5. Conclusions

No changes have been implemented to the HSMR 2023 model compared to the model of previous year. The COVID-19 model was also kept the same as previous year. Only the covariate “Year of discharge” was added to the COVID-19 model as there are now two years in the model (2022 and 2023), compared to one year (2022) in the previous model. As the predictive power of the model remained the same, further investigation into possible improvements was not performed.

To be able to distinguish different COVID-19 waves the additional category “before Year of discharge” was introduced to the covariate “Month of admission” in the COVID-19 model last year. An admission in e.g. December 2022 (and discharge in 2022) was thus distinguished from an admission in December 2021 and discharge in 2022, because the latter admission was given the category “before Year of discharge” for Month of admission. This also holds true now that there are two years in the model, with Year of discharge added as a covariate. With this covariate, it is possible to distinguish between an admission in December 2023 with a discharge in 2023 and an admission in December 2022 with a discharge in 2023. For the latter, Month of admission will be equal to “before Year of discharge” instead of “December”. However, since interactions are not included in the model, it is not possible to properly distinguish different COVID-19 wave patterns over the years. There is, for example, only one coefficient for “March” that is used both for admissions from 2022 and from 2023. Another disadvantage is that the “before Year of discharge” admissions on average have longer lengths of stay than the other admissions, as the month of discharge is later than the month of admission. In principle we do not want to correct for length of stay in the HSMR model, only for characteristics at the moment of admission. Although the effects of these disadvantages on the SMR will probably be small, it may be good to check whether the present COVID-19 model is still the most adequate for the HSMR 2024, with multiple years in the model.

Sections 4.4 and 4.5 evaluate the quality of the present HSMR model. The C-statistics have changed little compared to the previous model. The order of the covariates with regard to explanatory power is mostly the same, although some minor changes have occurred in the relative importance of some of the variables. The importance of month of admission has increased a bit further and the importance of year of discharge has dropped again after an increase 2022. Overall, the model and the quality of the model have changed little compared to previous year.