Every multi-facility operator eventually faces the same discovery: two buildings report the same metric and mean different things by it. One counts a missed call from the moment the phone rings; another only counts it after the caller leaves a voicemail. One includes agency hours in overtime reporting; another does not. When leaders compare these numbers, they are comparing definitions as much as performance.
Standardizing metrics fixes this, but done poorly it can flatten real differences between buildings and create resentment. Here is how to do it thoughtfully.
Start with a metric dictionary
A shared dictionary is the foundation. For each measure, document:
- Name and purpose: why the measure exists and what decision it supports
- Definition: exact calculation, including what is included and excluded
- Data source: which system produces it
- Time frame: daily, weekly or monthly, and how periods are cut
- Owner: who is accountable for accuracy
- Notes on limitations: known data gaps or caveats
Keep each entry short. If a definition takes a page, the measure may be too complicated for operational use.
Choose a small common core
Resist the urge to standardize everything. Start with a core set that matters in every building, such as:
- Call answer rate and time to answer
- Call-light response time (median and the slowest tenth)
- Referral response time
- Overtime hours as a share of worked hours
- Census and admissions
- A/R aging and days in A/R
- Selected quality process indicators
Let buildings add local measures beyond the core, as long as they are clearly labeled as local.
Make comparisons fair
Use ranges and trends, not just rankings
A leaderboard invites defensiveness. Show each building's own trend and a range across the group so leaders can see who is an outlier and in which direction.
Adjust for context where it makes sense
Building size, resident mix, local labor market and physical layout influence results. Present context next to the numbers, such as bed count and payer mix, so readers do not draw hasty conclusions.
Compare like with like
Group buildings by similar characteristics when comparing. A small rural building and a large urban one may face different constraints.
Treat outliers as questions
An outlier is a prompt to investigate. The best-performing building may have a practice worth sharing, or a data issue worth fixing.
Handle the data engineering carefully
- Map each building's source systems to the common definitions. Different phone systems, call-light vendors and EHR configurations produce different raw data.
- Validate with local staff. A building administrator will quickly spot a number that does not match reality.
- Document changes. If a definition changes, mark the date and avoid silently rewriting history.
- Test before rollout. Run the new definitions in parallel with existing reports for a short period and reconcile differences.
Bring building leaders into the process
Standardization imposed from above often fails. Involve administrators and department heads in choosing definitions. Explain the purpose: a shared language that helps the whole group support each building, not a tool for punishment.
Offer something in return. A common dashboard saves building leaders from building their own reports, and the data can help them make their own case for resources.
Use standard metrics in regular rhythms
- Weekly: exceptions by building, with attention to anything moving the wrong way
- Monthly: trend review and cross-building learning
- Quarterly: definition review and retirement of measures that no longer serve a purpose
Make time in monthly meetings for a building to describe something that is working. Data points to where to look; people explain why.
Avoid these mistakes
- Changing definitions often
- Adding measures without retiring any
- Using the numbers to rank without context
- Ignoring local differences
- Letting the dictionary live in one person's head
A hypothetical example
Suppose a group discovers that its call-answer rate looks excellent in one building and poor in another, until the dictionary reveals that one counts calls transferred internally as answered and the other does not. After aligning the definition, the gap narrows and the real conversation begins about staffing at the front desk.
Closing thought
Good standardization creates a shared language without erasing each building's identity. The payoff is trust in the numbers, which is what lets leaders spend meetings on decisions instead of debating definitions.
CarePulse Analytics works with groups to map different systems onto common definitions, and a demo can show how your buildings would look side by side.