ReviewPatient related outcome measures2025
The Use of Patient-Reported Measures Collected Data in Primary Care: A Systematic Review.
Review in Patient related outcome measures, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This systematic review aims to explore the utilization of patient-reported measures (PRMs) in primary care, focusing on healthcare providers' use of PRM data and factors influencing its effectiveness. Following the PRISMA 2020 guidelines, we registered the review in PROSPERO (CRD420251030695) and screened 2465 records, ultimately including eight studies. Data extraction and quality appraisal were conducted using a structured approach and the Mixed Methods Appraisal Tool (MMAT). Findings suggest that effective PRM data use depends on integration into electronic health records (EHRs) and clinical workflows, with barriers including technical limitations and organizational culture. PRM data can support clinical decision-making, shared decision-making, and communication and support professional empowerment and resource optimization. However, evidence quality was moderate, and conclusions should be interpreted with caution due to the small number of studies. Differences in health systems and study heterogeneity further constrain generalizability. This review highlights the need for seamless EHR integration, streamlined instruments, and active professional engagement to optimize PRM implementation, while identifying a critical research gap and calling for future studies on cost-effectiveness and equity impacts.
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What OpenQuestion holds
Registered trials
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.