[Identification of pharmacy cost outliers in primary care].
OBJECTIVE
To identify pharmacy cost outlier patients in Primary Care, describing epidemiological differences between normal users and outliers; and to study the explanatory power of risk adjustment tools based on Adjusted Clinical Groups (ACG) as regards the variability of pharmacy expenditure for both groups of patients.


METHODS
Observational, retrospective study.


METHODS
23 health centres located in the regions of Aragon, Catalonia and the Balearic Islands.


METHODS
The study sample consisted of 286,450 patients who were seen at least once in 2005.


METHODS
Variables related to demographic features, pharmacy cost, and case-mix (ACG 7.1) were collected. Pharmacy cost outliers were selected according to the inter-quartile range method. A linear regression model was developed to measure the explanatory power of ACG. This same model was applied stratifying the population by variables of the physician, the health centre and the region.


RESULTS
One out of ten patients was classified as an outlier. This group was responsible for 60% of the total pharmacy expenditure. These outlier patients were 26.3 years older than normal users and had a higher comorbidity. The explanatory power of the ACG classification system was markedly lower -3% vs. 26.4% for normal users-.


CONCLUSIONS
Further research should be done on factors causing a lack of adequacy of ACG among pharmacy outlier patients. Although it could be thought that social circumstances might play a role in the clinical state of patients, it is more likely that the applied trimming method does not allow outliers with justifiable clinical reasons for higher costs to be distinguished from those without them.
Prados Torres
Alexandra
A
Instituto Aragonés de Ciencias de la Salud (I+CS), Zaragoza, España. sprados.iacs@aragon.es
Sicras Mainar
Antoni
A
Estelrich Bennasar
José
J
Calderón Larrañaga
Amaia
A
Rabanaque Hernández
María José
MJ
López Cabañas
Anselmo
A
D000328:Adult; D003365:Costs and Cost Analysis; D004363:Drug Utilization / Q000191:economics* / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010593:Pharmaceutical Services / Q000191:economics*; D011320:Primary Health Care; D012189:Retrospective Studies