From Allegations to Actions: Examining the Impact of Fraud Reporting Mechanisms in Healthcare

From Allegations to Actions: Examining the Impact of Fraud Reporting Mechanisms in Healthcare | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article From Allegations to Actions: Examining the Impact of Fraud Reporting Mechanisms in Healthcare Isaac Asamoah Amponsah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4361321/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: The U.S. healthcare sector is characterized by a diverse mix of public and private funding and provision, resulting in a lack of a singular governing philosophy. Both the public and private sectors are known for providing high-quality medical services. However, since 1980, healthcare spending in the U.S. has substantially increased. The immense size and financial resources of the healthcare sector make it a prominent target for fraudulent activities. Aim This study investigated the impact of collaborative efforts between managed care organizations (MCOs) and oversight agencies on the detection and reduction of healthcare fraud within the Illinois Medicaid program. Method This study examines how collaboration between MCOs and oversight agencies impacts healthcare fraud in Illinois Medicaid. A FOIA request for complaint data was sent to the Illinois Department of Healthcare and Family Services. The Illinois Medicaid Office of the Inspector General oversees program integrity and maintains e database to prevent the enrollment of excluded providers. Results As of September 20, 2023, 2,741 providers were sanctioned, including 857 physicians, 679 waiver service providers, 159 pharmacies, and 157 Medicare providers. Over the period from September 2022 to August 2023, 1,059 fraud referrals were recorded, with internal data mining contributing the most (448) and County Care being the top-referring MCO (260 cases). The collaborative efforts between MCOs and the Medicaid – Office of Inspector General led to the identification of $ 23,830,110 in questioned costs, resulting in a recovery of $ 13,441,726 in fiscal year 2021. Conclusion/Recommendation: The findings emphasize the significance of data sharing and transparency in the fight against fraud. The imposition of sanctions on errant healthcare providers has emerged as a key deterrent against fraudulent activities. To combat fraud and information gaps, a comprehensive strategy is needed. This includes empowering patients, improving communication, using advanced analytics, and enforcing regulations. User-friendly digital platforms provide reliable information, enabling informed decisions and reducing disparities. Strengthened collaboration and advanced analytics are crucial for early fraud detection, preserving healthcare integrity, and preventing financial losses. Health Policy Figures Figure 1 Figure 2 Figure 3 INTRODUCTION There is too much fraud committed in the healthcare system. Since 1980, healthcare expenditures in the US have increased significantly. The sheer magnitude of both the healthcare sector's scale and the substantial financial resources involved render it a prime target for fraudulent activities (Liu et al., 2013 ). Fraud involves intentional deception or misrepresentation intended to result in an unauthorized benefit. Fraud is widespread and very costly to the healthcare. Therefore, prioritizing robust fraud detection measures is imperative for mitigating the overall cost of healthcare services (Liu et al., 2013 ). Kenneth J. Arrow coined the phrase "asymmetric information" to refer to a situation in which there is an imbalance in knowledge among providers of medical services because only a select few have access to pertinent knowledge while the majority do not (Trihastuti et al., 2020 ). Informational asymmetries among economic agents have received a great deal of attention since Akerlof's groundbreaking study in 1970 (Cardon et al., 2001). Akerlof’s “lemon” theory applies in all markets where asymmetric information exchange exists between buyers and sellers (D. W. Johnson, 2015 ). A sick person knows more about their medical needs, giving them an advantage when buying health insurance. They are willing to pay more for coverage due to higher expected medical costs. In response, private insurers screen out high-risk clients, set coverage limits, and increase prices. This makes insurance more expensive for healthy people, causing some people to leave. This information gap adds to the high costs, administrative expenses, and uninsured population in the U.S. healthcare system. Many Americans struggle to afford necessary care as a result (D. Johnson, 2015 ). In 1971, before the advent of the internet and social media, the prominent Nobel Prize-winning economist Herbert A. Simon, PhD, noted that “information consumes the attention of its recipients” …a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. The problem of information asymmetry is exacerbated by ever-growing information overload. The healthcare industry is a trust industry since patients rely on doctors to provide them with good sound advice to stay healthy. Information imbalance among the various actors in the healthcare industry can leave room for fraud to occur. If patients fail to check or request their explanation of benefits (EOBs) from their healthcare providers, it opens the door for healthcare providers to bill for services they did not render to that patient. Managed Care Organizations (MCOs) are mandated by federal code 42. The CFR was 438.608 for tackling fraud, waste and abuse in healthcare. MCOs are mandated to have special investigative units (SIUs) that act as the first line of defense for fraud prevention and detection. Considering a situation where a healthcare provider is enrolled with multiple MCOs, there is need for these MCOs to share information on this provider to bridge any information gap they might have with this provider. It is the work of regulators (usually the Office of Inspectors Generals (OIG) to ensure that they bridge the information asymmetry gap between their contracting MCOs through strategies such as focus groups, round table discussions, tag calls and information sharing sessions. MCOs might not be the only source of allegations of healthcare fraud. Other sources of allegation include patients, law enforcement and other external agencies. Healthcare laws such as false claims, anti-kickback statues, and physician self-referral seek to ensure that physicians are making the best decisions for patients and not making decisions on monetary incentives. Reference). Regulators such as the Drug Endorsement Administration (DEA0) need to monitor doctors for the prescription of controlled substances such as opioids and ADHD medications (REFERENCE). Figure 1 above shows how the Medical Fraud Control Unit (MFCU) processes referrals received from the public, internal data mining and from state and federal agencies into potential outcomes such as convictions, settlements, recoveries, terminations and exclusions of providers from State Medicaid Programs. This emphasizes the importance of information sharing among various actors in the healthcare industry in bridging the gap in information asymmetry. Research Question and Hypothesis Development 1. How does the collaborative approach between MCOs and oversight agencies impact the detection and reduction of healthcare fraud in the Illinois Medicaid program? 2. How can the Medicaid Inspector General help prevent healthcare fraud in the wake of information asymmetry? LITERATURE REVIEW Information Asymmetry in Healthcare . Information asymmetry occurs in healthcare because patients lack the medical expertise that healthcare providers possess. Patients rely on health providers to work in their best interests without conflict because of this information asymmetry (Fabes et al., 2022 ). Numerous authors have studied the effects of asymmetric information on the value and cost of medical care since Kenneth Arrow introduced the topic of asymmetric information in health insurance (Major, 2019 ). There is a plethora of intricate relationships between individuals who receive, provide, and finance health care in the United States. Everyone is impacted by health care, whether they are well, occasionally ill, or suffering from a serious illness. Childbirth, cosmetic surgery, help managing a chronic disease, and hospice care at the end of life are all included in the field of medicine (Moses et al., 2013 ). Although the American health care system offers some of the most cutting-edge options available in the world, it is not the most effective. Inequalities in health care costs, availability, and quality also exist among the population, mainly due to information asymmetry (Care et al., 2013 ). Information asymmetries exist in two forms. When important information is dispersed across entities that are close to each other, there is horizontal information asymmetry. Even if some of the entities might have access to more information than others, none of them possesses all the information. When one type of entity has information while another does not, and when an aggregated collection of information-poor entities does not, there is vertical information asymmetry (Clarkson et al., 2007 ). Asymmetrical information between two parties might result in ineffective exchanges and even health consequences. Concerns regarding information asymmetry are crucial when one party is unaware of the caliber of another party or when that party is worried about the behavioral propensity of the other party (Courtney et al., 2016 ). Consumers have limited control over healthcare service choices, leading to inefficiency in the United States due to information asymmetry. This unequal distribution of information among stakeholders is a major issue (Cruz & Kini, 2007 ). The interactions between patients and other healthcare professionals, as well as those between patients and doctors, are governed by professional ethics, which includes both individual and organizational standards of conduct. Among them are moral standards, or bioethics, which nonmaleficence, autonomy, and fairness. In their capacity as professionals, doctors are in charge of all patient medical care (Trihastuti et al., 2020 ). Patients who are also consumers are unable to fully comprehend the efficacy of medical interventions because they are more concerned with finding a cure for their illness or a way to achieve pain relief. Therefore, it is particularly challenging for consumers to understand and assess the quality of healthcare services (Cruz & Kini, 2007 ). Patients with low medical and health literacy may find it difficult to comprehend and communicate their health needs to healthcare professionals, which may lead to higher healthcare costs and subpar health outcomes. However, due to the internet, technological improvements have provided people with a platform for obtaining health-related information that is crucial for managing medical issues (Osei-frimpong et al., 2016 ). For many, it has become standard practice to access medical information from websites, medical publications, doctors, health plans, family, and friends. Often, patients question doctors about treatment plans, forcing them to respond in a considerate manner (Cruz & Kini, 2007 ). Many economists believe that information asymmetry is a primary cause of market failure. As information overload, continues to worsen, information asymmetry becomes more severe (Wolfe et al., 2021 ). The COVID-19 epidemic and tightening budgets have heightened the need for cost-effective healthcare worldwide. The evidence implies that practitioners have a low level of cost awareness. According to a systematic review by, only 33% of physicians reported that pharmaceutical companies searched databases for appropriate treatments, and medical device manufacturers struggled to handle requests as demand for their products increased exponentially, highlighting the importance of effective information and knowledge management within healthcare organizations. Information asymmetry is also a social scenario in which some members of the system have access to information while others do not. The evidence suggests that the health care system has radical information asymmetry. In terms of the development of medical research, the availability of highly qualified physicians and nurses and access to the most recent medications have made the American health care system among the best in the world. However, it is by no means the most fruitful. For instance, the United States was ranked first by the WHO for health spending per person but only 37th for overall health system performance (Care et al., 2013 ). It is clear that a doctor does not work in a vacuum and does not independently make judgments; instead, they compete with other doctors inside the facility for better roles, reputation, and ultimately for greater pay and cost reimbursement (Major, 2019 ). Currently, without full patient access, medical information is commonly maintained by individual clinicians or private data collectors. To completely describe a patient’s medical history, patients are unable to fully explore alternatives, contribute to and fix inaccuracies in their own data, or share their information with new practitioners. By ensuring that accurate health information is made available to appropriate individuals at the appropriate time, patient-centered information exchange should provide patients with more control and better results (Engelhardt, 2017 ). Less documented is the impact that information asymmetry has on healthcare delivery once patients enter the system. Information asymmetry helps cause “lemon-like” outcomes in the following three ways: doctors and other caregivers overwhelm patients with information and deliver unnecessary treatments; doctors and other caregivers do not engage patients sufficiently and fail to provide necessary care; and uniformed patients demand unnecessary treatments (D. Johnson, 2015 ). Fraud in the US Healthcare Industry Ai et al., ( 2018 ) define fraud as “…an intentional deception or misrepresentation made by a person with the knowledge that the deception could result in some unauthorized benefit to himself or to some other person.” In particular, in the United States, fraud occurs frequently and has an impact on a variety of businesses and organizations. One specific form of fraud that has become a major issue for many citizens is healthcare fraud. The American government and its private sector organizations have battled healthcare fraud for decades, and the war continues. People often cheat for a variety of reasons, one being pressure. This could be internal or external pressure. Family problems, financial or the drive to advance professionally might put someone under internal pressure. External factors may include a faltering economy (Dean et al., 2013 ). Because healthcare fraud can be caused by a variety of parties, including the patient, the health care professional, and any intermediates, fraud identification is difficult, especially in claims involving medical services (Alzubi, 2021 ). Healthcare fraud includes actions taken by a diverse group of people. It encompasses fraud committed by and against medical staff, medical facilities, health insurers, MCOs, producers of prescription medications and other medical supplies, and even patients (Krause, 2015 ). Health insurance fraud is the deliberate deception of a health insurance company that causes unauthorized payment of healthcare benefits to a person or organization. Billing for services that were not given, upcoding of services, upcoding of products, duplicate claims, and unnecessary services are the major categories used to describe claims of health insurance fraud (Rawte, 2015 ). Fraud in the healthcare insurance market is a pressing concern, as fraudulent healthcare activities are costly (Alzubi, 2021 ). The ordering of treatments or diagnostic tests that are not required is one of the many scams that are carried out on unwary patients (Hannigan, 2006 ). Aside from actual health concerns, testing and billing are the two areas where there is the greatest danger, notably fraud risk (Dean et al., 2013 ). Upcoding is one of the most common fraudulent practices in healthcare coding and billing. Upcoding is the practice of invoicing for higher-priced services than those that are actually rendered. This occurs when medical professionals or claimants enter codes that denote either incomplete or unreceived treatment (R. Bauder et al., 2016 ). Utilizing patient ignorance to create supplier-induced demand and technology imperatives may indicate that the principle of patient autonomy has been violated (Trihastuti et al., 2020 ). It is never simple to acknowledge healthcare fraud because of its immediate, detrimental effects on human lives. To cease denying losses, however, is the first step toward lowering them. How can a company apply the best solution and lessen losses if it is unaware of the size or type of those losses? (Gee et al . 2010). Since the advent of electronic medical records, emergency physicians have been shown to adjust their billing codes upward. Although fraudulent billing has always occurred, the era of electronic medical records has made it more blatant. Doctors’ handwritten notes were considerably less likely to contain descriptions of actions that the doctor had not taken. Some people do not seem to be able to resist the desire to employ a few clicks (Hoffer, 2023 ). Approximately one-third of all healthcare costs in the US are attributable to fraud, waste, and abuse. Fraud can take many different forms, including being perpetrated by dishonest service providers, organized crimes, compliciting patients, and falsely stating eligibility for health insurance coverage. Due to its patient demographics and less rigorous payer supervision than commercial insurers, Medicaid, a state-run healthcare program funded by the federal government, is particularly vulnerable (Thornton et al., 2015 ). Because the Medicaid system is operated separately and has no coordination between the states, it is particularly vulnerable to fraud and abuse. Because the insurer, beneficiary, and provider have asymmetrical information, insurance fraud and abuse are typically difficult to detect (Travaille et al., 2011 ). Given that states spend more than a fourth of their annual budget on the Medicaid program, which competes with financing for other crucial services, fraud control enforcement is crucial for the sustainability of states' medical insurance programs (Flasher & Lamboy-Ruiz, 2017 ). Individuals' and communities' rights are violated by corruption. Health systems, people, and health outcomes are all significantly impacted by corruption in regard to health. In addition to worsening antibiotic resistance and undermining all of our attempts to manage infectious and noncommunicable diseases, it is estimated that corruption kills at least 140000 children per year. A pandemic that is neglected is corruption (García, 2019 ). Health-related corruption can range from low-level local corruption to high-level national or even international corruption. It manifests in a variety of ways, including extortion, theft, embezzlement, nepotism, and improper influence (García, 2019 ). Legislation alone cannot stop Medicare fraud. Medicare fraud has been acknowledged as a concern since the Clinton administration, and partnerships across government organizations have been formed as a preventative measure. Medicare fraud has been a recurring offense, and laws and procedures alone have not been sufficient to stop it. Medicare fraud can be reduced but will likely not be completely eradicated with additional investments in governmental collaborations and improved detection tools. To ''keep a lid on'' the issue, continued attention is necessary (Hill et al., 2014 ). Healthcare fraud continues to pose a serious threat to the American economy and public despite increasing financing and prosecution efforts on the part of the government. Even though healthcare fraud cannot be completely eradicated, particular measures can be used to control these sophisticated fraudulent operations (Stowell et al., 2018 ). Drugs that are being sold as counterfeits are those that have been made fraudulently or intentionally or that have had their source, manufacturer, or identity incorrectly identified. Both branded medications and their less expensive generic analogs are subject to counterfeiting. Common counterfeiting targets include expensive high-demand medications such as chemotherapeutic agents, antibiotics, vaccinations, erectile dysfunction medications, weight loss aids, hormones, analgesics, steroids, antihistamines, antivirals, and antianxiety medications (Williams & McKnight, 2014 ). In the United States and throughout the world, the sale of fake pharmaceuticals is on the rise. Since most complaints of fake pharmaceuticals are anecdotal, it is challenging to determine the actual scope of the issue. Additionally, some people may never suspect or recognize that they are taking a product that may be fake or have altered chemicals. The classes of pharmaceuticals that are most frequently found to be fake are antibiotics and antiparasitics (Fantasia & Vooys, 2018 ). The prevalence of market-place counterfeit drugs has increased during the last ten years. In regard to the identification, legitimacy, and/or effectiveness of the product, counterfeit pharmaceutical products can be defined as the manufacture and distribution of dishonestly labeled drugs. The widespread use of fake drugs has had life-threatening effects on populations, including an increased risk of chronic illness, inadequate treatment results, severe drug responses, and fatality (Bolla et al., 2020 ). A study by Taleb & Madadha, (2013) confirmed that drug fraud is a significant public health issue that affects governments, pharmaceutical firms, and the general population globally. It also highlights the need for new statistical databases and national studies on the prevalence of drug counterfeiting to assess and make it easier to monitor the scope of the issue. Impacts of Information Asymmetry and Fraud The fraudulent use of health insurance results in annual costs of hundreds of billions of dollars. In particular, the US healthcare sector accounted for approximately one-sixth of the US economy in 2017 (or $ 3.5 trillion; 18% of GDP). Therefore, it is critical to reduce fraud, waste, and abuse to increase the effectiveness of the healthcare system (Ai et al., 2018 ). high degree of knowledge asymmetry is one of the main causes of greater costs and lower quality (Care et al., 2013 ). Worldwide, fraud costs the economy more than $ 4.5 trillion annually (Wolfe et al., 2021 ). As long as one does not become overtly blatant or arrogant, healthcare providers can cheat because it is simple to do so and generally risk-free. It may be said that lying is a side job. High pay has always been an important factor in choosing to pursue a career in medicine, but today's demand is greater than ever (Skeen, 2003 ). Healthcare fraud jeopardizes patient safety, lowers the standard of service, and wastes limited resources (Lorenz, 2013 ). Untrue knowledge about medicine is one of the greatest threats to world health. By escalating already existing societal injustices, stigmas, gender discrepancies, and generational chasms, misinformation can make societies less cohesive (Shajahan & Beaumont, 2022 ). Patient harm can result from taking advantage of patients' ignorance or convincing them to use additional health services during a consultation or prescription. This can be accomplished utilizing the technological imperative, in which doctors push patients to submit to a variety of laboratory tests or offer to employ cutting-edge technology that may not be essential so that they can quickly determine the type of medical care that is needed. Additionally, because of their collaboration with pharmaceutical firms, doctors can also recommend more expensive medications to their patients. Patients may incur increased costs to buy products as a result (Trihastuti et al., 2020 ). Healthcare fraud is a major issue that costs the American government billions of dollars annually. Fraud, waste, and abuse account for approximately one-third of all healthcare costs in the US. The US healthcare system loses between $ 600 and $ 850 billion yearly to fraud, waste, and abuse, with $ 125 to $ 175 billion of this coming from fraudulent behavior (Travaille et al., 2011 ). More than US $ 7 trillion is thought to be spent globally on healthcare services, and at least 10–25% of that amount—hundreds of billions of dollars annually—is lost directly to corruption. The amount of corruption wasted by these billions is greater than what the WHO estimates will be required each year to close the gap and provide universal health care globally by 2030 (García, 2019 ).Due to the significant financial repercussions, fraud, especially upcoding, is a major concern. To decrease the number of fraudulent instances and associated cost consequences, fraud detection is essential (Bauder & Khoshgoftaar, 2017 ). The most straightforward form of harm to identify is probably financial harm to patients, partly because it reflects economic cost to the government. The cost-sharing nature of the healthcare reimbursement system means that patients are frequently financially impacted by fraud (Krause, 2015 ). Fraudulent acts can also affect patients physically, albeit financial harm may be the easiest kind of harm to spot. When unneeded medical operations are carried out just to be reimbursed by the federal health care program, individuals are at risk of physical harm (Krause, 2015 ). Patients may suffer less obvious harm from healthcare fraud in addition to financial and bodily loss. Information, primarily patient information, is one of the main commodities in the healthcare system. At its foundation, information is the record of our individual health histories; it will be used to make judgments about future medical treatments as well as for a variety of other things, such as insurance underwriting and job applications (Krause, 2015 ). The health of a patient may suffer from using counterfeit drugs. Adverse side effects, treatment failure, resistance, toxicity, and even mortality can occur as a result of the use of subpar medications. Pharmaceutical firms, healthcare workers, pharmacists, and patients must all be informed about fake drugs and the laws that are being implemented to stop them (Williams & McKnight, 2014 ). Drug counterfeiting endangers the public's health, wastes consumer money, and lessens incentives for innovation and research. Better state licensing oversight of the medicine vendors would be beneficial prevent patients from losing faith in the value of pharmaceuticals and failing to adhere to their treatments, it is crucial to find a solution to counterfeit drug problems. Consumer purchases of counterfeit pharmaceuticals have significantly increased as a result of the growth of the internet and the challenges in regulating drug sellers via the internet (Blackstone et al., 2014 ). Information Asymmetry between Managed Care Organizations and Providers: Implications for Healthcare Fraud in the USA There are complex and diverse relationships between healthcare fraud and information asymmetry among healthcare providers in the U.S. Information asymmetry occurs when one side of a transaction or connection has more information than the other, and it can lead to opportunities for exploitation or unethical behavior (Capelleveen et al., 2016 ; Perez, 2017 ). MCOs frequently rely on healthcare organizations to submit complete and correct claims for payment. Nevertheless, if there is substantial information asymmetry and providers know more about the precise services provided, the coding systems, or the medical necessity of the procedures, it may present opportunities for fraudulent billing. Providers may take advantage of this knowledge imbalance by upcoding, unbundling, or purposefully misrepresenting services (Capelleveen et al., 2016 ; Ekin et al., 2018 ; Thornton et al., 2015 ). Due to information asymmetry, it may be difficult for MCOs to properly monitor and identify provider fraud. By filing false claims or participating in actions that are not in the patients' best interests, providers may take advantage of the absence of scrutiny. MCOs may have trouble spotting patterns of dishonest behavior or determining the medical necessity of the services rendered without access to complete and accurate information regarding the services rendered (Care et al., 2013 ; Ekin et al., 2018 ; Thornton et al., 2015 ). Information asymmetry can also be caused by MCOs not having access to complete patient data. Providers may have critical patient-specific data, such as past diagnoses, treatments, or prescriptions, that are not disclosed to MCOs. Due to the potential incomplete knowledge of the medical history and current treatments of MCOs, this information gap may result in fraudulent behaviors, including double billing, needless surgeries, or prescription fraud (Capelleveen et al., 2016 ; Care et al., 2013 ; Goel, 2020 ). Addressing information asymmetry between MCOs and providers is crucial in combating healthcare fraud in the USA. Efforts to improve transparency, enhance communication channels, and promote data sharing can help reduce the information gap. Implementing robust fraud detection systems, conducting audits and investigations, and promoting provider education and compliance programs are additional strategies for mitigating the risk of fraud. How can the offices of inspectors generally help prevent healthcare fraud in the wake of information asymmetry? In light of information asymmetry, regulators such as the Federal and State Offices of the Inspector General (OIG) are essential for avoiding healthcare fraud. The U.S. Department of Health and Human Services (HHS), which functions as an independent oversight body, is in charge of maintaining the integrity of all federal healthcare programs, including Medicare and Medicaid (Anthony, 2017 ). The HHS – OIG works in collaboration with sister agencies such as the Federal Bureau of Investigations (FBI), Department of Justice (DOJ), Medicaid Fraud Control Units, Medicaid Inspector General Offices, and Drug Enforcement Administration (DEA). To find instances of fraud, waste, and abuse within the healthcare system, the OIG primarily conducts audits and investigations. Through these initiatives, the OIG reveals fraudulent schemes, investigates billing procedures, and pinpoints fraud-prone locations. The OIG can help resolve information asymmetry by obtaining crucial data and exposing fraudulent acts by using its jurisdiction to access information and investigate suspicious actions (Kalb, 2015 ; Lorenz, 2013 ; Stowell et al., 2018 ; Travaille et al., 2011 ). To identify patterns of fraud, the OIG also employs advanced data analytics strategies such as predictive modeling, link analysis, improbable billing hours, and time dependent billing. The OIG can find outliers, anomalies, interrelated providers, and potential fraud schemes by examining claims data and other pertinent information they receive from the public, law enforcement and MCOs. The OIG can help prioritize investigations and reduce information asymmetry by concentrating on high-risk providers and practices using these data-driven methodologies, which also enhances fraud prevention efforts (Ai et al., 2018 ; R. A. Bauder & Khoshgoftaar, 2017 ; Capelleveen et al., 2016 ; Drabiak & Wolfson, 2020 ; Skeen, 2003 ; Stowell et al., 2018 ). To encourage adherence to federal healthcare rules and regulations, the OIG also offers advice and instruction to healthcare professionals, organizations, and beneficiaries. The OIG offers guidelines for preventing fraud, identifies prevalent fraud schemes, and assists stakeholders in better understanding their responsibilities through publications, fraud briefs, press releases, public and provider notices, and training programs. OIG helps to reduce information asymmetry and promote transparency in the healthcare system by distributing knowledge and encouraging a culture of compliance (Dean et al., 2013 ; Drabiak & Wolfson, 2020 ; Hill et al., 2014 ; Kalb, 2015 ; Stowell et al., 2018 ). State regulators such as the Illinois Department of Healthcare and Family Services release providers notices from time to time to keep providers abreast of change policies as well as fee-for-service payment schedules, as does the federal Center for Medicare and Medicaid Services (C.M.S.). These are the ways in which regulators try to reduce information asymmetry. Notably, the public health emergency (PHE) declared in March 2020 raises concerns about how difficult it might be for providers to keep up with changing policies and notices issued by regulators. The uncertainty surrounding public health emergencies has led to constant changes in policies making it difficult for healthcare providers to catch up. To improve fraud prevention efforts, the various Medicaid OIGs work with a variety of stakeholders, including law enforcement agencies, state Medicaid Fraud Control Units (MFCUs), and commercial organizations. This cooperation makes it easier to share information, conduct joint investigations, and plan enforcement measures. These organizations can overcome information asymmetries, combine resources, and create strategies to prevent healthcare fraud more successfully by cooperating (Carroll, 2016 ; Kalb, 2015 ; Stowell et al., 2018 ). To strengthen program integrity and prevent healthcare fraud, the OIG makes policy recommendations. These suggestions might be made in the form of new laws, revised regulations, or better program management. The OIG helps to resolve information asymmetry and boost fraud prevention efforts at both the systemic and organizational levels by lobbying for regulatory reforms and exchanging best practices (Dobrzykowski, 2019 ; Drabiak & Wolfson, 2020 ; Kalb, 2015 ; Stowell et al., 2018 ). Various Medicaid and Medicare OIG offices also work with other state agencies when they establish from investigations that other agencies are needed to address the original allegation. For example, if a Medicaid OIG office receives an allegation from a patient concerning quality of care concerns, the Medicaid OIG office might refer it to the Department of Public Health to also investigate and address the quality-of-care concerns expressed by the patient in his allegation. For criminal allegations, the Medicaid OIG can also choose to refer to the Federal Bureau of Investigations (FBI). METHODOLOGY/ DATA COLLECTION AND ANALYSIS To answer my research question on how the collaborative approach between MCOs and oversight agencies impacts the detection and reduction of healthcare fraud in the Illinois Medicaid program, I sent a Freedom of Information Act (FOIA) request, pursuant to the FOIA Act, 5 ILCS 140/1 et seq., to the Illinois Department of Healthcare and Family Service through its privacy officer for a monthly count of complaint referrals received by the Medicaid Office of Inspector General from MCOs from 1st September 2022–31st August 2023, organized by an allegation source. The Illinois Medicaid Office of the Inspector General is the agency that has oversight responsibility for ensuring integrity in the state Medicaid program. The Illinois Medicaid – OIG among other duties, maintains a public facing sanction database that keeps track of all healthcare providers who have been excluded, suspended, terminated or barred from the Illinois Medicaid program. These sanctions prevent any MCO from enrolling a sanctioned provider in the Medicaid program. ILLINOIS MEDICAID – OIG SANCTIONS LIST BASED ON PROVIDER TYPE AS AT 20 TH SEPETEMBER 2023 PROVIDER TYPE COUNT OF PROVIDERS PHYSICIAN 857 WAIVER SERVICE PROVIDER 679 (blank) 516 PHARMACY 159 MEDICAR PROVIDER 157 DENTIST 94 PODIATRIST 42 CHIROPRACTOR 39 TAXICAB LIVERY CO 36 PHYSICIANS 29 OTH PROV MES-NON-REG 18 INDEPENDENT LAB 14 NURSE PRACTITIONER 13 OPTOMETRIST 11 AMBULANCE SERV PROV 7 OTH TRAN PROV-NO-REG 6 RURAL HEALTH CLINIC 6 NURSING FACILITIES 6 PSYCHOLOGIST 5 ADVANCED PRACTICE NURSE 5 GROUP 4 TRANSPORTATION - AA 4 HOME HEALTH AGENCY 4 AUDIOLOGIST 3 OCCUPATIONAL THRPST 3 OTH PROV MES-NON-RE 3 LABORATORY 3 PHYSICAL THERAPIST 3 FED QLFY HEALTH CNTR 2 MENTALLY RETRD FCLTY 2 DME/SUPPLIES 2 NURSING 2 CLINICAL SOCIAL 2 OTH BHVR HLTH PRFSNL 1 REGISTERED NURSE 1 SPEECH THERAPIST 1 DMHDD-OBRA 1 HOSPICE 1 Grand Total 2741 Analysis with an Excel pivot table revealed that as of 20th September 2023, 2741 providers had been suspended, excluded or terminated from the Illinois Medicaid program. This list of sanctions is available to the general public including the MCOs who receive sanction alerts firsthand from the Illinois Medicaid – OIG. The sanctions list (which is similar to the federal LEIE database maintained by the HHS – OIG) prevents any MCO that has a Medicaid contract with the Illinois state from enrolling a barred provider. Sometimes. The Medicaid OIG might also sanction recipients (patients) using strategies including but not limited to locking them to a particular physician or provider. This prevents the recipient from doctor shopping if there is credible allegation of the intent to commit healthcare fraud by the recipient. Of the 2741 sanctioned providers, 857 were physicians, 657 were on waiver service program (usually from other agencies such as the Department of Aging and Department of Revenue Services), 159 were pharmacies, and 157 were medical providers. MANAGED CARE ORGANISATIONS HEALTHCARE FRAUD ALLEGATION SOURCES BETWEEN 1 ST SEPTEMBER 2022 TO 31 ST AUGUST2023 THROUGH THE ILLINOIS MEDICAID – OIG FRAUD REPORTING PORTAL ALLEGATION SOURCE MCO Aetna Blue Cross Blue Shield CountyCare Humana Meridian Molina Total Data Mining 89 34 135 10 137 43 448 Customer 4 83 46 17 33 22 205 OIG Subcommittee 30 26 48 3 23 33 163 Care Coordinator 25 65 6 2 22 23 143 Provider Network 2 1 13 1 30 2 49 Law Enforcement 7 5 4 2 1 19 (blank) 3 10 1 4 18 HFPP/NHCAA 6 1 7 Trade Association 3 2 5 Service Broker 1 1 2 Total 160 227 260 34 249 129 1059 The approval to my FOIA request from Illinois MEDICAID – OIG came in the form of an Excel file with the various allegation sources, the MCO who submitted it and the record date or time range. I used Microsoft Excel pivot table to analyze and present the table above. From the above table, we observe that between September 1 2022, and August 31 2023, there were 1059 fraud referrals to the Illinois Medicaid – OIG healthcare fraud reporting portal. These 1059 referrals are shared among 6 MCOs who have a Medicaid contract with Illinois State. Of these 1059 referrals, 448 were discovered or found based on internal data mining by the MCO’s. Among these referrals, 205 were customers. Illinois Medicaid OIG – MCO subcommittee meetings accounted for 163 of the referrals. The OIG subcommittee meeting is a periodic meeting that the Illinois Medicaid – OIG has put in place to allow the sharing of information to help reduce healthcare fraud in the Medicaid program. Participants in this focus group include law enforcement agencies, MCOs, and representatives from the Medicaid Inspector General Office, among other sister organizations. Other sources of allegations include Care coordinators, law enforcement agencies and external agencies, the Healthcare Fraud Prevention Partnership (HFPP) and the National Healthcare Anti-Fraud Association (NHCAA). County Care (260) made the most referrals through the portal within the time frame. The HFPP and NHCAA are private‒public partner organizations committed to combating healthcare fraud. ILLINOIS DEPARTMENT OF HEALTHCARE AND FAMIL SERVICE ANNUAL REPORT 2021 Analysis of the Illinois Medicaid – OIG 2021 Annual Report shows that the collaboration between the MCOs and Medicaid – OIG led to $ 23,830,110 in questioned costs. This figure represents total overpayments identified by the collaborative effort of the Medicaid – OIG, MCOs and other external actors. Out of the total $ 23,830,110 questioned costs, the Medicaid – OIG recovered $ 13,441,726 in fiscal year 2021. CONCLUSION The results from the study showed that the collaborative approach between MCOs and regulators such as Illinois Medicaid – OIG in fraud referral reporting plays a crucial role in the detection and reduction of healthcare fraud within the Illinois Medicaid program. The results underscore the critical role of data sharing and transparency in the fight against healthcare fraud. Furthermore, sanctions meted out to healthcare providers who found guilty of misconduct to play a vital role in combating fraud within the healthcare sector. RECOMMENDATION Addressing information asymmetry and fraud requires a comprehensive approach, including patient empowerment, improved communication, data analytics, and stringent regulatory oversight, ultimately contributing to a more transparent, accountable, and patient-centered healthcare system. The implementation of user-friendly digital platforms for patients and the provision of reliable and accessible medical information can help individuals make informed healthcare decisions and mitigate the risks associated with information asymmetry. Additionally, strengthening collaborative efforts for information sharing among stakeholders and leveraging advanced data analytics tools are crucial strategies for proactively detecting and preventing healthcare fraud, ensuring the integrity of the healthcare system and safeguarding against financial losses. References Ai, J., Lieberthal, R. D., Smith, S. D., & Wojciechowski, R. L. J. (2018). Examining Predictive Modeling – Based Approaches to Characterizing Health Care Fraud. Society of Actuaries . Alzubi, A. J. (2021). Asymmetric Information, Fraud, and Switching Costs in Healthcare Insurance Markets . The University of Queensland. Anthony, M. (2017). Fraud and Abuse. 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Technology Innovation Management Review , 7 (10), 22–35. Fabes, J., Avşar, T. S., Spiro, J., Fernandez, T., Eilers, H., Evans, S., Hessheimer, A., Lorgelly, P., Spiro, M., & The Health Economics Survey group. (2022). Information Asymmetry in Hospitals : Evidence of the Lack of Cost Awareness in Clinicians. Applied Health Economics and Health Policy , 20 , 693–706. https://doi.org/10.1007/s40258-022-00736-x Fantasia, H. C., & Vooys, K. M. (2018). Public Health Implications of Counterfeit Medications. Nursing for Women’s Health , 22 (3), 264–268. https://doi.org/10.1016/j.nwh.2018.03.001 Flasher, R., & Lamboy-Ruiz, M. A. (2017). Impact of Enforcement on Healthcare Billing Fraud : Evidence from the USA. Journal of Business Ethics . https://doi.org/10.1007/s10551-017-3650-z García, P. J. (2019). Corruption in global health : the open secret. Lancet , 394 , 2119–2124. https://doi.org/10.1016/S0140-6736(19)32527-9 Gee, J., Button, M., & Brooks, G. (n.d.). The financial cost of Healthcare fraud:What data from around the world shows . Goel, R. K. (2020). Medical professionals and health care fraud : Do they aid or check abuse ? Managerial and Decision Economics , 41 , 520–528. https://doi.org/10.1002/mde.3117 Hannigan, N. S. (2006). Blowing the whistle on healthcare fraud : Should I ? Journal of the American Academy of Nurse Practitioners , 18 , 512–517. https://doi.org/10.1111/j.1745-7599.2006.00175.x Hill, C., Hunter, A., Johnson, L., & Coustasse, A. (2014). Medicare Fraud in the United States Can it Ever be Stopped? The Health Care Manager , 33 (3), 254–260. https://doi.org/10.1097/HCM.0000000000000019 Hoffer, E. P. (2023). The Electronic Medical Record and Fraudulent. MAYO Clinic Proceedings: Digital Health , 1 (2), 161. https://doi.org/10.1016/j.mcpdig.2023.03.009 Johnson, D. (2015). When Healthcare is a “ Lemon ”: Asymmetric Information and Market Failure. 4Sighthealth . Johnson, D. W. (2015). When Healthcare is a “ Lemon ”: Asymmetric Information and Market Failure How “ Inside Information ” Distorts the Used Car Market . Kalb, P. E. (2015). Health Care Fraud and Abuse. Jama , 282 (12), 1163–1168. Krause, J. H. (2015). A PATIENT-CENTERED APPROACH TO HEALTH FRAUD RECOVERY. The Journal of Criminal Law and Criminology , 96 (2), 579–619. Liu, Q., States, U., Vasarhelyi, M., & States, U. (2013). Healthcare fraud detection : A survey and a clustering model incorporating Geo-location information . Lorenz, F. A. (2013). HEALTHCARE FRAUD IN THE UNITED STATES: ASSESSING CURRENT POLICY AND ITS ROLE IN FRAUD PREVENTION . CALIFORNIA STATE UNIVERSITY. Major, I. (2019). Two-Sided Information Asymmetry in the Healthcare Industry. Int Adv Econ Res , 25 , 177–193. https://doi.org/https://doi.org/10.1007/s11294-019-09732-9 Two-Sided Moses, H., Matheson, D. H. M., Dorsey, R., George, B. P., Sadoff, D., & Yoshimura, S. (2013). The Anatomy of Health Care in the United States. Jama , 310 (18), 1947–1963. https://doi.org/10.1001/jama.2013.281425 Notices . (n.d.). https://hfs.illinois.gov/medicalproviders/notices.html Osei-frimpong, K., Wilson, A., & Lemke, F. (2016). Technological Forecasting & Social Change Patient co - creation activities in healthcare service delivery at the micro level : The in fluence of online access to healthcare information. Technological Forecasting & Social Change . https://doi.org/10.1016/j.techfore.2016.04.009 Perez, V. (2017). Effect of privatized managed care on public insurance spending and generosity : Evidence from Medicaid. Health Economics , 1–19. https://doi.org/10.1002/hec.3608 Phillips, W., Roehrich, J. K., Kapletia, D., & Phillips, W. (2021). Responding to information asymmetry in crisis situations : innovation in the time of the COVID-19 pandemic pandemic. Public Management Review , 1–24. https://doi.org/10.1080/14719037.2021.1960737 Rawte, V. (2015). Fraud Detection in Health Insurance using Data Mining Techniques . Shajahan, A., & Beaumont, W. (2022). Editorials Countering Medical Misinformation Online and in the Clinic . Skeen, J. W. (2003). Health Care Fraud and Industry Structure in the United States. Social Policy & Administration , 37 (5), 516–529. Stowell, N. F., Schmidt, M., & Wadlinger, N. (2018). Healthcare Fraud Under the Microscope : Improving its Prevention. Journal of Financial Crime . https://doi.org/https://doi.org/10.1108/JFC-05-2017-0041 Taleb, Y. A., & Madadha, R. Al. (2013). Pharmacists ’ Awareness of Drug Counterfeiting in Jordan. JOURNAL OF THE ROYAL MEDICAL SERVICES , 20 (2). https://doi.org/10.12816/0000079 Thornton, D., Brinkhuis, M., Amrit, C., & Aly, R. (2015). Categorizing and Describing the Types of Fraud in Healthcare. Procedia - Procedia Computer Science , 64 , 713–720. https://doi.org/10.1016/j.procs.2015.08.594 Travaille, P., Müller, R. M., Thornton, D., & Travaille, P. (2011). Electronic Fraud Detection in the U . S . Medicaid Healthcare Program : Lessons Learned from other Industries Electronic Fraud Detection in the U . S . Medicaid Healthcare Program : Lessons Learned from other Industries. AMCIS 2011 Proceedings - All Submissions , 328 . https://doi.org/http://aisel.aisnet.org/amcis2011_submissions/328 Trihastuti, N., Putri, S., & Widjanarko, B. (2020). The impact of asymmetric information in medical services : A study in progressive law. Systematic Reviews in Pharmacy , 11 (12), 850–855. Williams, L., & McKnight, E. (2014). The Real Impact of Counterfeit Medications. US Pharm , 39 (6), 44–46. Wolfe, J., Abbott, R., & Berk, M. (2021). Sustaining Investment in Brain Health : The Dangers of Information Asymmetry . 7–12. OIG Provider Sanctions · Custom Portal (dynamics365portals.us) 2021 Annual Report (pdf) (illinois.gov) Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4361321","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":298167555,"identity":"79832020-828b-4c16-a695-8a09a921993e","order_by":0,"name":"Isaac Asamoah Amponsah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYBCDBH4GBjYStUg2MJOqxeAAsVr4p509+Ljgj12e8Y38Yw8YauoIa5G4nZdsPLMtudjsRjK7AcMxYmy6nWMmzdvAnLjtRjKbBGMDD2Ed8iAtPH/qEzfPAGuRIKzFAKyF7XDiBgmwFgPCWgxBfuFtO54448xjc4OEYwmEtcjdzj34mOdPdWJ/e+KzBx+ICTEGBmQPE2EHupZRMApGwSgYBdgAAG/NNSYAiJGjAAAAAElFTkSuQmCC","orcid":"","institution":"University of Illinois Springfield","correspondingAuthor":true,"prefix":"","firstName":"Isaac","middleName":"Asamoah","lastName":"Amponsah","suffix":""}],"badges":[],"createdAt":"2024-05-03 00:42:09","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4361321/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4361321/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56023491,"identity":"26e062d2-6909-40a8-ac78-a282be45e6c5","added_by":"auto","created_at":"2024-05-07 16:41:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":174582,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTYPICAL LIFE CYCLE OF A MEDICAID FRAUD CONTROL UNIT (MFCU) CASE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSource: Medical Fraud Control Unit Annual Report 2021\u003c/p\u003e","description":"","filename":"image.png","url":"https://assets-eu.researchsquare.com/files/rs-4361321/v1/9971904859fa29605094fce6.png"},{"id":56023493,"identity":"d76ee8c4-b881-4915-b601-75d824d6ba2f","added_by":"auto","created_at":"2024-05-07 16:41:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91199,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Literature Review section.\u003c/p\u003e\n\u003cp\u003eSource: OIG analysis of annual statistical reports for FYs 2018 through 2022\u003c/p\u003e","description":"","filename":"UF1.png","url":"https://assets-eu.researchsquare.com/files/rs-4361321/v1/d6a9008d3a28e6a41131a99e.png"},{"id":56023492,"identity":"7178135c-f510-4d56-8476-f9b93ff07a9a","added_by":"auto","created_at":"2024-05-07 16:41:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":148386,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Methodology/Data Collection and Analysis section.\u003c/p\u003e\n\u003cp\u003eSource: \u003cem\u003eIllinois HFS – OIG Annual Report, 2021\u003c/em\u003e\u003c/p\u003e","description":"","filename":"UF2.png","url":"https://assets-eu.researchsquare.com/files/rs-4361321/v1/f062608118cc674f050f35c4.png"},{"id":56024450,"identity":"93dc536e-f447-4169-b316-0e2cd0fbe872","added_by":"auto","created_at":"2024-05-07 16:49:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1018416,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4361321/v1/a87c29d5-0fa7-44b9-8949-09e17130fe44.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eFrom Allegations to Actions: Examining the Impact of Fraud Reporting Mechanisms in Healthcare\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThere is too much fraud committed in the healthcare system. Since 1980, healthcare expenditures in the US have increased significantly. The sheer magnitude of both the healthcare sector's scale and the substantial financial resources involved render it a prime target for fraudulent activities (Liu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Fraud involves intentional deception or misrepresentation intended to result in an unauthorized benefit. Fraud is widespread and very costly to the healthcare. Therefore, prioritizing robust fraud detection measures is imperative for mitigating the overall cost of healthcare services (Liu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eKenneth J. Arrow coined the phrase \"asymmetric information\" to refer to a situation in which there is an imbalance in knowledge among providers of medical services because only a select few have access to pertinent knowledge while the majority do not (Trihastuti et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Informational asymmetries among economic agents have received a great deal of attention since Akerlof's groundbreaking study in 1970 (Cardon et al., 2001). Akerlof\u0026rsquo;s \u0026ldquo;lemon\u0026rdquo; theory applies in all markets where asymmetric information exchange exists between buyers and sellers (D. W. Johnson, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). A sick person knows more about their medical needs, giving them an advantage when buying health insurance. They are willing to pay more for coverage due to higher expected medical costs. In response, private insurers screen out high-risk clients, set coverage limits, and increase prices. This makes insurance more expensive for healthy people, causing some people to leave. This information gap adds to the high costs, administrative expenses, and uninsured population in the U.S. healthcare system. Many Americans struggle to afford necessary care as a result (D. Johnson, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 1971, before the advent of the internet and social media, the prominent Nobel Prize-winning economist Herbert A. Simon, PhD, noted that \u0026ldquo;information consumes the attention of its recipients\u0026rdquo; \u0026hellip;a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. The problem of information asymmetry is exacerbated by ever-growing information overload. The healthcare industry is a trust industry since patients rely on doctors to provide them with good sound advice to stay healthy.\u003c/p\u003e \u003cp\u003eInformation imbalance among the various actors in the healthcare industry can leave room for fraud to occur. If patients fail to check or request their explanation of benefits (EOBs) from their healthcare providers, it opens the door for healthcare providers to bill for services they did not render to that patient. Managed Care Organizations (MCOs) are mandated by federal code 42. The CFR was 438.608 for tackling fraud, waste and abuse in healthcare. MCOs are mandated to have special investigative units (SIUs) that act as the first line of defense for fraud prevention and detection. Considering a situation where a healthcare provider is enrolled with multiple MCOs, there is need for these MCOs to share information on this provider to bridge any information gap they might have with this provider. It is the work of regulators (usually the Office of Inspectors Generals (OIG) to ensure that they bridge the information asymmetry gap between their contracting MCOs through strategies such as focus groups, round table discussions, tag calls and information sharing sessions. MCOs might not be the only source of allegations of healthcare fraud. Other sources of allegation include patients, law enforcement and other external agencies. Healthcare laws such as false claims, anti-kickback statues, and physician self-referral seek to ensure that physicians are making the best decisions for patients and not making decisions on monetary incentives. Reference). Regulators such as the Drug Endorsement Administration (DEA0) need to monitor doctors for the prescription of controlled substances such as opioids and ADHD medications (REFERENCE).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e above shows how the Medical Fraud Control Unit (MFCU) processes referrals received from the public, internal data mining and from state and federal agencies into potential outcomes such as convictions, settlements, recoveries, terminations and exclusions of providers from State Medicaid Programs. This emphasizes the importance of information sharing among various actors in the healthcare industry in bridging the gap in information asymmetry.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResearch Question and Hypothesis Development\u003c/b\u003e \u003c/p\u003e \u003cp\u003e1. How does the collaborative approach between MCOs and oversight agencies impact the detection and reduction of healthcare fraud in the Illinois Medicaid program?\u003c/p\u003e \u003cp\u003e2. How can the Medicaid Inspector General help prevent healthcare fraud in the wake of information asymmetry?\u003c/p\u003e "},{"header":"LITERATURE REVIEW","content":"\u003cp\u003e \u003cb\u003eInformation Asymmetry in Healthcare\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eInformation asymmetry occurs in healthcare because patients lack the medical expertise that healthcare providers possess. Patients rely on health providers to work in their best interests without conflict because of this information asymmetry (Fabes et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Numerous authors have studied the effects of asymmetric information on the value and cost of medical care since Kenneth Arrow introduced the topic of asymmetric information in health insurance (Major, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is a plethora of intricate relationships between individuals who receive, provide, and finance health care in the United States. Everyone is impacted by health care, whether they are well, occasionally ill, or suffering from a serious illness. Childbirth, cosmetic surgery, help managing a chronic disease, and hospice care at the end of life are all included in the field of medicine (Moses et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Although the American health care system offers some of the most cutting-edge options available in the world, it is not the most effective. Inequalities in health care costs, availability, and quality also exist among the population, mainly due to information asymmetry (Care et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInformation asymmetries exist in two forms. When important information is dispersed across entities that are close to each other, there is horizontal information asymmetry. Even if some of the entities might have access to more information than others, none of them possesses all the information. When one type of entity has information while another does not, and when an aggregated collection of information-poor entities does not, there is vertical information asymmetry (Clarkson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Asymmetrical information between two parties might result in ineffective exchanges and even health consequences. Concerns regarding information asymmetry are crucial when one party is unaware of the caliber of another party or when that party is worried about the behavioral propensity of the other party (Courtney et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConsumers have limited control over healthcare service choices, leading to inefficiency in the United States due to information asymmetry. This unequal distribution of information among stakeholders is a major issue (Cruz \u0026amp; Kini, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The interactions between patients and other healthcare professionals, as well as those between patients and doctors, are governed by professional ethics, which includes both individual and organizational standards of conduct. Among them are moral standards, or bioethics, which nonmaleficence, autonomy, and fairness. In their capacity as professionals, doctors are in charge of all patient medical care (Trihastuti et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Patients who are also consumers are unable to fully comprehend the efficacy of medical interventions because they are more concerned with finding a cure for their illness or a way to achieve pain relief. Therefore, it is particularly challenging for consumers to understand and assess the quality of healthcare services (Cruz \u0026amp; Kini, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePatients with low medical and health literacy may find it difficult to comprehend and communicate their health needs to healthcare professionals, which may lead to higher healthcare costs and subpar health outcomes. However, due to the internet, technological improvements have provided people with a platform for obtaining health-related information that is crucial for managing medical issues (Osei-frimpong et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For many, it has become standard practice to access medical information from websites, medical publications, doctors, health plans, family, and friends. Often, patients question doctors about treatment plans, forcing them to respond in a considerate manner (Cruz \u0026amp; Kini, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMany economists believe that information asymmetry is a primary cause of market failure. As information overload, continues to worsen, information asymmetry becomes more severe (Wolfe et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The COVID-19 epidemic and tightening budgets have heightened the need for cost-effective healthcare worldwide. The evidence implies that practitioners have a low level of cost awareness. According to a systematic review by, only 33% of physicians reported that pharmaceutical companies searched databases for appropriate treatments, and medical device manufacturers struggled to handle requests as demand for their products increased exponentially, highlighting the importance of effective information and knowledge management within healthcare organizations.\u003c/p\u003e \u003cp\u003eInformation asymmetry is also a social scenario in which some members of the system have access to information while others do not. The evidence suggests that the health care system has radical information asymmetry. In terms of the development of medical research, the availability of highly qualified physicians and nurses and access to the most recent medications have made the American health care system among the best in the world. However, it is by no means the most fruitful. For instance, the United States was ranked first by the WHO for health spending per person but only 37th for overall health system performance (Care et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It is clear that a doctor does not work in a vacuum and does not independently make judgments; instead, they compete with other doctors inside the facility for better roles, reputation, and ultimately for greater pay and cost reimbursement (Major, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Currently, without full patient access, medical information is commonly maintained by individual clinicians or private data collectors. To completely describe a patient\u0026rsquo;s medical history, patients are unable to fully explore alternatives, contribute to and fix inaccuracies in their own data, or share their information with new practitioners. By ensuring that accurate health information is made available to appropriate individuals at the appropriate time, patient-centered information exchange should provide patients with more control and better results (Engelhardt, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLess documented is the impact that information asymmetry has on healthcare delivery once patients enter the system. Information asymmetry helps cause \u0026ldquo;lemon-like\u0026rdquo; outcomes in the following three ways: doctors and other caregivers overwhelm patients with information and deliver unnecessary treatments; doctors and other caregivers do not engage patients sufficiently and fail to provide necessary care; and uniformed patients demand unnecessary treatments (D. Johnson, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eFraud in the US Healthcare Industry\u003c/h2\u003e \u003cp\u003eAi et al., (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) define fraud as \u003cem\u003e\u0026ldquo;\u0026hellip;an intentional deception or misrepresentation made by a person with the knowledge that the deception could result in some unauthorized benefit to himself or to some other person.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e \u003cp\u003eIn particular, in the United States, fraud occurs frequently and has an impact on a variety of businesses and organizations. One specific form of fraud that has become a major issue for many citizens is healthcare fraud. The American government and its private sector organizations have battled healthcare fraud for decades, and the war continues. People often cheat for a variety of reasons, one being pressure. This could be internal or external pressure. Family problems, financial or the drive to advance professionally might put someone under internal pressure. External factors may include a faltering economy (Dean et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Because healthcare fraud can be caused by a variety of parties, including the patient, the health care professional, and any intermediates, fraud identification is difficult, especially in claims involving medical services (Alzubi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHealthcare fraud includes actions taken by a diverse group of people. It encompasses fraud committed by and against medical staff, medical facilities, health insurers, MCOs, producers of prescription medications and other medical supplies, and even patients (Krause, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Health insurance fraud is the deliberate deception of a health insurance company that causes unauthorized payment of healthcare benefits to a person or organization. Billing for services that were not given, upcoding of services, upcoding of products, duplicate claims, and unnecessary services are the major categories used to describe claims of health insurance fraud (Rawte, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFraud in the healthcare insurance market is a pressing concern, as fraudulent healthcare activities are costly (Alzubi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The ordering of treatments or diagnostic tests that are not required is one of the many scams that are carried out on unwary patients (Hannigan, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Aside from actual health concerns, testing and billing are the two areas where there is the greatest danger, notably fraud risk (Dean et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Upcoding is one of the most common fraudulent practices in healthcare coding and billing. Upcoding is the practice of invoicing for higher-priced services than those that are actually rendered. This occurs when medical professionals or claimants enter codes that denote either incomplete or unreceived treatment (R. Bauder et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Utilizing patient ignorance to create supplier-induced demand and technology imperatives may indicate that the principle of patient autonomy has been violated (Trihastuti et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It is never simple to acknowledge healthcare fraud because of its immediate, detrimental effects on human lives. To cease denying losses, however, is the first step toward lowering them. How can a company apply the best solution and lessen losses if it is unaware of the size or type of those losses? (Gee \u003cem\u003eet al\u003c/em\u003e. 2010). Since the advent of electronic medical records, emergency physicians have been shown to adjust their billing codes upward. Although fraudulent billing has always occurred, the era of electronic medical records has made it more blatant. Doctors\u0026rsquo; handwritten notes were considerably less likely to contain descriptions of actions that the doctor had not taken. Some people do not seem to be able to resist the desire to employ a few clicks (Hoffer, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApproximately one-third of all healthcare costs in the US are attributable to fraud, waste, and abuse. Fraud can take many different forms, including being perpetrated by dishonest service providers, organized crimes, compliciting patients, and falsely stating eligibility for health insurance coverage. Due to its patient demographics and less rigorous payer supervision than commercial insurers, Medicaid, a state-run healthcare program funded by the federal government, is particularly vulnerable (Thornton et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Because the Medicaid system is operated separately and has no coordination between the states, it is particularly vulnerable to fraud and abuse. Because the insurer, beneficiary, and provider have asymmetrical information, insurance fraud and abuse are typically difficult to detect (Travaille et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Given that states spend more than a fourth of their annual budget on the Medicaid program, which competes with financing for other crucial services, fraud control enforcement is crucial for the sustainability of states' medical insurance programs (Flasher \u0026amp; Lamboy-Ruiz, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIndividuals' and communities' rights are violated by corruption. Health systems, people, and health outcomes are all significantly impacted by corruption in regard to health. In addition to worsening antibiotic resistance and undermining all of our attempts to manage infectious and noncommunicable diseases, it is estimated that corruption kills at least 140000 children per year. A pandemic that is neglected is corruption (Garc\u0026iacute;a, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Health-related corruption can range from low-level local corruption to high-level national or even international corruption. It manifests in a variety of ways, including extortion, theft, embezzlement, nepotism, and improper influence (Garc\u0026iacute;a, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Legislation alone cannot stop Medicare fraud. Medicare fraud has been acknowledged as a concern since the Clinton administration, and partnerships across government organizations have been formed as a preventative measure. Medicare fraud has been a recurring offense, and laws and procedures alone have not been sufficient to stop it. Medicare fraud can be reduced but will likely not be completely eradicated with additional investments in governmental collaborations and improved detection tools. To ''keep a lid on'' the issue, continued attention is necessary (Hill et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHealthcare fraud continues to pose a serious threat to the American economy and public despite increasing financing and prosecution efforts on the part of the government. Even though healthcare fraud cannot be completely eradicated, particular measures can be used to control these sophisticated fraudulent operations (Stowell et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Drugs that are being sold as counterfeits are those that have been made fraudulently or intentionally or that have had their source, manufacturer, or identity incorrectly identified. Both branded medications and their less expensive generic analogs are subject to counterfeiting. Common counterfeiting targets include expensive high-demand medications such as chemotherapeutic agents, antibiotics, vaccinations, erectile dysfunction medications, weight loss aids, hormones, analgesics, steroids, antihistamines, antivirals, and antianxiety medications (Williams \u0026amp; McKnight, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the United States and throughout the world, the sale of fake pharmaceuticals is on the rise. Since most complaints of fake pharmaceuticals are anecdotal, it is challenging to determine the actual scope of the issue. Additionally, some people may never suspect or recognize that they are taking a product that may be fake or have altered chemicals. The classes of pharmaceuticals that are most frequently found to be fake are antibiotics and antiparasitics (Fantasia \u0026amp; Vooys, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The prevalence of market-place counterfeit drugs has increased during the last ten years. In regard to the identification, legitimacy, and/or effectiveness of the product, counterfeit pharmaceutical products can be defined as the manufacture and distribution of dishonestly labeled drugs. The widespread use of fake drugs has had life-threatening effects on populations, including an increased risk of chronic illness, inadequate treatment results, severe drug responses, and fatality (Bolla et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA study by Taleb \u0026amp; Madadha, (2013) confirmed that drug fraud is a significant public health issue that affects governments, pharmaceutical firms, and the general population globally. It also highlights the need for new statistical databases and national studies on the prevalence of drug counterfeiting to assess and make it easier to monitor the scope of the issue.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eImpacts of Information Asymmetry and Fraud\u003c/h2\u003e \u003cp\u003eThe fraudulent use of health insurance results in annual costs of hundreds of billions of dollars. In particular, the US healthcare sector accounted for approximately one-sixth of the US economy in 2017 (or \u003cspan\u003e$\u003c/span\u003e3.5 trillion; 18% of GDP). Therefore, it is critical to reduce fraud, waste, and abuse to increase the effectiveness of the healthcare system (Ai et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). high degree of knowledge asymmetry is one of the main causes of greater costs and lower quality (Care et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Worldwide, fraud costs the economy more than \u003cspan\u003e$\u003c/span\u003e4.5 trillion annually (Wolfe et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As long as one does not become overtly blatant or arrogant, healthcare providers can cheat because it is simple to do so and generally risk-free. It may be said that lying is a side job. High pay has always been an important factor in choosing to pursue a career in medicine, but today's demand is greater than ever (Skeen, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHealthcare fraud jeopardizes patient safety, lowers the standard of service, and wastes limited resources (Lorenz, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Untrue knowledge about medicine is one of the greatest threats to world health. By escalating already existing societal injustices, stigmas, gender discrepancies, and generational chasms, misinformation can make societies less cohesive (Shajahan \u0026amp; Beaumont, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Patient harm can result from taking advantage of patients' ignorance or convincing them to use additional health services during a consultation or prescription. This can be accomplished utilizing the technological imperative, in which doctors push patients to submit to a variety of laboratory tests or offer to employ cutting-edge technology that may not be essential so that they can quickly determine the type of medical care that is needed. Additionally, because of their collaboration with pharmaceutical firms, doctors can also recommend more expensive medications to their patients. Patients may incur increased costs to buy products as a result (Trihastuti et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHealthcare fraud is a major issue that costs the American government billions of dollars annually. Fraud, waste, and abuse account for approximately one-third of all healthcare costs in the US. The US healthcare system loses between \u003cspan\u003e$\u003c/span\u003e600 and \u003cspan\u003e$\u003c/span\u003e850\u0026nbsp;billion yearly to fraud, waste, and abuse, with \u003cspan\u003e$\u003c/span\u003e125 to \u003cspan\u003e$\u003c/span\u003e175\u0026nbsp;billion of this coming from fraudulent behavior (Travaille et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). More than US\u003cspan\u003e$\u003c/span\u003e7 trillion is thought to be spent globally on healthcare services, and at least 10\u0026ndash;25% of that amount\u0026mdash;hundreds of billions of dollars annually\u0026mdash;is lost directly to corruption. The amount of corruption wasted by these billions is greater than what the WHO estimates will be required each year to close the gap and provide universal health care globally by 2030 (Garc\u0026iacute;a, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).Due to the significant financial repercussions, fraud, especially upcoding, is a major concern. To decrease the number of fraudulent instances and associated cost consequences, fraud detection is essential (Bauder \u0026amp; Khoshgoftaar, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe most straightforward form of harm to identify is probably financial harm to patients, partly because it reflects economic cost to the government. The cost-sharing nature of the healthcare reimbursement system means that patients are frequently financially impacted by fraud (Krause, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Fraudulent acts can also affect patients physically, albeit financial harm may be the easiest kind of harm to spot. When unneeded medical operations are carried out just to be reimbursed by the federal health care program, individuals are at risk of physical harm (Krause, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Patients may suffer less obvious harm from healthcare fraud in addition to financial and bodily loss. Information, primarily patient information, is one of the main commodities in the healthcare system. At its foundation, information is the record of our individual health histories; it will be used to make judgments about future medical treatments as well as for a variety of other things, such as insurance underwriting and job applications (Krause, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe health of a patient may suffer from using counterfeit drugs. Adverse side effects, treatment failure, resistance, toxicity, and even mortality can occur as a result of the use of subpar medications. Pharmaceutical firms, healthcare workers, pharmacists, and patients must all be informed about fake drugs and the laws that are being implemented to stop them (Williams \u0026amp; McKnight, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDrug counterfeiting endangers the public's health, wastes consumer money, and lessens incentives for innovation and research. Better state licensing oversight of the medicine vendors would be beneficial prevent patients from losing faith in the value of pharmaceuticals and failing to adhere to their treatments, it is crucial to find a solution to counterfeit drug problems. Consumer purchases of counterfeit pharmaceuticals have significantly increased as a result of the growth of the internet and the challenges in regulating drug sellers via the internet (Blackstone et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eInformation Asymmetry between Managed Care Organizations and Providers: Implications for Healthcare Fraud in the USA\u003c/h2\u003e \u003cp\u003eThere are complex and diverse relationships between healthcare fraud and information asymmetry among healthcare providers in the U.S. Information asymmetry occurs when one side of a transaction or connection has more information than the other, and it can lead to opportunities for exploitation or unethical behavior (Capelleveen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Perez, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMCOs frequently rely on healthcare organizations to submit complete and correct claims for payment. Nevertheless, if there is substantial information asymmetry and providers know more about the precise services provided, the coding systems, or the medical necessity of the procedures, it may present opportunities for fraudulent billing. Providers may take advantage of this knowledge imbalance by upcoding, unbundling, or purposefully misrepresenting services (Capelleveen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Ekin et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Thornton et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDue to information asymmetry, it may be difficult for MCOs to properly monitor and identify provider fraud. By filing false claims or participating in actions that are not in the patients' best interests, providers may take advantage of the absence of scrutiny. MCOs may have trouble spotting patterns of dishonest behavior or determining the medical necessity of the services rendered without access to complete and accurate information regarding the services rendered (Care et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ekin et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Thornton et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInformation asymmetry can also be caused by MCOs not having access to complete patient data. Providers may have critical patient-specific data, such as past diagnoses, treatments, or prescriptions, that are not disclosed to MCOs. Due to the potential incomplete knowledge of the medical history and current treatments of MCOs, this information gap may result in fraudulent behaviors, including double billing, needless surgeries, or prescription fraud (Capelleveen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Care et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Goel, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAddressing information asymmetry between MCOs and providers is crucial in combating healthcare fraud in the USA. Efforts to improve transparency, enhance communication channels, and promote data sharing can help reduce the information gap. Implementing robust fraud detection systems, conducting audits and investigations, and promoting provider education and compliance programs are additional strategies for mitigating the risk of fraud.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHow can the offices of inspectors generally help prevent healthcare fraud in the wake of information asymmetry?\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn light of information asymmetry, regulators such as the Federal and State Offices of the Inspector General (OIG) are essential for avoiding healthcare fraud. The U.S. Department of Health and Human Services (HHS), which functions as an independent oversight body, is in charge of maintaining the integrity of all federal healthcare programs, including Medicare and Medicaid (Anthony, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The HHS \u0026ndash; OIG works in collaboration with sister agencies such as the Federal Bureau of Investigations (FBI), Department of Justice (DOJ), Medicaid Fraud Control Units, Medicaid Inspector General Offices, and Drug Enforcement Administration (DEA).\u003c/p\u003e \u003cp\u003eTo find instances of fraud, waste, and abuse within the healthcare system, the OIG primarily conducts audits and investigations. Through these initiatives, the OIG reveals fraudulent schemes, investigates billing procedures, and pinpoints fraud-prone locations. The OIG can help resolve information asymmetry by obtaining crucial data and exposing fraudulent acts by using its jurisdiction to access information and investigate suspicious actions (Kalb, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lorenz, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Stowell et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Travaille et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). To identify patterns of fraud, the OIG also employs advanced data analytics strategies such as predictive modeling, link analysis, improbable billing hours, and time dependent billing. The OIG can find outliers, anomalies, interrelated providers, and potential fraud schemes by examining claims data and other pertinent information they receive from the public, law enforcement and MCOs. The OIG can help prioritize investigations and reduce information asymmetry by concentrating on high-risk providers and practices using these data-driven methodologies, which also enhances fraud prevention efforts (Ai et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; R. A. Bauder \u0026amp; Khoshgoftaar, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Capelleveen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Drabiak \u0026amp; Wolfson, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Skeen, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Stowell et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo encourage adherence to federal healthcare rules and regulations, the OIG also offers advice and instruction to healthcare professionals, organizations, and beneficiaries. The OIG offers guidelines for preventing fraud, identifies prevalent fraud schemes, and assists stakeholders in better understanding their responsibilities through publications, fraud briefs, press releases, public and provider notices, and training programs. OIG helps to reduce information asymmetry and promote transparency in the healthcare system by distributing knowledge and encouraging a culture of compliance (Dean et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Drabiak \u0026amp; Wolfson, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hill et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kalb, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Stowell et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). State regulators such as the Illinois Department of Healthcare and Family Services release providers notices from time to time to keep providers abreast of change policies as well as fee-for-service payment schedules, as does the federal Center for Medicare and Medicaid Services (C.M.S.). These are the ways in which regulators try to reduce information asymmetry. Notably, the public health emergency (PHE) declared in March 2020 raises concerns about how difficult it might be for providers to keep up with changing policies and notices issued by regulators. The uncertainty surrounding public health emergencies has led to constant changes in policies making it difficult for healthcare providers to catch up.\u003c/p\u003e \u003cp\u003eTo improve fraud prevention efforts, the various Medicaid OIGs work with a variety of stakeholders, including law enforcement agencies, state Medicaid Fraud Control Units (MFCUs), and commercial organizations. This cooperation makes it easier to share information, conduct joint investigations, and plan enforcement measures. These organizations can overcome information asymmetries, combine resources, and create strategies to prevent healthcare fraud more successfully by cooperating (Carroll, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kalb, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Stowell et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo strengthen program integrity and prevent healthcare fraud, the OIG makes policy recommendations. These suggestions might be made in the form of new laws, revised regulations, or better program management. The OIG helps to resolve information asymmetry and boost fraud prevention efforts at both the systemic and organizational levels by lobbying for regulatory reforms and exchanging best practices (Dobrzykowski, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Drabiak \u0026amp; Wolfson, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kalb, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Stowell et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cp\u003eVarious Medicaid and Medicare OIG offices also work with other state agencies when they establish from investigations that other agencies are needed to address the original allegation. For example, if a Medicaid OIG office receives an allegation from a patient concerning quality of care concerns, the Medicaid OIG office might refer it to the Department of Public Health to also investigate and address the quality-of-care concerns expressed by the patient in his allegation. For criminal allegations, the Medicaid OIG can also choose to refer to the Federal Bureau of Investigations (FBI).\u003c/p\u003e "},{"header":"METHODOLOGY/ DATA COLLECTION AND ANALYSIS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003cp\u003eTo answer my research question on how the collaborative approach between MCOs and oversight agencies impacts the detection and reduction of healthcare fraud in the Illinois Medicaid program, I sent a Freedom of Information Act (FOIA) request, pursuant to the FOIA Act, 5 ILCS 140/1 et seq., to the Illinois Department of Healthcare and Family Service through its privacy officer for a monthly count of complaint referrals received by the Medicaid Office of Inspector General from MCOs from 1st September 2022\u0026ndash;31st August 2023, organized by an allegation source. The Illinois Medicaid Office of the Inspector General is the agency that has oversight responsibility for ensuring integrity in the state Medicaid program. The Illinois Medicaid \u0026ndash; OIG among other duties, maintains a public facing sanction database that keeps track of all healthcare providers who have been excluded, suspended, terminated or barred from the Illinois Medicaid program. These sanctions prevent any MCO from enrolling a sanctioned provider in the Medicaid program.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eILLINOIS MEDICAID \u0026ndash; OIG SANCTIONS LIST BASED ON PROVIDER TYPE AS AT 20\u003csup\u003eTH\u003c/sup\u003e SEPETEMBER 2023\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePROVIDER TYPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCOUNT OF PROVIDERS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHYSICIAN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWAIVER SERVICE PROVIDER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(blank)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e516\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHARMACY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMEDICAR PROVIDER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDENTIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePODIATRIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHIROPRACTOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAXICAB LIVERY CO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHYSICIANS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOTH PROV MES-NON-REG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINDEPENDENT LAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNURSE PRACTITIONER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOPTOMETRIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMBULANCE SERV PROV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOTH TRAN PROV-NO-REG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRURAL HEALTH CLINIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNURSING FACILITIES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSYCHOLOGIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADVANCED PRACTICE NURSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGROUP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRANSPORTATION - AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOME HEALTH AGENCY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUDIOLOGIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOCCUPATIONAL THRPST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOTH PROV MES-NON-RE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLABORATORY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHYSICAL THERAPIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFED QLFY HEALTH CNTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMENTALLY RETRD FCLTY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDME/SUPPLIES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNURSING\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLINICAL SOCIAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOTH BHVR HLTH PRFSNL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eREGISTERED NURSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPEECH THERAPIST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMHDD-OBRA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOSPICE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrand Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2741\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnalysis with an Excel pivot table revealed that as of 20th September 2023, 2741 providers had been suspended, excluded or terminated from the Illinois Medicaid program. This list of sanctions is available to the general public including the MCOs who receive sanction alerts firsthand from the Illinois Medicaid \u0026ndash; OIG. The sanctions list (which is similar to the federal LEIE database maintained by the HHS \u0026ndash; OIG) prevents any MCO that has a Medicaid contract with the Illinois state from enrolling a barred provider. Sometimes. The Medicaid OIG might also sanction recipients (patients) using strategies including but not limited to locking them to a particular physician or provider. This prevents the recipient from doctor shopping if there is credible allegation of the intent to commit healthcare fraud by the recipient. Of the 2741 sanctioned providers, 857 were physicians, 657 were on waiver service program (usually from other agencies such as the Department of Aging and Department of Revenue Services), 159 were pharmacies, and 157 were medical providers.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMANAGED CARE ORGANISATIONS HEALTHCARE FRAUD ALLEGATION SOURCES BETWEEN 1\u003c/b\u003e \u003csup\u003e \u003cb\u003eST\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eSEPTEMBER 2022 TO 31\u003c/b\u003e\u003csup\u003e\u003cb\u003eST\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eAUGUST2023 THROUGH THE ILLINOIS MEDICAID \u0026ndash; OIG FRAUD REPORTING PORTAL\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALLEGATION SOURCE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAetna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlue Cross Blue Shield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCountyCare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHumana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMeridian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMolina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData Mining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCustomer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOIG Subcommittee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCare Coordinator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvider Network\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaw Enforcement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(blank)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHFPP/NHCAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrade Association\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService Broker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe approval to my FOIA request from Illinois MEDICAID \u0026ndash; OIG came in the form of an Excel file with the various allegation sources, the MCO who submitted it and the record date or time range. I used Microsoft Excel pivot table to analyze and present the table above.\u003c/p\u003e \u003cp\u003eFrom the above table, we observe that between September 1 2022, and August 31 2023, there were 1059 fraud referrals to the Illinois Medicaid \u0026ndash; OIG healthcare fraud reporting portal. These 1059 referrals are shared among 6 MCOs who have a Medicaid contract with Illinois State. Of these 1059 referrals, 448 were discovered or found based on internal data mining by the MCO\u0026rsquo;s. Among these referrals, 205 were customers. Illinois Medicaid OIG \u0026ndash; MCO subcommittee meetings accounted for 163 of the referrals. The OIG subcommittee meeting is a periodic meeting that the Illinois Medicaid \u0026ndash; OIG has put in place to allow the sharing of information to help reduce healthcare fraud in the Medicaid program. Participants in this focus group include law enforcement agencies, MCOs, and representatives from the Medicaid Inspector General Office, among other sister organizations.\u003c/p\u003e \u003cp\u003eOther sources of allegations include Care coordinators, law enforcement agencies and external agencies, the Healthcare Fraud Prevention Partnership (HFPP) and the National Healthcare Anti-Fraud Association (NHCAA). County Care (260) made the most referrals through the portal within the time frame. The HFPP and NHCAA are private‒public partner organizations committed to combating healthcare fraud.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eILLINOIS DEPARTMENT OF HEALTHCARE AND FAMIL SERVICE ANNUAL REPORT 2021\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003cp\u003eAnalysis of the Illinois Medicaid \u0026ndash; OIG 2021 Annual Report shows that the collaboration between the MCOs and Medicaid \u0026ndash; OIG led to \u003cspan\u003e$\u003c/span\u003e23,830,110 in questioned costs. This figure represents total overpayments identified by the collaborative effort of the Medicaid \u0026ndash; OIG, MCOs and other external actors. Out of the total \u003cspan\u003e$\u003c/span\u003e23,830,110 questioned costs, the Medicaid \u0026ndash; OIG recovered \u003cspan\u003e$\u003c/span\u003e13,441,726 in fiscal year 2021.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe results from the study showed that the collaborative approach between MCOs and regulators such as Illinois Medicaid – OIG in fraud referral reporting plays a crucial role in the detection and reduction of healthcare fraud within the Illinois Medicaid program. The results underscore the critical role of data sharing and transparency in the fight against healthcare fraud. Furthermore, sanctions meted out to healthcare providers who found guilty of misconduct to play a vital role in combating fraud within the healthcare sector.\u003c/p\u003e "},{"header":"RECOMMENDATION","content":"\u003cp\u003eAddressing information asymmetry and fraud requires a comprehensive approach, including patient empowerment, improved communication, data analytics, and stringent regulatory oversight, ultimately contributing to a more transparent, accountable, and patient-centered healthcare system. The implementation of user-friendly digital platforms for patients and the provision of reliable and accessible medical information can help individuals make informed healthcare decisions and mitigate the risks associated with information asymmetry. Additionally, strengthening collaborative efforts for information sharing among stakeholders and leveraging advanced data analytics tools are crucial strategies for proactively detecting and preventing healthcare fraud, ensuring the integrity of the healthcare system and safeguarding against financial losses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAi, J., Lieberthal, R. D., Smith, S. D., \u0026amp; Wojciechowski, R. L. J. (2018). Examining Predictive Modeling \u0026ndash; Based Approaches to Characterizing Health Care Fraud. \u003cem\u003eSociety of Actuaries\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eAlzubi, A. J. (2021). \u003cem\u003eAsymmetric Information, Fraud, and Switching Costs in Healthcare Insurance Markets\u003c/em\u003e. The University of Queensland.\u003c/li\u003e\n \u003cli\u003eAnthony, M. (2017). 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Effect of privatized managed care on public insurance spending and generosity : Evidence from Medicaid. \u003cem\u003eHealth Economics\u003c/em\u003e, 1\u0026ndash;19. https://doi.org/10.1002/hec.3608\u003c/li\u003e\n \u003cli\u003ePhillips, W., Roehrich, J. K., Kapletia, D., \u0026amp; Phillips, W. (2021). Responding to information asymmetry in crisis situations : innovation in the time of the COVID-19 pandemic pandemic. \u003cem\u003ePublic Management Review\u003c/em\u003e, 1\u0026ndash;24. https://doi.org/10.1080/14719037.2021.1960737\u003c/li\u003e\n \u003cli\u003eRawte, V. (2015). \u003cem\u003eFraud Detection in Health Insurance using Data Mining Techniques\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eShajahan, A., \u0026amp; Beaumont, W. (2022). \u003cem\u003eEditorials Countering Medical Misinformation Online and in the Clinic\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eSkeen, J. W. (2003). 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The impact of asymmetric information in medical services : A study in progressive law. \u003cem\u003eSystematic Reviews in Pharmacy\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(12), 850\u0026ndash;855.\u003c/li\u003e\n \u003cli\u003eWilliams, L., \u0026amp; McKnight, E. (2014). The Real Impact of Counterfeit Medications. \u003cem\u003eUS Pharm\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(6), 44\u0026ndash;46.\u003c/li\u003e\n \u003cli\u003eWolfe, J., Abbott, R., \u0026amp; Berk, M. (2021). \u003cem\u003eSustaining Investment in Brain Health : The Dangers of Information Asymmetry\u003c/em\u003e. 7\u0026ndash;12.\u003c/li\u003e\n \u003cli\u003eOIG Provider Sanctions \u0026middot; Custom Portal (dynamics365portals.us) 2021 Annual Report (pdf) (illinois.gov)\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4361321/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4361321/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eThe U.S. healthcare sector is characterized by a diverse mix of public and private funding and provision, resulting in a lack of a singular governing philosophy. Both the public and private sectors are known for providing high-quality medical services. However, since 1980, healthcare spending in the U.S. has substantially increased. The immense size and financial resources of the healthcare sector make it a prominent target for fraudulent activities.\u003c/p\u003e\u003ch2\u003eAim\u003c/h2\u003e \u003cp\u003eThis study investigated the impact of collaborative efforts between managed care organizations (MCOs) and oversight agencies on the detection and reduction of healthcare fraud within the Illinois Medicaid program.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eThis study examines how collaboration between MCOs and oversight agencies impacts healthcare fraud in Illinois Medicaid. A FOIA request for complaint data was sent to the Illinois Department of Healthcare and Family Services. The Illinois Medicaid Office of the Inspector General oversees program integrity and maintains e database to prevent the enrollment of excluded providers.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAs of September 20, 2023, 2,741 providers were sanctioned, including 857 physicians, 679 waiver service providers, 159 pharmacies, and 157 Medicare providers. Over the period from September 2022 to August 2023, 1,059 fraud referrals were recorded, with internal data mining contributing the most (448) and County Care being the top-referring MCO (260 cases). The collaborative efforts between MCOs and the Medicaid \u0026ndash; Office of Inspector General led to the identification of \u003cspan\u003e$\u003c/span\u003e23,830,110 in questioned costs, resulting in a recovery of \u003cspan\u003e$\u003c/span\u003e13,441,726 in fiscal year 2021.\u003c/p\u003e\u003ch2\u003eConclusion/Recommendation:\u003c/h2\u003e \u003cp\u003eThe findings emphasize the significance of data sharing and transparency in the fight against fraud. The imposition of sanctions on errant healthcare providers has emerged as a key deterrent against fraudulent activities. To combat fraud and information gaps, a comprehensive strategy is needed. This includes empowering patients, improving communication, using advanced analytics, and enforcing regulations. User-friendly digital platforms provide reliable information, enabling informed decisions and reducing disparities. Strengthened collaboration and advanced analytics are crucial for early fraud detection, preserving healthcare integrity, and preventing financial losses.\u003c/p\u003e","manuscriptTitle":"From Allegations to Actions: Examining the Impact of Fraud Reporting Mechanisms in Healthcare","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-07 16:41:27","doi":"10.21203/rs.3.rs-4361321/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0e8912d0-6741-4dd9-bd1f-01bfd8ccc77c","owner":[],"postedDate":"May 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":31543751,"name":"Health Policy"}],"tags":[],"updatedAt":"2024-05-07T16:41:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-07 16:41:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4361321","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4361321","identity":"rs-4361321","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}