Evidence map›Paper›PMID 42344231›Full record

ArticleJournal of patient experience2026

Designing Artificial Intelligence Tools to Strengthen Human Connection in Healthcare: The CoCo Experience.

Richard M Elias, Shawn M Grimsley, Brooke L Werneburg, Sheila K Stevens, Sunanda Kane

Abstract read
In one paragraph

Article in Journal of patient experience, 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

5 authors.

Richard M EliasDivision of Hospital Medicine, Mayo Clinic, Rochester, MN, USA.ORCID https://orcid.org/0000-0003-3389-5472
Shawn M GrimsleyDepartment of Quality, Mayo Clinic, Rochester, MN, USA.
Brooke L WerneburgDepartment of Quality, Mayo Clinic, Rochester, MN, USA.
Sheila K StevensDepartment of Quality, Mayo Clinic, Rochester, MN, USA.
Sunanda KaneDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare organizations face persistent tension between efficiency and human connection. Digital systems often fragment attention and unintentionally distance staff from patients. At Mayo Clinic, we developed a conversational artificial intelligence (AI) agent embedded in Microsoft Teams to address this challenge. Connecting and Communicating (CoCo) provides staff with communication guidance, drawing on institutional resources aligned with the Mayo Model of Communication (MMOC). Built in Microsoft Copilot Studio and shaped by clinicians and operational stakeholders, CoCo was designed to be values-aligned and usable within existing workflows. CoCo is an active, user-initiated tool used primarily before or after challenging interactions to support preparation, reflection, and communication planning. Staff valued CoCo as a "just-in-time coach" that reinforced empathy while reducing stress. From August 2025 through February 2026, CoCo supported 1,903 conversation sessions, with early descriptive analytics suggesting favorable satisfaction and response-quality signals. We share insights from development and deployment, along with practical recommendations, to support other organizations considering bespoke, values-aligned AI tools to enhance patient and staff experience. We distill practice-based implementation lessons around governance, human factors, and change management, and offer practical recommendations to inform similar efforts elsewhere.

Indexed as

artificial intelligenceclinician/staff engagementcommunicationempathyorganizational culture

Identifiers

PMID42344231
PMCPMC13287415

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.