Evidence map›Paper›PMID 27528494›Full record

SynthesisThe Cochrane database of systematic reviews2016

Interventions to reduce corruption in the health sector.

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

Open access · hybridAbstract readSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 6 pooled it
30.1field-weighted citation impact, top 1% 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

48 citing papers in PubMed, 6 syntheses or guidelines pooled it, 96 citations in OpenAlex.

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  6. Interventions to reduce corruption in the health sector.The Cochrane database of systematic reviews · 2016
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  9. Do institutions matter for citizens' health status? Empirical evidence from Italy.The European journal of health economics : HEPAC : health economics in prevention and care · 2025
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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

4 authors at 4 institutions in 5 countries.

Rakhal GaitondeDepartment of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Andrew D Oxman
Peter O Okebukola
Gabriel Rada
Indian Institute of Technology Madras · INJohns Hopkins University · USNorwegian Institute of Public Health · NOPontificia Universidad Católica de Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCorruption 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.

objectivesOur 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. SEARCH

methodsWe 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. SELECTION CRITERIA: 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. DATA COLLECTION AND ANALYSIS: 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. MAIN

resultsNo 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. AUTHORS'

conclusionsThere 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.

Indexed as

Health Care SectorLaw EnforcementControlled Before-After StudiesCross-Sectional StudiesFraudGermanyGuidelines as TopicHumansIndiaKyrgyzstanReimbursement MechanismsRepublic of KoreaSocial ResponsibilityUnited States

Identifiers

PMID27528494
PMCPMC5014759
OpenAlexW1727765787

What OpenQuestion holds

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LicenceCC BY-NC
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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.