprise data warehouse should be the foundation of their analytics platform:
Incorporating data from a wide range of sources
Ease of reporting
The data mart concept
Relevance of each to value-based care
Relevance of each to managing population health
Surfacing results of sophisticated analysis for physicians at the right time
Ability to combine best practices, data, and technology tools into a system of improvement
This executive report starts by examining the origin of EHRs and EDWs, then dives into the value derived from both in terms of their contributions to the major issues impacting healthcare delivery today.
Every provider agrees on the need for healthcare interoperability to achieve clinical data insights at the point of care. The question is how to get there from the myriad technologies and the volumes of data that comprise electronic medical records. It’s been difficult to organize among participants that have had little incentive to cooperate. And standards for sending and receiving data have been slow to develop. This is changing, but the key components that are still vital to realizing insights are closed-loop analytics and its accompanying tools, an enterprise data warehouse and analytics applications. This article defines the problems and explores the solutions to optimizing clinical decision making where it’s needed most.
Optimize physician workflow and you’ll contribute to optimizing patient care. But what is it physicians look for to improve diagnoses, decision-making, patient care, and ultimately, outcomes? To answer this, consider what constitutes ideal working conditions in any industry: the right tools, training, and information to maximize productivity and deliver results. Physicians need analytics integrated into the EHR to maximize their efficiency, a common quest among the chronically overworked. And by flowing the universe of global, local, and individual data back into an enterprise data warehouse, a healthcare system can close the analytics loop, and begin to realize true precision medicine.
Healthcare organizations preparing for the value-based payment model shift have found their internal resources pushed to the limit. Often, in an attempt to address regulatory timetables, systems will use point solutions rather than move toward a long-term strategy of developing robust clinical analytics. If an organization is using their EHR for analytics, they will soon discover that these built-in analytics packages cannot help them identify opportunities for cost effectiveness and clinical best practices. Sophisticated data management and healthcare analytics solutions, however, can provide leaders with the integrated clinical, financial, and patient satisfaction data they need to transform their systems into data-driven enterprises.
We know that healthcare costs are increasing and that value will become more important than ever. But the concept of value can be subjective. When it comes to healthcare, we can’t afford to be subjective in our assessment of value. I like referring to the Porter equation where value is equal to quality over cost. What this equation makes clear is that we must markedly improve the quality of healthcare in order to improve value. The adoption of the EHRs in clinical systems should help drive the quality agenda. But it’s important to recognize that EHRs alone may not be sufficient to deliver data intelligence, to really deliver data to clinicians in a meaningful way that will help them improve value.
Healthcare systems are struggling to figure out how to shift to a value-based model and remain competitive. This will require hospitals to identify and reduce waste in three categories: the variation in 1) the care that is ordered, 2) how efficiently that care is delivered, 3) in care delivery that causes preventable complications .Clearly, EHRs aren’t the answer. What’s needed is the industry-wide adoption of adaptive, clinical data warehouses capable of integrating disparate transactional source systems and analytical tools that can provide crucial actionable intelligence
Accountable care is changing the way Payers and Providers look at their healthcare data. Many healthcare enterprises believed that their Electronic Health Record (EHR) would be the silver bullet to this data problem, but they are beginning to discover the limitations of the EHR for managing at the enterprise-level all of the information necessary for effective risk-sharing. Health information exchanges (HIEs) help eliminate data silos but are not designed to store or analyze the data with the level of sophistication required for supporting a risk-sharing model. The reality is, until now, providers and payers have lacked consistent incentives to share data.
One of my clients, Texas Children’s Hospital, recently made tremendous strides in this data-driven journey. Getting data from their EHR in a timely fashion was difficult, time consuming and resource intensive. Now, with the proper tools in place, namely a healthcare enterprise data warehouse, a suite of healthcare analytics applications and a process for information deployment, they have shifted the cost curve to drastically increase the availability and usability of information.T CH used their healthcare enterprise data warehouse (EDW) to meet demands for EHR
data and reports, and slashed their reporting costs by 67%.
Many CIOs, along with their other C-suite colleagues, are anticipating a catharsis on completing massive EHR deployment projects. Before long, however, they come to the unwelcome realization that the EHR is just one component needed to provide the actionable intelligence health systems need to survive in a value-based purchasing environment.
“The EHR alone is not enough without a data platform that enables an
enterprise wide, consistent view of data from many sources. Since this
challenge seems to be pervasive, let me offer a perspective on some of
the most oft-repeated data questions posed by health system leaders.”
At no time in the history of U.S. healthcare has a flexible, scalable platform for delivering data-driven insights been more important than it is today. But EHRs alone don’t provide the intelligence that physicians, group practices, and hospitals need to significantly improve both the effectiveness and efficiency of care delivery. Learn what you can do to harness all of the data you’re collecting to make real change.