Predicting Hospital Discharge to Post-Acute Care
Author Information
Author(s): Louis Simonet Martine, Kossovsky Michel P, Chopard Pierre, Sigaud Philippe, Perneger Thomas V, Gaspoz Jean-Michel
Primary Institution: University Hospitals, Geneva, Switzerland
Hypothesis
What factors predict the risk of hospitalized patients being discharged to a post-acute care facility?
Conclusion
A simple score computed on the 3rd hospital day predicted discharge to a PAC facility with good accuracy.
Supporting Evidence
- The score was validated in a separate cohort with similar results.
- A score ≥ 8 points predicted discharge to a PAC facility with 87% sensitivity.
- The day-3 model was more parsimonious and easier to implement than the day-1 model.
Takeaway
Doctors can use a simple score to figure out if patients will need extra help after leaving the hospital, which helps them plan better.
Methodology
The study used logistic regression models to predict discharge to a PAC facility based on patient variables collected on admission and day 3.
Potential Biases
Potential bias due to the exclusion of patients who died or were transferred to other acute care settings.
Limitations
The study was conducted at a single institution and excluded certain patient groups, which may limit generalizability.
Participant Demographics
Patients included were hospitalized for acute medical conditions, with a mean age of 65 years.
Statistical Information
P-Value
p<0.001
Confidence Interval
95% CI: 0.76 – 0.87
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website