Data integration is a daunting task for organizations in every sector. Companies today are generating and collecting more information than ever before, and leveraging these resources demands a high-degree of integration between different systems. Any obstacles in this area will undermine the data’s value and cause countless complications elsewhere.
The issue of data integration has become particularly important for organizations in the health care sector, thanks to the rise of electronic health records, implementation of the Affordable Care Act and a variety of other factors. As a recent report from MeriTalk revealed, these issues have a steep financial cost. By improving their data integration capabilities with superior Health IT expertise and resources, care providers will be able to not only save a tremendous amount of money, but also deliver better results for their patients.
“Data integration problems cost government care providers $342 billion annually.”
Hundreds of Billions in Integration Costs
The study focused specifically on data integration challenges in the government health care space. The firm interviewed more than 150 social services IT professionals and program/case managers. These respondents were asked to identify the leading challenges standing in the way of health care benefits delivery.
Data integration was the most common answer. Forty-seven percent of survey participants believed that by improving data integration across and between agencies, care providers could reduce their expenses. In fact, survey respondents collectively estimated that problems in this area cost government care providers $342 billion annually.
A User-friendly Future
Obviously, the steep price tag associated with data integration issues should be enough to motivate organizations to upgrade their capabilities in this area. Additionally, the MeriTalk survey emphasized data integration is essential for the development of a genuinely user-friendly IT system, one which incorporates data from all relevant sources and departments. Survey participants stated that such a system would deliver and feature a better overall quality of service, faster eligibility determination and verification, greater accuracy, improved employee productivity and more.
All of this is only possible, though, if health care systems are able to share and access data freely with one another. Silos that prevent data integration will compromise accuracy and performance, and lead to worse outcomes for patients. Naturally, this will also damage health care providers’ reputations, especially as others in the industry make greater strides toward data-integrated, user-friendly systems and strategies.
Big Data Needs
A similar state of affairs can be seen in the health care sector’s accelerating efforts to utilize big data analytics. With analytics, care providers can potentially gain tremendous insight into patients’ level of risk, likelihood of requiring future treatment and much more. The introduction and adoption of EHRs on a widespread level makes it possible for these analytics programs to access far more raw data than ever before, greatly improving their utility and saving hospitals a tremendous amount of time and money through their more efficient policies and practices.
Big data analytics requires extensive integration.
Yet, in order to function, analytics systems must have access to all available data, or else the results may be compromised by their incompleteness. This can be difficult, especially for large provider networks comprised of numerous organizations, each of which will have multiple systems.
However, such challenges are not insurmountable. As TechTarget contributor Ed Burns recently highlighted, Advocate Health Care – an organization formed through a series of mergers and acquisitions – was able to integrate data from numerous hospitals and systems through the use of a standardization-heavy strategy, developed in conjunction with a third-party IT consulting firm.
As this example makes clear, the right tools and approach can allow care providers to overcome the inherent cost and complexity challenges inherent to IT data integration.