The US Medicaid Program is a health insurance system created in 1965 to provide access to medi-cal care for economically disadvantaged and disabled persons.
MEDICAID DATABASES
The
US Medicaid Program is a health insurance system created in 1965 to provide
access to medi-cal care for economically disadvantaged and disabled persons
(Hennessy et al., 2005). It is
supported jointly by federal and state funds, and managed by states with
federal oversight. Benefits are available for members of three groups: (1)
low-income preg-nant women and families with children; (2) persons with chronic
disabilities; and (3) low-income elderly, including those receiving benefits
from the federal Medicare (65 years and older) program. In addi-tion to these
categories for eligibility, individual states may set up their own programmes
for specific groups of persons who do not qualify for federally supported
programs. Services provided by the states under the federal Medicaid programme
include inpa-tient hospital services, outpatient hospital services and
physician services. All states provide outpatient prescription drugs for at
least some categories of enrollees, even though this coverage is not federally
mandated. Rather than serving as a direct provider of health care services,
Medicaid functions as a payer for eligible services provided by participating
physi-cians, hospitals and pharmacies. Of the US popu-lation 16%, or 51 million
persons, received health care services through Medicaid in 2002, serving as the
largest health insurance programme in the United States (Iglehart, 2003).
Compared with the overall US population, the Medicaid population has a
dispropor-tionate number of children, females and non-whites. Income and
disability status are also not representa-tive of the total population. These
are the populations that are often under-represented in randomized trials.
The
Medicaid programme is administered by the Centers for Medicare and Medicaid
Services (CMS), which has established a mechanism for researchers for obtaining
data that have been received from the indi-vidual states and have undergone
editing and range checks. A lag-time of 4 years currently exists for the
availability of the cleaned Medicaid Analytic Extract (MAX) files; crude data
from the Medicaid Statis-tical Information System (MSIS) are also available.
Support for the process of obtaining files and technical assistance in the use
of the data is supplied through a contract with the University of Minnesota’s
Research Data Assistance Center (ResDAC), instituted in its School of Public
Health. ResDAC’s description of the CMS data and of its services is publicly
avail-able through its website: http://www.resdac.umn.edu/. Data can also be
obtained through a commercial data vendor, a common source of Medicaid data in
the past (Hennessy et al., 2005).
Five
types of MAX files are available for CMS Medicaid data, separately by year and
by state: personal summary, inpatient, prescription drug, long-term care and
other therapy. The personal summary file contains one record per person
enrolled in the specific state’s Medicaid programme for any part of the specific
year. It includes demographic data, namely date of birth, sex, race and zip
code of resi-dence, and identifies the months in which the person was enrolled
in the plan. The inpatient file contains information on hospitalizations,
including admission and discharge dates, discharge status, up to nine
diagnoses, up to six procedures, and payment informa-tion. Drugs used during
hospitalization are not avail-able in this file. The prescription drug file
contains records for drugs reimbursed for outpatient or nurs-ing home
prescriptions. NDC Codes provide informa-tion on the manufacturer and the name,
strength and dosage form of the drug. Data elements include date and quantity
dispensed, whether the drug was new or a refill, and cost information. The
long-term care file contains information on care provided by skilled nursing,
intermediate care and independent psychi-atric facilities. Data elements
include type of facility, dates of service, diagnosis and discharge status. The
other therapy file contains records for physician, labo-ratory, radiology and
clinic services. Date, type of service, diagnosis and procedure codes (where
appli-cable) are recorded. Although the types of laboratory and radiology
testing are recorded, their results are not reported. Medicaid data have been
linked to other databases, such as Medicare data (for persons eligible for both
programmes), the National Death Index and state vital statistics registries.
The
quality of the Medicaid database has been evaluated for six states. Results suggest
the need for macro-level descriptive analyses of the parent dataset, with a
particular focus on the number of medical and pharmacy claims over time,
checking for gaps, assessing the validity of markers for hospitalization and
the accuracy of diagnostic and demographic data (Hennessy et al., 2003).
The
strengths of the Medicaid databases are their large size, permitting the study
of infrequently used drugs and rare outcomes, and the accuracy of the drug
data. More than 10 states have over a million Medi-caid recipients each;
prescriptions for the top medica-tion dispensed numbered 9.3 million
prescriptions (for albuterol) for the total Medicaid programme in 2001. Far
down the list, ranked at number 50, were prescrip-tions for
trimethoprim/sulfamethoxazole, accounting for 2.4 million prescriptions
(Hennessy et al., 2005).
As
a claims database (similar to most of the other databases described),
information is lacking on vari-ables often needed to control for confounding,
such as smoking, environmental exposures, illicit drug use, alcohol use,
occupation, family history and use of over-the-counter drugs.
The
International Classification of Disease Ninth Revision – Clinical Modification
(ICD-9-CM) is the coding scheme for diagnoses. Together with factors such as
the level of accuracy of the clinical diagnosis and need for information on
poten-tial confounding variables, experience suggests that investigators should
obtain medical records in at least a sample of outcomes to confirm the
diagnosis and characterize the severity of the disease, in addition to
obtaining information on potential confounding variables. Although a mechanism
exists through the recently implemented Health Insurance Portability and
Accountability Act (HIPAA) for requesting hospi-tal records of specific
patients without patient contact, the willingness of hospitals to use this
mechanism has yet to be gauged. Studies where primary record confirmation is
less important are those which focus on drug-to-drug relationships, or studies
which can use drugs or procedures as markers of diagnoses.
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