Almost every building can tell you roughly how quickly the phones get answered. Ask how they know, and the answer is usually a feeling: the front desk seems busy, or a family member complained last week. When a number does exist, it is often a single average pulled from the phone system, and that average can be quietly misleading.
Phone performance matters in long-term care because the caller is rarely casual. It might be a family member checking on a resident, a hospital discharge planner with a patient who needs a bed today, or a physician's office returning a call. Measuring those calls well is one of the simplest ways to protect both resident relationships and admissions.
Why a single average misleads
An average blends the easy calls with the hard ones. Suppose most calls are answered within a few rings, but a handful sit for several minutes or roll to voicemail. The average may still look acceptable, while the callers who waited longest form their opinion of your building from that one experience.
Better measures look at the shape of the data:
- Median answer time, which shows what a typical caller experiences.
- The slow tail, such as the share of calls that wait longer than a threshold you choose (for example, 60 seconds).
- Abandoned calls, meaning callers who hung up before anyone answered.
- Calls that went to voicemail, and how long it took to call back.
Define what counts as answered
Before you chart anything, agree on definitions. A call that rings through to a general voicemail box has been connected, but it has not been answered by a person. A call transferred three times may technically be answered at the first pickup and still leave the caller frustrated.
Decide in writing:
- When does the clock start, at the first ring or when the caller enters a queue?
- What counts as answered: a live person, or any pickup including an auto-attendant?
- How are transfers and holds treated?
- Are internal calls excluded, so the numbers reflect outside callers only?
Consistent definitions matter more than perfect ones. If every building measures the same way, trends mean something.
Slice the data by time and by line
The most useful insights usually come from breaking the numbers apart.
By hour and day
Most buildings have predictable pressure points: the start of the day, shift change, mid-morning when therapy and activities draw staff away, and the hour after lunch. A heat map of missed calls by hour and weekday shows where coverage thins. The fix might be as small as staggering a break or routing calls to a second person during one specific window.
By line or department
Admissions, business office, nursing stations and the main number each behave differently. A main line that performs well can mask an admissions line that rarely gets picked up. Measuring each separately keeps problems from hiding inside a combined figure.
By caller type, where you can
If your phone system or call log can distinguish known referral sources or families from unknown numbers, look at how those calls fare. You do not need to identify individuals. Even a rough split can tell you whether the people most important to your census are reaching you.
Pair the numbers with a callback standard
Answer time only tells half the story. A missed call that is returned within fifteen minutes is a very different experience from one that is never returned. Track callback time for abandoned calls and voicemails. Many operators find that adding a simple callback standard, with a visible count of calls still waiting for a return, changes behavior faster than any answer-time goal.
Avoid the common traps
- Measuring only business hours. Calls after hours and on weekends are often where families feel the most anxious.
- Ignoring seasonality. A holiday week or a flu-season surge changes call patterns. Compare like with like.
- Using the data to punish. If front-desk staff believe the numbers will be used against them, they will stop trusting the dashboard. Frame it as a staffing and process question first.
- Looking at it once. A one-time audit is useful, but the real value comes from watching the trend week over week.
Turning the data into a routine
Start small. Pick two or three measures, such as median answer time, abandoned call count and slowest hour of the week. Review them for ten minutes in a weekly leadership meeting. When a pattern shows up, assign one person to test one change, and look again next week.
CarePulse connects to the phone systems buildings already use and turns call logs into dashboards by hour, line and day, so you can see these patterns without exporting spreadsheets. If you would like to see what your own call data looks like, a short demo is a good place to start.