Posted by: adelvecchio
business intelligence, data visualization, payers, Quality improvement
Guest post by Zach Watson, content manager, TechnologyAdvice
For large healthcare organizations, aggregating and analyzing data isn’t sufficient to improve business and care performance. Accountable care organizations, patient-centered medical homes, and other new models of care delivery require cross functional teams and greater integration of healthcare services. Any findings discovered by healthcare data analysts must be packaged in a consumable fashion for a range of audiences.
This enables the data to be more easily processed and used across departments. Luckily, the barrier to entry for using business intelligence or data visualization is lower than ever before. Some medical software suites now include basic data visualization capabilities. This makes it easier for executives to partner with analysts and produce effective data visualizations that convey clinical insight.
It makes sense to use data visualizations when possible because humans process information more easily when it’s presented with a strong visual element. Rows and columns of numbers may entice an analyst, but for the majority of their audience, such a presentation requires a heavy amount of explanation.
The most insightful reports often contain complex data sets that have been sliced and diced from multiple perspectives to arrive at an actionable conclusion. These reports usually present a mixture of regulatory, financial, and clinical data, making user-friendly visualization even more important.
As business intelligence has become more widespread, templates have emerged for common healthcare data visualizations. As a side note, these visualizations require the implementation of an enterprise data warehouse to normalize and order the data — which should be standard practice for large healthcare organizations using data at this scale. Let’s look at a few of the most useful visualizations for healthcare organizations.
Payer reimbursement mix
In order to effectively keep pace with the regulatory and reimbursement changes happening throughout the healthcare system, providers should record and analyze reimbursement trends on a per payer basis — with a particular focus on payers that make up a large percentage of a provider’s overall revenue.
A payer mix visualization displays the names of a hospital’s top payers in descending order with the percentage of total reimbursement each payer represents to the provider. In a complementary column, displaying the yearly payments for each payer helps executives quickly analyze broad reimbursement trends.
If providers have the capabilities to break down data by facility or location, then it’s possible to create a dashboard that can highlight differences in regional reimbursement rates. This type of payer mix has its benefits, but adding gains and losses data will maximize this visualization’s usefulness. This can be accomplished with a column of deviation charts that correspond to each payer on an annual basis.
A yearly visualization allows executives to view and share information about annual gains and losses on a per payer basis. Again, adding an interactive element for sorting historical data can increase the dashboard’s utility. Other options for data segmentation include distinct outpatient or inpatient views.
Analyzing historical and current payer trends and matching them with gains and losses allows providers to more easily identify which procedures, facilities, and patient populations cause the largest drain on resources.
Quality improvement initiatives
Once a provider’s leadership team has a better understanding of reimbursement movement in the payer arena, they can focus on improving their internal processes to achieve the three main goals of healthcare: lower costs, better patient outcomes and improved patient experiences.
These types of quality improvement initiatives require significant data analysis, with best of breed systems combining clinical, cost, billing, and ICD-9 or ICD-10 codes to sort and rank clinical processes. Once the data is structured and presented in graphical form, it’s best practice to look for significant variations in cost, which usually represent large variations in care quality.
Presenting this data as a bubble chart helps organizations identify the processes with the highest degree of variation compared to the number of times those processes occur. This type of visualization makes it easier to identify cross-departmental areas for improvement that will affect outcomes and resource use.
A number of other visualizations are quickly becoming commonplace in healthcare. Heat maps are a great method for presenting trends on patient populations at a geographic level, but these visualizations require data from each county in each state, placing them out of reach for all but the largest healthcare organizations.
Data analytics is quickly becoming embedded in the operating and decision making processes of healthcare organizations. Once the analysis is complete, it’s vital that executives supply stakeholders throughout their organization with a way to intuitively understand the conclusions that have been uncovered. Better data visualizations regarding payer reimbursements and quality improvements are becoming two common areas for analysis that can help organizations convey actionable findings.