SynthesisJMIR medical informatics2026
Digital Public Reporting Systems for Evaluating Health Care Quality: Systematic Review.
Synthesis in JMIR medical informatics, 2026. 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Health care public reporting (PR) refers to making information about the quality and performance of health care providers available to the public. The primary targeted use of PR is the selection of a health care provider. Previous studies suggest that PR has improved health care quality; however, the overall adoption rate of PR systems remains low. Misalignment between PR information and users' actual needs can explain this gap. Objective: This study conducts a systematic literature review of PR systems in health care, aiming to explore how data encoding and presentation influence user utilization, with particular attention to the impact of data inconsistencies and inaccuracies on actual use. Methods: A literature search was conducted on 5 electronic databases (Web of Science, CINAHL, Embase, PsycINFO, and PubMed), focusing on studies providing information in health care from an individual perspective. Subsequently, the quality of the included studies was assessed using the Mixed Methods Appraisal Tool (McGill University). Finally, a total of 25 empirical studies were included in this study. Results: Among the 25 studies, 40% (10/25) investigated website presentation formats, 20% (5/25) explored dashboard-based data presentation formats in PR systems, 48% (12/25) examined data quality, and 20% (5/25) addressed user heterogeneity. Quantitative methods were used in 80% (20/25) of studies, while qualitative and mixed method designs accounted for 16% (4/25) and 4% (1/25), respectively. Findings suggest that standardized website and dashboard guidelines improve data reliability and user comprehension and that user heterogeneity mediates the effects of structural and process indicators on outcomes. Data collection was completed in February 2025, and the study was projected to be fully completed by September 2025. Conclusions: This study provides an integrated structure-process-outcome-based framework for PR in health care. By presenting data through dashboards, inconsistencies and inaccuracies in data across different web pages can be mitigated, thereby decreasing conflicting information and improving comprehension in PR systems. Based on the literature findings and identified knowledge gaps, this study also proposes future research directions for online PR.
Indexed as
Identifiers
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.