*WAR ON DRUGS MUST END*
reported by youarewithinthenorms.com
NORMAN J CLEMENT RPH., DDS, NORMAN L. CLEMENT PHARM-TECH, MALACHI F. MACKANDAL PHARMD, BELINDA BROWN-PARKER, IN THE SPIRIT OF JOSEPH SOLVO ESQ., INC.T. SPIRIT OF REV. C.T. VIVIAN, JELANI ZIMBABWE CLEMENT, BS., MBA., IN THE SPIRIT OF THE HON. PATRICE LUMUMBA, IN THE SPIRIT OF ERLIN CLEMENT SR., WALTER F. WRENN III., MD., JULIE KILLINGWORTH, LESLY POMPY MD., CHRISTOPHER RUSSO, MD., NANCY SEEFELDT, WILLIE GUINYARD BS., JOSEPH WEBSTER MD., MBA, BEVERLY C. PRINCE MD., FACS., NEIL ARNAND, MD., RICHARD KAUL, MD., LEROY BAYLOR, JAY K. JOSHI MD., MBA, ADRIENNE EDMUNDSON, ESTER HYATT PH.D., WALTER L. SMITH BS., IN THE SPIRIT OF BRAHM FISHER ESQ., MICHELE ALEXANDER MD., CUDJOE WILDING BS, MARTIN NJOKU, BS., RPH., IN THE SPIRIT OF DEBRA LYNN SHEPHERD, BERES E. MUSCHETT, STRATEGIC ADVISORS
Dr Neil Anand, MD’s case began with malfeasance as Government Agency(s) hacked his electronic medical record, DrChrono.
Dr. Norman J Clement, RPh, DDS, and his late brother Walter R. Clement had first reported and suspected years earlier that data mining appeared to be used as a tool by DOJ-DEA in their Arcos System.
Dr. Anand discovered an article (identifying him by name) that had appeared in FORBES Magazine on February 9, 2020, written by Thomas Brewster (FORBES Chief Cypertech), which not only that law enforcement agents were using outside data mining but also that they were doing direct data mining from his electronic medical record; which is at the least a HIPAA violation and, at worst, a felony. (See the article in Forbes Magazine on February 9, 2020).
Then, Dr. Anand discovered the people hacking his medical record, mysteriously manipulating and altering them similarly to what had previously been reported by Montana Physician Dr. Mark Ibsen.
Dr. Ibsen stated:
“The Montana Board of Medicine scrambled my documents, accusing me of overprescribing when I was on the merits of overprescribing. They did accuse me of poor documentation, and it was them that scrambled the documents.”
The Question here is “WHY”??
EVIDENCE LAUNDERING AND INTIMIDATION
The Department of Justice has employed data-mining techniques to target practices and providers whose frequency of certain treatments and procedures exceeds most of their peers.
Examples include the number and strength of opioid prescriptions, high-reimbursement injections, and the frequent ordering of high-complexity labs.
Yet, perfectly legitimate reasons could explain these deviations, such as patient populations with unique needs or practitioners specializing in specific treatments.
Thomas Brewster of Forbes Magazine, Article “Explained: Why The Feds Are Raiding Tech Companies For Medical Records“ Senior writer at Forbes covering cybercrime, privacy, and surveillance;
“In a separate case, in July 2019, DrChrono supplied the government with records related to the Pennsylvania-based practice of Neil Anand. He was being investigated for handing out “goody bags” of drugs to patients who didn’t need or ask for them. He’s since pleaded not guilty to all charges of healthcare fraud and conspiracy to distribute controlled substances.
In a search warrant I uncovered, the investigating agent goes into a little detail about what exactly he was able to determine from DrChrono’s record.“
ARTIFICIAL INTELLIGENCE MAY INFLUENCE WHETHER PAIN IS CARED FOR AND TREATED
Jacob Foster, Principal Assistant Chief of the DOJ’s Health Care Fraud Unit, understands the limitations of data analytics, noting that “data is not the truth. While it can point us in the right direction, we have to go out and investigate.”
Despite this understanding, there have been instances where the government has not heeded this advice, leading innocent healthcare providers to bear the financial and reputational costs of defending federal enforcement actions based on statistical analyses.
FORBES MAGAZINE: FEDS RAI D DrCHRONO FOR PRIVATE MEDICAL RECORDS
In one separate case in July 2019, DrChrono supplied the government with records related to the practice of Dr. Neil Anand, MD, who was being investigated for distributing drugs to patients who did not request them.
The involvement of private companies like Qlarant, a Maryland-based technology company, further complicates the landscape. Qlarant has developed algorithms to identify questionable behavior patterns related to controlled substances and opioids.
These algorithms have attracted partnerships with state and federal enforcement entities, including the Department of Health and Human Services’ Office of Inspector General, the FBI, and the Drug Enforcement Administration.
“CDC OPIOID GUIDELINES FLAWED BY WEAK EVIDENCE AND METHODOLOGICALLY UNSOUND RESEARCH”
NOW CALLED A DRUG DEALER IN A WHITE COAT
American Medical Association (AMA)
However, concerns regarding the use of algorithms and data analytics have caught the attention of the American Medical Association (AMA). The AMA has raised the issue of unreviewed algorithms leading to immediate suspensions of physicians’ prescribing privileges without due process. This, they argue, can harm patients in pain due to delays and denials of care.
The outcome of this case has the potential to set important precedents in the use of AI and data analytics in law enforcement, particularly concerning the protection of individuals’ rights and the integrity of healthcare providers.
HETZNECKER’S Pre-Crime” and Risk Assessments” Explored in United States v. Anand
The evolving landscape of modern law enforcement has ushered in the concept of “pre-crime,” reminiscent of the science fiction thriller “Minority Report.”
In this dystopian world, law enforcement identifies and apprehends criminals before they have the chance to commit a crime. However, this once-fictional notion has now found its place in reality, raising significant concerns about civil liberties, racial bias, and the erosion of constitutional protections.
The case of United States v Anand highlights the critical need for a balanced approach in the use of advanced technologies in healthcare fraud detection. As the legal battle continues, it underscores the importance of ensuring that constitutional rights are upheld and that evidence obtained through potentially unconstitutional means is not used in legal proceedings.
Attorney Paul J. Hetznecker, a federal public defender in Philadelphia, penned an article titled “Pre-Crime” and the Danger of “Risk Assessments” in 2016, which provides a critical analysis of this concerning trend.
Published on September 12, 2016, the article is especially relevant today in the context of the case of United States v. Anand and Dr. Neil Anand. Hetznecker’s article introduces the concept of “pre-crime,” derived from the world of “Minority Report,” where individuals are arrested before they can commit crimes.
The author asserts that this once far-fetched idea is becoming a reality through the use of “risk assessments” in contemporary law enforcement. These assessments, which are portrayed as tools for crime prevention, involve profiling individuals based on data-driven, computer-based risk assessments.
These risk assessments use data extracted from police and court records, focusing on factors like the suspect’s neighborhood, family criminal history, income, and education.
However, Hetznecker contends that this data-centric approach fails to consider the underlying systemic issues contributing to crime, such as poverty, lack of education, economic opportunities, and racism. By focusing on statistics, this method perpetuates the symptoms of an unjust system without addressing the root causes.
The article introduces the concept of “pre-designation,” where law enforcement targets individuals within specific groups for profiling, essentially shifting the focus of the criminal justice system from punishing and rehabilitating offenders to identifying and targeting potential future offenders without any crime having been committed.
This approach, Hetznecker argues, undermines constitutional protections and exacerbates racial and class-based biases within the system.
RECENT COURT ACTIONS ON THE USE OF DATA ANALYTICS IN FEDERAL PROCEEDINGS
The Intricacies of Statistical Sampling and Extrapolation in FCA Enforcement
“…The incorporation of data analytics into the mechanisms of FCA enforcement has stimulated a profound dialogue concerning the intersection of technology, jurisprudence, and due process rights. Two pivotal lawsuits—United States ex rel. Michaels v. Agape Senior Community, Inc., and United States ex rel. Martin v. LifeCare Centers of America, Inc.— manifests these dynamics.
In Agape Senior Community, the Plaintiff-Relators and the Government alleged that a network of South Carolina nursing homes utilized a widespread fraudulent scheme to submit fraudulent claims for medically unnecessary services.
The Plaintiffs argued for the use of statistical sampling to define the scope of liability, asserting that a comprehensive, claim-by-claim review would be financially prohibitive and unduly time-consuming. The United States District Court for the District of South Carolina rejected this proposal, emphasizing the necessity for an intricate, individual claim assessment to ascertain the medical necessity of each claim.2
On appeal, the Fourth Circuit abstained from issuing a definitive statement on the deployment of statistical sampling in FCA lawsuits, instead leaving it as a question of fact subject to the district court’s discretion.3
Conversely, in LifeCare Centers, the United States District Court for the Eastern District of Tennessee affirmed the practicality of statistical sampling and extrapolation in establishing FCA liability while also noting its limitations.4
Plaintiff-Relators – former employees – accused Life Care Centers of America of inflating Medicare claims for unnecessary services. Despite objections to statistical extrapolation, the court accepted its usage for proving liability when claim-by-claim review is impracticable.
In doing so, the court noted that courts had discretion regarding the weight given to the use of statistical sampling and extrapolation and referenced its endorsement in other contexts to determine damages. This verdict represents a careful equilibrium between technological advancements and due process, confirming that statistical evidence, although valuable, cannot solely satisfy the FCA’s scienter requirement. Stated differently, it cannot, without more, demonstrate that a defendant knowingly committed fraud.
The rulings in these cases spotlight the need for an equilibrium—one that acknowledges the efficiency and potential of statistical sampling but also ensures the protection of due process rights.
The use of data analytics in FCA enforcement must adhere to stringent audit procedures, ensure transparency, and offer defendants sufficient opportunity to challenge statistical extrapolations. Only such a balanced approach can truly harness the power of data analytics while preserving fairness and efficiency in FCA prosecutions...”
PRE-CRIME: THE LEVELS OF DECEPTION
According to Blue Cross Blue Shield documents presented at the Economic Crime Institute (Exhibit 128), Blue Cross Blue Shield Corporate Financial Investigations Department (CFID) utilizes STARS (Services: Tracking, Analysis & Reporting System) and STAR Sentinel sophisticated software data-mining tools that analyze all categories of claims received.
EXHIBIT 128 ECONOMIC CRIME INSTITUTE
Blue Cross Blue Shield CFID aims for recovery of payments, exclusion of professionals from networks, schemes in changing provider behavior, induces criminal prosecution for pecuniary gain through criminal restitution, and engages in the referral of physician licenses to State Medical Boards for purposes of permanent incapacitation (Exhibit 128). Blue Cross Blue Shield also publicizes entities convicted of fraud to create a sentinel effect in the provider community (Exhibit 128).
According to Blue Cross Blue Shield CFID documents (Exhibit 128), CFID employees consist of former federal, state, and local law enforcement agents and lawyers who communicate with current State and Federal law enforcement agents to influence and induce investigations into unfavored medical professionals or business competitors at Blue Cross Blue Shield CFID’s request (violating impartiality regulation and disqualification arising from personal or political relationship, 28 C.F.R. § 45.2).
The Blue Cross Blue Shield franchisees, in their conduct as government agents within a public-private joint enterprise, are subject to Constitutional law, such as the 14th Amendment Equal Protection Clause.
One of the primary purposes of Dr. Anand’s FOIA litigation was to obtain relevant documents of the Defendant Heath and Human Services (HHS), which is partnered in a joint enterprise with Blue Cross Blue Shield through the Healthcare Fraud Preventive Partnership (HFPP).
The partnership seeks for purposes of pecuniary and proprietary gains from civil and criminal asset forfeitures from “suspect class (race and religious),” minority physicians, and healthcare professionals, who subsequent to asset “stripping,” are concentrated within American prison camps.
Dr. Anand seeks documents pursuant to FOIA that would foreclose unlawful U.S. executive Branch asset confiscation schemes upon U.S. physicians and health professionals that are analogous to the historical asset confiscation of Native Indian Land and concentration of Native Americans upon American reservations or historical asset confiscation of Japanese Americans and concentration of Japanese Americans within American internment camps.
The article raises concerns about the potential unfair targeting of medical providers and violations of Fourth Amendment rights through evidence laundering and parallel construction.
Hetznecker concludes by asserting that the use of pre-crime and risk assessments contradicts the principles of the traditional criminal justice system, which relies on evidence of past crimes. He highlights the dangers of relying on predictive models and data analysis without considering the complexities of human behavior and the potential for bias. He calls for re-evaluating these practices to ensure constitutional rights are upheld, and justice is served.
In the ongoing case of United States v. Anand, where medical records have been seized, and the evidence is under scrutiny, Hetznecker’s article provides a thought-provoking backdrop to the debate surrounding the use of pre-crime methodologies and their implications for civil liberties, constitutional protections, and the pursuit of justice. The outcome of this case could significantly impact the use of such risk assessments in law enforcement.
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