Evidence map›Paper›PMID 36964454›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2023

A composite measure for patient-reported outcomes in orthopedic care: design principles and validity checks.

Lukas Schöner, David Kuklinski, Alexander Geissler, Reinhard Busse, Christoph Pross

Open access · hybridAbstract read
In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
2.3field-weighted citation impact, top 8% of its field
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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 4 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Lukas SchönerDepartment of Health Care Management, Technical University Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany. Lukas.schoener@tu-berlin.de.ORCID http://orcid.org/0000-0003-0881-2145
David KuklinskiDepartment of Health Care Management, University of St. Gallen, St. Gallen, Switzerland.
Alexander GeisslerDepartment of Health Care Management, University of St. Gallen, St. Gallen, Switzerland.
Reinhard BusseDepartment of Health Care Management, Technical University Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany.
Christoph ProssDepartment of Health Care Management, Technical University Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany.
Technische Universität Berlin · DEUniversity of St.Gallen · CH

Funding

Gemeinsame Bundesausschuss 01NVF18016
6 · The paper itself

Abstract

backgroundThe complex, multidimensional nature of healthcare quality makes provider and treatment decisions based on quality difficult. Patient-reported outcome (PRO) measures can enhance patient centricity and involvement. The proliferation of PRO measures, however, requires a simplification to improve comprehensibility. Composite measures can simplify complex data without sacrificing the underlying information. OBJECTIVE AND

methodsWe propose a five-step development approach to combine different PRO into one composite measure (PRO-CM): (i) theoretical framework and metric selection, (ii) initial data analysis, (iii) rescaling, (iv) weighting and aggregation, and (v) sensitivity and uncertainty analysis. We evaluate different rescaling, weighting, and aggregation methods by utilizing data of 3145 hip and 2605 knee replacement patients, to identify the most advantageous development approach for a PRO-CM that reflects quality variations from a patient perspective.

resultsThe comparison of different methods within steps (iii) and (iv) reveals the following methods as most advantageous: (iii) rescaling via z-score standardization and (iv) applying differential weights and additive aggregation. The resulting PRO-CM is most sensitive to variations in physical health. Changing weighting schemes impacts the PRO-CM most directly, while it proves more robust towards different rescaling and aggregation approaches.

conclusionCombining multiple PRO provides a holistic picture of patients' health improvement. The PRO-CM can enhance patient understanding and simplify reporting and monitoring of PRO. However, the development methodology of a PRO-CM needs to be justified and transparent to ensure that it is comprehensible and replicable. This is essential to address the well-known problems associated with composites, such as misinterpretation and lack of trust.

Indexed as

Patient Reported Outcome MeasuresQuality of LifeHumansQuality of Health CareReference StandardsComposite measureComposite measure development validationOutcome quality measurementPatient reported outcome measuresValue-based health care

Identifiers

PMID36964454
PMCPMC10329084
OpenAlexW4360825561

What OpenQuestion holds

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LicenceCC BY
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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.