Tag Archives: data

Data is the Key to Value-based Healthcare

The transition to value-based care is well underway. From healthcare delivery organizations to clinicians, payers, and patients, everyone feels the impact.  Each has a role to play. Moving to a value-driven model demands agility from people, processes, and technology. Organizations that succeed in this transformation will be those in which:

  • Collaboration is commonplace
  • Clinicians and business leaders wear new hats
  • Data is recognized as an enterprise asset

The ability to leverage data will differentiate the leaders from the followers. Successful healthcare organizations will:

1)      Establish analytics as a core competency
2)      Rely on data to deliver best practice care
3)      Engage patients and collaborate across the ecosystem to foster strong, actionable relationships

Trustworthy data is required to power the analytics that reveal the right answers, to define best practice guidelines and to identify and understand relationships across the ecosystem. In order to advance, data integration must also be agile. The right answers do not live in a single application. Instead, the right answers are revealed by integrating data from across the entire ecosystem. For example, in order to deliver personalized medicine, you must analyze an integrated view of data from numerous sources. These sources could include multiple EMRs, genomic data, data marts, reference data and billing data.

A recent PWC survey showed that 62% of executives believe data integration will become a competitive advantage.  However, a July 2013 Information Week survey reported that 40% of healthcare executives gave their organization only a grade D or F on preparedness to manage the data deluge.

value-based healthcare

What grade would you give your organization?

You can improve your organization’s grade, but it will require collaboration between business and IT.  If you are in IT, you’ll need to collaborate with business users who understand the data. You must empower them with self-service tools for improving data quality and connecting data.  If you are a business leader, you need to understand and take an active role with the data.

To take the next step, download our new eBook, “Potential Unlocked: Transforming healthcare by putting information to work.”  In it, you’ll learn:

  1. How to put your information to work
  2. New ways to govern your data
  3. What other healthcare organizations are doing
  4. How to overcome common barriers

So go ahead, download it now and let me know what you think. I look forward to hearing your questions and comments….oh, and your grade!

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Posted in Data Governance, Data Integration, Data Warehousing, Healthcare, Master Data Management | Tagged , , , | Leave a comment

Nine Forms of Analytics Data That Matter the Most

Big Data takes a lot of forms and shapes, and flows in from all over the place – from the Internet, from devices, from machines, and even from cars. In all the data being generated are valuable nuggets of information.

The challenge is being able to find the right data needed, and being able to employ that data to solve a business challenge. What types of data are worthwhile for organizations to capture?

In his new book, Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams With Advanced Analytics, Bill Franks provides an wide array of examples of  the types of data that can best meet the needs of business today. Franks, chief analytics officer with Teradata, points out that his list is not exhaustive, as there is almost an unlimited number of sources that will only keep growing as users discover new ways to apply the data. (more…)

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Why Data Integration Technology Beats Manual Coding Every Time

With the ready availability of data integration technology, it’s amazing to me that the use of manual coding for data integration flows is even a consideration. However, based upon this article in SearchDataManagement, the concept is still out there.

Of course the gist of the article is that hand coding is no longer considered the most productive way to go, which is correct. However, just the fact that this is still an issue and a consideration for anyone moving to data integration solutions perplexes me. Perhaps it’s the new generation of architects and data management professionals who need a quick lesson on the pitfalls of doing data integration by hand.  (more…)

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Posted in Data Integration | Tagged , , , , | 1 Comment

Leverage Big Data or Go Out of Business

I’m sitting in the Taiwan airport on my way to Guangzhou. We just completed the Informatica World Tour in Hong Kong, Beijing and Taiwan, and I’ve had the opportunity to deliver the keynote presentation, Maximize Your Return on Big Data.

All of our audiences exceeded our expectations. We had 50% more attendees than planned. Why? Big data. It is a hot topic and everyone is trying to determine how to leverage big data in their enterprise to get a competitive advantage. At the event, I made the point – if you’re not trying to understand how to leverage big data in your enterprise, your successor will. Kitty Fok, the IDC China Country Manager, spoke after me. Her consistent comment was – “if your company isn’t looking to leverage big data, you will be out of business.” (more…)

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Posted in Big Data, CIO | Tagged , , , , , , , , | 1 Comment

Data Governance and Technical Issues

In contrast to addressing the management and process issues, we might say that the technical issues are actually quite straightforward to address. In my original enumeration from a few posts back, I ordered the data issue categories in the reverse order of the complexity of their solution. Model and information architecture problems are the most challenging, because of the depth to which business applications are inherently dependent on their underlying models. Even simple changes require significant review to make sure that no expected capability is inadvertently broken. (more…)

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Posted in Data Governance, Data Quality | Tagged , , , , | Leave a comment

Stop Hoarding Data – Retire Your Old, Redundant Applications!

Just like your house needs yearly spring cleaning and you need to regularly throw out old junk, your application portfolio needs periodic review and rationalization to identify legacy, redundant applications that can be decommissioned to reduce bloat and save costs. If you have a hard time letting go of old stuff, it’s probably even harder for your application users to let go of access to their data. However, retiring applications doesn’t have to mean that you also lose the data within them. If the data within those applications are still needed for periodic reporting or for regulatory compliance, then there are still ways to retain the data without maintaining the application.  (more…)

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Posted in Application ILM, Database Archiving, Informatica Events | Tagged , , , , , , , , , , | Leave a comment

Classifying Types of Data Management Issues

Coincidentally, my company is involved with a number of different customers who are reviewing the quality criteria associated with addresses. Each scenario has different motivations for assessing address data quality. One use case focuses on administrative management – ensuring that things that need to happen at a particular location have an accurate and valid address. A different use case considers one aspect of regulatory compliance regarding protection of private information (since mail delivered to the wrong address is a potential exposure of the private information contained within the envelope). Another compliance use case looks at timely delivery of hard copy notifications as part of a legal process, requiring the correct address. (more…)

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Scoping Failure Analysis

In adapting the six-sigma technique of failure mode and effects analysis for data quality management, we are hoping to proactively identify the potential errors that lead to the most severe business impacts and then strengthen the processes and applications to prevent errors from being introduced in the first place. In my last post, though, I noted that the approach to this analysis starts with the errors and then figures out the impacts. I think we should go the other way so as to optimize the effort and reduce the analysis time to focus on the most important potentialities. (more…)

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Dear Santa…

Back in the good ol’ days, Santa Claus received letters and post cards from children all over the world.  When telephones and faxes became commonplace, they were also used to contact Santa.  In addition to those traditional methods, children today can also use the internet to send emails, Twitter, Facebook and even LinkedIn to notify Santa of their wish list. (more…)

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Posted in Business Impact / Benefits, Enterprise Data Management | Tagged , , , , | Leave a comment

The Myth of Unlimited Resources

Last time we looked at the failure mode and effect analysis technique from the six-sigma community and slightly adjusted it to be data-centric so that it can be used to anticipate the different types of data errors that could occur and adjust application design to accommodate the prevention of data errors in the first place. This approach really is proactive since you are proactively considering the many different types of errors that could be introduce and then shoring up the process in anticipation of their occurrence. (more…)

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