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Customer Experience and Design

More Data More Problems? The Importance of Quality Analysis

My colleague, Lesli Adams, is a regular blogger on Perficient’s Oracle technologies blog. As the Director of Oracle Healthcare Business Intelligence, she often posts about topics that are also relevant in the healthcare world. She recently posted a blog about data reporting standards that would be a good read for those interested in healthcare analytics, below:

In a recent blog, I wrote about parallel industries; Manufacturing, Airline, and Healthcare and the need to get to a Balance Sheet of Clinical Results for the Healthcare Industry. With EMR Adoption Rates increasing year over year, HIMSS is reporting for the Final 2012 reporting period, that over 36% of facilities have at least a CPOE in place. As that number advances, there will be more and more harvestable data. Data will no longer be siloed, but available and ready for data mining, analysis, comparison, and predictive analysis.

Now that you have the data, what are you going to do with it?

Are pre-defined vendor provided reports adequate for analysis? To any user? Is the single threaded view of the patient and an a la carte Q&A sufficient? Remember folks, this is the ENTIRE data set for your ENTIRE facility. Just because you adopted your EMR and CPOE to receive incentive dollars from CMS, don’t stop there! I am in awe of the amount of data that resides in these colossal giants of patient medical records and yet I find too often that the facility and the champion of the EMR is focused only on Meaningful Use measures. Don’t get me wrong, this is the right step in the right direction. But don’t stop there, the Quality department could use it, Performance Improvement, Provider Credentialing, Financial Planning & Analysis….

Oh, but wait. Learn to crawl before you walk. Facilities of every size have “analysts”, some are exclusive resources dedicated to analytical support, sometimes with large teams, but still in other cases, analysis is a defacto collateral assignment that happens in addition to everything else in the day. Clinicians and non-clinicians, not trained in the science of reconciliation and balancing, but trained in lab medicine, nursing care, or discharge planning. So then how will you serve up the data to let these “non-analysts” do analysis?

A few years ago I sat inside the Washington DC beltway and had a great discussion about clinical measurement. I was asked “How do you do this? How did you learn this? Did you go to NQF school?” My answer was a simple NO. I was trained as an Accountant. I learned GAAP, Generally Acceptable Accounting Principles. I learned FASB and GASB, the Financial and Government Standards. So to me it is a natural extension to see a Clinical Data Warehouse through the same lens that I saw a Financial General Ledger. The rigor that I apply GAAP to Financial Statements is the same rigor I apply to HEDIS, MU, NQF, and Clinical Operations Measures. Looking at the entire organization and having the ability to see how it all fits together. Not tunnel vision, asking one specific question with personalized parameters, but seriously applying consistent and repeatable processes to the entire data set to get the holistic and absolute truth about the patient’s served. Technology now supports that rigor in the Healthcare Industry.

For more information on the Final 2012 EMR Adoption rates,

To read Lesli’s original blog, click here.

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