Evidence map›Paper›PMID 17002482›Full record

ArticlePharmacoEconomics2006

Hospitalisation costs of cystic fibrosis.

Jonas Schreyögg, Helge Hollmeyer, Miriam Bluemel, Doris Staab, Reinhard Busse

Abstract read
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In one paragraph

Article in PharmacoEconomics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
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

8 citing papers in PubMed, 28 citations in OpenAlex.

  1. Estimation of care costs for individuals with cystic fibrosis at a referral center: cohort study, Salvador, 2005-2022.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2026
    Article
  2. Observational
  3. Article
  4. Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data.The European journal of health economics : HEPAC : health economics in prevention and care · 2015
    Article
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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

5 authors at 1 institution in 1 country.

Jonas SchreyöggDepartment of Health Care Management, WHO Collaborating Centre for Health Systems Research and Management, Berlin University of Technology, Berlin, Germany. jonas.schreyoegg@tu-berlin.de
Helge Hollmeyer
Miriam Bluemel
Doris Staab
Reinhard Busse
Charité - Universitätsmedizin Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo calculate per-case hospital costs for patients with cystic fibrosis under routine conditions from a healthcare provider's perspective; identify the impact of different cost categories; investigate whether cases with cystic fibrosis can be grouped into homogenous cost groups according to defined severity levels; and determine the value of specific factors as predictors of hospital cost variations.

methodsAll data were collected from cases (n = 131) admitted to an inpatient cystic fibrosis unit under routine conditions during a period of 6 months in 2004. All costs were calculated for the year 2004 and divided into categories with high and low impact on variation in hospitalisation costs between patients. Staff costs for patient care, laboratory costs and drug costs were defined as categories with high impact, thus the individual resource utilisation for each case was measured. Cost categories that were classified as having a low impact were measured as overhead costs. Cases were classified according to two different severity models; within each model, patients were classified according to three severity levels. The diagnosis-related model classifies patients with pulmonary hypertension and global respiratory insufficiency as having severe disease, patients with Pseudomonas aeruginosa as having moderate disease, and patients with no colonisation of the lungs as having mild disease. The lung-function-related model differentiates patients as having mild, moderate and severe disease when patients have forced expiratory volumes in 1 second (FEV(1)) that are > or =70%, between > or =40% and <70%, and <40%, respectively. Analysis of variance tests were performed to investigate the differences of mean costs between the groups. Ordinary least squares regression analysis was used to determine predictors for cost variation.

resultsThe mean total costs per case were 7326 euro. Almost one-third of the total mean costs were attributable to drug costs (28% of total costs), while shares of staff costs for patient care and laboratory costs (both 9% of total costs) were relatively small. Most of the difference in costs between severity levels was attributable to the variation in overhead costs and drug costs. For both severity models differences in mean total costs of mild and severe cases were statistically significant (p < 0.01 and p < 0.05, respectively) when compared with the mean costs of non-mild and non-severe cases. However, in moderate cases, significant differences compared with cases that were not of moderate severity were only seen for certain cost categories. In the multiple regression model the variables 'diagnosis-related severity' and 'FEV(1)' explained 31% of the variance of 'Ln (total costs per case)' between severity levels (p < or = 0.01).

conclusionThis study shows that to a large extent hospitalisation costs for patients with cystic fibrosis vary according to the severity of their disease; drug costs play a major role in these differences. In the light of this variation it seems plausible to create separate reimbursement rates for two or three severity groups. Diagnoses as well as FEV(1) seem suitable criteria for such a classification.

Indexed as

Health Care CostsAnalysis of VarianceCystic FibrosisDiagnosis-Related GroupsFemaleForced Expiratory VolumeHospitalizationHumansMaleRegression Analysis

Identifiers

PMID17002482
OpenAlexW1976657305

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.