Evidence map›Paper›PMID 37255794›Full record

ArticleJournal of diabetes and metabolic disorders2023

Main drivers of diabetes pharmaceuticals expenditures: evidence from OECD countries and Iran.

Zahra Akbarpour, Leila Zarei, Vida Varahrami, Farzad Peiravian, Nazila Yousefi

Abstract read
In one paragraph

Article in Journal of diabetes and metabolic disorders, 2023. 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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.

Zahra AkbarpourFaculty of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Leila ZareiHealth Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Vida VarahramiDepartment of Economics, Shahid Beheshti University, Tehran, Iran.
Farzad PeiravianDepartment of Pharmacoeconomics and Pharma Management, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Nazila YousefiDepartment of Pharmacoeconomics and Pharma Management, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0001-8079-7424

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to identify the impact of prominent drivers on drug expenditure for diabetes. Method: Following the examination of previous studies, this study identified possible factors contributing to diabetes pharmaceutical expenditures. The explanatory variables for the study were the median population age, access to innovative drugs, GDP per capita, prevalence, price, and consumption of diabetes drugs. Then, to estimate the per capita expenditure among diabetic patients, this study developed the panel data model and two time-series regression models for OECD countries and Iran, respectively. Results: In the panel data regression model, R2 was 0.43. The influence of the age, prevalence, consumption volume and GDP per capita coefficients were + 1.79, + 0.704, + 3.86057, + 0.00054, respectively. Also, the probability level of all variables was less than 0.05. In Iran's comparative time-series regression model, R2 was 0.9, and the only significant influence coefficient was the age (β=+0.91). In the another model for Iran, R2 was 0.99, the influence coefficient of age was + 0.249, the prevalence was + 0.131, innovation was + 0.029, and the price was + 0.00054; all the probability levels were less than 0.05. Conclusion: Pharmaceutical per capita expenditure is affected by several factors. These factors are not the same in various counties. Passing a judgment on drug utilization only based on pharmaceutical per capita expenditure cannot be perfect. Also, judging whether the per capita drug expenditure in one country is desirable without attention to the affecting factors and only relying on the value of utilized medicines is defective.

Indexed as

DiabetesHealth SystemPanel DataPharmaceutical ExpendituresTime-Series Regression

Identifiers

PMID37255794
PMCPMC10225425

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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.