Prescription-event monitoring: Methodology and recent progress

0895s4356/90 $3.00+ 0.00 Copyright Q 1990 Pergamon Pressplc

J clin Epidemiol Vol. 43, No. 5, pp. 509-522, 1990 Printed in Great Britain. All rights reserved

PRESCRIPTION-EVENT MONITORING: METHODOLOGY AND RECENT PROGRESS S. B. RAWSON,* GILLIAN L. PEARCE and WILLIAM H. W. INMAN

NIGEL

Drug Safety Research Unit. Bursledon Hall, Southampton (Received

Abstract-Event monitoring adverse reactions to drugs.

in rerised form

So3 $3~4, U.K

19 July 1989)

was first suggested 25 years ago as a way of detecting Prescription-event monitoring (PEM), which has been

developed by the Drug Safety Research Unit, is the first large-scale systematic post-marketing surveillance method to use event monitoring in the U.K. PEM identifies patients, who have been prescribed a particular drug, and their doctors from photocopies of National Health Service prescriptions which are processed centrally in England. A personalized follow-up questionnaire (“green form”) is mailed to each patient’s general practitioner, usually on the first anniversary of the initial prescription, asking for information about the patient, especially any “events” that he or she may have experienced since beginning treatment with the drug. The methodology of PEM is presented, together with examples of analyses that can be performed using results from recent studies. The problems and benefits of PEM are discussed. Post-marketing monitoring

surveillance Drug monitoring

Adverse

INTRODUCTION

In 1965, only a few years after the thalidomide tragedy, David Finney, a founding member of the Adverse Reaction Subcommittee of the Committee on Safety of Drugst, published a paper in the Journal of Chronic Diseases on the design and logic of post-marketing surveillance (PMS) [l]. In it, he discussed the principles and problems of monitoring the use of drugs in objective terms. Finney laid great emphasis on the reporting of events rather than adverse drug reactions (ADRs), defining an euent as “a particular untoward happening experienced by a __-._ address: Psychiatric Pharmacoepidemiology *Present Research Consortium, Applied Psychiatric Research, University of Saskatchewan, Box 92, University Hospital, Saskatoon, Saskatchewan, Canada S7N 0X0. tin 1971, the Committee on Safety of Drugs became the present Committee on Safety of Medicines with the introduction of the 1968 Medicines Act.

drug reactions

Prescription-vent

patient, undesirable either generally or in the context of his disease”. An event was “not to be limited either to recognized side-effects of a drug or to incidents that are in some sense unexpected”, and every patient experiencing an event was to be noted by the reporting physician or institution, irrespective of whether the event was thought to have any relationship with the drug. Finney argued that many more unsuspected associations between drugs and adverse effects would come to light with event monitoring. Finney also urged that even if an ideal scheme could not be implemented immediately, a modest one should be started and expanded as experience grew. In spite of his exhortations, little progress was made towards the systematic monitoring of drugs. It took the practolol tragedy of the 1970s to rekindle interest in improving PMS. By 1974, practolol (a fladrenergic receptor blocking drug) had been

510

NIGEL S. B. RAWSONet al.

marketed in the U.K. for more than 3 years and perhaps 100,000 patients had been treated with it. Many hundreds had suffered from an unusual skin reaction and a severe form of dry-eye (the “oculomucocutaneous syndrome”) resulting in blindness in some cases [2]. A smaller number of patients had experienced unusual changes in the peritoneum causing intestinal obstruction from which some died. Although doctors had seen these signs, they had not realized their significance and, therefore, not reported them either to the manufacturer or to the Committee on Safety of Medicines (CSM) in time to prevent a disaster. Soon after this tragedy, several new PMS schemes [3-61 were proposed, including Inman’s Recorded Release, Dollery and Rawlins’ Registered Release and the CSM’s Retrospective Assessment of Drug Safety; these have been reviewed elsewhere [7-91. Two essential features of all these schemes were the identification of patients by prescriptions issued to them and the subsequent reporting of events experienced by them. Although a study of a prospective monitoring scheme was successfully completed in one small area of England [lo], none was implemented on a national scale. Even before he suggested Recorded Release [3], Inman saw a need for an independent PMS research centre in the U.K. and began discussions about setting one up in 1976. He formally consulted the British Medical Association, the General Medical Council, the Prescription Pricing Authority (PPA), and the Department of Health and Social Security (DHSS). In addition, informal discussions were held with the CSM, the Medical Research Council, the Royal College of General Practitioners, and the Association of the British Pharmaceutical Industry. All these organizations gave their approval to his proposals, and efforts to raise funds for the enterprise were started in 1977. In 1980, the Post-marketing Drug Surveillance Research Unit was established within the Faculty of Medicine at the University of Southampton as a centre for PMS research. It was supported by a grant from the DHSS and unconditional donations from more than 20 pharmaceutical companies. The unit was re-established and re-named in 1986 as the Drug Safety Research Unit (DSRU) managed by an independent charitable trust, whose founding trustees are Sir Douglas Black, Dr Denis Burley, Professor David Finney, Dr Gordon Higginson and Professor Bill Inman, the director of the

DSRU. One of the principal objectives of the unit has been and continues to be the development and assessment of new techniques for PMS [l l-131. The first PMS scheme to be developed by the DSRU is known as prescriptionevent monitoring (PEM). PEM is a method for generating and testing hypotheses about ADRs which, unlike voluntary reporting systems, provides estimates of the incidence of events during a defined follow-up period. Thus, for the first time, PEM enables almost every patient receiving a new drug in England to be included in a monitoring scheme in which “events” are recorded in a population of known size. METHODOLOGY OF PRESCRIPTION-EVENT MONITORING

In PEM, patients who have been prescribed a monitored drug are identified by the PPA during the normal course of its work. The PPA is a special health authority whose main role is the reimbursement of pharmacists who have dispensed National Health Service (NHS) prescriptions issued by general practitioners in England. It also provides the DHSS with information on the quantity and cost of drugs dispensed under the NHS. Scotland, Wales and Northern Ireland, which have their own pricing authorities, have so far not been included in PEM. The PPA processes more than 350 million prescription items each year and, until the end of the 1970s this work was performed manually. During the 1980s computers have been gradually installed and the process is now automated. When PEM began, the number of drugs that could be monitored by the PPA was limited to four, since this was the maximum number of names that the clerks could memorize and, thus, reliably identify all prescriptions for those drugs. However, with the computerization of the PPA, the DSRU now monitors nearly all new chemical entities as soon as they are marketed. The limiting factor is the volume of prescriptions issued rather than the total number of drugs being studied. The names and addresses of the recipients of the prescriptions are not recorded by the PPA for confidentiality reasons. However, the name and address of each patient is essential for PEM and, therefore, it is impossible to obtain all the required information by direct transfer from the PPA’s computers to the DSRU’s computer. As a result, a compromise method has been devel-

Prescription-Event

oped in which photocopies of the relevant prescriptions are made by PPA staff and sent to the DSRU in monthly batches. When the photocopies reach the unit, information from them is entered into the DSRU’s minicomputer. Approximately 20,000 patients, many of whom have several prescriptions, form a normal PEM cohort and 10-20 drugs are monitored at a time. This huge volume of data necessitates both a large amount of on-line storage capacity (presently 5 10 Mbytes) and an efficient database management system. The patient’s family name, forename, sex (if stated on the prescription or deducible from the patient’s forename) and abbreviated address, together with the date of the prescription, a surgery code (shared by all the partners in the practice), a code for one of up to three different addresses for the practice and a unique doctor code, are recorded in the computer. To ensure that only one record is created for each patient, the prescription-entry clerk checks the list of patients already stored under the shared surgery code before entering a new patient’s details. The prescriptions are a means of identifying patients and practices so that information about the patients can be obtained from their doctors. To elicit this information, follow-up questionnaires, known as “green forms”, are generated by the computer and mailed to the general practitioners who issued the initial prescriptions. A green form is normally sent during the month after the first anniversary of the date of the initial prescription for the patient. The form is designed so that each one is personalized for the individual patient and doctor by printing the patient’s details and the name and address of the practitioner on the top section (Fig. 1). A unique reference number is printed on both parts. The doctor is requested to detach the top section before returning the lower part because, firstly, it is intended that the top section should be retained in the patient’s notes and, secondly, any information about the patient that is subsequently written on the lower section is anonymous if it is lost in the mail. Brevity and simplicity were considered to be of paramount importance when the green form was designed. On each one (Fig. l), the general practitioner is asked to record the patient’s sex (if not already obtained from the prescription) and date of birth, the indication for which the drug was prescribed, and whether the treatment was effective. If the patient has discontinued treatment with the drug, the doctor is requested

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to enter the date on which the treatment was stopped, the reason for stopping, and whether another drug was substituted. Finally, the doctor is asked to record dates and details of any events that were experienced by the patient after the first prescription for the monitored drug, including those which may have occurred after the patient ceased treatment with it. An event is defined as “any new diagnosis, any reason for referral to a consultant or admission to hospital, any unexpected deterioration (or improvement) in a concurrent illness, any suspected drug reaction, or any other complaint which was considered of sufficient importance to enter in the patient’s notes”. This definition is printed on each green form. To emphasize that doctors should not restrict their reports to those events which are suspected ADRs, the simple example of a broken leg is given (Fig. 1). A broken leg could, for instance, be a consequence of hypotension or metabolic bone changes induced by the drug, but it could also result from a straightforward accident. Apart from dividing the events into those which occurred during treatment with the monitored drug and (if appropriate) those which occurred after the treatment ceased, the event recording section of the form is deliberately unstructured. This is to encourage practitioners to reply and to allow them as much flexibility as possible when doing so. It is thought that if doctors are forced to categorize the events in some way, they will be deterred from completing the forms and potentially important signals might be missed. When a green form is received, it is stamped with the “form completion date”, which allowing for postal delays is assumed to be 4 days prior to its receipt by the DSRU, and the following are added to the original computer record: (1) the patient’s sex (if not already entered) and date of birth, (2) the indication for treatment with the drug (the dose is not recorded routinely, but the prescriptions can be retrieved manually if required), (3) the dates on which the treatment began and (if applicable) stopped, and the form completion date, (4) whether the doctor considered the treatment was effective, (5) whether the period of treatment was continuous,

NIGELS. B. RAWSONet

512

al.

PLEASE RETAIN THIS SECTION OF THE FORM FOR YOUR RECORDS Professor W.H.W. Inman, FRCP, FFCM, North Croft House, Winchester Road, Botley, Southampton, SO3 2BX. Telephone: (0703) BOO263

DRUG SAFETY RESEARCH UNIT PRESCRIPTION EVENT MONITORING CONFIDENTIAL

An EVENT is any new diagnosis,any reason for referral to a consultant or admission to hospital, any unexpetted deterioration (or imprwement) in a concurrent illness,any suspected drug reaction, or any other complaintwhich was considered of sufficientimportance to enter in the patient’s notes.

1

I-

DR D JONES THE HEALTH CENTRE WEST STREET NEWTOWN HANTS so22 1PZ

Example: A broken leg is an EVENT. If more fractures were associated with this drug they could have been due to hypotension, CNS effects or metabolic bone changes.

Please note

J

L

thatthe following are essential:

1. Date of birth, indication for this drug and datesof starting and ceasing treatment with this drug.

WOULD YOU PLEASE COMPLETE THIS QUESTIONNAIRE FOR

2. Details of all events even if this drug has been discontinued.

JOHN SMITH MALE 27 EAST STREET

3. Reason for stopping this drug and name of any other drug substituted. 4. Date and cause of death (if appropriate).

WHO WAS PRESCRIBED INNOVACE (ENALAPRIL) ON 29/02/88

Ref:

oamoousbm~i777777

._. ______. INO. Jzlmel worKIn@ m ~~Peratlon

I-

The DSRU is mane,& by the [hug Safety R-ear& Trust, an indepBndent cl?arlfy Trustees: Professor Sir Dougla Black MD FRCP, Or. D.M. Burley FRCP, Professor DJ. Professor W.H.W. Inman FRCP FFCM.

Finnw

_-

mm tne UnlMRlfY ot Soulnamplon CBE ScD FRS FRSE, Dr. G.R. Higoinron FICEFI Mech E,

_______-_-----------------------------------------

LEASE RETURN NO-EVENT FORMS SEX

M

INDICATION

DATE OF BIRTH FOR PRESCRIBING

/

PLEASE

/

INNOVACE ?

EVENTS WHI LE TAKING

IMPORTANT:

Ref:

THIS ~)RUG

INDICATE

08/91001/SM01/?77777

WAS THIS DRUG EFFECTIVE?

YesO

No0

PLEASE SPECIFY THE REASON FOR STOPPING THIS DRUG AND THE NAME OF ANY OTHER DRUG SUBSTITUTED

EVENTS AFTER STOPPING THIS DRUG

ANY EVENT REPORTED

TO CSM OR MANUFACTURER

Fig. 1. An example of a “green form”.

Prescription-Event

(6) whether the patient was still alive at the form completion date, (7) the type and date of occurrence of events experienced after the first prescription (subject to the rules and conventions described below), and (8) the name of any product substituted for the monitored drug (drugs issued on the same prescription can be identified after manual retrieval). The computer calculates the patient’s age at the date on which the treatment was first prescribed. It also calculates the duration of the treatment period and that of the period between the date of stopping the drug and the form completion date. If the drug has not been taken continuously, the treatment period is taken to be the overall time on treatment. PEM was initially designed for monitoring drugs taken for chronic conditions where treatment periods were likely to be measured in months or even years rather than days and, consequently, each period is calculated in months. If it is not an exact number of months, it is rounded up to the next integer if the remainder is 16 or more days. Therefore, patients who receive treatment for less than 16 days are recorded as having a treatment period of zero months. New software is being installed so that treatment duration can be recorded more accurately. Many of the events reported by general practitioners in PEM are signs and symptoms, and it was found that the standard disease and diagnosis coding systems, e.g. the International Classification of Diseases [14], were unsuitable for the coding of such events. The main reason was that many of these events would be classified as miscellaneous or non-specific rather than clearly defined diagnoses, but also some are simply uncodeable in ICD. Consequently, a text recording system has been developed by the DSRU which contains some 2000 terms. In processing a green form, the unit’s technical officers attempt to match the doctor’s own words with the nearest equivalent term in the event dictionary. If a term does not fit, a new one may be created after consulting a medicallytrained member of staff. In the dictionary, events are grouped into appropriate “body systems”, e.g. “musculoskeletal” and “gastrointestinal”. Within some of these, the events are sub-grouped according to whether they are signs or symptoms, acute or chronic conditions, etc. Thus, this coding system has many similarities

Monitoring

513

with ICD. For each event, the following information is also recorded:

0) the number of months between the date of the first prescription and the date of occurrence of the event, and (if appropriate) the number of months between the date of stopping the drug and the date of the event, (ii) whether the event occurred during treatment or after treatment ceased, or whether the date was unknown, (iii) whether the event was fatal, and (iv) whether the general practitioner thought that the event was an ADR either to the monitored drug or to any other product; in the latter case, the name of the drug is also recorded. An event is only marked in this way when a doctor clearly states that, in his opinion, the event is an ADR. Practitioners are specifically requested to record all events not just ADRs. When the technical officers record the events in the computer, they apply the following rules and conventions:

(4 An event is recorded only once in the

(b)

relevant time period (i.e. during or after treatment with the monitored drug) irrespective of the number of times it occurred. This is to avoid bias created by patients who repeatedly attend the surgery with the same complaint. A slight variation to this rule occurs when a patient dies during the course of a PEM study. For each of these patients, the event which is considered to be the cause of death is recorded, together with the code “[F]” indicating that the outcome was fatal, on the date of onset (Fig. 2). The time between the date of onset and the date of death may, of course, vary between zero days (if death occurs on the same day) and several months. In order to show both the date of onset of the event which was ultimately fatal and the date of death if these two dates are not the same, another code is included in the computer record to indicate the actual date of death. These latter codes are omitted from analyses of PEM data so that deaths are not recorded twice. Pre-existing diseases or conditions are not recorded, but exacerbations of such disorders are.

NIGEL S.

514

B. RAWSONet al.

Number of events during and after treatment Months after first prescription All Events

Event Name CCF[F] CHILBLAINS COR PULMONALE COR PULMONALE[F] CVA CVA [F] DVT EFFUSION PERICARDIAL EMBOLUS PULMONARY EMBOLUS PULMONARY GANGRENE HAEM SUBARACH [F] HYPERTENSION HYPOTENSION IHD IHD[F] ISCHAEMIA ISCHAEMIA PERIPHERAL LVF LVF[F] Ml

MIFI

PHLEBITIS RAYNAUDS STENOSIS ARTERY SVT THROMBOPHLEBITIS THROMBOSIS ARTERY TIA VALVE INCOMP VASCULITIS VBS VEINS VARICOSE Sub-total ARRHYTHMIA BRADYCARDIA COLD EXTREMITIES CYANOSIS EXTRASYSTOLES FIBRILLATION ATRIAL HEART BLOCK TACHYCARDIA

[F]

10 2 1 1 28 17 16 2 3 2 1 1 83 10 10 1 2 10 13 1 36 33 33 4 3 2 7 1 22 4 1 2: 440

1

1

2

0

:

3

0

0 0

0

30

27

NK

1

2

2

1

5 1

1 0 0 0 1

0000000

0

21

r12

2

0 1 0001100

0

0

0

0 0 0 0 0 0 0000000000

0 1 3 7 7 0 1 0 110000 000001 0 0 0 0131001 0 11 0 0 0 2 4 2 0105130121003 5213114111425 0 0 0 000011 000010 0 0 1 0 0 0 3120221201114 000101 1 0 0 0010000011002 1103241

12

0

7

0 0 0

0

11

0

6

1 0

0 00000000000 0 0 0

0

10

0

5

0 0

0 1 0 0 02111331 0 2 0010113 000001 100000 0 0

5 1

11 1

5 1

0

0

1

0 0 4

11111110 0 0 2 2

0

2

1

0 0

1 0

0 0

9

9

4

3 111110 041211 0000010 0000000 0000010

0000000 3 653849 0 0 1 0 0 1 0000000 0000010 201000

0011 1 1

0

0

1 0000000 1 333315

0 0 1 0000010 0000100 1 000101 0001000

0

0

0

0

:, 0 1 0 0 0 6 2 1 0 0 1 2 0 1 0 0 0 0 0 1 0 2

201404 27

1 1 5 2 2 17 3 7

0 0 0 0 010000 0 1 0 0 1 0 0 0 0 0 0 0 0111041131111 10000001 0101010211000

Sub-total

38

3312053

ANGINA CLAUDICATION FAINTNESS PALPITATIONS

78 13 11 24

6 9 3 10 1100011 420211 20152112110620

31

30

0

0

0 0 0

0 0 0

24

23

28

0000000 0 0 0 2001010 0 1 0 0001000 0

6

2 0

7 3 021102 0 0

: a

ii 0 0 26

33

19

47

22

52

0

0

0

0

0

0

0

0

0

1

0

0

b 0 0 1 1 0 0

0 0 0 0 0 0 0 0

3

0

4 2 0

1 1 0 0

544221 4

3 0 0

: 1 1 1 0 1 1 4 0 0 0 1 1 0 16 2 0 0 0 1 0 0 0 0 0 0

0002000 0000000000

Other

6

2

7

8

1

0

0

0

Fig. 2. A sample of the type of analyses available from PEM data.

(4 Multiple unrelated events are all recorded but, where there is a clear relationship between events, only the unifying diagnosis (if reported by the practitioner) is recorded. For example, if influenza was diagnosed, this term would be recorded but any symptoms also reported, such as pyrexia and sore throat, would not. If no diagnosis is reported by the doctor all the signs and symptoms are recorded; diagnoses are not made by DSRU staff.

(4

If an event is considered to be an exacerbation of another event, which is either reported at the same time or just previously, only the more “serious” one is recorded. The most common example of the use of this convention is where a patient is nauseated and soon after vomits, in which case only vomiting is recorded.

General practitioners often do not report all events for patients who die during the course of

Prescription-Event

Monitoring

515

ANALYSIS OF PEM DATA a PEM study, the primary reason being that they do not have the patient’s notes because Analyses of PEM data produced routinely these have been returned to the Family Pracare: titioner Committee (FPC). In this case, the patient is simply recorded’ as having died with (4 Basic analyses of demographic data, e.g. no specified cause. To avoid missing any possisex, age, and regional distributions of the ble drug-related deaths, doctors are asked if patients, together with analyses of the they have any objection to the FPC releasing the indication for treatment and efficacy. notes to the DSRU. For more than 90% of the (b) Overall and regional response rates as a patients permission is given, in which case a simple ratio of the number of green forms request is sent to the relevant FPC for the returned to the number sent, and the patient’s notes; these are obtained for around general practitioner response according 85% of the patients. From the notes, a separate to the number of forms sent. computer file is created in which details of the (4 Frequencies of events reported as ADRs medical histories of the patients who died are to the monitored drug and to other drugs. recorded. This file contains all pertinent infor(4 Details of other drugs substituted for the mation about the patients including pre-existing monitored one. conditions and concomitant medications. In (4 Analyses of the daily doses of the moniaddition to obtaining the patient’s notes, a tored drug noted on the initial prescripdeath entry is obtained from the Office of tions and of other products written on the Population Censuses and Surveys (OPCS), same forms. These are produced manually although there may be a delay of about a year from a large sample (at least 1000) of preafter the patient’s death before it is received by scriptions. The DSRU does not have the the DSRU. The cause of death is coded using computer capacity or the staff that would ICD [14] and, where information about the be required to record this information cause of death is available from more than one from all the prescriptions in its computer. source, the order of priority used is: medical Unfortunately, this limits the potential of records, death entry, green form. PEM for dose-response analyses. Potentially life-threatening events, e.g. blood (f) Numbers of each event occurring in each dyscrasias, are also routinely followed-up by letter month during the year following the first to the relevant general practitioner and/or hosprescription, irrespective of whether the pital consultant. Further details are sought about patients were still taking the drug at the other events on an ad hoc basis. In the future, time of occurrence; a sample of this type PEM will be used to identify patients who either of analysis is shown in Fig. 2. take particular drugs or who experience specific Numbers and rates of each event occur63) events so that they can be “tagged” at the NHS ring in each month during the year folCentral Record office; the details of deaths lowing the first prescription, limited to among these patients will be sent automatically those events occurring during treatment. to the DSRU. The methodology and software (h) Numbers and rates of each event occurfor this procedure have been prepared but an ring in each month after the date on opportunity to test them has yet to occur. which treatment was stopped, limited to Since it began in 1981, great emphasis has those events occurring after patients had been placed on the improvement and developdiscontinued treatment. ment of PEM which has necessitated several (0 Analyses of the type (f) to (h) based solely changes in its methodology. Some of these have on fatal events are produced once the been small, e.g. alterations in the design of the follow-up of patients who died during the green form. In contrast, others have been major, course of the study has been completed. especially the improvements in the management Analyses of the type (f) to (h) based on of the data following the installation of a new other subsets of the data, e.g. patients computer system in 1984. The methodology of aged 60 years or more, are not produced the pilot study, together with that of some of routinely but are readily available if the other early studies, has been described by required. Rawson [8], while Inman et al. [15] and Rawson Comparative analysis is the essence of most [93 have outlined the methodology of studies epidemiological research and PEM is no excepperformed in the mid-1980s.

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RAWSON

tion. However, it is a problem to obtain a suitable “standard” with which to compare the PEM results [8], especially for a new, innovative drug. Formerly, when microcomputers were used to record and analyze PEM data, the green forms were sent at varying periods of time after the initial prescriptions. Since the dates of the events were not recorded and it was, therefore, impossible to limit the subsequent analyses to a standardized period of time [8], bias may have been introduced. Nevertheless, comparisons were made between the rates of events occurring during treatment with a particular drug (irrespective of the timing of the event) and the rates occurring during treatment with another similar type of product. The rates of events occurring during treatment with a particular drug were also compared with the rates of events experienced after ceasing treatment by those patients who discontinued the drug during the observation period. Some useful results were obtained from these analyses in studies of six non-steroidal anti-inflammatory drugs (benoxaprofen, fenbufen, piroxicam, zomepirac, and two formulations of indomethacin), and a histamine-Zreceptor antagonist (ranitidine) [8,9, 15-191. The introduction of the new minicomputer in 1984 has allowed the recording of the dates of the events and, as a result, has opened up a wider range of possible comparisons based on standardized observation period, i.e. the year

et al.

following the first prescription for the drug. For instance, one can look for suspected acute ADRs by comparing the rate of an event occurring during the first month after the initial prescription with the average rate occurring during the remaining 11 months of the observation period (regardless of whether treatment was discontinued). Results of this type of analysis for selected events from a recent PEM study of an anti-hypertensive drug [20] are shown in Table 1. It can be seen that the excess rates occurring during the first month are especially large for dizziness, headache, hypotension, tachycardia, cough, diarrhoea, and nausea and vomiting. Trends across the 12 months can also be assessed on a month-by-month basis. For example, the high rates of dizziness and headache occurring during the first month after the initial prescription as compared with those recorded during the subsequent 11 months are illustrated in Figs 3 and 4. Analyses of subsets of the data can be performed too. For instance, Figs 5 and 6 show the differences between the rates of dizziness and headache recorded during the 12 months for those aged under 70 years and those aged 70 years or more. The rate of dizziness in the first month for patients aged 70 years or more is twice as large as that for patients in the younger age group. However, the rate of headache in the first month is almost the same in both age groups.

Table 1. Rates of selected events recorded in a PEM study of an anti-hypertensive drug [20]

Selected individual events

Number during 12 months of observation

Percent of patients (n = 12,543)

2-l 32 313

Number of events and excess rate per 1000 patients during first month No.

Excess rate

0.2 0.3 2.5

6 5 37

0.3 0.2 0.9

483 310 126 155

3.8 2.5 1.0 1.2

152 94 29 29

9.7 5.9 1.6 1.4

218 194

1.7 1.5

71 69

4.6 4.6

360

2.9

54

2.1

236 326

1.9 2.6

63 97

3.8 6.1

Skin

Angioedema Urticaria Other acute events Nervous system

Dizziness Headache Paraesthesia Syncope Cardiovascular

Hypotension Tachycardia Respiratory

Cough Gastrointestinal

Diarrhoea Nausea and vomiting

Prescription-Event

Monitoring

18

517

0

patients aged lessthan7Oyears

??patients aged Myears

or more

16

O-

123

4 5

6

7

8

9W

1112

monthsafterfirst prescription

Fig. 3. Rate of dizziness per 1000 patients by month during the year following the initial prescription for an anti-hypertensive drug.

42o-

DlSCUSSlOlV

The methodology of PEM has been designed so that the scheme interferes as little as possible with the normal work of both the PPA and the general practitioners. Since PEM is a voluntary scheme, interference in the practitioners’ work is minimized in order to encourage them to complete the green forms. In addition, considerable effort is put into informing the doctors of the results obtained from their replies. For example, “PEM News”, which is a booklet containing details of the work being carried out by the DSRU, is distributed annually to all general practitioners in the U.K. The constraints imposed on the methodology of PEM has resulted in the scheme being somewhat cumbersome and labour intensive in that it requires the entry of data from photocopies of often poorly-written prescriptions, large mailings, record searching and transcribing by general practitioners, the entry of the reported

r

10

monthsafterfirst prescriphon

Fig. 5. Rate of dizziness per 1000 patients by month during the year following the initial prescription for an anti-hypertensive drug by age group.

events, and the follow-up of a variable proportion of the patients (usually done by sending personal letters to the relevant practitioners and/or hospital consultants). Additional work is required to obtain information about patients who have died. Nevertheless, with the present financial climate and concerns about confidentiality, it seems unlikely that an alternative large-scale scheme designed to generate hypotheses about potential adverse effects of new drugs, which is both less cumbersome and less expensive than PEM, will be established in the U.K. within the foreseeable future. Prescriptions are clearly one of the fundamental elements of PEM in that they provide the identities of the patient and the prescriber. However, the recording of the details from each prescription depends on the legibility of the photocopies and the ability of the DSRU’s

??patients aged Tlyearsor more

3

2o-

p

I2

3

4

5

6

7

8

910

?T12

months after firstprescriphon

Fig. 4. Rate of headache per 1000 patients by month during the year following the initial prescription for an anti-hypertensive drug.

monthsafterfirst prescrjptiiwr

Fig. 6. Rate of headache per 1000 patients by month during the year following the initial prescription for an anti-hypertensive drug by age group.

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prescription-entry clerks to read them accurately. Prescriptions which are incorrectly read may lead to general practitioners being unable to identify their patients and, consequently, unable to complete the green forms. In a study of the legibility of a random sample of 1076 prescriptions [8], it was found that the patient’s surname was illegible or doubtful on almost a quarter of the prescriptions, while the forename was not given on 38% and was illegible or doubtful on a further 5%; the patient’s address was clearly legible on two-thirds of the prescriptions. If one of the items on a prescription was illegible, then often so were the other items for the simple reason that all the information on prescriptions issued by doctors with poor handwriting was difficult to read, and vice versa. In practice, it has been found that the proportion of prescriptions which can be deciphered is usually around 70%. However, experienced clerks can often improve on this especially for drugs taken for proportion, chronic conditions in which a series of prescriptions for each patient are received, thus enabling the clerks to verify their identification. The legibility of the green forms is much less of a problem because the terms used to describe events are relatively limited when compared with the many thousands of combinations of names and addresses. The proportion of green forms returned in each PEM study has varied between 50 and 70%, but at present for almost all the drugs at least two-thirds of the green forms are returned. Of the third which are not returned, it is thought that in many cases the practitioner has been unable to identify the patient from the details provided on the form or the patient has left the practice. The response rate is also related to the rate at which a drug is prescribed in that if doctors prescribe the drug for many patients and, consequently, receive many green forms, the response is poorer. The best response is achieved for those products for which there is a steady increase in prescribing. Whether there are any differences between the patients for whom green forms are not completed and those for whom green forms are returned is unknown. Ideally, one would like to perform a study to identify the reasons why general practitioners do not take part in PEM and whether there are any differences between their patients and those of doctors that do take part. It would be beyond the resources of the DSRU to send

out staff to visit non-responding general practitioners and, therefore, a study of this type would have to be pursued by mail. Those doctors who never return green forms are unlikely to respond to additional requests for information about themselves or their patients. Also, such a study might be counterproductive in that those practitioners who have responded in PEM studies in the past may feel that they are being pressurized to take part in what is after all a voluntary scheme, in which case they may be discouraged from taking part in future studies. Consequently, the DSRU is reluctant to perform a study of this nature. One of the reasons why general practitioners do not complete green forms could be worries about confidentiality. However, less than 0.1% of the practitioners have expressed any concerns about this aspect of PEM. Since up to a third of the responding doctors return the whole green form [8], thus providing the identification of the patient for anyone who sees the form, this suggests that many general practitioners feel that taking part in PEM presents no confidentiality problems. Another reason why doctors may not respond is that they are unable to supply the requested information due to poor record-keeping. Inevitably, the quality of reports received on green forms is reliant on the quality of the general practitioners’ records which is often said to be poor [21,22]. In fact, a few doctors have informed the DSRU that, when they read their case notes in order to complete the green forms, they realized how poor their records were and had decided to improve them. There are several ways in which the quality of the report received by the DSRU can be adversely affected: the doctor may fail to record the problem reported by the patient or record it inaccurately, when completing the green form the practitioner may be unable to read the notes made by other doctors in the practice or their notes are unclear, the doctor may selectively record events on the green form (e.g. only serious events may be noted), and occasionally the DSRU’s technical officers cannot decipher the details written on the green form. However, event reporting is predominantly a series of “keywords” and these are often available from the poorest of records. No formal study to assess the accuracy, completeness or unbiasedness of the reports received from general practitioners has been performed for reasons similar to those for which no attempt has been made to see if there are

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differences between the patients of responding and non-responding doctors. Nevertheless, informal evidence has been accumulated in the follow-up of patients who died and of patients who experienced potentially life-threatening events (where the patients’ notes have been examined by DSRU staff), which indicates that serious events are not significantly underreported but minor events are. In the past, the indication for treatment was missing on up to 40% of the returned green forms. Higher proportions tended to occur in studies of drugs used for a limited number of conditions, which suggests that general practitioners feel it is unnecessary to record the indication in such situations. In studies of drugs with a wide range of indications, the proportion of forms without an indication was generally lower. Increased efforts by the DSRU to encourage doctors to record the indication has resulted in a decrease in the proportion of green forms without this information to 15-20%; it is hoped to reduce this proportion even further. Although the DSRU can do little to improve the quality of general practitioners’ records, it can ensure that the information on the green forms is recorded as accurately as possible. Almost all the technical officers who enter this information in the DSRU’s computer have some medical background, e.g. former nurses or laboratory technicians. Careful training is given to new recruits and, although the DSRU does not have the resources to verify the entry of each green form, random checks are carried out on the work of the technical officers (and also the prescription-entry clerks) to ensure that a satisfactory standard of work is maintained. The technical officers are required to make some decisions in their work but, if they are in any doubt, the form is referred to the senior officer who will either resolve the problem or refer it to a medically-trained member of staff. In a small-scale, blind experiment to assess the quality of the work of the most inexperienced officer against that of the most experienced, it was found that there was complete agreement for 18 of the 26 green forms (69%) entered by both workers. Although this proportion is not as good as we would like, none of the differences in coding that were identified resulted in a potentially serious error. In spite of PEM being dependent on the quality of general practitioners’ records, it does have the advantage that it should not be subject

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to recall bias as some other PMS techniques are [23]. Although the patient may see different partners in the practice on different occasions who will record details of the consultation in the patient’s notes in their own way, only one set of notes is kept for each patient within the surgery and the events are documented at the time at which they occur (or shortly afterwards). General practitioners are requested to use these notes when completing the green forms, but it is possible that some complete them from memory. They are also requested to record all events, but are not required to make any judgement about whether or not the events are causally related to the drug exposure. As a result, most events recorded in PEM are unrelated to the drug. However, almost all events occur more frequently during treatment than after stopping. The probable explanation for this difference is a bias due to surgery attendance. A greater tendency to attend the surgery during treatment is to be expected due to the illness and the need for further prescriptions which gives patients the opportunity to report events, however trivial. If patients cease treatment and do not attend the surgery regularly for other disorders, an appointment must be made to see the doctor before events can be reported, thus acting as a deterrent for the reporting of events (especially minor ones). In some of the early PEM studies, under-reporting in the after treatment period may have been increased by practitioners failing to see the relevance of recording events which occurred after treatment had been discontinued [8]. Due to this surgery attendance bias, confidence intervals for the ratios of rates of events occurring during treatment and rates occurring after treatment are potentially misleading. Comparisons of rates of events occurring during treatment with the monitored drug with rates occurring after treatment are complicated by other problems too. For instance, there is no way to allow for the different reasons why treatment is discontinued. It may be stopped because the patient improved, in which case lower rates of events after ceasing treatment might be due to the fact that patients who discontinued treatment are healthier rather than the events being due to the drug. On the other hand, if treatment is more likely to be stopped in sicker patients, events occurring after treatment might do so at a higher rate than those occurring during treatment, regardless of any effect of the drug. In addition, patients who

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cease to take the PEM drug may have another drug substituted which may influence their likelihood to experience events, making comparisons between rates occurring during treatment with the monitored drug and rates occurring after treatment at best irrelevant and at worst invalid. Such problems should not affect comparisons between rates of events occurring during treatment with a particular drug and the corresponding rates occurring during treatment with another drug, nor between the rates of events occurring during the first month after the initial prescription and the corresponding average rates occurring during the other 11 months of the observation period. Therefore, these comparisons appear to offer better ways of detecting potential ADRs. Large differences between the rates in these analyses would constitute “signals” for possible ADRs. Classical statistical significance tests do not, however, have a major role to play in such analyses because due to the nature of PEM (the DSRU cannot decide which patients are to take which drugs or for how long) there are, as discussed above, several potential biases (e.g. surgery attendance, non-response and recording biases) and confounders (e.g. different indications for treatment and substitute or concomitant therapy) which may affect the quality of the data. In such situations, frequentist statistical methods are inappropriate because the underlying assumptions made about the procedures used to collect the data are invalid [23-271. In addition, just one occurrence of some events, e.g. Stevens-Johnson syndrome, would be of importance clinically but would be unlikely to achieve statistical significance. The medical significance and interpretation of PEM data are more important than statistical significance. For example, the excess rates for dizziness and headache in the first month in the data shown in Table 1 are, if one performs the calculations [20], significantly different from zero and one might conclude that these events are probable ADRs. However, these events could be ADRs that may occur at any time after starting the treatment and the rates are higher during the first month because the number of susceptible patients is decreasing as they experience these ADRs and subsequently cease to take the drug; an examination of the rates of these two events occurring during treatment shows that this hypothesis is incorrect. On the other hand, dizziness and headache are sometimes caused by hypertension (the condition that the drug

is designed to alleviate) and, therefore, it is possible that the significant excess rates are a manifestation of lower rates occurring during later months due to the efficacy of the drug. It is, in fact, most likely that the excess rates of dizziness and headache are due to some patients suffering ADRs and others receiving benefit, together with some degree of underestimation during later months due to multiple events of the same type being reduced to only one in each period. Whatever the correct interpretation, it is clear that it is not always easy to distinguish between harmful and beneficial effects in PMS and that, if false alarms are not to be raised, an examination of statistical significance alone is insufficient. In spite of the potential biases and other problems, the results of PEM have been encouraging. Even in the early work using microcomputers to analyze the data, the known adverse effects of the drugs were detected, together with some that were previously unrecognized [8, 16-191; the new computing system presents greater analytical possibilities. PEM has a potential for generating hypotheses about possible ADRs [20,28] and also a number of other important advantages. The scheme has the ability to estimate rates of events within specific periods of time and to compare (at least qualitatively) both the rates occurring in patients taking different drugs and the rates within subgroups of patients taking the same drug. This is a considerable improvement over PMS methods in which rates of adverse events are reported as percentages of the number of patients which totally ignores time as a determinant of the risk of an ADR [23,29,30]. Previously, PEM results were commonly reported as rates per total population treatment exposure and they still can be. Such rates do not, however, take full account of the distribution of exposure and, unless the distributions of exposure are the same, which is unusual, erroneous inferences may be drawn when comparing the event profiles of two or more drugs [8,23]. The rates of events calculated from PEM have been compared informally with the results of clinical trials and post-marketing studies performed by pharmaceutical companies (in so far as they are available) and they were relatively similar. One would not, of course, expect close similarity because the patients in clinical trials are a highly selected group (as are the patients in many company PMS studies [31]), whereas the patients in PEM are unselected and are

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the general population to whom drugs are prescribed. PEM databases can also be used as a starting point for hypothesis-resting investigations [32]. The ability of PEM to test hypotheses has been further illustrated in a study of blood disorders and suicide in patients taking mianserin or amitriptyline [33]. In addition, PEM data have a potential use for providing information of importance in wider public health problems. PEM has been criticized because. in the time between the commencement of treatment and the mailing of the green form, it is possible for a patient to experience a serious ADR soon after the first prescription, which will only be detected by PEM several months later. Consequently, many other patients are put at risk and may suffer the ADR unnecessarily, simply because the PEM data have not been collected. In October 1988, PEM was modified in an attempt to overcome the difficulties caused by the delay of a year between the first prescription and the mailing of the green form. Green forms will now be posted to the general practitioners as soon as their patients have been identified, perhaps 3 months after the issue of the first prescription to each patient. At this time, events (particularly those which might be acute ADRs) should be fresh in the doctor’s mind. Information from returned forms will be entered in the computer and interim analyses performed. Subsequently, after a fixed interval (probably on the first anniversary of the initial prescription) the same green form will be returned to the practitioner so that the information on the patient can be updated. The precise timing of the update can be varied to suit different types of drug. For example, it may be preferable to return the forms after 6 months for patients treated with an antibiotic for only 7-10 days, whereas it may be preferable to wait for 18-24 months before returning the forms for patients treated for a chronic condition over many months. Several updates may be performed to assess delayed adverse effects. In conclusion, PEM is an important development in PMS within the U.K. It is now the second national PMS system, the first being the CSM’s voluntary reporting scheme (the yellow card system). The two schemes are complementary, not competitive, and should work together but, since the CSM does not record the names and addresses of patients for whom reports are received, the potential for coopera-

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tion is limited. Almost all new chemical entities introduced into general practice are now monitored routinely, with more than 20 drugs presently being studied. The time taken to assemble a large cohort of around 20,000 patients depends only on the rate at which the drug is prescribed, although promotional postmarketing studies carried out by pharmaceutical companies have led to an extension of the prescription collection period [20,34]. Improved analyses, together with the recent modification to PEM, should enable the early recognition of suspected ADRs occurring with a frequency of around 1 per 1000 patients (it is unlikely that PEM will detect rare ADRs except by chance). Improvements in the routine follow-up of deaths reported during PEM should mean that suspected fatal ADRs will be detected more quickly. Until full medical record linkage is established in the U.K., PEM is the closest to the ideals proposed by Finney [l] 25 years ago that is likely to be achieved. Acknowledgements-We thank the PPA and the many thousands of general practitioners for their invaluable work, without which PEM would be impossible. We are also indebted to hospital consultants, the FPCs and the OPCS for their assistance with follow-up investigations, and to the sponsoring pharmaceutical companies for their financial support. Finally, we thank our colleagues at the DSRU, especially Anne Boggust, Marilyn Skipp and Lynda Wihon for their contributions to PEM and Patrick Wailer for his helpful comments on an earlier version of this article.

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