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Table 4 Microenvironmental and Collaborative factors that influence health insurance fraud

From: Fourteen years of manifestations and factors of health insurance fraud, 2006–2020: a scoping review

Description Explanation Contribution of studies
+− + ++ − - ++
Microenvironmental Factors
 Demographic characteristics Sex woman    (Musal, 2010; Zhou et al., 2016)   (Lesch & Baker, 2013) (Manocchia et al., 2012)
It affects more adults and the eldery    (Timofeyev & Busalaeva, 2019; Zhou et al., 2016)   (Lesch & Baker, 2013) (Goel, 2020)
Predominant white race       (Manocchia et al., 2012)
Married, marital status   (Zhou et al., 2016)     
Place of residence: more urbanized states    (Musal, 2010; Ribeiro et al., 2020)    (Goel, 2020)
They have insured       (Manocchia et al., 2012)
 Predominant English language In cities where multiple languages are spoken, the predominant language can influence HIF.       (Manocchia et al., 2012)
 Diagnostics The diagnosis of patients is one of the main data produced in health providers, which is used to prevent and detect fraud and abuse and determine the future risk of becoming ill. (Sun et al., 2020)   (Manocchia et al., 2012; Shin et al., 2012)   (Johnson & Nagarur, 2016; Massi et al., 2020; Park et al., 2016) (Liou et al., 2008)
 Medical and surgical treatments Medical procedures, treatment and surgical decisions can become complex and specialized, which could hide fraud.    (Hillerman et al., 2017)   (Lee et al., 2020) (Liou et al., 2008; Manocchia et al., 2012)
 Specialities Medical or other health -related specialties.   (Bauder et al., 2017) (Shin et al., 2012)   (Herland et al., 2020; Johnson & Nagarur, 2016)  
 Medications Medical prescription, dispensing, cost and consumption are variables of analysis that can condition collusion or other forms of fraud and medical abuse. (Haddad Soleymani et al., 2018; Sun et al., 2020; Victorri-Vigneau et al., 2009)   (Kose et al., 2015; Shin et al., 2012)   (Johnson & Nagarur, 2016) (Aral et al., 2012; Herland et al., 2018; Lin et al., 2008; Liou et al., 2008; Weiss et al., 2015)
 Chronic health condition The health condition could condition the fraud, includes rare and orphan chronic conditions.     (Manocchia et al., 2012)   (Liou et al., 2008)
 Risk of illness The risk score for illness is considered.       (Manocchia et al., 2012)
 Ethics and morals The health insurance market is not immune to intrapersonal processes such as ethics and the offer of moral risks, which could influence the actors’ positions and their behaviour. (Tseng, 2016) (Bourgeon & Picard, 2014; Dionne et al., 2009; Jou & Hebenton, 2007; Kumar et al., 2011; Tseng & Kang, 2015; Wang, 2014; Zhou et al., 2016) (Ribeiro et al., 2020) (Duszak & Duszak, 2011) (Lesch & Baker, 2013)  
 Perception of inequity and injustice The relational dynamic produces a perception of injustice or inequity. (Ribeiro et al., 2020)     (Lesch & Baker, 2013)  
 Information asymmetry Asymmetric information occurs when one of the actors does not have the same information, this is reflected in the behaviours adopted by the different actors and their billing processes.    (Kerschbamer & Sutter, 2017; Kumar et al., 2011; Ribeiro et al., 2020; Zhou et al., 2016)    
 The decision of the adjusters The person who can decide when a settlement is approved or disapproved is one of the most decisive factors.      (Tseng & Kang, 2015)  
 Strengthening of capacities Training, seminars. (Myckowiak, 2009)      
 High deductibles and coinsurance The deductible is a fixed payment before the insurance covering the remaining eligible expenses, while coinsurance is a percentage of the cost of care. Both are out-of-pocket payments and depend on the health insurance plan contract.       (Lammers & Schiller, 2010)
 Bad economic situation A bad economic situation generates financial pressure, which can cause fraud.    (Ribeiro et al., 2020)    
Collaborative factors
 Relationship between the health professional and the patient The familiarity that exists between the health professional and the patient can influence fraud and abuse.   (Wang et al., 2017) (Wan & Shasky, 2012)    
 The complicity between the provider and the insurer The rates agreed between providers and insurers are usually high to increase premiums, deductibles and coinsurance.    (Bayerstadler et al., 2016)    (Lin et al., 2008)
 Relationship between the consumer and the provider Relationships between consumers and providers could generate an excessive demand for health services. The high number of patients per provider could hide the possibility of HIF.    (Musal, 2010; Shin et al., 2012)    (Lin et al., 2008)
 Relationship between the consumer and the insurer Greater interaction between the consumer and the insurer through complaints or calls is associated with the fraud.      (Lesch & Baker, 2013) (Manocchia et al., 2012)
 The influence of bosses The bosses often influence the personnel’s decisions to modify their behaviour, for example, the processes related to the approval of medical claims.       (Tseng & Kang, 2015)
 The guānxi between insurance salespeople and customers Guānxi refers to the lasting social connections and relationships that a person in China uses to exchange favours with a specific purpose. These connections can be expressed in attitudes, intentions or perceptions.       (Tseng, 2016)
  1. For each study, we denote with a positive sign (+) when the factor increases the HIF, and a negative sign (−) if the factor reduces the HIF; when used a single sign, it indicates that the study proved a theoretical or narrative contribution. A factor can show both signs simultaneously (+−), which means that its influence is ambivalent. In contrast, a double sign indicates that the study has an applied validation based on a method de experimentation or quasi experimentation