4. Conclusion

In general the quality of the 2023 models is similar to that of previous versions of the hospital readmission models. However, there were some shifts in quality and estimated parameters for the models of some of the diagnosis groups. In part, this was likely caused by the disruption of hospital care by the COVID-19 pandemic, which may have affected the 2021 readmission model. The number of admissions increased in the 2023 model, compared to the 2021 model, but did not return to the values in the 2018 model.

Like in the previous models, ‘to and fro’ transfers are excluded as readmissions. This removes some of the noise from the model, as these planned transfers are not of interest when the readmission ratio is used as an indicator of quality of care. Additionally, several diagnosis groups consisting of diseases that require treatment during multiple, consecutive admissions have been excluded from the model. However, it is possible that the data still contains planned readmissions, resulting in a less reliable prediction. Although the predictive power of the model is generally low, the case mix correction performed by the model does remove some of the differences between the hospitals caused by population differences. However, because of the weak predictive power of the models, it is likely that there are still population differences remaining for which the model does not correct. Nevertheless, applying the model for calculating readmission ratios for individual hospitals is preferable to calculating crude rates.