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Minnesota’s Health Care Quality Measures are Prime for Business Intelligence Tools


Author: Greg Beaumont

The State of Minnesota has long been a healthcare industry leader for total quality of care.  United Health Foundation’s America’s Health Rankings ranks Minnesota as the best State in the Union for a combined score of “All Outcomes.”

In November of 2010, The Minnesota Department of Health released a Statewide Quality Report for Health Care Quality Measures.  About 520 Minnesota clinics reported data for analysis via these measures.  The reports can be viewed at this link.

The Health Care Quality Measures provide scores for the treatment quality of conditions such as diabetes, vascular disease, and cancer screening.  These scores can be viewed for individual clinics, and for the State.  Basically, a report is available that is a static scorecard to benchmark Minnesota’s clinics in comparison to one another.

These reports are monumental leaps forward in the transparency of healthcare quality reporting.  Yet, they cannot answer certain fundamental questions that are subsequently raised by the measures.  For example, why does a certain clinic do well with diabetes treatment?

The logical next step for agencies that collect data for these reporting purposes, or for constituent clinics looking to monitor their own Health Care Quality Measures scores, is to add the drill-down analysis capabilities of Business Intelligence (BI) tools.  With BI tools, the ability to drill-down into these measures with slice-and-dice capabilities would be actualized.

Imagine having the ability to separate out how an individual clinic scores for diabetes care by age group, gender, insurance provider, zip code, and many more categories.  With BI tools, such analysis would be available with the click of a mouse on a reporting dashboard.  Without having to order or generate custom reports, the specific patient populations that contribute to a score can be isolated and analyzed.

The Minnesota Department of Health’s Health Care Quality Measures are a giant leap forward in healthcare performance monitoring.  The next step is to enable analysis of the root causes of those reported scores.  As mentioned in my previous blog post submission, Barack Obama’s Healthcare IT Coordinator has already requested for that next step to be taken.  The tools for that next step already exist, and it is only a matter of time before healthcare organizations and reporting agencies put the next foot forward.

GNet Group has created just such a BI-based tool with their Healthcare Intelligence Framework (HIF).  The HIF is designed to integrate healthcare data using Microsoft SQL Server Analysis Services (SSAS) and SharePoint dashboards.  In addition to BI tools for drill-down and slice-and-dice analysis capabilities, GNet’s HIF also adds statistical analysis capabilities with tools commonly used for Six Sigma, Lean, and predictive analytics.

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GNet Group’s HIF Solution achieves Blumenthal’s ideas for meaningful use


We ran into a post on Fierce Health IT, that highlighted Dr. David Blumenthal’s speech at the HIT Policy Committee meeting.  During that speech, Blumenthal, the national healthcare IT coordinator, mentioned enabling and calling out users that are able to demonstrate significant outcomes versus “vanilla meaningful users”.

Speaking at this month’s meeting of the HIT Policy Committee, an HHS advisory panel, Blumenthal mused about distinguishing between “vanilla meaningful users” and others that might be able to demonstrate significantly better-than-average outcomes, healthsystemCIO.com reports. According to Blumenthal, some in the latter group “might say, ‘If I’ve accomplished performance outcomes which are three standard deviations better than other institutions, related to 10 outcomes criteria using health information technology, maybe I should be exempt from the task of checking boxes, because I’m there; I’ve risen above the criteria you put in the regulation.”

There were a few committee members that expressed concerns that such an approach to monitoring would be a huge chore, and the process would be time consuming and almost impossible to manage the data. 

Fear not! GNet Group’s Health Intelligence Framework (HIF) is an acceleration framework that intuitively joins data that already exists in most electronic medical record, billing & coding, financial management, and operations applications.  Business Intelligence tools applied to Six Sigma Management Strategy Statistics, Predictive Analytics, Performance Measure tracking, and advanced demographic analysis capabilities provide intelligent insights into Healthcare data.

Post Credit to GNet Group Consultant: Greg Beaumont

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Welcome to the GNet Group Blog!


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