How to Fill the Growing Patient Data Gap Between Hospitals and Post-Acute Care Organizations

Hospital Data Gap

To increase the likelihood that discharged patients will stay on their respective paths to recovery vs. return to the ER or get readmitted, hospitals need to monitor patients through the continuum of care as they engage various post-acute care (PAC) organizations, such as inpatient rehabilitation facilities, skilled nursing facilities, home health agencies, and so on. Yet in order to achieve this critical objective, hospitals must get timely and accurate information from these external sources — and that is causing a major patient data gap.

Lack of Alignment

To begin with, it is important to point out that the reason for this disconnect is not a lack of cooperation. PACs understand the importance of sharing patient data with hospitals. After all, regardless of what the sign on the building or door says, the focus of all health care organizations is always on what is best for patients. Everyone knows this and agrees with it. In fact, it is axiomatic and belongs on the “goes without saying” list.

The problem, however, is rooted in the day-to-day practical application of this lofty collaborative vision. Simply put: there is little alignment and standardization among the IT systems and products used by different PACs. To say that this creates a messy situation for hospitals is an understatement. It is dangerous, because it triggers two things that are unacceptable and unsustainable: reduces results and increases risks.

There is little alignment and standardization among the IT systems and products used by different PACs.

At the same time, this hazardous scenario was predictable. Wading into population health and data integration with PACs is new territory for hospitals, and there are only a few good models that provide a functional framework for moving forward. Basically, most hospitals are obliged to improvise, experiment, iterate and “figure things out as they go.” And while that approach may be fine for an artistic pursuit like painting, it is antithetical to what hospitals need and patients expect.

What’s more, most population health software vendors are developing or selling applications that are geared towards multiple buyers — since they obviously need to generate revenues and make profits. That is perfectly fine. But what is not fine, is that this model forces hospitals to fit into the software’s methodology, structure and approach. It is similar to how EMR software dictates how physicians must do certain things; and, unsurprisingly, it is creating (and will continue to create) just as much dissent and frustration.

Growing Pains and Alarm Bells

In time, it is possible that software will become more intelligent, flexible and customizable, and will therefore — at least to a tolerable degree, and to an acceptable extent — fill some of the information gap between hospitals and PACs. But that possibility is still several years away. The population health software industry is in its infancy. There will be many growing pains (with emphasis on “pains”) experienced by hospitals before the situation becomes manageable, and the alarm bells can stop ringing.

Right now and in the foreseeable future, hospitals need a practical and realistic way — logistically, technologically and financially — to get the patient data they need from PACs that they do not govern or control, and who in turn use disparate IT systems and products that were not designed for information sharing. That is where customized data analytics makes a transformative difference.

The Solution: Customized Data Analytics

Customized data analytics is a proven model that connects hospitals with PACs, so that they can efficiently and effectively monitor patients through the continuum of care. The model is based on seven defining principles:

  1. Investing time to understand each hospital’s unique priorities and objectives.
  2. Positioning hospitals to get the data they need as quickly as possible.
  3. Making data easy to access and consume (e.g. data visualization).
  4. Ensuring that data transfer is secure.
  5. Carrying out ongoing refinements to improve efficiencies and outcomes.
  6. Staying flexible and nimble as hospitals work more closely and collaboratively with PACs.
  7. Using a concierge business model and all-inclusive pricing to ensure cost-effectiveness.

The Bottom Line

These seven principles noted above integrate to do what matters most: help hospitals improve results and reduce risks. This makes it more than the best way for hospitals — and the PACs they partner with — to move forward on an increasingly data-driven healthcare landscape. In the big picture and long run, it is the only way.

Next Steps

At Polaris, our in-house healthcare analytics experts use a comprehensive set of scalable tools to build customized reports and dashboards that integrate data from disparate systems — and close the patient gap between hospitals and PACs.

To learn more about our solutions, technologies and approach, contact the Polaris team today.

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