Prescription Event Monitoring (PEM)

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What is PEM?

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.

Evolution of PEM

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 patients2. Large no of patients receiving the drug for

small durations3. Doses and formulations of the drug may

change during drug development4. Exclusion of special population from the

clinical trials

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).

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)

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

Products that are selected for study by PEM

1. New drugs, expected to be used widely2. 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

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

Green form for PEM study on Celecoxib

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

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

PEM process

Advantages

1. PEM is non-interventional2. The method is national in scale and thus

provides real world data3. Exposure data is derived from dispensed

prescriptions4. 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

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

Disadvantages

1. Not all green forms are returned2. PEM depends upon reporting by

doctors. Underreporting is possible3. PEM is currently restricted to

general practice4. Its not known whether the patient

took the dispensed medication5. Detection of rare ADRs is not always

possible

Applications of PEM

1. Searching for signal2. Assessment of important AE3. Medically important events4. Reason for stopping the drug5. Analysis of events during the study

while on drugs6. Ranking of ID and reason for

withdrawal7. Automated signal generation8. Long latency adverse reactions

9. Comparison with external data10.Outcomes of pregnancy11.Studies to examine hypothesis

generated by other methods12.Studies of background effects and

diseases

Example for PEM

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.

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.

Conclusions: Although the risk of sedation was low with all four drugs, fexofenadine and loratadine may be more appropriate for people working in safety critical jobs. This study not only showed the sedative effects of the anti-histaminic, and compared them, it also gave an idea about the incidence of other ADRs associated with the 4 drugs.

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

Record Linkage Systems

What is Record Linkage?

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

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

Diagrammatic representation of a linkage between two or more independent entries

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

Need for record linkage?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

Objective of record linking The objective of the linking process

is to determine whether two or more records refer to the same person, object or event

Types of record linkage methods

Types of Record Linkage

Strategies

Probabilistic

Deterministic

Deterministic record linkage

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.

Probabilistic Record Linkage

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

General record linkage system

Claims databases 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

Medical record databases

Recent development with increased use of computerization in medical care

Computers are used to record medical information

Advantages

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

Disadvantages

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

Applications

1. Data Quality2. Bias3. Coverage4. Tracing Tool5. Benchmarking/Calibration6. Building New Data Sources (e.g.,

Registries)7. Creation of patient-oriented, rather than

event-oriented statistics8. Reducing costs and respondent burden

Thank you!