There’s a ridiculous amount of data flowing through medical practices and billing companies 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 – from both a patient and organizational level. It’s not just about capturing and managing data anymore, it’s about interpretation. How can you transform data – from management to analysis – into insightful information that will drive process improvement initiatives?
Business Analytics in Healthcare
Because of the heightened demand for value and transparency, one tool many organizations are beginning to embrace is healthcare analytics, particularly through business and clinical intelligence software. When you give analysts the means to capture and analyze data, you empower them to transform your practice into one with a data-driven, value-based culture. You initiate a chain reaction: Empowering the users, making better decisions as a provider, and improving both business operations and patient outcomes.
Medical billing is hard, that's where we come in.
A little background knowledge is required to fully understand the power of this tool. All data must go through a particular set of stages before an analyst can achieve meaningful analytics:
- Data capture – It all begins with the way people and devices produce and capture data, which must be done efficiently (is the data collected in a timely manner?) and accurately (is the data relevant to the analytical needs of the organization?).
- Data acquisition – Analysts must collect data from multiple sources throughout the organization to produce 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 including:
- RIS – For radiologist interpretations
- PACS – All picture archives
- EMR – For clinical notes
- Clinical Decision Support Systems
As a manual process, it's nearly impossible to pull data into a single location and format while ensuring that all data points are speaking each other (that they’re linked by a common identifier, either patient or provider) without creating errors. As a result, analysts may spend more time collecting data as opposed to transforming data into meaningful analytics. That’s where business intelligence comes in. Tools like ImagineIntelligenceTM allow users to integrate multiple data sources right into the software and under one platform.
3. Data analysis – Once the data is captured and tied together, the analysis process can finally begin. Three important steps in data analysis include:
- Evaluation – If analysts don’t understand the data they’ve collected, they can’t effectively communicate their findings with their audience (executives, staff, etc.) Analysts should take the time to explore the 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?
- Interpretation – How will you interpret this information in such a way that all levels of the organization will understand?
- Presentation – The analyst should 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 identifies the problem you're solving for?
Benefits of Business Intelligence in Healthcare
1. Reduce hospital readmissions – Business Intelligence tools 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.
2. 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 allow you to predict future trends based on factors like revenue and billing costs.
3. Improve and develop treatment programs – This falls under both care and process improvement. When more information on health and disease is readily available, that insight will allow for both treatment programs to be more quickly adjusted, as well as earlier identification of appropriate treatment. Those benefits trickle down: increased improvement on preventative treatment programs can reduce total cost of care, prevent medical episodes, and increase patient satisfaction.
4. Define major KPIs – Consistent and repeated use of analytics allow you to identify significant areas 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 key performance indicators and distinguish areas for improvement.
Utilizing analytics allows you to discover insights that can drive care, process improvement initiatives, and financial stability of your organization. The reality of business intelligence in healthcare is that we’re just beginning to scratch the surface of its capabilities and the possibility behind data-driven, organization-wide improvement. Business analytics in healthcare is an enormously positive step to understanding and improving all facets of your practice.