Evidence map›Paper›PMID 32975465›Full record

ArticleInquiry : a journal of medical care organization, provision and financing

Fraud and Abuse in the Saudi Healthcare System: A Triangulation Analysis.

Wadi B Alonazi

Abstract read
In one paragraph

Article in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

1 author.

Wadi B AlonaziHealth Administration Department, King Saud University, Riyadh, Saudi Arabia.ORCID 0000-0002-3850-4437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the insurance industry, the majority of fraud and abuse cases fall into a limited number of patterns, yet false claims normally lead to negative national, local, and organizational effects. Through monitoring the exploitative and abusive behavior commonly found in healthcare services, this paper aims to analyze initiatives implemented by governmental and related healthcare insurance agencies in Saudi Arabia to reduce moral offenses. To accomplish this objective, major governmental health insurance policy documents were analyzed at the macro-level. At the meso-level, semi-structured interviews were conducted with five health insurance professionals on measures undertaken to prevent such incidents. At the micro-level, the critical factors of fraudulent behaviors were analyzed using a retrospective analysis. Data were retrieved from anti-fraud records of ten leading health insurance companies and the focus was mainly on individuals involved in unethical practices between 2014 and 2019. After a full audit was completed, the results concluded that the Saudi healthcare system is composed of twenty-six cooperative health insurance agencies and over 5,202 health services providers. The official documents contain the details of various moral hazard measures. On annual average, more than 196 fraudulent cases were reported with a claim rejection rate of approximately 15%. The majority of fraud cases were reported in dental services with invalid card usage, followed by obstetrics-gynecology services (47 and 113 cases, respectively). Females tended to make up most deceit cases in obstetrics-gynecology with a high level of abuse (95% confidence interval: -83.398 to -24.202;

Indexed as

Delivery of Health CareFraudInsurance, HealthFemaleHumansRetrospective StudiesSaudi Arabiaabusefraudhealth insuranceMeasuresSaudi Arabia

Identifiers

PMID32975465
PMCPMC7522845

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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.