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Factors associated with prescribing costs: analysis of a nationwide administrative database

Overview of attention for article published in Cost Effectiveness and Resource Allocation, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)

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Title
Factors associated with prescribing costs: analysis of a nationwide administrative database
Published in
Cost Effectiveness and Resource Allocation, February 2018
DOI 10.1186/s12962-018-0091-1
Pubmed ID
Authors

O. Hirsch, M. Schulz, M. Erhart, N. Donner-Banzhoff

Abstract

All health care systems in the world struggle with rising costs for drugs. We sought to explore factors impacting on prescribing costs in a nationwide database of ambulatory care in Germany. Factors identified by this research can be used for adjustment in future profiling efforts. We analysed nationwide prescription data of physicians having contractual relationships with statutory health insurance funds in 2014. Predictor and outcome variables were aggregated at the practice level. We performed analyses separately for primary care and specialties of cardiology, gastroenterology, neurology and psychiatry, pulmology as well as oncology and haematology. Bivariate robust regressions and Spearman rank correlations were computed in order to find meaningful predictors for our outcome variable prescription costs per patient. Median age of patients and proportion of DDD issued were substantial predictors for prescription costs per patient in Primary Care, Cardiology, and Pulmology with explained variances between 41 and 61%. In Neurology and Psychiatry only proportion of patients with polypharmacy ≥ 2 quarters was a significant predictor for prescription costs per patient, explaining 20% of the variance. For gastroenterologists, oncologists and haematologists no stable models could be established. Any analysis of prescribing behaviour must take the degree into account to which an individual physician or practice is responsible for prescribing patients' medication. Proportion of prescriptions/DDDs is an essential confounder for future studies of drug prescribing.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Postgraduate 3 19%
Other 2 13%
Student > Bachelor 2 13%
Student > Ph. D. Student 1 6%
Other 2 13%
Unknown 1 6%
Readers by discipline Count As %
Social Sciences 5 31%
Medicine and Dentistry 2 13%
Economics, Econometrics and Finance 2 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Agricultural and Biological Sciences 1 6%
Other 3 19%
Unknown 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 February 2018.
All research outputs
#4,120,297
of 23,020,670 outputs
Outputs from Cost Effectiveness and Resource Allocation
#132
of 431 outputs
Outputs of similar age
#93,050
of 439,449 outputs
Outputs of similar age from Cost Effectiveness and Resource Allocation
#8
of 11 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 431 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 439,449 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.