Healthcare organizations have mastered the art of data collection. But in order to be forward-looking, they need to focus on how to turn their data into valuable information.
For what it’s worth, most hospitals and health systems have realized the value in investing in big data. They’re eagerly raking in a plethora of data, focusing solely on the collection aspect.
But that’s insufficient!!!
“The real story is: How do you have data that’s accessible that can actually become information? Because data is not information.
Most healthcare organizations have gotten the data gathering process down pat, and they’ve become experts at utilizing data to report what happened. However, the industry needs to keep moving forward so that data can be used to get descriptive insights, predictive insights and prescriptive recommendations.
Systems are clearly impeded from making good use of the data they have. Part of the problem is the fact that much of the data is siloed.
For other organizations, it’s simply a budget issue. The majority of health systems can hardly obtain the financial resources to maintain their existing tools, let alone implement new processes and programs.
When a hospital does hop on the bandwagon and begin to manage data, it’s often pulled into believing in a one-size-fits-all model. Every tool and solution that a certain hospital utilizes will work for me, the hospital thinks.
Each hospital has a different patient population and budget, meaning it requires its own unique solution.
The need for better data integration is especially applicable in this day and age as the healthcare sector pushes for “value-based care”.
Since the industry is moving toward shared risk models, figuring out how to use data is more important than ever. Health system leaders need to ask, How do we manipulate and manage our data? How can we use it to make the lives of our clinicians easier?
On top of asking these questions, everyone from payers to providers needs to be finding ways to share data with each other. Only by doing so can the healthcare field glean meaningful insights and information.
Becoming a data-centric entity. But it also boils down to planning for the long term. Instead of focusing solely on installing one-off solutions and collecting data, systems must consider their ultimate goals.
The huge potential for big data applications in the future, the report identifies the following 9 strategies for healthcare organizations venturing into the realm of big data:
1. Implement a data governance framework– A carefully structured framework for enterprise-wide data governance is arguably the first and most critical priority to ensure the success of any effort to leverage big data for health care delivery.
2. Engagement providers– Engaging providers is critical to changing the culture of resistance to new approaches to data collection and analysis.
3. Foster competition and transparency– Health care organizations are attaching monetary incentives to measuring and looking at data; displaying peer and colleague data with respect to patient satisfaction and quality metrics; and using dashboards, all in an effort to leverage competition and improve performance among clinicians.
4. Bake analytics into training– More institutions are recognizing that physicians and nurses both need training in analytics to understand how big data tools add value to overall health care performance.
5. Provide for flexibility in information transference– There is a growing recognition that work and learning styles vary among clinicians; facilities are demonstrating a growing willingness to deliver data in multiple ways based on clinician preference and style.
6. When possible, choose in-house solutions over vendor-generated solutions– At times the inflexibility of some vendor-generated solutions can be a major obstacle to leveraging big data technology in a given organization.
7. Create simple, understandable tools such as dashboards for clinicians on the front lines to visualize incoming data– Organizations should strive to update processes and develop capabilities to enable tool use, and focus on real- or near-real time clinical decision support.
8. Don’t Scale up, Scale out– Some organizations may be prone to lean toward replacing their older servers with bigger and more powerful servers.
9. Close the Quality Loop– Achieving health care transformation requires dramatic and sustainable changes to the structure and processes of health care.