Difference between observed and predicted length of stay as an indicator of inpatient care inefficiency.
OBJECTIVE
To evaluate the performance of the difference between observed and predicted length of stay (OLOS-PLOS) as an inefficiency of care indicator for inpatients.


METHODS
The Internal Medicine and the General Surgery departments of Hermanos Ameijeiras Hospital in Havana.


METHODS
Two sets of clinical histories were needed for each department: one for deriving the predictive equation and another to validate it. The equation was a linear multiple regression model which included variables recognized as affecting length of stay. The validation group of histories was thoroughly examined and separated into two groups: (i) adequate efficiency or mild problems and (ii) inefficiencies considered to be moderate or severe. This classification was the gold standard to obtain a receiver operating characteristic (ROC) curve for the indicator.


RESULTS
The function explained 41% of the total variation for Internal Medicine and 70% for General Surgery. The indicator's mean difference between the two validation groups of histories was around 10 days for both departments. The areas under the ROC curve were 0.80 for Internal Medicine and 0.88 for General Surgery. Sensitivity and specificity > 0.7 for detecting inefficiencies of care are achieved with a cut off point of 2 days for Internal Medicine and 1 day for General Surgery.


CONCLUSIONS
The use of predictive equations might be quite useful for detecting efficiency problems in inpatient health care.
Jiménez
R
R
Research Section, Hermanos Ameijeiras Hospital, Havana City, Cuba. rjimenez@infomed.sld.cu
López
L
L
Dominguez
D
D
Fariñas
H
H
D003462:Cuba; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D005260:Female; D006748:Hospital Departments / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D007388:Internal Medicine / Q000706:statistics & numerical data; D007902:Length of Stay / Q000706:statistics & numerical data*; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D017064:Process Assessment, Health Care; D019984:Quality Indicators, Health Care; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D013503:Surgery Department, Hospital / Q000592:standards / Q000706:statistics & numerical data