Related Experiment Video
Updated: Nov 30, 2025
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Development of a risk prediction model of potentially avoidable readmission for patients hospitalised with
Anne-Laure Mounayar1, Patrice Francois2, Patricia Pavese1
1Infectious Diseases, CHU Grenoble Alpes, Grenoble, Rhône-Alpes, France.
Introduction:
30-day readmission rate is considered an adverse outcome reflecting suboptimal quality of care during index hospitalisation for community-acquired pneumonia (CAP). However, potentially avoidable readmission would be a more relevant metric than all-cause readmission for tracking quality of hospital care for CAP. The objectives of this study are (1) to estimate potentially avoidable 30-day readmission rate and (2) to develop a risk prediction model intended to identify potentially avoidable readmissions for CAP.
Methods And Analysis:
The study population consists of consecutive patients admitted in two hospitals from the community or nursing home setting with pneumonia. To qualify for inclusion, patients must have a primary or secondary discharge diagnosis code of pneumonia. Data sources include routinely collected administrative claims data as part of diagnosis-related group prospective payment system and structured chart reviews. The main outcome measure is potentially avoidable readmission within 30 days of discharge from index hospitalisation. The likelihood that a readmission is potentially avoidable will be quantified using latent class analysis based on independent structured reviews performed by four panellists. We will use a two-stage approach to develop a claims data-based model intended to identify potentially avoidable readmissions. The first stage implies deriving a clinical model based on data collected through retrospective chart review only. In the second stage, the predictors comprising the medical record model will be translated into International Classification of Diseases, 10th revision discharge diagnosis codes in order to obtain a claim data-based risk model.The study sample consists of 1150 hospital stays with a diagnosis of CAP. 30-day index hospital readmission rate is 17.5%.
Ethics And Dissemination:
The protocol was reviewed by the Comité de Protection des Personnes Sud Est V (IRB#6705). Efforts will be made to release the primary study results within 6 months of data collection completion.
Trial Registration Number:
ClinicalTrials.gov Registry (NCT02833259).
Related Concept Videos
01:30Pneumonia I: Introduction
Risk Factors
Various factors influence the likelihood of developing pneumonia. Age plays a crucial role, with infants, children under two, and individuals over 65 at increased risk due to their...
01:30Pneumonia III: Complications and Assessment
01:30Pneumonia V: Nursing management and Prevention
The nurse must practice strict medical asepsis and adhere to infection control guidelines to minimize healthcare-associated infections.
Enhance airway patency
Position the patient correctly to facilitate drainage of the affected lung segments. Manual or mechanical percussion and vibration can also be employed....
01:28Pneumonia IV: Management
Bacterial Pneumonia Treatment
For bacterial pneumonia, antibiotics serve as the cornerstone of therapy. Initial treatment often begins with empirical antibiotics, tailored to the anticipated causative organism and adjusted based on culture results. Key antibiotic choices include:
01:22Healthcare Associated Infections II: Preventive Measures
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
01:29Pneumonia II: Pathophysiology