Here is an uncomfortable thing about healthcare call center metrics: most of the benchmarks you will find for them are not about healthcare.
Search for a target first-call resolution rate and you get figures drawn from retail, banking and telecom, repeated across vendor pages until the original source disappears. Search for an acceptable abandonment rate and you find numbers with no study behind them. The healthcare-specific literature is thin, and the gap gets filled with confident-sounding percentages.
That matters because these numbers get reported upward. A practice manager who tells the executive team the industry standard is 70% first-call resolution is making a claim they cannot support, and anyone who checks the source will find out.
Here we do something different. For each of the five metrics below, we give a benchmark where a real one exists, name what population it describes, and say plainly when there is not one.
Why Healthcare Call Center Metrics Matter More in 2026
Patient access has moved up the agenda. When MGMA polled 236 medical group leaders in December 2025 about their top patient access focus for the coming year, 22% named phone access, putting it alongside no-shows at 27%, online scheduling at 24%, and wait times at 21%, according to MGMA.
There is no dominant priority there. Roughly a fifth of leaders picked each of four problems, and phones sit in the middle of the pack.
What has changed is who asks. Healthcare call center metrics used to live inside the practice as operations data, reviewed by the people who ran the phones. They are increasingly reported upward as patient access data, which puts them in front of executives and board members who do not know what average handle time is and will not take “it’s fine” as an answer. Patients do not see these numbers; the people setting your budget increasingly do.
That raises the bar on provenance. If you are putting a number in front of your governing board or your executive team, you need to know where it came from and what it describes.
First Contact Resolution (FCR)
First contact resolution is the share of callers who get what they called for without a callback, a transfer, or a second attempt. Of the healthcare call center metrics here, it tracks most closely whether a patient actually got helped, which is why it belongs first.
It is also the one most likely to be quoted at you with a fabricated benchmark.
Here is the real one. Across all industries, only 5% of call centers perform at the world-class FCR standard of 80%, and the benchmark average sits at 71%, according to SQM Group, which has published FCR benchmarking for more than two decades.
No healthcare-specific published FCR benchmark exists that we have been able to locate. Anyone quoting you a healthcare FCR standard should be able to name the study, and usually cannot.
The distribution is more useful than the headline number anyway. Across industries in 2024, the aggregated FCR average was 69%, with 46% of call centers landing in the 70% to 79% band and 49% falling below 70%, per SQM’s 2024 benchmark data.
So roughly half of all call centers resolve fewer than seven in ten calls on the first attempt. If your practice sits at 68%, you are not an outlier. You are the middle of the distribution, which is a very different conversation than a fabricated 75% standard produces.
Why the gap persists is the subject of a separate look at healthcare call center automation. Here the point is narrower: measure it honestly, and compare it to a number you can source.
Average Handle Time and Speed of Answer
Average handle time is the mean duration of a call from answer to wrap-up. Speed of answer is how long the patient waits before a human or a system picks up.
These two get confused constantly, and only one of them is a patient-facing metric.
Average handle time is an internal efficiency measure with a well-documented failure mode: optimize it directly and first-call resolution falls. Agents rush, patients call back, and the practice trades a metric it reports for one it does not. Watch it as a diagnostic; do not target it.
Speed of answer is the one patients experience. Of the medical call center metrics on this list, it is the closest thing to a direct measure of access.
Real numbers exist here, from a peer-reviewed source. In a study of Veterans Health Administration call centers, average speed of answer fell from 87 seconds in October 2014 to 69 seconds in September 2016, according to Griffith and colleagues in the American Journal of Managed Care. VHA’s own performance goal is an average speed of answer of 30 seconds or less.
What that describes: one integrated health system, measured over two years. It is not a national benchmark and should not be presented as one. It is useful because it is specific: real numbers, a published target, and the distance between them.
Even in a system actively working the problem, 69 seconds was the improved figure against a 30-second goal, worth knowing before you decide your own numbers are unusually bad.
For how these healthcare call center metrics get used day to day, our companion piece on contact center AI and actionable metrics covers the reporting side.
Patient Satisfaction (PSAT)
Patient satisfaction at the call level is distinct from visit-level satisfaction, and practices routinely conflate them. A patient can rate their care highly and their experience of reaching the practice poorly. If your only instrument is a post-visit survey, the phone experience is invisible in it.
The Griffith study’s central contribution is establishing that this connection is real and measurable: call center performance affects patients’ perceptions of access and satisfaction. The study reports its findings as odds ratios rather than as a simple correlation, so the honest summary is directional. Better call center performance is associated with better patient perceptions of access, and the relationship held across a large integrated system.
The practical difficulty with PSAT is measurement design. Three things distort it more than anything else:
- A survey sent days later measures memory. One sent immediately measures relief.
- If you survey only callers who reached someone, you have excluded everyone whose experience was worst.
- Who answers. Response rates skew toward the very satisfied and the very frustrated.
The second matters most. The patients who abandoned the call are the ones whose experience you most need to understand, and they are the hardest to survey. Which is a good argument for treating abandonment rate as their proxy.
Abandonment Rate
Abandonment rate is the share of callers who hang up before reaching anyone. Of the five metrics here, it is the most honest, because it is a count of people who gave up rather than a judgment about quality.
It is also the one where a real healthcare figure exists.
In that same VHA study, the average abandonment rate fell from 12.0% to 8.3% between October 2014 and September 2016, per the American Journal of Managed Care. VHA’s published performance goal is an abandonment rate of 5% or less.
Again, this is one health system rather than an industry benchmark. But a published target of 5% from a large integrated system is a far better reference point than the vendor-sourced ranges that circulate without attribution.
What abandonment costs is harder to quantify than most content admits: it depends on payer mix, appointment types and what the caller wanted. Rather than assert a dollar figure, we worked the arithmetic openly in a separate piece on the cost of in-house call center services.
One operational note. Abandonment concentrates. Monday mornings, the hour after lunch, and the period right after a closure tend to carry most of it. A monthly average hides its own cause.
This is the pattern healow Genie’s AI Agent is built for. Routine calls get answered when the volume spikes, so the staff you have are handling the conversations that need a person rather than working through a queue.
EHR Integration Efficiency: The Metric With No Benchmark
This one is healthcare-specific, which is exactly why the benchmark literature has nothing to say about it. There is no cross-industry equivalent, so nobody has published a standard.
That does not make it less important. It may be the most important of these healthcare call center metrics, because it determines whether the other four can move at all.
The measure is straightforward: how often is a call resolved without the person handling it leaving the patient’s record, and how often does a call require a callback because the information was not available in the moment.
Consider what happens without it. A patient calls about a referral. The person answering confirms identity and takes a message but cannot see whether it was sent, so the call ends in a promise to call back. That call was answered, handled promptly, and resolved nothing, and it counts as a success in four of your five metrics.
This is why FCR without EHR integration tends to plateau. The calls that fail to resolve are disproportionately the ones needing information the answering system cannot reach.
healow Genie is an EHR-agnostic solution that can be used alongside the EHR of your choice, and it works with many telephony systems, so routine calls can be resolved against the record rather than routed around it. Where information is not available or a question needs clinical judgment, the call goes to a person with the context already attached.
Two things to measure if you never have: the share of calls that end in “someone will call you back,” and how many of those callbacks happen the same day.
Putting Your Healthcare Call Center Metrics to Work
A few practical notes on reading all five healthcare call center metrics together.
Review quarterly, not weekly. Contact center data is noisy at short durations and small sample sizes produce conclusions that reverse the following month. Weekly numbers are for spotting operational problems. Quarterly numbers are for decisions.
Never optimize a single metric. The classic failure is driving average handle time down and watching first-call resolution follow it. Read the five as a set, and treat a metric that improves while another degrades as a warning rather than a win.
Expect the denominator to change. This is the one most practices miss. When routine calls start being handled automatically, the calls still reaching your staff are the harder ones by definition. Average handle time will rise. That is not a regression, and a year-over-year comparison that ignores it will be read backwards. Annotate the change in whatever you report.
Segment before you conclude. Abandonment by hour of day, FCR by call type, speed of answer by day of week. The aggregate hides the actionable part.
Patients increasingly expect access on their own schedule rather than the practice’s. These healthcare call center metrics are how you find out whether you are meeting that expectation or assuming you are.
Frequently Asked Questions (FAQ)
Are there healthcare-specific call center benchmarks, or only cross-industry ones?
Mostly cross-industry. The widely quoted first-call resolution benchmarks come from all-industry data, and no published healthcare-specific standard exists that we can source. Health-system figures do appear in peer-reviewed research, but describe individual systems. For healthcare call center metrics, your own trend plus a published target beats a borrowed average.
How does EHR integration impact call center efficiency?
Without integration, a call center can confirm identity and take a message, but it cannot resolve anything requiring information in the record. Those calls end in callbacks, which count as answered but not resolved. Integration is usually the difference between a first-call resolution rate that improves and one that plateaus.
What metrics best indicate patient satisfaction?
No single measure is sufficient. Use several together: direct surveys, verbal feedback, online reviews, and the operational measures your contact center produces, including first-call resolution, speed of answer and abandonment rate. Abandonment is a particularly useful proxy, because it captures the patients who never reached anyone to be surveyed.
How often should healthcare call centers review their metrics?
Quarterly for decisions, weekly for spotting problems. Short durations and small samples produce conclusions that reverse the next month. Quarterly reviews give you enough volume to distinguish a real trend from noise, while weekly monitoring still catches an outage or a staffing gap before it compounds.
How do AI solutions affect traditional call center metrics?
They change what the numbers mean, not just their values. Routine calls get resolved automatically, so the calls reaching staff are harder ones and average handle time typically rises. First-call resolution and abandonment usually improve. Annotate the shift in your reporting, or a year-over-year comparison will read backwards. See what that looks like for your practice.
What to Take Into Your Next Review
The five healthcare call center metrics above are the ones worth managing. What makes them hard to manage is how many of the numbers attached to them turn out to be unsourceable, which is why every figure here names its provenance and says plainly where a healthcare benchmark does not exist.
If you do one thing with this, do the segmentation. Abandonment by hour, first-call resolution by call type, speed of answer by day of week. Almost every practice that finds a real problem finds it there rather than in the monthly average.
And when the routine calls are being handled, watch what your team does with the hours. That does not show up in any of the five, and it is usually the reason the numbers moved.
Start with one number: pull your abandonment rate by hour of day and find the peaks. If that is where your access problem lives, see how healow Genie handles those hours. For the arithmetic behind that number, read what missed patient calls actually cost.
