HHCAHPS Says 86% of Patients Felt Well Communicated With. This Post Is About the Other 14%.

HHCAHPS Says 86% of Patients Felt Well Communicated With. This Post Is About the Other 14%.

The national HHCAHPS numbers for calendar year 2025 are out. Eighty-six percent of patients reported that their home health team communicated well with them. If you run an agency, you already know your own number and you already know it moves slowly, arrives late, and tells you almost nothing about which conversations went wrong.

That is not a criticism of the survey. It is a description of what a mailed survey with a 22 percent response rate can and cannot do. The useful question is what you do about the fourteen percent, and about the seventy-eight percent who never answered at all.

What the current national data actually says

CMS publishes national HHCAHPS results through the Provider Data Catalog. The current national file covers 2025 Q1 through 2025 Q4 and was released in July 2026. The headline measures:

Measure	National result
Team communicated well with patients	86%
Team gave care in a professional way	89%
Team discussed medicines, pain, and home safety	82%
Rated the agency 9 or 10	85%
Would definitely recommend the agency	79%
Completed surveys	1,007,318
Response rate	22%

Three things in that table deserve more attention than the 86 percent does.

The communication score is the second-highest number on the list. It sits above the recommend score by seven points. Patients rate the talking higher than they rate the overall relationship, which means communication is not the binding constraint on the composite — it is the part agencies have already mostly solved for the average patient.

The recommend measure is the low one at 79 percent. That is the measure most correlated with what an operator actually feels: referral relationships, family sentiment, complaint volume. It is also the measure furthest from any single interaction you can coach.

The gap between 1,007,318 completed surveys and a 22 percent response rate is the real story. Roughly four out of five sampled patients said nothing. Nonresponse in patient experience surveys is not random, and the patients hardest to reach by mail — the sickest, the most recently discharged, the ones whose care ended badly — are disproportionately the ones whose experience you most need to know about.

Why the composite is about your phones more than you think

The communication composite is not a question about your clinicians' bedside manner. Look at the actual instrument. The HHCAHPS questionnaire asks, among others:

• "In the last 2 months of care, how often did home health staff from this agency keep you informed about when they would arrive at your home?"
• "In the last 2 months of care, how often did home health staff from this agency explain things in a way that was easy to understand?"
• "In the last 2 months of care, how often did home health staff from this agency listen carefully to you?"

The first of those is an office function. Nobody's nurse calls from the car to explain a schedule change; a scheduler does, or a scheduler does not. Arrival-time communication is a contact center output that gets scored as a clinical one.

The second and third are split between the field and the phone. A patient who could not get a clear answer about a medication change when they called on a Saturday will answer "sometimes" to "explain things in a way that was easy to understand," and the clinician who visited on Monday will absorb the score.

This is the practical reason communication scores resist coaching. Agencies coach the visit and measure the relationship, and a meaningful share of the relationship happens on the phone.

The lag problem

Run the timeline on the current file. It covers care delivered from January through December 2025. It was issued in June 2026 and released in July 2026. A conversation that went badly in February 2025 reached the public data roughly seventeen months later, aggregated with thousands of others, attached to no episode, no staff member, and no date.

You cannot manage from that. You can benchmark from it, set a target from it, and report it to a board — but you cannot use it to find out what went wrong last Tuesday, which is the only timeframe in which anything can still be fixed.

What you can do is treat the survey as the confirmation layer and build a faster leading indicator underneath it.

And the sample is not the population

At a 22 percent response rate, the score describes the patients who filled out a survey. That is a real and useful population, but it is not your census. Every operator knows which episodes are least likely to produce a returned questionnaire: the patient who was rehospitalized, the family that was angry enough to switch agencies mid-episode, the patient with cognitive impairment whose mail is handled by someone who was not present for the care.

Those are the same episodes where communication most often broke down. Which means the direction of the bias is not neutral — the measure most likely understates exactly the failures you would most want it to catch. Your call records, by contrast, have no response rate. Every patient who picked up the phone is in them, including the ones who never mailed anything back.

That is not an argument to ignore the survey. It is an argument to stop treating it as the whole picture and start treating it as the slow, public confirmation of something you could have known sooner.

A hypothetical worth walking through

Consider an agency whose communication score sits at the national 86 percent. Steady, unremarkable. Over the same year, its inbound call log shows a recurring pattern: calls arriving between 4 p.m. and 6 p.m. asking whether tomorrow's visit is still on, most of them from the same two branches, most of them repeat callers.

Nobody has ever counted them, because they are logged as general inquiries and resolved in under two minutes each. They are, individually, a non-event. Collectively they are the arrival-time communication item, showing up eleven months before the survey does.

That is illustrative, not a case study. But the shape is common enough that it is worth checking whether it is true at your agency, and checking costs nothing.

What to do this week

• Pull your last 30 days of inbound calls and sort by reason code. If more than a fifth of them land in a generic bucket, your reason codes are not measuring anything and that is the first fix.
• Add one code: scheduling or arrival-time inquiry. It maps directly to a scored survey item. One code, one huddle, one month of data.
• Count repeat callers. Same patient or family calling twice in seven days about the same thing is the cleanest proxy you have for "did not explain things in a way that was easy to understand." It requires no analytics platform, just a sort.
• Look at your after-hours and weekend answer rate separately from your weekday number. Blended averages hide the exact window in which unanswered questions turn into survey answers.
• Take your five most recent low HHCAHPS communication responses and try to reconstruct the episode from call records. If you cannot, you have found the gap. That is a useful finding even though it is an uncomfortable one.

Why the 14% costs more than it looks like

A patient who felt poorly communicated with does not usually file a complaint. They disengage, decline the next visit, or their family moves them. The financial consequence shows up in episode volume long before it shows up in a public score, which is the argument we made in the hidden cost of patient churn in home health.

And the reason "the calls sounded fine" is not evidence: tone is a weak signal in healthcare conversations, where a calm patient can be a confused one. We wrote about that in why positive versus negative sentiment tells you nothing.

The category, briefly

The work of turning a year's worth of unstructured patient conversations into something you can count in the same week it happens is what call intelligence platforms do. SurfacerIQ builds in that category for home health, home care, and hospice contact centers.

This post is general information about publicly reported CMS quality data, not legal or reimbursement advice; how HHCAHPS results factor into your quality reporting and payment depends on program rules that change.

If you want help connecting your call data to your patient experience scores, talk to us.