Reduction in inappropriate hospital use based on analysis of the causes.
BACKGROUND
To reduce inappropriate admissions and stays with the application of an improvement cycle in patients admitted to a University Hospital. The secondary objective is to analyze the hospital cost saved by reducing inadequacy after the implementation of measures proposed by the group for improvement.


METHODS
Pre- and post-analysis of a sample of clinical histories studied retrospectively, in which the Appropriateness Evaluation Protocol (AEP) was applied to a representative hospital sample of 1350 clinical histories in two phases. In the first phase the AEP was applied retrospectively to 725 admissions and 1350 stays. The factors associated with inappropriateness were analysed together with the causes, and specific measures were implemented in a bid to reduce inappropriateness. In the second phase the AEP was reapplied to a similar group of clinical histories and the results of the two groups were compared. The cost of inappropriate stays was calculated by cost accounting.


METHODS
General University Hospital with 426 beds serving a population of 320,000 inhabitants in the centre of Murcia, a city in south-eastern Spain.


RESULTS
Inappropriate admissions were reduced significantly: 7.4% in the control group and 3.2% in the intervention group. Likewise, inappropriate stays decreased significantly from 24.6% to 10.4%. The cost of inappropriateness in the study sample fell from 147,044 euros to 66,642 euros. The causes of inappropriateness for which corrective measures were adopted were those that showed the most significant decrease.


CONCLUSIONS
It is possible to reduce inadequacy by applying measures based on prior analysis of the situation in each hospital.
Hospital Training and Research Unit; Morales Meseguer Hospital, Murcia, Spain. victoriano.soria@carm.es
Víctor
V
Soria-Aledo
Andrés
A
Carrillo-Alcaraz
Benito
B
Flores-Pastor
Alfredo
A
Moreno-Egea
Milagros
M
Carrasco-Prats
José Luis
JL
Aguayo-Albasini
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D016009:Chi-Square Distribution; D002648:Child; D003365:Costs and Cost Analysis; D005260:Female; D006300:Health Services Misuse / Q000706:statistics & numerical data*; D006302:Health Services Research; D006785:Hospitals, University / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000706:statistics & numerical data; D012189:Retrospective Studies; D014600:Utilization Review / Q000379:methods*