Annals of Health Law
READY OR NOT
program utilizes a collaborative approach by coordinating Federal, State
and local law enforcement activities as well as aligning the efforts of the
OIG, its HHS partners and the DOJ. 113 By illustration, HCFAC manages
the Health Enforcement Action Team (HEAT) program which uses Strike
Forces that employ data analysis to pinpoint fraud hot spots by identifying
suspicious billing patterns as they occur. 114
Moreover, the OIG has publicly touted a new audit series it is conducting
as part of a new hospital compliance initiative in which it uses data mining
to identify instances of fraud and abuse within a pre-selected list of high-risk hospital billing practices. 115 Undoubtedly, healthcare data analysis is
taking center stage in prevention and enforcement efforts. Collective
efforts through data mining and data sharing strategically position CMS to
make great strides in fraud enforcement and recovery efforts. For providers
who choose not to prepare in earnest for the pay-for-performance transition,
the use of data mining may uncover problematic patterns or practices that
lead to audits, pre-payment reviews, payment suspensions and/or
investigations, and ultimately even FCA liability. 116
established a comprehensive program to combat fraud committed against public (and
private) health plans. HIPAA required the establishment of a national Health Care Fraud and
Abuse Control Program under the joint direction of the Attorney General and the Secretary
of the HHS acting through the HHS’ OIG. See Healthcare Fraud and Abuse Control
Program Report, OFFICE OF INSPECTOR GEN., U.S. DEP’T OF HEALTH AND HUMAN SERV.,
available at https://oig.hhs.gov/reports-and-publications/hcfac/index.asp.
113. See id. Describing OIG’s collaborative approach, Inspector General Daniel
Levinson testified as follows before the US Senate Committee on Finance: “To support this
approach, OIG created a team of data experts composed of OIG special agents, statisticians,
programmers, and auditors. Together, the team brings a wealth of experience in using
sophisticated data analysis tools combined with criminal intelligence gathered directly from
special agents in the field to identify more quickly ongoing health care fraud schemes and
trends. To expand the coalition of data experts focused on this effort, OIG has garnered the
support and participation of our law enforcement partners at DOJ and FBI.” See also
Preventing Health Care Fraud, supra note 80.
114. See RISKSOLUTIONSHEALTHCARE,THERISE OFORGANIZEDCRIME INHEALTH
CARE: SOCIAL NETWORK ANALYTICS UNCOVER HIDDEN AND COMPLEX FRAUD SCHEMES 6
(2011), available at http://www.himss.org/content/files/LexisNexusRiseOrganized
Crime.pdf; see also Lewis Morris Testimony supra note 103.
115. See Improper Medicare Payments: Hearing Before the Subcomm. On Gov’t Org.,
Efficiency and Fin. Mgmt. of the H. Comm. on Oversight and Gov’t Reform, 112th Cong. 3
(2011) (testimony of Daniel R. Levinson, Inspector Gen. of the U.S. Dep’t of Health &
Human Servs.), available at https://oig.hhs.gov/testimony/docs/2011/levinson_
testimony_07282011.pdf. Levinson explained that after identifying problem areas revealed
through data mining, the OIG then selects claims to be tested and performs site visits where
comprehensive reviews of billing and medical record documentation are executed. See id.
