Sentence examples for models for readmission from inspiring English sources

Previous attempts to create universal risk prediction models for readmission have not met with success.

Risk adjustment models for readmission at both time points were developed separately for medical and surgical cases by randomly splitting the full samples into estimation and validation samples.

However, systematic reviews failed to find an effect on 30-day readmission [ 44] or that risk predictive models for readmission are generally poor [ 45].

Several countries have developed predictive models for readmission, for example, LACE and LACE+ index [ 4, 5] in Canada, PARR-30 [ 6] by the UK National Health System, and the HOSPITAL score in the United States [ 7].

In medical and surgical intensive care units, clinical risk prediction models for readmission have been developed; however, studies reporting the risks for cardiovascular intensive care unit (CVICU) readmission have been methodologically limited by small numbers of outcomes, unreported measures of calibration or discrimination, or a lack of information spanning the entire perioperative period.

Predictive models for readmissions are typically developed using clinical and administrative data collected as a part of the care process.

As a comparison, we used the LACE index approach to develop predictive models for readmissions [ 57] with our three complete derivation datasets, i.e. 2003 2012, 2008 2012, and 2009 2012.

We also examined the patients' demographic characteristics such as age and sex in a random-effect Poisson regression model for readmissions; these two factors were not significantly associated with potential cluster of readmissions.

In this study, a three-step approach to predictive analytics was proposed and piloted on an operational clinical dataset to develop predictive models for CHF readmission.

With regard to risk stratification, no studies to date have demonstrated strong model discrimination for readmission [ 14, 21].

The models for unplanned readmissions with COPD as primary or any diagnosis showed similar results with values of 0.65 (95% CI 0.64 0.67) and 0.65 (95% CI 0.63 0.66), respectively.