At a time of growing demand for more accurate and timely drug safety evidence, a landmark study supports the value of electronic medical records (EmR) for detecting new adverse reactions.

1. ACCESSPOINT • VOLUME 5 • ISSUE 10 PAGE 35
The author
David Ansell, mb, CHb, mRCS, PHD
is Associate Director, RWE Solutions, IMS Health
Dansell@uk.imshealth.com
Prospective identification of drug
safety signals from primary care EMR
At a time of growing demand for more accurate and timely
drug safety evidence, a landmark study supports the value of
electronic medical records (EmR) for detecting new adverse
reactions. It also shows that statistical associations in EmR must
be treated with as much caution as those from individual case
reports − and be subjected to clinical and epidemiological
review. A deep understanding of the methodologies, data
collection and clinical practice involved is implicit.

2. PAGE 36 IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS
INSIGHTS HEOR, PHARMACOEPIDEMIOLOGY & DRUG SAFETY
Insights from The Health Improvement Network (THIN) database
Increasingly stringent regulatory requirements
for pharmaceutical risk management and
safety surveillance have accelerated research
to improve the detection of new adverse drug
reactions (ADRs) under conditions of normal
product use.
For many years, the process of identifying potential signals
and the existence of previously unknown risk has relied
mainly on individual case safety reports (ICSRs). More
recently the use of longitudinal health data (LHD) has been
explored, both to complement ICSR information and
overcome some inherent limitations. Most studies looking
to apply LHD have investigated its ability to distinguish
established ADRs from unrelated adverse events; few have
attempted to examine a role for this data in detecting
emerging safety signals.
leveraging EmR in pharmacovigilance
Marking an important milestone in efforts to apply EMR in
day-to-day pharmacovigilance, a new study has sought to
evaluate a process for assessing temporally associated drugs
and medical events (adverse events) in this data.1
Specifically, the researchers aimed to determine (1) to what
extent exploratory analysis of EMR would identify
important potential safety signals and (2) what proportion
of false alarms could be expected if the temporal
associations were taken at face value rather than subjected
to epidemiological review.
Utilizing the Uppsala Monitoring Centre’s vigiTrace™
framework for health data exploration, the study
comprised integrating the vigiTrace™ software framework
with the primary care EMR and performing a structured
assessment of more than 500 pairs of drugs and medical
events in THIN (The Health Improvement Network) – an
electronic medical records resource from primary care in
the UK. THIN includes more than 12 million patients, with
over 3.8 million being currently active patients. The EMR
are collected from general practices and are representative
of the entire UK population in terms of age, gender,
medical conditions and death rates. The data extract for the
current evaluation was from January 2011 and covered 7.7
million patients.
A key element of vigiTrace™ is a graphical display
(chronograph) which summarizes and visualizes temporal
associations between two events. In this case, the
chronograph focused on the cohort of patients with new
prescriptions (Rx) of the drug in question and explored
variation over time in the recording of a medical event
relative to those new Rx. Further, it contrasted the observed
number of patients with a record of the particular event to
an expected value in each time period, based on an external
control group. VigiTrace™ also provided analytics to
support the structured assessment with a calibrated
self-controlled cohort analysis.
Evaluation process
Over 40 drugs were randomly selected from THIN on the
basis of specified inclusion/exclusion criteria, key amongst
which was the presence of more than 5,000 new Rx. Medical
events (up to 20 per drug) chosen at random from those
identified as temporally associated with a new Rx of the
drug in question, were assessed for relevance prior to
undergoing in-depth analysis.
The in-depth assessment was based on a structured
questionnaire and included a review of the UK Summary of
Product Characteristics (SPC) document as well as
additional exploration of data in THIN. Among factors
addressed as part of this appraisal were: the nature of the
temporal pattern; demographics of the cohort; use of
concomitant medicines; previous signs and symptoms; and
potential confounding by underlying disease.
Results
From the more than 500 relevant drug-event combinations
that were identified, 25% were categorized as known ADRs,
based on the SPC review (eg, sleep disturbance for a drug
with insomnia listed, glaucoma for a drug with acute
glaucoma listed).
Close to 100 of the remaining combinations were classified
as meriting full clinical review, beyond the restricted scope
of the study assessment. Examples include multiple organ
failure with a selective serotonin reuptake inhibitor (SSRI);
skin sensation disturbance (eg, paresthesia, numbness,
tingling) with a long-acting beta-2 agonist; and an
ophthalmic condition with a diuretic. The strength of
evidence for these combinations varied: most of them
merely lacked alternative explanations to suggestive
temporal patterns, whereas a few also had support in
experimental evidence or regulatory information from
other countries than the UK.
In contrast, the majority (approaching 300) of the
highlighted drug-event pairs were deemed unlikely to
reflect direct causal relations and hence dismissed from
further review. The most common reasons for this were
confounding by the underlying disease or earlier signs and
symptoms indicating that the onset of the medical event
preceded the start of drug treatment. Examples include
endometriosis with a drug for the relief of IBS where the
prior diagnosis of IBS (based on abdominal pain) was later
shown to be endometriosis, and eustacian tube dysfunction
with antibiotic drops utilized for treating an ear infection.
Examples of the chronograph outputs are shown in
Figure 1 opposite.
Prospective identification of drug
safety signals from primary care EmR

3. ACCESSPOINT • VOLUME 5 • ISSUE 10 PAGE 37
That said, the fact that 76% of the drug-event pairs were
dismissed from further evaluation following initial review,
indicates that signal detection using LHD should form part
of a wider, comprehensive process of detailed clinical and
epidemiological review. This is an important area for further
research to inform the future role of LHD in signal
detection. It would include examination of individual
patient histories, evaluation of more detailed information in
THIN (eg, temporal patterns for similar drugs and medical
events) as well as exploration of alternative, complementary
information sources such as the scientific literature and
collections of individual case reports. A broader, contextual
understanding of the methodologies employed, approaches
to data collection, and the prevailing medical practice in the
setting being studied would be a key part of this process.
Implications
With this study has come a clear demonstration that
exploratory analysis of EMR is a valid and feasible approach
for detecting important drug safety signals. If a primary care
EMR such as THIN is utilized as the source, then signal
detection will be confined to those drugs prescribed within
the primary care setting. The initial epidemiological review
revealed a considerable number of temporally associated
drugs and medical events, ranging from significant, life-
threatening conditions to less serious but potentially
problematic events for patients. Importantly, some of these
were conditions that the current pharmacovigilance system,
with its reliance on individual ADR case reporting, may be
challenged to capture. Some of the identified events have
not been previously linked to these therapeutic agents and
have highlighted the requirement for further investigation.
1
Cederholm S, Hill G, Asiimwe A, Bate A, Bhayat F, Persson Brobert G, Bergvall T, Ansell D, Star K, Norén GN. Structured assessment for
prospective identification of safety signals in electronic medical records: Evaluation in the Health Improvement Network. Drug Saf, 2015; 38:
87-100
Figure 1: Sample outputs from the vigiTrace™ chronograph
The study referenced in this article was performed in collaboration with scientists from Eli Lilly, Pfizer, Takeda, Bayer and Cegedim UK,
within the public-private partnership PROTECT, which is funded through the European Innovative Medicines Initiative.
509
Temporally
associated
drug-event
pairs
382
New
127Already known 291Dismissed
91Merit further evaluation
25%
75%
76%24%
Source: Cederholm S, Asiimwe A, bate A, bhayat F, brobert G, Hill G, Star K, Norén GN. Structured assessment for prospective identification of potential
safety signals in electronic health records (Poster). 30th International Conference on Pharmacoepidemiology and Therapeutic Risk management (ICPE)
24-27 October, 2014 Taipei, Taiwan
Cannot sleep – insomnia is temporally associated with new
prescriptions of reboxetine and was classified as already
known since insomnia is listed as a very common adverse
reaction to reboxetine in the UK SPC.
Endometriosis is temporally associated with new
prescriptions of hyoscine but was dismissed from further
review on account of suspected protopathic bias. Hyoscine
is given to treat abdominal cramps, which are a common
symptom of endometriosis.
Epiphora is temporally associated with new prescriptions of
amiloride and was classified as meriting further review on
account of the suggestive temporal pattern.