Transcript Exploring the Clinical Informatics Landscape in Europe, Asia, and

Exploring the Clinical
Informatics Landscape in
Europe, Asia, and Beyond
Presentation Document
October 19, 2010
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Real world data emerging as a basis for decision making
Early but definitive signs that payors are demanding
more real-world proofs of net value of treatments
▪ Payors are increasingly asking for evidence demonstrating
cost effectiveness and real-world value of drugs
▪ Head-to-head comparators by sub-populations on the rise for
drugs that have proven cost-effective
In addition to claims data, increasing availability of real
world clinical data
▪
U.S.: EHR/eRx providing access to clinical data sets that are
much larger than clinical trial data
▪ UK: GPRD provides real-world data on >10mn patients
▪ India: Collecting medical data on 10s of millions of patients
Providers and regulators are increasingly analyzing
real-world impact of pharma products
▪ Researchers at academic medical centers analyzing realworld data for safety signals and comparative efficacy
▪
FDA launched the Sentinel Initiative in 2008 to query EMR
and medical claims systems for safety signals
Threats and opportunities as
rules of the game change
▪ New products face coverage
challenges without sufficient costbenefit case presentation
▪ Preferential formulary status is
increasingly granted to pharmacos
based on real-world clinical data
▪ Safety concerns could escalate
into high-profile cases
▪ Phamacos can expand market
access by targeting subpopulation for whom treatments
are most efficacious
▪ Real-world outcomes provide fact
base for pharmacos to confidently
take on risk-based pricing
▪ Pharmacos’ ability to stay ahead
of the curve using real-world
clinical data will be critical to
winning in the future
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Private payors and gatekeepers for public funding are requiring realworld proofs of cost-effectiveness for drug treatments
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Drug submission guidelines to require costeffectiveness data for drug submissions in 2010
Cost-effectiveness based on real-world clinical
data will also be required for
coverage renewal submissions
All cost-effectiveness claims to be
expressed in terms that allow for
monitoring and verification
▪
Collaboration with
Wisconsin HIE to
encourage ER doctors
to use EMRs to reduce
redundant treatments
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Partnership expected
to be expanded
nationwide, possibly in
conjunction
with other payors
Since 2004, 11 drug assessment
reports completed, often considering
only head-to-head comparison trials,
disregarding indirect comparisons
On June 26, 2009, recommendation made
against Lantus (glargine) use based on
analysis of real-world clinical data
SOURCE: Press articles, team analysis
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NICE already evaluates value of product
compared to price
▪
Moving towards value-based pricing with
lower prices at launch and potentially
increased prices after cost-effectiveness
is proven
▪
Numerous payors lobbied US Congress to
establish an entity to analyze real-world data
and understand treatment cost-effectiveness
▪
Efforts resulted in introduction of Comparative
Effectiveness Research Act of 2009 to create
an institute funded by both public and private
payors to identify most cost-effective treatments
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Academic medical centers, health systems and regulators increasingly
mining real world data to conduct their own safety surveillance and
comparative efficacy reviews
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Regenstrief has created nation's only state-wide
EMR system
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Allows ED physicians to view all previous care
as a single virtual record in 6MM patient
database, with 900MM online coded results and
20 MM full reports
FDA increasing use of real-world data analysis for
pharmacovigilance through launch of Sentinel
Initiative on May 22, 2008 to query EMR and
medical claims systems for safety signals
▪
ARRA investing $1.1 Bn into comparative efficacy
research through AHRQ, HHS, and NIH
Also created center to provide access to its
EMR data to other institutions
▪ UK’s General Practitioner Research Database
▪
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Providers working to leverage their own EMR
systems to provide new services and improve
existing operations
Kaiser already secured $600k grant from AHRQ
evaluating heart disease management and
prevention
SOURCE: Press articles, team analysis
(GPRD) provides real-world data on >10mn patients
▪
500+ publications on treatment outcomes of various
interventions have been published by various
academic and commercial researchers over the past
10 years
▪
Several industry players have purchased full access
to database
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Real-world data comes from diverse sources
Types of data
Types of organization
Potential vendors/partners
▪ Academic Medical Centers
EMR data
▪ Health Information Exchanges
▪ EMR vendors
▪ Data aggregators
▪ Public payors
Claims data
ePrescription /
pharmacy
fulfillment data
▪ Claims data vendors
▪ PBMs
▪ Retail pharmacies
▪ Electronic prescription
companies
Laboratory data
▪ Laboratory and diagnostic
services provider
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Significant challenges in capturing value – creating an advantage for
those that crack the code
Key challenges
Representative quotes
Gathering fragmented real-world clinical data
▪ Sources of data highly fragmented across
providers and data vendors
▪ Inconsistent data quality may limit usefulness
Difficulty in aggregating multiple data sources
▪ Regulations regarding patient data privacy limit
data exchange and linking
▪ Advanced technical expertise required to integrate
non-standardized data formats
Lack of expertise to extract business insights
▪ Analytic expertise typically approached more as
scientific exercise rather than business analysis
▪ Clinical researchers face difficulties in translating
clinical findings into business strategies
Lack of organizational readiness to use
▪ Pharmacos are swamped by today’s priorities
▪ Fragmentation of responsibilities within pharma
organizations limits their ability to launch cohesive
effort to capture the opportunity
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Focus of today’s discussion
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While most of the UK is fragmented with multiple stakeholders and
little consolidation…
▪
~250 Hospital Trusts (HT) managing hospitals and specialist
care (operating ~400 NHS hospital sites)
Providers
private
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~34K primary care GPs, who are mostly self-employed
Private hospitals (concentrated into 5 large chains)
Payers public
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Fragmented but important source of claims data
– Previously organized into ~150 Primary Care Trusts (PCTs)
with decision-making authority over ~75% of NHS budget
– Currently undergoing reform
Payers private
▪
Low-priority source due to fragmentation, e.g., provide only
supplementary insurance and serve ~10% of the population
Providers
public
Source: UK Monitor website; NHS website; McKinsey analysis
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Two entities stand out as leaders in the clinical informatics space
▪ Government Multi-disciplinary team based at
▪ Private company with longitudinal primary-
the Medicines & Healthcare products
Regulatory Agency
Longitudinal primary-care EMR data on 13
million UK lives
Data is aggregated, normalized, and linked
with other healthcare data
Online access to data
Wide array of analytics including
– Clinical epidemiology, treatment patterns,
and drug utilization
– Drug safety / pharmacovigilance
– Health outcomes, economics, drug
effectiveness
– Health service planning and disease
management
Consulting services, primarily for research
care EMR data on 12 million UK lives
602 general practices using EMIS clinical
system
Sample sizes limited to 100,000 patients
Analytic services available
Strictly for academic research purposes by
universities or pharmacovigilance activities
by pharma through a 3rd party
49 publications to date since 2004
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Source: UK Monitor website; NHS website; McKinsey analysis
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In Germany, while fragmentation exists, a number of coalitions are
forming creating pockets of meaningful data
Providers public
▪ Fragmented network of ~700 small public hospitals
Providers
private
▪ ~1200 hospitals and ~140K GPs / specialists
– HELIOS group is a leading network with 42 hospitals, 19 rehabilitation
Payers public
▪ ~280 “sickness funds” (non-profit, quasi-public, self-governed
centers, 24 clinics and 4 senior care facilities
organizations) covering 80-90% of population
– Highly concentrated and consolidating rapidly
– AOK and vdek are the dominant sickness funds
Payers private
▪ ~50 private payers covering only ~10% of population
▪ Typically branches of larger insurance companies
Others
▪ Bremen Institute for Prevention Research and Social Medicine (BIPS)
▪ Pharmacy Data Center, a centralized provider of claims data (diagnosis
and prescription) sells anonymized data that AZ could access
Source: UK Monitor website; NHS website; McKinsey analysis
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Data and analytic capabilities are being developed both through
academia and payers
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Funded by government and University
of Bremen
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Group of 14 “sickness funds” that
provide health insurance to ~1/3 of
Germans
Full data sets from four different
sources (including an AOK) covering
~14 million lives
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Each AOK is independent but noncompetitive and coordinated through
the “AOK-Bundesverband”
~70 faculty and staff including
epidemiologists, statisticians, and
analysts
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Claims, demographic, procedure code
and medication data on ~24m
Germans, but siloed amongst the 14
AOKs
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Demonstrated capability for analyzing
claims data, e.g., quality management
programs with HELIOS group
Over 50 peer-reviewed articles per
year
Collaborates with outside stakeholders,
requires approval by Ministry of Health
Source: BIPS website; AOK website; press releases; McKinsey analysis
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Additional sources of data across Europe
Nordics1
▪ In Sweden, 70 National Quality Registries cover 80% of the population
▪ Quality registries cover 68% of the population across the Nordics
France
▪ Single payer system with a National Insurance Database
▪ Échantillon Généraliste de Bénéficiaires (EGB) – 3% extract of insurance
database made available for academic researchers
Italy
▪ Health Search Database (HSD), a research unit of the Italian College of
▪
Cegedim
General Practitioners, aggregating clinical information contributed by
Italian GPs with records from ~2M patients
Datasets include patient EMRs, drug prescriptions and prices, lab and
diagnostic tests, and hospital DRG tariffs
▪ 3rd party commercial provider of sales force performance data
▪ Has been developing longitudinal EMR data in Europe, particularly in
France with ~1.6M primary care lives and specialty care lives ~100K
IMS
▪ Traditional provider of prescription sales data
▪ Developing data assets across Europe with established product lines,
e.g., IMS “XX” Analyzer
1 Denmark, Sweden, Finland, Norway, Iceland
Source: Company websites and documents; ISPOR; interviews; team analysis
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In Asia, some markets are developing data although still in early stages
South
Korea
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Taiwan
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Thailand
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National Health Insurance Corporation covers 98% of 48M
population captured in database since 2005 but currently not
linked to other sources
Hospitals investing in EMR systems and beginning to mine data,
e.g., Catholic Medical Centers
National Health Insurance Data containing administrative claims
data
Multiple registries, including cancer, birth, death, rare disease,
and dialysis
Multiple registries including cardiovascular, diabetes, cancer
Developing databases for prescription sales, inpatient, and
outpatient care
Source: Websites and documents; ISPOR; interviews; team analysis
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Large investments into infrastructure offer opportunities to leapfrog ahead
of traditional health system evolution
China
Canada
▪ Existing infrastructure through
▪ Alberta Health and Wellness
Ministry of Human Resources
and Social Security
(MOHRSS) largely paperbased
(AHW) serves as the primary
payer and primary inpatient
provider for the province of
Alberta
▪ Undergoing healthcare reform
with objective to provide
increased coverage to
population
▪ Past transformative ventures
have created massive
infrastructure builds through
turnkey solutions
▪ Actively promoting EMR
United Arab Emirates
(Abu Dhabi)
▪ Designed healthcare system
bottom-up, including integrated
EMR system
▪ Beginning to collect data on
~0.9M population
adoption to cover Alberta’s
~4M people
▪ 46% of community physicians
use EMR and ~34,000
providers share (some) clinical
data through Alberta Netcare
(2009)
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Key takeaways
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The data landscape outside of the US is complex with
differing data owners with variable interests
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Regulatory and reimbursement agencies are requesting data
perceived as relevant to their markets, often data from their
own markets
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Countries with infrastructure investments present unique
opportunities to develop intelligently designed data assets for
secondary use
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