Evidence map›Paper›PMID 41982510›Full record

ReviewFrontiers in health services2026

Defining an integrative multidimensional framework for patient complaint management systems.

Aydin Teymourifar

Abstract readReview
In one paragraph

Review in Frontiers in health services, 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

1 author.

Aydin TeymourifarDepartment of Industrial Engineering, Istanbul Sabahattin Zaim University, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient complaints represent a significant yet sometimes underutilized source of organisational learning in hospitals. While they are sometimes processed as administrative tasks aimed at resolution, emerging research demonstrates their value as indicators of system vulnerability and early warning signals for patient safety. This mini-review contributes to the literature by offering a new integrative framework that synthesizes eight previously fragmented domains of complaint management: System Consistency in Learning from Complaints, standard classification of complaints, leadership commitment for organisational learning, effective individual and interpersonal behaviour for organisational learning, organisational change driven by organisational learning, data analytics for organisational learning, proactive risk detection, ethical and legal considerations. Using an integrative, framework-informed methodology, the paper combines inductive identification of conceptual patterns with deductive synthesis across theoretical and policy literatures. The review's key contribution lies in reconceptualizing patient complaints as a system embedded within hospital operations, rather than an administrative function. By mapping connections across the eight domains, the framework reveals how complaints serve as multidimensional organisational assets that can expose systemic weaknesses, cultural blind spots, and latent safety risks. The review also identifies significant theoretical and measurement gaps, including the lack of validated multidimensional instruments to assess complaint management holistically. It further proposes a new research direction by outlining how performance-based contracting could align incentives among patients, clinicians, and managers to strengthen responsiveness and learning, with implications for health system governance and public health oversight.

Indexed as

complaint managementhospital systemsorganisational learningpatient complaintsproactive risk detection

Identifiers

PMID41982510
PMCPMC13071003

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.