Laurel Borowski, MPH
Solutions Manager, Streamline Health, Inc.
When discussing the concept of Clinical Analytics (CA), many focus on how recent developments (ACA, the shift to value-based care, etc.) are accelerating the evolution of CA tools and methodologies. While these elements are certainly adding new emphasis on the need for CA, the desire for CA tools is nothing new. A recent conversation with a clinician at Montefiore Medical Center included the following statement: “Doctors love data. Clinical Analytics allows individual physicians to define what they want and get it. I use Clinical Analytics to better understand my own patients and their outcomes. Plus, the first run at the data is always a little rough. I usually need to refine the analysis to get at what I want. Clinical Analytics allows me to practice medicine with data.”
The challenge of CA hasn’t been lack of desire or need, but rather lack of access to simple, reliable tools that enable a DIY approach to analytics. CA empowers clinicians in the trenches of daily care delivery. DIY analytics provide quick access to the information you need without waiting for IT resources. When you give the most creative people on your healthcare team direct access to data, you enable creative solutions to be developed and quality of care to be rapidly improved. That’s when you can move the needle on care efficacy, delivery improvements and increased value.
When implementing a DIY Analytics program, consider the following basic needs:
- Start Simple: Start with a KPI, you don’t need to run a complex predictive algorithm in order to gain valuable insights into your patient population. Start with getting a handle on your population concentrating on different departments or high-risk disease areas.
- Gain Flexibility: Quality measurement rules for patient groups can be easily created to keep pace with the frequent changes to generally accepted and nationally mandated metrics.
- Immediate Results: The ability to run DIY analytics at the point of care allows you to find answers to how to treat patients like the one you see in front of you. You can run studies to immediately compare effectiveness treatment outcomes and interventions.
- Rapidly Discover: Consider patient cohorts or queries that can quickly and repeatedly be changed in order to examine the impact of those changes on the results. This allows the investigator to generate new questions that probe more deeply and quickly lead to answers.
- Easy and Timely Access to Data: A solution that empowers end users to build complex queries and evaluate complex conditions eliminates the need to compete for the availability of IT resources in order to create new functionality or reports. This easy access to data supports data-driven quality initiatives.
Healthcare is undergoing a fundamental shift to a value-driven business model. Capturing, measuring and monitoring the clinical data that defines value will be key to successfully transitioning providers to this new model. Clinicians are already the front line of care delivery; empowering them with DIY analytics will enable real-time assessments, actionable insight and near instantaneous feedback on efficacy and outcomes. That’s where true value will be realized for all stakeholders.
