ArticleCureus2025
Impact of Real-Time Comorbidity Capture on Clinical Escalation and Harm Prevention in Hospitalized Patients: A Benchmarking and Statistical Gap Analysis.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Comparison of chest X-ray radiography AI model to comorbidities for predicting intensive care unit admission for COVID-19.Journal of medical imaging (Bellingham, Wash.) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Systemic documentation deficiencies in hospitalized patients with high-acuity conditions such as systemic inflammatory response syndrome (SIRS) can compromise clinical decision-making, risk adjustment, and patient safety. Despite well-established evidence linking chronic conditions like chronic kidney disease (CKD), diabetes mellitus (DM), and liver failure to adverse outcomes, these comorbidities are often underrepresented in electronic health records (EHRs). This study introduces a statistically rigorous, informatics-assisted framework to benchmark and quantify real-world documentation gaps, advancing the field of clinical documentation integrity (CDI) through actionable metrics. Objective The objectives of this study are to evaluate the accuracy of comorbidity documentation in adult inpatients with SIRS and acute organ dysfunction by applying a benchmarking model based on peer-reviewed prevalence data and to assess the clinical, operational, and financial implications of these documentation deficits. Methods In this retrospective observational study, 82 adult patients admitted with a principal diagnosis of SIRS (ICD-10-CM R65.11) were analyzed using structured chart abstraction from EPIC EHR data. Six high-impact comorbidities were evaluated. Observed documentation rates were compared against literature-derived expected prevalence benchmarks. Gap scores were calculated as proportional differences, and one-sample z-tests were used to assess statistical significance, stratified by age and sex. Results Five of six comorbidities demonstrated statistically significant underdocumentation, with liver failure (expected: 57%, observed: 6.1%;
Indexed as
Identifiers
What Socratic 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 Socratic graph.