Better Data, Better Decisions. Improving Healthcare with Business Intelligence.

There’s a ridiculous amount of data flowing through medical practices every single day. EMR/EHR data, billing data, cost data, patient data… It’s enough to make your head spin. With the push to value-based care, every health organization is finding the need to transform that data into something that will improve outcomes – both for the practice and its patients. It’s not just about capturing and managing data anymore, it’s about interpretation. How can medical practices transform data – from management to analysis – into insightful information that will drive care and process improvement initiatives?

Because of the heightened demand for value and transparency, one key tool many organizations are beginning to embrace is healthcare analytics, particularly through business and clinical intelligence software. When you give analysts (Or whoever is handling your data. For the sake of continuity, will stick with this reference.) the means to not only capture, but analyze data as well, you empower them; allowing them to transform your practice into one with a data-driven, value-based culture. With that said, you initiate a chain reaction: Empower the users, make better decisions as a provider, and improve both business operations and patient outcomes.

To fully understand the power of this tool, a little background knowledge is required. All data must go through a particular set of stages before an analyst can even achieve meaningful analytics:

·         Data capture -  It all begins with the way people and devices produce and capture data, which must be done in the most efficient (is the data collected in a timely manner?) and accurate (is the data relevant to the analytical needs of the organization?) way possible.

·         Data acquisition – As previously mentioned, analysts must collect data from multiple sources throughout the organization to produce true, meaningful insights. Let’s use the example of an analyst assisting a radiology practice with a quality improvement issue. The analyst will pull information from a number of sources:

o   RIS – For radiologist interpretations

o   PACS – All picture archives

o   EMR – For clinical notes

o   Clinical Decision Support Systems

If you’re doing this manually – pulling this data into a single location, in one format, and ensuring that all data points are speaking each other (that they’re linked by a common identifier, either patient or provider) is nearly impossible without creating error. Not only that – analysts can spend too much time collecting as opposed to transforming data into meaningful analytics. That’s where business intelligence comes in. ImagineIntelligence, for example, allows users to integrate multiple data sources right into the software, under one platform.

·         Data analysis – Once the data is captured and tied together, the analysis process can finally begin.

o   Evaluation – At the end of the day, if analysts don’t understand the data they’ve collected, regardless of whether they utilize BI, they can’t effectively communicate their findings with their audience (executives, staff, etc.) Analysts should take the time to explore – take note of oddities and trends that could be essential to understanding process improvement or care coordination. If you don’t understand the data, how can you effectively solve problems with it?

o   Interpretation – How will you interpret this information in such a way that all levels of the organization will understand? Again, doing this manually is time consuming.

o   Presentation – This part is critical, and shouldn’t be overlooked. The analyst should essentially tell a story with the data presented. Tying into the interpretation step – how will you organize and present the information in a way that’s engaging, and that identifies the problem and solution?

These steps are all of equal importance; all leading to the drive of data transformation and improvement. So, it’s crucial that they’re part of your data analysis process, if not already!

We’ve discussed how business intelligence plays an important role during data analysis, but what else? Utilizing analytics allows you to discover insights that can drive care, process improvement initiatives, and financial stability of your organization.

·         Reduce hospital readmissions – Business Intelligence tools can allow you to compare patients who did not need readmission against those who did. Things like age, gender, ethnicity, and follow-up care are all factors taken into consideration by the software.  Once the data is collected and organized, you can identify patterns of readmission – perhaps those patients come from lower social economic groups or live alone.

·         Financial performance improvement – Imagine having the power to track exactly how much your practice is reimbursed for services over time, coupled with the ability to improve that level of reimbursement within the same interoperable software. Business Intelligence systems that integrate with practice and revenue cycle management software and automatically extract and analyze data housed in the platform will allow you to predict future trends based on factors like revenue and billing costs.

·         Improve and develop treatment programs -  This falls under both care and process improvement. When more information on health and disease is readily available at your fingertips, that insight will allow for both treatment programs to be more quickly adjusted, as well as earlier identification of appropriate treatment. Those benefits essentially trickle down: increased improvement on preventative treatment programs can reduce total cost of care, prevent medical episodes, and increase patient satisfaction.

·         Define major KPIs – Consistent, repeated use of analytics allow you to identify areas you deem most significant to business goals. Whether you’re aiming to increase collections, improve readmission rate, or reduce total days in A/R, business intelligence enables you to monitor fluctuations and major changes in your KPIS, allowing you to distinguish areas for improvement.

The reality of healthcare is that we’re just beginning to scratch the surface of business intelligence capabilities and the possibility behind data-driven, organization-wide improvement. For now, know that data analytics through BI is an enormously positive step to understanding and improving all facets of your practice.

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