Cost.xlsx | |
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H | Hospital identifier |
L | Location of the hospital |
y | Year (most recent year in the SQLape_input.txt file, with at least 10% of records) |
n | Number of hospital stays |
qCO | Data quality (warning if all requirements are not met) |
sCO | Number of days (DischargeDate-AdmissionDate+1-Vacation hours/24) |
eCO | Number of eligible stays |
CO1 | Observed length of stay (average) |
CO0 | Expected length (see prediction models for more details) |
CO0min | Minimal expected length (see prediction models for more details) |
CO0max | Maximal expected length (see prediction models for more details) |
RCO | Rate ratio (LS1 / LS0 ) |
CO0CH | Swiss average in all Swiss hospitals from 2018-2020 satisfying data quality requirement |
CO1a | Adjusted rate (rate ratio * benchmark average) |
vCO | Results |
A: low rate (LS1 < LS0min) | |
B: in the standard (LS0min < LS1 < LS0max) | |
C: high rate (LS1 > LS0max) | |
These results are given globally in “Length” Excel tab. They are given in separate Excel files for each site of the hospital, split according to the context of the stay: back to home with or without a potentially avoidable readmission, waiting for nursing home bed, medical justification of the stay, transfer, etc. |