Unified data management holds the key to unlocking the value in ever-growing and more complex healthcare data sets by ensuring that the right users have access to the right data, in the right format at the right time.
Integrated data management, coupled with a formal data governance program that stresses data quality, instills confidence in users to trust the data they are working with.
The entire healthcare ecosystem is challenged by countervailing objectives of improving the quality of patient care while reducing the cost of providing it. Meanwhile, pressures are mounting to implement the next stage of electronic health records (EHRs) and demonstrate meaningful use – just as big data is straining legacy systems.
With the sources of patient data expanding to include big data, a unified approach to data management facilitates the integration of conventional structured data with more challenging forms of semi- and unstructured data. This includes patient-sourced data, as the consumerization of IT spreads to healthcare. Smartphones, wearables and other monitoring technologies will be generating a new wave of endpoint data that can be integrated and managed to gain a 360-degree view of the patient.
Unified data management makes it easier to leverage newer technologies for advanced analytics that can yield better diagnoses and allow for more accurate prescriptive and predictive models. And as individuals become more proactive in their own care and monitoring, the added insights providers gain will enable them to deliver more personalized services and treatments.
Managing data more efficiently also reduces costs throughout the system while assuring adherence with GRC (governance, regulatory and compliance) requirements. Between operational efficiencies, higher patient satisfaction (a.k.a. user experience) and improved patient outcomes, the U.S. healthcare industry has the potential to generate over $300 billion a year in incremental value, according to estimates by the McKinsey Global Institute.
Big data challenges EHRs and meaningful use
Like other industries, every link in the healthcare system –from practitioners to payers – is grappling with unprecedented amounts of data. With its own language, taxonomies and standardized codes that map to different activities across the ecosystem, healthcare data is particularly complex to integrate and manage.
The healthcare landscape is littered with silos of inconsistent data formats locked in clinical, administrative and financial systems that inhibit analysis. This has resulted in operational inefficiency and overlooked opportunities at best, and fatal errors and fines for non-compliance under the worst scenarios.
Adopting standards that capture the meaning of data across the industry has helped ensure mutual understanding between organizations. While the Health Information Technology for Economic and Clinical Health Act (HITECH), which mandates the use of EHRs, and the “meaningful use” EHR Incentive Program requirements have created greater commonality in basic EHR functions, these initiatives have also led to a torrent of data from disparate systems that need to be integrated and managed. A unified approach to data management can help organizations unlock the value in this data.
Also driving the need for unified data management are measures that estimate the effectiveness of health plans. The National Committee for Quality Assurance's Healthcare Effectiveness Data and Information Set (HEDIS) performance metrics helps ensure that the quality of provider care is as high as possible.
Since HEDIS scores are based on multiple data sources, such as clinical applications, pharmacy and medical claims systems, the need to manage the data proactively is critical. Since these measures continue to evolve and are subject to change year-to-year ongoing data vigilance is a necessity.
For the industry, achieving meaningful use remains a work in progress. The common functional requirements established by the Centers for Medicaid and Medicare Services (CMS) for EHRs, coupled with its carrot and stick approach to ensuring practitioner adherence are steps in the right direction. These standards can drive economies of scale and higher levels of patient care that have eluded the industry in the past due to its data inefficiency.
The need for connected, accessible, high-quality data that is actionable has never been more critical. This is particularly so as new EHR requirements are implemented. These include Stage 2 functionality that lets patients communicate electronically with practitioners over a secure channel and access their medical information digitally. Early Stage 3 proposals take this further by suggesting connectivity with patient-controlled monitoring devices.
A unified approach to data management allows healthcare organizations to realize meaningful use of their data assets. It can improve financial return metrics while strengthening provider risk management profiles. And it can achieve all of this while demonstrating that the industry’s objectives need not be mutually exclusive.