A collaborative foundation for new diabetes insights in Germany

1. ACCESSPOINT • VOLUME 5 ISSUE 9 PAGE 45
InsIghts MIXED METHODS REGISTRY CREATION
The authors
Laura Garcia Alvarez, PHD
is Senior Consultant, RWE Solutions, IMS Health
LGarciaAlvarez@uk.imshealth.com
Joshua Hiller, MBA
is Senior Principal, RWE Solutions, IMS Health
jhiller@imshealth.com
A collaborative foundation
for new diabetes insights
in Germany
Researchers conducting analytics and epidemiological studies
using electronic medical record databases frequently find
themselves short of critical variables. The value from data
collected through a mixed methods registry like DIAREG spans
scientific and commercial applications and creates new
potential for exploring relationships between perspectives,
actions and outcomes.
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2. PAGE 46 IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS & HEOR
Researchers conducting analytics and epidemiological
studies using electronic medical record (EMR) databases
frequently find themselves short of critical variables,
potentially limiting the breadth of research they can
perform. Although widely available EMR databases such
as The Health Improvement Network (THIN), IMS® Disease
Analyzer, and the Clinical Practice Research Datalink
(CPRD) contain a great deal of longitudinal primary care
data, it is often the case that certain types of information
are missing – either because an EMR field has not been
completed or because a particular field does not exist
within the database.
In particular, behavioral detail such as reasons for changing
therapy or the physician’s perspective of important clinical
characteristics are rarely part of a structured health record
and thus are not contained in mainstream EMR databases.
Typically, researchers must then decide whether to sacrifice
the breadth of variables captured, and hence limit the
study scope, or use a purely prospective design and
sacrifice time and cost to implement an extended
prospective observational study.
LEVERAGING MIXED METHODS FOR A
COMPREHENSIVE RESOURCE
To address these challenges, IMS Health, in partnership
with AstraZeneca, has developed an innovative registry
(DIAREG) of patients with type 2 diabetes mellitus
(T2DM). AstraZeneca is committed to demonstrating the
efficacy and benefit of its medicines in a real-world
setting, especially in terms of patient-relevant outcomes.
The registry is based on the complementary methods of
retrospective and prospective data collection, thereby
overcoming the individual limitations of each, enabling
the creation of a rich data resource for observational
research in this area.
IDENTIFYING REQUIREMENTS
Work on DIAREG began in 2012. Understanding the key
requirements for a comprehensive prospective disease
registry, IMS® Disease Analyzer in Germany was selected
as the core data backbone, being representative with
input from physicians in general practice as well as
diabetologists,i
and validated with a documented
history of application in published scientific studies.
Initial analysis of data variables confirmed that Disease
Analyzer contained rich information on population
characteristics (eg, demographics, medical history) and
treatment patterns (eg, diagnosis, prescriptions, co-
medications, co-morbid conditions) in diabetes patients.
However, while some data existed for certain diabetes-
relevant clinical parameters, such as HbA1c and body
mass index (BMI), this was often recorded less frequently
or sometimes not at all. Furthermore, other clinical
outcomes (eg, cardiovascular events, hypoglycemic
episodes, hospitalizations), physician behavior (eg, drivers
of therapy decision, reasons for dose or treatment
modification) and patient-reported outcomes (PRO)
(eg, general quality of life, disease-specific quality of life
or treatment satisfaction), were not captured as
structured data within the patient record at all.
As a result of this initial analysis, a set of 27 variables were
identified for their potential research value if collected, to
enhance the available EMR resource.
DIAREG IS BORN
The identified need for an‘enhanced’EMR registry took
the next stage of development down two separate paths
– technical and ethical – to achieve an optimal solution.
technical implementation
To facilitate technical implementation of the registry,
IMS Health worked closely with the EMR software vendor
responsible for collecting the data underpinning Disease
Analyzer. Together, they designed and created the
capability for a retrieve form data capture window (or
‘pop up’) to be triggered in the physician office during the
patient visit, based on a set of criteria available within the
patient EMR (eg, diagnosis code, existence of prior anti-
diabetic treatment, etc). Every time an eligible patient was
identified through the trigger, the physician completed
an electronic case report form (eCRF) in the‘pop-up’
window to provide the required additional clinical data.
Enhanced insights from a mixed methods approach
patients
1,071
DIAREG
changed therapy
22%
InsIghts MIXED METHODS REGISTRY CREATION
i Becher H, Kostev K, Schröder-Bernhardi D. Validity and
representativeness of the Disease Analyzer patient database for use in
pharmacoepidemiological and pharmacoeconomic studies. Int J Clin
Pharmacol Ther, 2009; 47: 617-626
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3. ACCESSPOINT • VOLUME 5 ISSUE 9 PAGE 47
Since patient EMR was used as the basis for including or
excluding a patient from the registry, the potential impact
of subjective selection was reduced. Consecutive new
patients continued to be triggered for inclusion in the
registry until the physician reached a pre-defined cap, thus
providing a framework for random sample selection. Data
collected from the retrieve form data capture window eCRF
is currently being linked back to the EMR using a hash
de-id process that removes protected health information
(PHI) prior to extraction to the IMS Health database.
In addition to the enhanced clinical data collection, a
second phase of the registry build involved the
introduction of PROs to provide a further layer of
information. These are collected via paper-based
questionnaires handed to patients at the physician site
where they are filled in and returned for entry into an
electronic database. An additional hash algorithm has
been deployed for one-way linkage of the PRO data to
the EMR and eCRF (Figure 1).
Ethical implementation
From an ethical perspective, it was essential to ensure
that the registry was developed in accordance with sound
observational research practices. To that end, a Scientific
Advisory Board was created to provide guidance on the
methods for site identification, eCRF review, inclusion of
PROs, use of patient informed consent, and submissions
for ethics approval. The Committee is made up of six
independent academic researchers and physicians who
have no affiliation with either AstraZeneca or IMS Health.
Patients participating in the registry have given informed
consent for inclusion of their information from EMR, as
well as the eCRF and PRO questionnaire. The registry
protocol was reviewed and approved by the Ethics
Committee, Nordrhein, Germany (Ethikkommission der
Ärztekammer Nordrhein) under the name of DIAREG.
UNIQUELY GRANULAR OBSERVATIONAL
RESEARCH
As of September 2014, DIAREG has been collecting data
for more than 18 months. The registry currently contains
eCRF questionnaires, with comprehensive, longitudinal
data variables, for 1,071 diabetes patients, enabling
granular observational research. A subset analysis of
these patients (n=824) shows that 77% were enrolled by
GPs, the remainder being recruited by diabetologists.
Based on data from half of the cohort, average length of
time with T2DM is 12.3 years (median 11 years). Twenty-
two percent of patients (n=181/824) in the registry have
experienced a change to their anti-diabetes therapy at
least once within the last year, mostly by the GP (57%) but
also by diabetologists, who were responsible for 35% of
therapy changes. For 152 patients (84% of the therapy
modification population), this took the form of a dose
adjustment to their existing therapy, mainly due to
insufficient control of HbA1c (Figure 2). A change of drug
was recorded for 60 patients (33%) for the same reason.
Overall, doctors have reported high expectations of HbA1c
reduction when deciding on a new treatment regimen.
A total of 475 patients (58%) self-monitored their blood
glucose levels, with 30% checking their blood sugar more
than twice a day. Visits to other specialists were recorded
for 43% of 824 patients, the most frequently visited being
ophthalmologists (57%) for diagnosis of retinopathies.
Of the 824 patients in the subset, 43 experienced at least
one hypoglycemic event, four of whom required
hospitalization (Figure 3).
ENABLING EVIDENCE-BASED CONNECTIONS
The data captured in DIAREG enables researchers to
identify and explore associations across measures that
have not been collected before in a sustainable and
integrated manner.
Patient characteristics of
interest programmed into
EMR database to trigger eCRF
EMR and PRO linked to disease-specific data at
patient level creating enhanced patient record
Double hash algorithm applied for data anonymization
IMS Disease Analyzer
eCRF pop-up
PRO
Enhanced Disease
Cohort
FIGURE 1: CUSTOMIZEd EMR ANd REGISTRY dATA COHORT
continued on next page
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4. PAGE 48 IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS & HEOR
InsIghts MIXED METHODS REGISTRY CREATION
By allowing comparison of clinical parameters at a
patient level, it provides evidence of associations from a
real-world setting that previously could only be
identified anecdotally or through market research.
As an example, the capture of BMI and HbA1c
measurements without DIAREG was recorded in 61.9%
and 42.3% of the population respectively. With DIAREG,
the capture of these critical lab measurements increases
to 83.3% and 77.6% respectively (Figure 4).
Source: Disease registries including Patient Reported Outcomes - IMS® DIAREG
YesNo
Number of patients with
at least one dose adjustment
Reason for therapy adjustment
0 20 40 60 80 100 120
16% (n=29)
84%
(n=152)
Other
Co-medication
Weight gain
Patient request
Hypoglycemic events
Microvascular complications
Macrovascular complications
Change of substance combination
Insufficient HbA1c reduction
39
9
13
10
22
16
2
23
112
FIGURE 2: MOSTTHERAPY AdJUSTMENTS ARE dUETO POOR HbA1C CONTROL
N= 824 Patients, of which 43 had at least 1 hypoglycemic event as reported in DIAREG
Source: Disease registries including Patient Reported Outcomes - IMS® DIAREG
4 or more 3 2 1
Number of patients having a hypoglycemic event
Type of
hypoglycemic event
0 2 4 6 8 10 12 14 16
1
1
3
3
4
2
2
6
7
12
9
15
13
17
Hypoglycemia requiring
hospitalization
Hypoglycemia with
glucose consumption
Number of events per patient
Hypoglycemia
requiring assistance
Blood sugar <70 mg/dl
measured by patient
FIGURE 3: PATIENTS EXPERIENCING A HYPOGLYCEMIC EVENT
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5. ACCESSPOINT • VOLUME 5 ISSUE 9 PAGE 49
Prior to implementation of DIAREG, real-world
information on the proportion of patients checking blood
sugar, the reason for modifying treatment, the number
and type of hypoglycemic events, diagnosis for specialist
visits or quantity of lab measurements captured was non-
existent. Figure 5 outlines categories of data enhanced
through the mixed methods approach.
EXTENDEDVALUEWITH MULTIPLE APPLICATIONS
The value from data collected through a mixed methods
registry like DIAREG spans scientific and commercial
applications. For researchers, the depth of detail from the
comprehensive patient record allows retrospective analysis
using measures that are not available in other datasets. For
brand teams, the behavioral information from physicians
and patients, such as reasons for switch and quality of life,
creates new potential for exploring relationships between
perspectives, actions and outcomes.
DIAREG: n=407 patients
Source: Disease registries including Patient Reported Outcomes - IMS® DIAREG
Already in DA Update in DIAREG Missing
57.0%
61.9%
42.3%
29.0%
15.7%
41.0%
14.0%
22.4%
16.7%
0% 10 20 30 40 50 60 70 80 90 100
Blood pressure
Height/Weight
HbA1c
FIGURE 4: dIAREG ENAbLES INCREASEd CAPTURE OF CRITICAL MEASUREMENTS
FIGURE 5: CATEGORIES OF dATA ENHANCEdTHROUGH A MIXEd METHOdS APPROACH
Information in IMS® Disease Analyzer
Documented type of diabetes
Therapy duration at the treating physician
Disease-relevantparameters(eg,HbA1c,bloodglucose,weight/BMI,bloodpressure)
–
–
–
Diabetes-related complications
Referral to hospital
Referral to specialists
Referral to rehabilitation
Patient education
–
–
Information in IMS® DIAREG
Confirmation of type 2 diabetes diagnosis
Start/duration of type 2 diabetes
Complete documentation of all disease-relevant parameters
Frequency and severity of hypoglycemias
Treatment goals (related to symptoms, laboratory parameters and complications)
Reasons for change of therapy and treatment goals associated with the change
Complete documentation of all diabetes-related complications
Allstaysinhospitalwithreasonsforhospitalization,diagnosisatdischargeandhospitaldays
All specialist consultations with diagnosis
All rehabilitation measures with diagnosis
All educational activities
Frequency of blood glucose self monitoring
Physician's estimate of the patient's therapy adherence
The IMS® DIAREG registry is open to other collaborations.
For further information please email
Jhiller@imshealth.com
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