Evidence map›Paper›PMID 40205564›Full record

ArticleBMC health services research2025

A framework for patient access management: consensus from a Delphi panel of US health system leaders.

Elizabeth Woodcock, Chris Profeta

Abstract readConsensus Statement
In one paragraph

Article in BMC health services research, 2025. 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

2 authors.

Elizabeth WoodcockPatient Access Collaborative, Emory University Rollins School of Public Health, . elizabeth@elizabethwoodcock.com.ORCID http://orcid.org/0000-0002-0674-8234
Chris ProfetaPatient Access Collaborative, Emory University Rollins School of Public Health.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient access management in the ambulatory setting is important for health systems as waits and delays lead to reduced health outcomes, inequity, and poor patient experience. Health systems may benefit from a framework that catalogs the determinants of access management in the ambulatory setting to deliver timely care to all patients.

methodsThe aim of this research is to define patient access and document the determinants of patient access management through a consensus from a two-stage Delphi panel of access leaders in US academic health systems and children's hospitals.

resultsThe study demonstrates a patient-centered definition of patient access management focusing on the delivery of timely, simple, connected access to care. Twelve major determinants were identified for patient access management: executive leadership support, dedicated access leadership, system strategy prioritization, data collection and analysis, contact center management, capacity management, appointment availability, appointment accuracy, measurable and defined goals, simplification of system for patients, timely offering of care, and patient-clinician connection. The determinants were applied to a framework using the Donabedian model. Frameworks may improve validity and reliability in performance improvement activities.

conclusionsHealth systems may benefit from prescriptive strategies to identify, diagnose, resource, and address the determinants that constitute patient access management. Additional research is warranted to understand each determinant.

Indexed as

Health Services AccessibilityDelphi TechniqueHospitals, PediatricHumansLeadershipUnited StatesAccess to careAmbulatoryEquityManagementScheduling

Identifiers

PMID40205564
PMCPMC11983827

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.