Evidence map›Paper›PMID 41169644›Full record

ArticleLearning health systems2025

Achieving an Intelligent HealthScience System: Aligning science, health, business, policy and technology for patients and society.

SYNERGY Forum

Abstract read
In one paragraph

Article in Learning health systems, 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. Article
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

1 author.

SYNERGY Forum

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: All societies benefit from a healthy population, and access to affordable, quality, evidence-based medical care can improve health, productivity, and prosperity for all. Two decades ago, experts and stakeholders met at the Institute of Medicine and called for a "new health system for the 21st century." More recently, efforts have been made to achieve a Learning Health System (LHS). Still, reform efforts in the United States have only marginally succeeded in improving the situation despite innovation, technology, enormous economic resources, and one of the strongest medical research endeavors in the world. Objectives: To bring together diverse stakeholders in healthcare, science, technology, business, government and patient advocacy, to envision what lies beyond the so-called Learning Health System approach. Methods: In December 2022, the SYNERGY Forum was hosted by the National Academy of Medicine, convened in Washington, DC. This envisioning exercise, the first in a planned series of such events, was proposed and organized by the global non-profit Alliance for Clinical Research Excellence and Safety (ACRES). The two-day exercise combined didactic lectures on systems thinking, focused working-groups, and interactive discussion, to create a vision for an integrated Intelligent HealthScience System (IHSS). Results: The participants proposed creation of a platform and an engine of People, Processes, Policy, and Technology to design and realize this vision through an effective hard and soft systems approach. Conclusions: This report captures what the multi-stakeholder collaboration recommends toward achieving such a System and a proposal for continuation of a SYNERGY Forum to further advance needed change and a design process.

Indexed as

collaborationcomplex problemsglobal healthcarehealth systemslearning health systemsmedical research and developmentperson‐centerednesssocial changesystems sciencesystems theory and applicationtransformative change

Identifiers

PMID41169644
PMCPMC12569440

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.