EULAR Rheumatology Open 2025 · Peer-reviewed · Open Access
Clinically evaluated.
Nixi AI was tested in everyday clinical practice as part of a peer-reviewed, prospective real-world observational study, on exactly the kind of consultation that makes documentation hardest: long, complex rheumatology conversations with disease course, medication changes and multiple diagnoses. 88 consultations, 108 patients. The result: documentation time was reduced in 82% of cases, no major errors, and not a single patient declined to participate.
Last updated: May 2026
Study at a glance
| Title | Ambient AI scribes in rheumatology: early real-world clinician and patient experience |
|---|---|
| Authors | Dr. med. Johannes Knitza (ORCID 0000-0001-9695-0657), Institute for Digital Medicine, University Hospital Marburg · Dr. med. Peer Aries, Dept. of Rheumatology, Immunologikum Hamburg & University Hospital Giessen-Marburg |
| Journal | EULAR Rheumatology Open |
| Year | 2025 |
| DOI | 10.1016/j.ero.2025.12.002 |
| Licence | Open Access · CC BY 4.0 |
| Study design | Prospective real-world observational study, single-centre |
| Sample | 88 consultations, 108 patients |
| Setting | Rheumatology practice, Germany |
| System studied | Nixi AI (ambient AI documentation) |
Primary outcome
Documentation time reduced in 82% of consultations.
In 72 of 88 consultations the treating rheumatologist estimated documentation time was reduced. In 62 of 88 a saving of two to five minutes was reported, in 10 of 88 more than five minutes. These are the clinician's estimates, not measured times.
72 von 88 consultations where the treating rheumatologist estimated documentation time was reduced
Full breakdown. Perceived time change per consultation:
| Perceived time change per consultation (n=88) | n=88 |
|---|---|
| Documentation time estimated as reduced | 72 of 88 |
| → of which 2–5 minutes | 62 of 88 |
| → of which more than 5 minutes | 10 of 88 |
| No meaningful change | 13 of 88 |
| Documentation time increased | 3 of 88 |
Model calculation: how the study values become “about 1 hour per day”
72 of 88 consultations × avg 3.5 min, extrapolated to 20 consultations ≈ 60 min per day
Model calculation for 20 consultations; not directly measured. The study records an estimate per consultation (2–5 minutes, and more than 5 minutes in 10 of 88). A per-day figure only arises by extrapolating to an assumed consultation count, and depends on specialty, caseload and documentation style.
We deliberately don't write "up to 2 hours". The data don't support it. Honesty is our competitive edge.
Accuracy
Zero major errors. 19% minor deviations.
Minor errors occurred in 19% of consultations. For example, typos in medication names or pronoun gender mismatches. Major, clinically relevant errors: zero. Not one across the entire study period.
Across the 88 documented consultations: 19% contained minor errors (e.g. typos). Clinically relevant errors: zero.
What "minor" means:
The reported errors were minor in classification: spelling variants in medication names instead of the canonical INN form, occasional pronoun gender mismatches. None of these were clinically relevant. No incorrect findings, no incorrect diagnoses, no incorrect treatment suggestions.
What "zero major" means:
Major errors. Defined as errors that would have influenced a treatment decision. Did not occur. Zero out of 88 consultations.
Why we publish the 19%:
Other vendors hide their error rates. We show ours, because that builds trust rather than breaking it. The vendor that publishes its error rate transparently is the one that lowers it. That's our standard.
Patient acceptance
108 patients surveyed. Zero declined.
Of 108 surveyed patients (64.8% female, mean age 59), not a single person declined to participate in AI-assisted documentation. 56% expressed a positive attitude toward AI in the consulting room, 14% very positive. About 49% agreed that the clinician spent less time on the screen and more time in conversation.
Patient demographics:
108
Patients
64.8%
Female
59 years
Mean age
0%
Decline rate
Attitude toward AI in the consulting room:
| Very positive | 14% |
| Positive | 56% |
| Neutral | 30% |
| Negative or refusing | 0% |
About 49% of patients agreed or strongly agreed that the clinician spent less time at the screen and more time in direct conversation during the consultation.
The most common pushback we hear from clinicians: "My patients won't accept this." This study shows the opposite. Zero rejections across 108 patients. And half actively noticed that the clinician was more present with them.
Transparency
What we don't yet know. And why we say it.
Every study has limitations. This one too. We name them because honesty about study limits is a stronger trust signal than a marketing slide without sources.
1/5
Single-centre, one rheumatologist
The study was conducted in a single rheumatology practice, with one treating clinician. The findings are therefore not directly transferable to all specialties, settings, or individual documentation styles.
2/5
Modest sample size
88 consultations and 108 patients. That's a robust starting point but not an RCT with thousands of participants. We are planning follow-on studies with larger samples and multiple sites.
3/5
Self-reported time perception
Time savings were not measured by stopwatch but estimated by the clinicians themselves. Self-reported data can be systematically biased, in either direction.
4/5
Short observation window
The study covers a limited time period. Long-term effects, e.g. acclimatisation, workflow changes after 6 or 12 months, have not yet been investigated.
5/5
Copy-paste into the practice system
In the study setting, Nixi AI was not API-connected to the practice management system (PVS). Clinicians transferred the generated documentation manually via copy-paste. Nixi AI Practice Pro removes this step with the optional direct EMR integration. That advantage was not evaluated in this study.
No other AI documentation vendor in the German-speaking market publishes a peer-reviewed study with transparent limitations. We do, because that should be the standard, and because clinicians see through vendors who only show their best numbers.
Study co-author
What the study co-author says about everyday practice.
“You only realise the true value of Nixi AI when you have to work without it. The other day I had to see patients in a room without Nixi AI and felt genuinely constrained. In just three weeks, Nixi AI has become so fundamental to my practice that I can hardly imagine high-quality patient care without it.”
Disclosure: Dr. Aries is one of the two authors of the EULAR study cited above and is on our Clinical Advisory Board. The study's methodology, data collection and analysis were carried out independently by the study authors and confirmed in peer review; Nixi AI was not involved. His quoted statement here reflects his daily use of Nixi AI in his rheumatology and immunology practice.
For your practice
What this study means for your practice.
If you're a solo clinician:
In 72 of 88 consultations documentation time was estimated as reduced. Extrapolated to a practice day of 20 consultations that is about one hour (model calculation, not directly measured). Basic is free; Practice Pro from €89/month or €828/year.
If you work in a practice team:
The study shows that Nixi AI works in real-world practice, not only under lab conditions. Practice Pro adds the EMR integration that the study had to handle via copy-paste.
If you decide for a clinic or MVZ:
Standardised documentation with measurable time savings, zero major errors, and patients who welcome the use. Those are the three KPIs your leadership wants to see.
Frequently asked
Questions about the EULAR study
Conducted by Dr Johannes Knitza (Institute for Digital Medicine, University Hospital Marburg) and Dr Peer Aries (Immunologikum Hamburg, University Hospital Giessen-Marburg). Published in EULAR Rheumatology Open 2025 (DOI 10.1016/j.ero.2025.12.002), peer-reviewed, Open Access under CC BY 4.0. Nixi AI provided the system; methodology, data collection and analysis sat with the study authors. Dr Aries is on Nixi AI's clinical advisory board. We state all of this so you can judge independence for yourself.
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