Evidence map›Paper›PMID 19520462›Full record

ArticleAtencion primaria2009

[Identification of pharmacy cost outliers in primary care].

Alexandra Prados Torres, Antoni Sicras Mainar, José Estelrich Bennasar, Amaia Calderón Larrañaga, María José Rabanaque Hernández, Anselmo López Cabañas

Abstract readEnglish Abstract
In one paragraph

Article in Atencion primaria, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexandra Prados TorresInstituto Aragonés de Ciencias de la Salud (I+CS), Zaragoza, España. sprados.iacs@aragon.es
Antoni Sicras Mainar
José Estelrich Bennasar
Amaia Calderón Larrañaga
María José Rabanaque Hernández
Anselmo López Cabañas

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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.

designObservational, retrospective study.

setting23 health centres located in the regions of Aragon, Catalonia and the Balearic Islands.

participantsThe study sample consisted of 286,450 patients who were seen at least once in 2005. MEASUREMENTS: 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.

resultsOne 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-.

conclusionsFurther 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.

Indexed as

Primary Health CareAdultCosts and Cost AnalysisDrug UtilizationFemaleHumansMaleMiddle AgedPharmaceutical ServicesRetrospective Studies

Identifiers

PMID19520462
PMCPMC7021977

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.