Posts Tagged ‘healthcare data’

Healthcare leaders have access to more healthcare data and technology than ever before allowing them to transform patient and member care. A one-size-fits-all-approach doesn’t work anymore and we’re being challenged to do more through personalized medicine. In season 1 episode 2 of the Intelligent Data Podcast, host Arvind Murali and his guest Juliet Silver, Perficient’s […]

My last blog outlines cloud as a secure and central hub for all of your data. My next blog in this series examines how cloud provides efficient access to your healthcare data. Faced with multiple sources of data, healthcare organizations have the difficult task of integration, managing legacy systems and connecting disparate data siloes created […]

What are the business rules that companies are using for claims processing? This is a common question when it comes to performing analysis on claims data and is becoming increasingly important with regulations on billing transparency on the way. The logic used for claims processing is typically embedded in code and is not transparent to […]

I’m often asked how data and analytics can help to solve key industry problems in healthcare. With that in mind, three key industry issues rise to the top of the list. 1. Cost of Care Delivery The cost of care delivery is at the center of the problems facing the healthcare Industry. Healthcare spending accounts […]

The following is the third blog in a series about why healthcare organizations are moving to the cloud. In this series so far, we have looked at how the cloud brings robust data security and the cost savings and efficiencies that the cloud delivers for healthcare organizations. In this blog, we’ll examine at one of […]

Previously, I highlighted artificial intelligence, and all the opportunities it brings to the industry. In the final blog of this series we explore data governance and its role in digital health. Given the other four trends, one of the biggest challenges will continue to be obtaining executive buy-in for digital health initiatives. That means actively […]

There are numerous obstacles in making healthcare data useful for downstream analysis for decision making. There may be no bigger challenge than taking data that has been captured from disparate healthcare EMR systems and cleansing and normalizing them into something uniform for consumption. This is a result of the way that data is captured in […]

Governance forms the framework for information, content, and knowledge management to operate. Establishing clear, common, and consistent models in healthcare upon which to ground governance components provides a solid foundation executing the management activities that enforce these governance requirements. This ensures the consistency and relevancy of the information for the business – the ultimate goal […]

Of all the governance trends, none is more foundational and critical to the success of the governance program – indeed the organization itself – than the need for accurate, consistent, and relevant models that communicate the meaning, use, and residency of the assets of the enterprise. Modeling not only addresses the integration and ingestion of […]

Democratization of Ownership and Stewardship The rise of big data, self-service, and more powerful and flexible end-user information visualization and preparation tools, consumer/ member/patient experience is impacting governance in a significant manner with regard to structure, decision rights, and accountabilities. End-users are gaining more control of these assets, including the ability to integrate and manipulate […]

Related to the trend of recognizing the difference between information and data, content, and knowledge is that governance of information requires it be viewed as a business capability. This recognition is starting to take hold because healthcare organizations are realizing that it is the business needs and drivers that supply the context for data, content, […]

I’ve said it before and I’ll say it again… it is impressively difficult to integrate data from one or more EMR systems into a cohesive analytical warehouse database. Especially if you’re doing it from scratch. In my last two blogs (Data Integration: Taming the Beast of Healthcare & Data Integration: Taming the Beast of Healthcare […]