Numerous drug safety studies have been completed in MEMO. For example, the cohort study design has been used to evaluate the risk profile of non-steroidal anti-inflammatory drugs (NSAIDs).
CURRENT AREAS OF INVESTIGATION
Numerous
drug safety studies have been completed in MEMO. For example, the cohort study
design has been used to evaluate the risk profile of non-steroidal
anti-inflammatory drugs (NSAIDs). Although the increased risk of upper
gastrointestinal complica-tions associated with NSAID use is well established
(Hawkey, 1990), the large number of study subjects and the additional
information available in MEMO have allowed more detailed investigations. For exam-ple,
a cohort study among 78 191 patients newly exposed to NSAIDs and 78 207
unexposed compara-tors showed that there was an increased risk only among
patients without a history of upper gastroin-testinal events (McMahon et al., 1997). Another study in 50 000
subjects investigated the risk with dura-tion of use, and found that it
remained constant with continuous exposure (MacDonald et al., 1997) in contrast to previous findings (Carson et al., 1987).
The
case–control method is an efficient study design requiring fewer subjects than
cohort stud-ies. This is an important consideration when a study involves
validating information by checking the original medical notes of patients. The
case–control design has been used in a range of studies investi-gating the
adverse effect profile of topical NSAIDs. These studies found that oral NSAIDs,
but not topical NSAIDs, are implicated in hospitalisation for upper
gastrointestinal haemorrhage and perforation (Evans et al., 1995b), acute renal failure (Evans et al., 1995a) and acute
colitis (Evans et al., 1997b), but
that they are unlikely to be associated with acute appendicitis (Evans et al., 1997c).
The
case–crossover design was employed in a study examining the risks of road
traffic accidents associ-ated with benzodiazepine use (Barbone et al., 1998). This design is suitable
for the evaluation of tran-sient risks, and because cases are used as their own
controls, problems of confounding can be dealt with neatly.
MEMO
is able to produce detailed drug utilisa-tion data, broken down by age, sex,
date, day of week prescribed, prescriber, generic or proprietary dispensing,
co-prescribing, acute prescribing and/or repeat prescribing, dose and duration.
One impor-tant dimension is the audit of GP prescribing in the population,
although GP-specific data are analysed anonymously and individual GPs are never
identified. For example, one study identified rare instances of potentially
hazardous co-prescribing of -antagonists and β-agonists to patients in Tayside
likely to have asthma or chronic obstructive airways disease, by linking the
dispensed prescribing database to hospital admission records (Hayes et al., 1996). The process-ing of
prescribing data according to the demographic characteristics of prescribing
GPs has also yielded some useful insights into the characteristics of ‘good’
prescribers. For example, a difference in the prescrib-ing of antibiotics was
seen between GP registrar train-ing and non-training practices (Steinke et al., 2000a).
Prescribing
may vary by patient factors that are inde-pendent of need or disease severity.
For example, the variation of use of hormone replacement ther-apy by
socio-economic status independent of need (Evans et al., 1997a). Compliance to labelled medi-cation direction or
therapy is a related issue. By assessing how patients collect dispensed
medication, in terms of numbers of prescriptions dispensed and intervals
between them, and linking to outcome data sets, patient compliance or
non-compliance to medi-cation can be studied. For example, a study in diabetes
showed that adolescents in Tayside who have ‘brittle’ diabetes are often
non-compliant with insulin (Morris et al.,
1997b).
Pharmacoepidemiology
studies often have a phar-macoeconomic analysis ‘attached’ to the protocol.
Both methods have specific objectives that are clearly defined and apparently
independent. Pharmacoeco-nomic analyses have become more widely used over the
past 10 years. Their primary use is for selecting more efficient drugs; in
other words, those exhibit-ing a better relationship between acquisition cost
and therapeutic effects and/or economic benefits. Pharma-coeconomic studies use
the tools of clinical pharma-cology, epidemiology and economics to obtain data
on the effects (beneficial or harmful) of drugs and the costs of treatment
alternatives.
MEMO
has the ability to identify the drug, type of medication (either generic or
proprietary), strength, amount and directions for use and therefore can
accu-rately cost the medication for cost analyses. For example, a comparison of
the use and cost of self-monitoring reagent strips and patterns of drug use by
type 1 and type 2 diabetics was investigated by Evans et al. (1999, 2000). Both studies found a difference between the diabetes type and the cost
of medication and health resource use.
The
MEMO/DARTS collaboration is a joint initia-tive of the Department of Medicine
and MEMO at the University of Dundee, together with the Diabetes Units at three
Tayside Health Care Trusts (Ninewells Hospital and Medical School, Dundee;
Perth Royal Infirmary and Stracathro Hospital, Brechin) and all Tayside GPs
with an interest in diabetes care. They have combined their expertise to create
the Diabetes Audit and Research in Tayside, Scotland (DARTS) initiative (Morris
et al., 1997a). It has been in
opera-tion since 1995, continually developing and gathering data from the
population base of Tayside.
The
MEMO/DARTS collaboration has used elec-tronic record-linkage of information to
create a robust clinical information system of all patients with type 1 and
type 2 diabetes in Tayside whether they attend primary or secondary care. The
DARTS database has information from many different sources including: patients
attending hospital diabetes clinics, dispensed prescriptions for
diabetes-related medica-tion and monitoring equipment, patients discharged from
hospital, patients attending a community-based mobile diabetic eye screening
facility, glycosy-lated haemoglobin and plasma glucose results from the
regional biochemistry database, and information collected from case records of
patients in every general practice in Tayside. The register has been used for
pharmaco-epidemiologic research (Morris et
al., 1997b,c).
The Epidemiology of Liver Disease in Tayside (ELDIT) study
group has registered and validated a group of patients with potential and
definite liver disease in Tayside for research purposes only. This disease
register has a range of liver diseases that affect the whole organ including
viral hepatitis (A, B and C) (Steinke et
al., 2000b), autoimmune hepati-tis, alcoholic liver disease (Steinke et al., 2000c), primary biliary
cirrhosis and hepatocellular carci-noma (Weston et al., 2000) and complications of liver disease like ascites. The
ascertainment of liver disease by electronic record-linkage was maximised
because of the unique integration of multiple sources of data to create a
patient-specific information system. The specificity of virology, immunology
and biochemistry tests increases the completeness of the data. Accurate incidence
and prevalence rates of liver disease and its complications are used to ensure
that hepatology services run effectively and efficiently.
The
latest addition to MEMO’s disease management databases is the HEARTS database
of cardiovascular disease in Tayside. This is a regional collaborative effort
to support improvements in clinical care, educa-tion and research in
cardiovascular disease and to provide GPs with information that will be useful
for audit and clinical governance purposes. The database contains information
on high-risk patient populations like those who have suffered a myocardial
infarction (MI) and those who have undergone coronary angio-plasty or artery
bypass grafting (CABG). The database includes a variety of other cardiovascular
diseases. For example, those with angina pectoris, peripheral vascu-lar
disease, ischaemic stroke, cardiac failure, hyper-tension and those undergoing
primary prevention for cardiovascular disease. The aims of HEARTS are to
identify and determine the risk factors of cardiovas-cular disease from a
population base and to evaluate and determine whether medications are optimised
in these patients. This information is fed back in various ways to GP practices
in an effort to support them in improving care. HEARTS also provides high
quality epidemiological data for research, understanding and care of similar
patients and their families.
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