Posts Tagged ‘healthcare IT’

It is very important to make sure you determine your hardware requirements if you are implementing EDI for the first time, changing your EDI software or your EDI data needs. If you have already met your needs then you’re ahead of the game. If not, then once again make sure you get all key stakeholders […]

The U.S. healthcare industry has come head-to-head with tremendous challenges that have the potential to cripple the industry and reap havoc on multiple stakeholders, whose different interests and incentives have made change and progress difficult. However, a new era of data-driven healthcare is emerging as players are starting to explore the power of “big data.” […]

Quality and Performance Initiatives The implementation and integration of information systems in traditional healthcare data processing and archiving has not only facilitated inter-communication, but also has the potential to develop intra- and inter-organizational benchmarking methodology focused on the improvement of quality of care. The inception of performance and quality measures can be based on national […]

Much has been touted about Big Data being “schema-less,” thus minimizing data modeling, especially Physical Data Modeling. At a low level (e.g., Map Reduce level), there is some truth to this as Map Reduce works with key value pairs. In the Map phase of a Map Reduce job, the input data is read in and […]

There is growing interest in Big Data these days. The common definition for Big Data is data sets which are too large (e.g., hundreds of terabytes or into petabytes) to be handled by traditional means. Leveraging Big Data requires an extensive degree of parallelism of both data and computing and may take advantage of low-cost […]

I’m happy to announce that Perficient’s healthcare team has again been ranked in the Healthcare Informatics Top 100 list. This year we ranked 69th. Even though Perficient provides technology consulting services across many industries, our ranking among the best in the healthcare industry is an honor based on the hard work of our team of […]

The biggest challenge in today’s healthcare environment is the use of clinical data. Everybody knows that the healthcare industry is “behind the times” compared to other industries when it comes to using data to drive meaningful outcomes, largely due to the complexity of healthcare data. However, with rising costs, constant regulatory changes, and ever-increasing competition, […]

Certain terms within requirements signal details are missing, thus ensuring additional discussions. Discovery sessions are the norm but when a requirement document has the follow statements, requirements are not completed. 1.) The number one offending term:;TBD – “To be discussed” or “To be Determined.” A requirement with the letters “TBD” is not a requirement and […]

Join us Wednesday, May 30, at 12:00 PM CDT, for the Perficient webinar, “Using Big Data for Improved Healthcare Operations & Analytics.” Register now! Healthcare providers are faced with significant challenges due to regulatory and reimbursement requirements and the everyday pressures of managing care. Providers must be proactive to manage the health of a population […]

Now that we’ve established what a canonical data model is, let’s talk about our objectives for what we want to achieve with our Canonical Data Model and what toolsets can be applied. In my Canonical Data Modeling environment, I want to store and manage my entities and their relationships. I want support for the Conceptual, […]

ACOs are paving the way for a healthcare payment model that is based on quality and efficiency instead of volume. They were created as a response to health reform initiatives that focus on improving patient safety, quality of care and affordability. As the name suggests, ACOs are institutions that collectively share the risks associated with […]

Spurred on by Meaningful Use, there has been an explosion in the implementation of EHRs over the last several years. This tidal wave has been sweeping through the healthcare community, sucking up much of the available bandwidth that organizations have to deal with change of this magnitude. The effect is really no different than what […]