Healthcare organizations are breaking down information siloes and adopting agile visualization tools
A sea of change in the healthcare industry has complicated how providers measure and use financial analytics. As healthcare organizations start to move away from the traditional fee-for-service model, they are no longer able to rely on a few variables, such as volume and payer mix, to understand what drives their financial performance.
Today, new outcome-based payment models demand a comprehensive financial analytics strategy that allows information to be more freely shared across departments giving the right people access to the information they need to make decisions. In this new landscape, it’s important to recognize in this new landscape that healthcare organizations must be able to connect to varied data sources to leverage their data as a strategic asset.
New Strategies in Financial Analytics
Innovative health systems and hospitals are starting to create financial analytics strategies that involve moving key data into visualization tools. These graphic depictions help them to identify their pain points. Uncovering what’s really happening in a program or department—a surgery department’s actual supply costs or how much time physicians or nurses spend on cases, for example—provides information that can be used to change behaviors.
However, traditional approaches to financial analytics are limited as they don’t provide relevant, and timely information to those who need to make informed decisions. The healthcare industry often reports and understands financial data from a departmental view. The cardiology team, for example, wants to know its revenue and expenses for cardiology only. They want to manage their department and their patients coming in the door, and that’s it.
This siloed, departmental view of financial reporting doesn’t recognize the important connections between departments, which are critical to the successful implementation of value-based patient care, risk contracts, and bundled payments. These new payment models place more emphasis on understanding not only which patients are coming in the door but also what quality of care they receive and how that care is coordinated across various departments.
In this outcomes-based environment, there are more challenges in understanding what drives financial performance. You need more than just pure financial data to know where you stand in some of these payment models and how your financial performance is affected. Traditional financial reporting does not include outcomes-based measures, thus getting insight into areas like quality, interdepartmental coordination, or episodes of care to better understand performance is very difficult. Even when an organization makes it a priority to include this type of data, it is a cumbersome and manual process to access the data and analyze it in a meaningful way.
Developing a Robust Technology for an Analytics Culture
The first step in creating an advanced financial analytics solution is understanding that your organization will need access to many different data sources. New payment models require advanced technology systems capable of pulling, processing, and tracking data on quality and costs, and also other outcome metrics. Healthcare organizations should focus on providing direct access to that information on an as-needed basis to decision makers through an agile visualization tool that enables them to manipulate, model and process data to develop business strategies and change behaviors.
An operating room manager, for example, would be able to look at start times, utilization, patient satisfaction, and patient outcomes on both a historic and day-to-day basis to develop insights into where improvements need to be made.
Once you have that kind of agile visualization tool, there are many ways to enhance its use, including adding predictive and prescriptive analytics. In the past, there has always been a consultant or business analyst who meets with a physician or administrative leadership to help them interpret their financial results. With current technology and the addition of the artificial intelligence products, there is now a way to deliver those insights through the tool.
It all starts, of course, with leadership making analytics and data a strategic priority for the entire organization. Leaders must also encourage programs and departments to take that important first step and break from their comfortable, silo-based organizational structures. By working together on enterprise initiatives, such as episode of care programs, shared savings, and risk contracts, departments and leadership should be able to deliver the clear message that departments and programs are aligned to achieve those initiatives.
Moreover, while financial analytics once resided solely in the finance department, there should be recognition that going forward it needs more support from other departments within the organization. Cross-functional analytics teams that include members from finance and clinical areas, as well as quality analysts, will bring much-needed expertise in care coordination, quality metrics, and patient satisfaction. Ultimately, having those cross-functional analytics teams in place will make it easier to affect change across the entire organization.
