Evidence map›Paper›PMID 42225789›Full record

ArticleNPJ digital medicine2026

Privacy preserving digital platform for patient reported outcomes in inflammatory bowel disease.

Yuki Ohta, Takashi Taida, Sadahisa Ogasawara, Takuma Aizu, Takahito Konagaya, Mitsunori Ota, Ryoko Koborita, Ryuji Suzuka, Toshiyuki Ito, Yusuke Ozeki and 15 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Yuki Ohta *Department of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Takashi Taida *Department of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Sadahisa Ogasawara *Department of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan. ogasawaras@chiba-u.jp.
Takuma AizuCenter for Next Generation of Community Health, Chiba University Hospital, Chiba, Japan.
Takahito KonagayaSmart Healthcare, Smart World Business, Business Solution Division, NTT DOCOMO BUSINESS, Inc., Tokyo, Japan.
Mitsunori OtaCenter for Next Generation of Community Health, Chiba University Hospital, Chiba, Japan.
Ryoko KoboritaSmart Healthcare, Smart World Business, Business Solution Division, NTT DOCOMO BUSINESS, Inc., Tokyo, Japan.
Ryuji SuzukaCenter for Next Generation of Community Health, Chiba University Hospital, Chiba, Japan.
Toshiyuki ItoDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Yusuke OzekiDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Makoto FuruyaDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Nobuaki ShuDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Ryosuke HorioDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Ariki NagashimaDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Wataru ShiratoriDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Yuya YokoyamaDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Masato NakamuraDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Kenichiro OkimotoDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Keiko SaitoDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Tomoaki MatsumuraDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Tomoo NakagawaDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Minobu ShimazuClinical Research Center, Chiba University Hospital, Chiba, Japan.
Yoichi SakuraiCenter for Next Generation of Community Health, Chiba University Hospital, Chiba, Japan.
Kensuke YoshimuraCenter for Next Generation of Community Health, Chiba University Hospital, Chiba, Japan.
Jun KatoDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Chiba, Japan. kato.jun@chiba-u.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We developed a privacy-preserving digital platform for patient-reported outcomes in inflammatory bowel disease using secure multi-party computation (SMPC), which encrypts and fragments data to ensure complete anonymity. In a prospective multicenter study of 322 patients, 277 respondents (86.0%) completed the survey; 60.1% reported greater comfort in providing candid responses under anonymized conditions. The system revealed substantial underreporting: only 65.1% of patients experiencing clinically important symptoms (including urgency and other key concerns) discussed them with physicians; medication adherence discrepancies occurred in 28.9% of patients, with 68.0% unrecognized by clinicians. This approach captured previously inaccessible information about sensitive symptoms and socioeconomic burdens, enabling a more accurate understanding of real-world disease impact. Our findings suggest that SMPC-based anonymization may help reveal patient-reported information that is often underrepresented in routine clinical care. (Registered with the University Hospital Medical Information Network Clinical Trials Registry: UMIN000039131; registered January 11, 2020).

Identifiers

PMID42225789
PMCPMC13269890

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.