When a car manufacturer wants to boost quality, they measure things like production defects, failure rates, and customer complaints. A coffee shop looks at order remakes and customer surveys. But a hospital? Take all of those things, multiply them by the number of cells in a human body, scramble them up with a thousand inconsistencies, and now try to measure them.
Metrics are harder with healthcare.
Why? Because healthcare data is not like other data.
For starters, the basic elements of healthcare are more nuanced—and less predictable—than most industries. There’s no way to automate illness, humans, and care. And, when it comes to the intricate workings of disease and injury, any metric—like surgical complications—could be impacted by many factors, so even measuring it can be complicated. Should this complication be attributed to comorbid conditions? To the quality of the post-discharge care? The patient’s age? A recent fall? All of the above?
The truth is, tracking information and measuring improvements is simply more challenging in healthcare. And if you work in healthcare quality, we’re not telling you anything new. You know this firsthand.
So what’s the solution?
The answer has three parts.
1. First, create a standard definition for every metric.
Isn’t it enough to just name the metric? Unfortunately, no. One of the biggest factors creating metric chaos is when everyone thinks they’re measuring the same thing the same way, but… they aren’t.
For example, maybe your finance team is measuring Length of Stay based on the way patients are billed (in 24-hour segments that start at midnight), while your performance improvement team is measuring it based on the actual number of hours a patient was in the facility. So when both teams show up to a meeting with Average Length of Stay reports, and nothing matches, what happens next?
Are you able to quickly see what’s causing this discrepancy? Can you find the definitions of each team’s metrics and understand why they differ? Or are you pulling your hair out to understand the true length of stay at your organization?
Creating metric definitions is the foundation for driving quality without driving yourself mad.
Here’s how that process might look:
- Identify an owner for each metric.
Select a person or team that will be responsible for defining each measurement and tracking it ongoing.
- Research the metric.
Talk to those who are working with this measurement—the analysts who report it, the leaders who review it, and the nurses who, frankly, live it. What are they seeing? What do they need? Also look at industry standards for this metric. Are there external definitions that need to be considered? Does CMS require a specific methodology? Do payers require something different? If so, will you need to define two different metrics instead of combining them into one?
- Write the metric name and definition.
Once you have all the insights, create a clear name for the metric and a detailed definition—with inclusions and exclusions fully spelled out. In the Length of Stay example above, the finance team and the performance improvement team each need to continue measuring their metrics separately, because they each have specific needs. In this case, you would need to clearly label these as two different metrics—perhaps Length of Stay/Billing and Length of Stay/Actual—each with its own definition.
- Write the code.
Work with your metric developer to build the metric that will be used throughout your organization. Make sure it matches the agreed-upon definition. And validate, validate, validate.
- Integrate the metric into a healthcare-specific data governance tool like Compendium.
Input your metric into your central data governance tool. We recommend Compendium. It’s the only data catalog that includes a Healthcare Metric Hub, and it’s the only one built to handle the unique needs and complexities of healthcare data.
2. Next, link all your reports and dashboards to your healthcare metric hub.
Be sure everyone is pulling data from the same metric repository. And be sure this metric definition can be automatically updated as needed, organization-wide, without needing to manually alert every developer and update every report.
Here’s how that process can look:
- Partner with your BI developers to consistently link their work to this standard metric definition, instead of creating something new for each report and dashboard.
- Include the written metric definition and the metric owner in your metric hub so anyone can dig into the details of what’s being measured, what’s included and what’s not, when the definition was created, who owns it, and where to go with questions.
And remember, Compendium is the only data catalog that includes a free Healthcare Metric Hub. Other data catalogs require further investment to create a metric hub, and even then, they may not be able to handle the robust definitions of healthcare metrics.
3. Now you’re ready to track quality—based on reliable metrics.
Imagine if you could view dashboards and run reports without having to wonder what the measurements are based on or worry whether they actually reflect reality. That’s how life can look with the Compendium Healthcare Metric Hub in place.
Once you’ve fully defined your metrics and linked your organization to your healthcare metric hub, you can:
- Monitor and validate each metric on an ongoing basis to ensure it continues to measure what was intended.
- Be confident that if there’s a change to underlying data, it won’t derail your metrics.
- Set up goals and performance alerts that track when your metrics improve or drop.
A healthcare metric hub is the key.
The reality is, you can’t effectively increase quality in a healthcare setting until you have metrics and measurements you can trust. The Compendium Healthcare Metric Hub is the only tool that’s built to handle healthcare data in a way that will set your organization up for success, without the endless frustration of metric chaos.
And Compendium is far easier and faster to implement than you think.