2. PEM is a non-interventional, observational
cohort form of pharmacovigilance.
It is the method of studying the safety of new
medications used by the general practitioner.
PEM was developed by Professor Bill Inman
at the Drug Safety and Research Unit (DSRU)
at Southampton in 1981.
3. Pre-marketing clinical trials are effective in
studying the efficacy of medicine but are not
able to define many aspects of drug safety
because:
1. Small no of patients
2. Large no of patients receiving the drug for small
durations
3. Doses and formulations of the drug may
change during drug development
4. Exclusion of special population from the clinical
trials
4. The contribution of spontaneous reporting
system in detecting hazards such as
oculomucocutaneous syndrome with practolol
led Inman to establish the system of
Prescription Event Monitoring (PEM) at DSRU.
In New Zealand, the medicines adverse reaction
committee (MARC) is responsible for conducting
such studies for academic purposes and the
programme is known as Intensive medicine
monitoring programme(IMMP).
5.
6. In UK, all the patients are registered with
NHS-GP provides the primary care
and act as a gateway to specialist and
hospital care
File notes in general practice contains
information about primary care, secondary
and tertiary care (life long record)
7. GP issues prescription for medications he
considers medically warranted
Patient takes the prescription to the
pharmacist, who dispenses the medication
and sends the prescription to the PPD
(which is a part of NHS-BSA), for
reimbursement
PPD provides DSRU with electronic copies
of all the prescriptions issued throughout
UK, for the drugs being monitored
8. Products that are selected for study by PEM
1. New drugs, expected to be used widely
2. Established products, used for new
indication/ new population
Collection of exposure data begins soon
after the new product is launched
These arrangements operate for a length of
time necessary for the DSRU to collect first
50,000 prescriptions, that identify 20,000-
30,000 patients given the new drug being
monitored
9. For each patient in the study, DSRU prepares
a computerized longitudinal record in the
date order of drug use
After 3-12 months from the date of first
prescription for each patient, the DSRU
sends the prescriber a green form
questionnaire
This is done on an individual patient basis
Doctor receives maximum of 4 green forms in
a month
10. Request information
on:
Age
Sex
Indication for Rx
Dose
Start date
Stop date
Concurrent diseases
Concomitant
therapy
All events that have
occurred since Rx
Cause of death
11. Each green form is reviewed by a medical/
scientific officer monitoring the study, to
identify possible serious ADRs or events
requiring action
Events are coded and entered in database
using a hierarchical dictionary arranged by
system-organ class with specific lower terms
grouped under broader higher terms
12.
13. 1. PEM is non-interventional
2. The method is national in scale and thus
provides real world data
3. Exposure data is derived from dispensed
prescriptions
4. Method can detect adverse reactions or
syndromes that none of the reporting
doctors suspected to be due to the drug
5. Method allows close contact between the
research staff and reporting doctors
14. 6. ADR reporting is more complete by this
method
7. Method is found to be successful in regularly
producing data in 10,000 or more patients
given newly marketed drugs
8. Method identifies patient with ADRs who
can be studied further
9. Allows comparison of safety profile of drugs
belonging to the same therapeutic group
10. Evaluate signals generated by other systems
or databases
15. 1. Not all green forms are returned
2. PEM depends upon reporting by doctors.
Underreporting is possible
3. PEM is currently restricted to general
practice
4. Its not known whether the patient took the
dispensed medication
5. Detection of rare ADRs is not always
possible
16. 1. Searching for signal
2. Assessment of important AE
3. Medically important events
4. Reason for stopping the drug
5. Analysis of events during the study while on
drugs
6. Ranking of ID and reason for withdrawal
7. Automated signal generation
8. Long latency adverse reactions
17. 9. Comparison with external data
10. Outcomes of pregnancy
11. Studies to examine hypothesis generated by
other methods
12. Studies of background effects and diseases
18. A study was carried out to assess the sedation
properties of 4 anti-histaminic in the market
loratadine, cetrizine, fexofenadine and
acrivastine
Objectives: To investigate the frequency with
which sedation was reported in post
marketing surveillance studies of four second
generation antihistamines: loratadine,
cetrizine, fexofenadine, and acrivastine
Design: Prescription event monitoring
studies.
19. Setting: Prescriptions were obtained for each
cohort in the immediate post marketing
period.
Subjects: Event data were obtained for a
total of 43,363 patients.
Main outcome measure: Reporting of
sedation or drowsiness.
Results: The odds ratios for the incidence of
sedation were 0.63 (95% confidence interval
0.36 to 1.11; P = 0.1) for fexofenadine; 2.79
(1.69 to 4.58; P < 0.0001) for acrivastine, and
3.53 (2.07 to 5.42; P < 0.0001) for cetrizine
compared with loratadine. No increased risk
of accident or injury was evident with any of
the four drugs.
20. Incidence density of ADRs in first moth of
treatment with 4 anti-histaminics
Incidence density of events related to sedation in first
month of treatment with 4 anti-histaminics
21.
22. Record linkage is the process of bringing
together two or more records relating to the
same individual (person), family or entity (e.g.
event, object, geography, business etc).
It is the process of assembling the outcomes of
drug exposure into a single database
23. Record linkage can be considered as part of
the data cleaning process
Provides rapid access to records of thousands
of patients and thus reduces the time
required for exploring the relationship
between drug exposure and outcomes
24.
25. An ideal database would include records from
inpatient, outpatient, emergency care,
mental health care, laboratory and
radiological tests, prescribed and over-the-
counter medications as well as alternative
therapies
All the parts should be easily linked by a
unique patient identifier
It should be updated regularly
26. Researchers and the community‘s demand for detailed statistical information
Reducing respondent burden and costs
Improving data quality and timeliness
In response to increasing business and health needs.
In reducing the complexity of data
International collaborative
works
27. The objective of the linking process is to
determine whether two or more records refer
to the same person, object or event
29. A pair of records is said to be a link if the two
records agree exactly on each element within
a collection of identifiers called the match
key.
For example, when comparing two records on
last name, street name, year of birth, and
street number, the pair of records is deemed
to be a link only if the names agree on all
characters, the years of birth are the same,
and the street numbers are identical.
30. Pairs of records are classified as links,
possible links, or non-links.
Here, we consider the probability of a match
in the given observed data.
In probability matching, a threshold of
likelihood is set (which can be varied in
different circumstances) above which a pair
of records is accepted as a match, relating to
the same person, and below which the match
is rejected
31.
32. Patient goes to pharmacy drug gets
dispensed pharmacy bills the insurance
carrier for cost of that medication
Should specify which drug was dispensed,
amount dispensed, etc.
Patient goes to hospital/physician for medical
care bills the insurance carrier for cost
of the medical care
Should justify the bill with diagnosis
Common patient identification no: link
pharmacy and medical care claims
33. Recent development with increased use of
computerization in medical care
Computers are used to record medical
information
34. Provide large sample size, esp. for
pharmacoepidemiological studies
Inexpensive
Data will be complete
Population based
Include information on outpatient drugs and
diseases
Avoid recall and interviewer bias
35. Uncertainty of diagnosis data
May not contain information regarding
smoking, alcohol, date of menopause, etc.
May not contain data of medications
obtained without prescription or outside
insurance carriers prescription plan
Instability of population due to job changes,
changes in insurance plans, etc.
Include illnesses severe enough to come to
medical attention
36. 1. Data Quality
2. Bias
3. Coverage
4. TracingTool
5. Benchmarking/Calibration
6. Building New Data Sources (e.g., Registries)
7. Creation of patient-oriented, rather than
event-oriented statistics
8. Reducing costs and respondent burden
