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Cochrane Database of Systematic Reviews

Interventions to reduce corruption in the health sector

Overview of attention for article published in Cochrane database of systematic reviews, August 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
3 news outlets
policy
1 policy source
twitter
40 tweeters
facebook
6 Facebook pages

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
440 Mendeley
citeulike
1 CiteULike
Title
Interventions to reduce corruption in the health sector
Published in
Cochrane database of systematic reviews, August 2016
DOI 10.1002/14651858.cd008856.pub2
Pubmed ID
Authors

Rakhal Gaitonde, Andrew D Oxman, Peter O Okebukola, Gabriel Rada

Abstract

Corruption is the abuse or complicity in abuse, of public or private position, power or authority to benefit oneself, a group, an organisation or others close to oneself; where the benefits may be financial, material or non-material. It is wide-spread in the health sector and represents a major problem. Our primary objective was to systematically summarise empirical evidence of the effects of strategies to reduce corruption in the health sector. Our secondary objective was to describe the range of strategies that have been tried and to guide future evaluations of promising strategies for which there is insufficient evidence. We searched 14 electronic databases up to January 2014, including: CENTRAL; MEDLINE; EMBASE; sociological, economic, political and other health databases; Human Resources Abstracts up to November 2010; Euroethics up to August 2015; and PubMed alerts from January 2014 to June 2016. We searched another 23 websites and online databases for grey literature up to August 2015, including the World Bank, the International Monetary Fund, the U4 Anti-Corruption Resource Centre, Transparency International, healthcare anti-fraud association websites and trial registries. We conducted citation searches in Science Citation Index and Google Scholar, and searched PubMed for related articles up to August 2015. We contacted corruption researchers in December 2015, and screened reference lists of articles up to May 2016. For the primary analysis, we included randomised trials, non-randomised trials, interrupted time series studies and controlled before-after studies that evaluated the effects of an intervention to reduce corruption in the health sector. For the secondary analysis, we included case studies that clearly described an intervention to reduce corruption in the health sector, addressed either our primary or secondary objective, and stated the methods that the study authors used to collect and analyse data. One review author extracted data from the included studies and a second review author checked the extracted data against the reports of the included studies. We undertook a structured synthesis of the findings. We constructed a results table and 'Summaries of findings' tables. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess the certainty of the evidence. No studies met the inclusion criteria of the primary analysis. We included nine studies that met the inclusion criteria for the secondary analysis.One study found that a package of interventions coordinated by the US Department of Health and Human Services and Department of Justice recovered a large amount of money and resulted in hundreds of new cases and convictions each year (high certainty of the evidence). Another study from the USA found that establishment of an independent agency to investigate and enforce efforts against overbilling might lead to a small reduction in overbilling, but the certainty of this evidence was very low. A third study from India suggested that the impacts of coordinated efforts to reduce corruption through increased detection and enforcement are dependent on continued political support and that they can be limited by a dysfunctional judicial system (very low certainty of the evidence).One study in South Korea and two in the USA evaluated increased efforts to investigate and punish corruption in clinics and hospitals without establishing an independent agency to coordinate these efforts. It is unclear whether these were effective because the evidence is of very low certainty.One study from Kyrgyzstan suggested that increased transparency and accountability for co-payments together with reduction of incentives for demanding informal payments may reduce informal payments (low certainty of the evidence).One study from Germany suggested that guidelines that prohibit hospital doctors from accepting any form of benefits from the pharmaceutical industry may improve doctors' attitudes about the influence of pharmaceutical companies on their choice of medicines (low certainty of the evidence).A study in the USA, evaluated the effects of introducing a law that required pharmaceutical companies to report the gifts they gave to healthcare workers. Another study in the USA evaluated the effects of a variety of internal control mechanisms used by community health centres to stop corruption. The effects of these strategies is unclear because the evidence was of very low certainty. There is a paucity of evidence regarding how best to reduce corruption. Promising interventions include improvements in the detection and punishment of corruption, especially efforts that are coordinated by an independent agency. Other promising interventions include guidelines that prohibit doctors from accepting benefits from the pharmaceutical industry, internal control practices in community health centres, and increased transparency and accountability for co-payments combined with reduced incentives for informal payments. The extent to which increased transparency alone reduces corruption is uncertain. There is a need to monitor and evaluate the impacts of all interventions to reduce corruption, including their potential adverse effects.

Twitter Demographics

The data shown below were collected from the profiles of 40 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 440 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Netherlands 1 <1%
Saudi Arabia 1 <1%
Unknown 437 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 69 16%
Researcher 54 12%
Student > Ph. D. Student 42 10%
Student > Bachelor 34 8%
Student > Postgraduate 24 5%
Other 86 20%
Unknown 131 30%
Readers by discipline Count As %
Medicine and Dentistry 92 21%
Nursing and Health Professions 57 13%
Social Sciences 30 7%
Psychology 19 4%
Economics, Econometrics and Finance 16 4%
Other 68 15%
Unknown 158 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 57. 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 06 September 2022.
All research outputs
#653,569
of 23,368,819 outputs
Outputs from Cochrane database of systematic reviews
#1,312
of 12,645 outputs
Outputs of similar age
#12,863
of 315,102 outputs
Outputs of similar age from Cochrane database of systematic reviews
#37
of 261 outputs
Altmetric has tracked 23,368,819 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,645 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 33.0. This one has done well, scoring higher than 89% 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 315,102 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 261 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.