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It is axiomatic across the healthcare world that, while appropriate standards must be met and required protocols must be followed, there is no “same-sized” approach to ensuring patient engagement and delivering quality care. Patients have unique needs and preferences, organizations specialize in different areas (e.g. pediatric care, sports medicine, eldercare, etc.), and physicians have individualized frameworks based on their training, research and experience.
Yet, despite this awareness, many hospitals are struggling from — or better stated, saddled with — a same-sized approach to capturing and leveraging health data. As a result, they are getting plenty of information, but it is not the accurate, data-driven insight they need to make the right decisions. In order to establish that critical competence, hospitals need to rely on analytics in three critical areas:
To solve problems, hospitals can create a list of options by reading journals, consulting other hospitals, having internal discussions, or even relying on hunches and gut feels. But analytics is necessary to ensure that hospitals get a full picture of all — not just some — of the options available to them; especially since it’s likely that the best-fit solution will only be revealed by in-depth analysis.
Leveraging healthcare data is not an administrative function; it is fundamentally a strategic one. This means that decision-makers need analytics to develop an action plan that separates wants from needs, establishes and ranks priorities, and determines not just what kind of data is required, but how that data will be exploited to achieve measurable, desirable gains.
Lacking analytics, hospitals have a destination in mind, but lack a practical way to get there. With analytics, they have the building blocks to create a realistic and functional action plan that drives them forward in the right direction.
After the best-fit option is selected from all available possibilities, and a robust plan is developed to turn aspirations into achievements, hospitals need analytics to evaluate results and validate strategic direction — and adjust accordingly.
It is also important to highlight that analytics in an evaluation context is not just about identifying course corrections. It is also about revealing what is working well, so that these gains can be optimized and integrated across the organization.
For example, a hospital may have a “hunch” that unassigned patients (i.e. those who do not have a primary care physician and are admitted through emergency) experience longer stays, because their medical history is not readily available. Based on this speculation, the hospital may believe that the best way to reduce length of stay is to make significant adjustments to the on-call physician assignment process, or implement a hospitalist program. Both of these options are rational and logical responses to the problem (albeit complex and costly). But are they the correct solutions? Not necessarily!
This is because an in-depth analysis of assigned and unassigned patients may reveal that, contrary to belief, the latter group experiences a comparatively shorter length of stay. Based on this startling new premise — one that is based on analysis-driven hard data vs. anecdotal evidence and speculation — the hospital is empowered to explore new options that were not previously unavailable, yet make all the difference, such as choosing to improve service lines.
Notably, this example also illustrates that analysis does more than solve the specific problem under focus. Improving service lines increases overall efficiency, which is a win for all patients assigned and unassigned — just as it is for staff.
Hospitals know that while adopting established standards, credible frameworks and best practices have their place, delivering healthcare is not about following a generic script. It is about treating real people. Indeed, just as all politics is local, all healthcare is personal.
In the same spirit, hospitals need to recognize that taking right-sized vs. a same-sized approach to leveraging healthcare data is both wise and necessary. When that happens, various systems and the volumes of data they generate function to serve hospitals — not the other way around.
At Polaris, we help hospitals access and exploit accurate, trusted and actionable analytics, in order to evolve from same-size information to right size insight — which is the key to making faster, smarter and safer decisions.
To learn more about our solutions, technologies and approach contact Polaris today.
