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Meaningful Health Care Informatics Blog

Feb 13 2011   7:21PM GMT

Top 7 steps for a successful business intelligence implementation in a meaningful use era

Posted by: RedaChouffani
BI, business intelligence, Stage 2, Stage 3

In a recent article, I reviewed the HIT Policy Committee’s proposed measures for meaningful use stages two and three. As we begin to see more questions in regard to which measures will make it to the final requirements, with much of the focus being on clinical implications required to become a meaningful user on a certified system, it leaves a large task on the hands of CMIOs, CIOs, and other executives — the task being to collect, analyze and trend the information, predict, react, and measure progress from the pre-captured clinical data.

While there are still questions regarding the format of the questionnaires and surveys required to capture patients activation, skills, knowledge, and level of patient awareness (as listed in the proposed measures), several organizations have started to create their action plan to gauge and record such measures.

With all the data that will be available to support improved outcome measures, comes the responsibility of using the right business intelligence tools to assist with the analysis and trending of the data required for meaningful use stages two and three.

In order to ensure that your business intelligence (BI) is successful you will need to follow these simple and critical steps:

1.     Get the right data at the right time

As discussed earlier, it is very critical to ensure that there is sufficient data available to plot your progress in certain areas. This would require first analyzing the reports and trends, not limited to meaningful use stages. Second, identify at what frequency the data will need to be reported on for each department within the organization.

2.     Define where the data is

The majority of the analysis will be applied against existing data that has been collected through the hospital system and internal applications. But there are a few data sets that will need to come from third party entities and/or other public or federal groups. As an example, when reviewing the suggested measures which will assess the appropriate use of medications based on standards of care for applicable conditions, we realize that we are comparing data collected within the hospital against standards that are outside the IDN.  This clearly indicates the importance of knowing the origin of the other data collected.

3.     Share the value with the rest of the group

Unfortunately, not everyone appreciates the power and value of BI provides to organizations.  But it can be sometimes just a matter of education that can make a world of difference.  In most successful organizations, the executive team realizes that in order to keep the finger on the pulse you must have a near real-time exposure to stats, scorecards, and other meaningful measures (even on your mobile device).   So it would be beneficial to share with all management and executive team what are the capabilities and value of BI within your organization’s context. Whether the team needs to apply it to A/R analysis, the revenue cycle, quality metrics, general charge capture, patient satisfaction, or marketing, there numerous areas that can benefit from the analysis of the overall data.

4.     Define reporting and analysis intervals

For the data to be properly analyzed and meaningful, it must query from the production system at different frequencies. This will store it at different processing data repositories. But in order to avoid performance issues, one must plan the difference extraction and processing frequencies ahead. For example if we are looking at reviewing the clinical services and perform a comparative analysis over a period of five years, then this is a job to be performed during non-peak hours and would most likely take many hours. But if we are looking to review a ticker in real-time that displays patient admissions or discharges then a simple query can be executed periodically throughout the hour and voila.

5.     Select the right tool for you

There are a variety of BI tools, from spreadsheets, to OLAP, and reporting tools. Some are open sources, while others are provided under the SaaS model. But really, the tools that need to be implemented would depend on several things: overall data size, current platform, in-house skill set, physical architecture, mobile app capabilities and support.

Another component to selecting the right tools is actually identifying the analytical data model for your specific needs.  There are several third party vendors that specialize in business performance management  that can reduce the customization and building time for your organization.

6.     Hire help if you are not sure

Many healthcare organizations have the talent needed to implement the BI widely available. However, given the ongoing complex requirements that require a deep understanding of the data model, metadata, data integration, quality, analytics, and different management metrics, it is usually recommended to work with a third party vendor, if budgets permit, to ensure that at least the initial implementation is done right, and in a timely fashion.  It also ensures that your team is involved in all the steps so they can take over and ensure that future BI needs are met internally and kept in-house.

For a successful implementation of BI and in a patient-centric environment, there are many complex tasks that need to be addressed.  Some are related to showing value and engaging the leadership to back the initiative, and other relate to all the technical requirements for a successful install and deployment.  But whether you’re focusing on logistics, ER, AR, or nursing dashboards, all of these areas have meaningful data that will help ensure the organization’s goals are met at all levels and everyone is in line with the objectives.


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