Evidence map›Paper›PMID 40629133›Full record

ArticleNPJ digital medicine2025

Digital transformation with clinical alerts and personalized care systems in an integrated value based model.

Dinh Nguyen, Sinjin Lee, Ronil Synghal, Leon Chan, Ferdinand Justus, Mark Moromisato, Tianyuan Shao, Caleb Wang, Mason Kellogg, Brett Anwar and 6 more

Abstract read
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. From Integrated Care to Learning Systems.Healthcare (Basel, Switzerland) · 2026
    Review
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

16 authors.

Dinh NguyenSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA. dinh.l.nguyen@kp.org.
Sinjin LeeSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Ronil SynghalSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Leon ChanSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Ferdinand JustusSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Mark MoromisatoSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Tianyuan ShaoSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Caleb WangSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Mason KelloggSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Brett AnwarSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Julie CreechSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Kari OchoaSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Danette GigliottiSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Omar OrtizSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Kien LaSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.
Khang NguyenSouthern California Permanente Medical Group (SCPMG), Pasadena, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient portals are widely available to facilitate self-service interactions, including appointment booking, offering convenience to users. Promoting clinically appropriate care pathways, however, is complex; portals must recognize patient intent while striving for an intuitive experience. In October 2024, the Southern California Permanente Medical Group, which serves 4.9 M patients, deployed the Kaiser Permanente Intelligent Navigator (KPIN), a system that augments the patient portal to enhance care navigation and the patient experience. It applies natural language processing to generate alerts for high-acuity cases, and it recommends suitable care offerings. Early findings are promising, with the AUC for clinical alerts and clinical navigation at 0.977 and 0.889, respectively. KPIN's adjusted successful booking rate was 53.68%, with an abandonment rate of 2.94% (IQR: 2.77-3.11%), aligning with patient survey results showing an 8.63 percentage point increase for positive sentiment. These results highlight the success of KPIN in an integrated value-based care delivery model.

Identifiers

PMID40629133
PMCPMC12238570

What Socratic 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 Socratic graph.