Related Experiment Video
Updated: Jan 22, 2026
Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
Published on: June 30, 2023
Development of a predictive score for potentially avoidable hospital readmissions for general internal medicine
Anne-Laure Blanc1,2,3, Thierry Fumeaux4, Jérôme Stirnemann5
1Pharmacy, Geneva University Hospitals, Geneva, Switzerland.
Insights
This study developed a risk score to predict potentially avoidable readmissions (PAR) using patient data. The score helps identify high-risk patients for targeted interventions, improving hospital care.
Area of Science:
- Internal Medicine
- Clinical Informatics
- Health Services Research
Background:
- Identifying patients at high risk of hospital preventable readmission is crucial for targeted transitional interventions.
- Potentially avoidable readmissions (PAR) represent a significant burden on healthcare systems and patient well-being.
Purpose of the Study:
- To derive and validate a predictive risk score for potentially avoidable readmission (PAR).
- To identify key factors, including medication data, associated with hospital readmissions.
Main Methods:
- Retrospective analysis of internal medicine admissions (2011-2014).
- Comparison of readmitted vs. non-readmitted patients using a custom algorithm.
- Multivariate logistic regression to identify PAR predictors from demographic, clinical, and medication data.
- Derivation and internal validation of a PAR-Risk Score.
Main Results:
- Significant PAR predictors included: prolonged hospital stay, prior admissions, heart failure, ischemic heart disease, diabetes with organ damage, cancer, anemia, hypertension, arrhythmia, hyperkalemia, and opioid prescription.
- The PAR-Risk Score showed fair discriminatory and calibration power in both derivation (C-statistic=0.699) and validation (C-statistic=0.687) cohorts.
- Factors like acute myocardial infarction were associated with lower readmission risk.
Conclusions:
- Routinely available patient factors can effectively predict potentially avoidable readmissions.
- A validated PAR-Risk Score can aid in identifying patients who may benefit from specific interventions.
- This tool supports proactive patient management to reduce hospital readmission rates.
Background:
Identifying patients at high risk of hospital preventable readmission is an essential step towards selecting those who might benefit from specific transitional interventions.
Objective:
Derive and validate a predictive risk score for potentially avoidable readmission (PAR) based on analysis of readmissions, with a focus on medication.
Design/Setting/Participants:
Retrospective analysis of all hospital admissions to internal medicine wards between 2011 and 2014. Comparison between patients readmitted within 30 days and non-readmitted patients, as identified using a specially designed algorithm. Univariate and multivariate regression analyses of demographic data, clinical diagnoses, laboratory results, and the medication data of patients admitted during the first period (2011-2013), to identify factors associated with PAR. Using these, derive a predictive score with a regression coefficient-based scoring method. Subsequently, validate this score with a second cohort of patients admitted in 2013-2014. Variables were identified at hospital discharge.
Results:
The derivation cohort included 7,317 hospital stays. Multivariate logistic regressions found significant associations with PAR for: [adjusted OR (95% CI)] hospital length of stay > 4 days [1.3 (1.1-1.7)], admission in previous 6 months [2.3 (1.9-2.8)], heart failure [1.3 (1.0-1.7)], chronic ischemic heart disease [1.7 (1.2-2.3)], diabetes with organ damage [2.2 (1.3-3.8)], cancer [1.4 (1.0-1.9)], metastatic carcinoma [1.9 (1.3-3.0)], anemia [1.2 (1.0-1.5)], hypertension [1.3 (1.1-1.7)], arrhythmia [1.3 (1.0-1.6)], hyperkalemia [1.4 (1.0-1.7)], opioid drug prescription [1.3 (1.1-1.6)], and acute myocardial infarction [0.6 (0.4-0.9)]. The PAR-Risk Score, derived from these results, demonstrated fair discriminatory and calibration power (C-statistic = 0.699; Brier Score = 0.069). The results for the validation cohort's operating characteristics were similar (C-statistic = 0.687; Brier Score = 0.064).
Conclusion:
This study identified routinely-available factors that were significantly associated with PAR. A predictive score was derived and internally validated.
Related Concept Videos
00:59Hospitals-II
Nurses that work in...
01:28Hospitals-I
01:14Frustration and Conflict: Avoidance-Avoidance, Double-Approach Avoidance
02:00Internal Energy
01:31Internal Receptors
01:06Introduction to z Scores
z scores...