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Considerations for Comparative

Observational Studies of Implantable

Medical Devices

Jessica J Jalbert, PhD

Director of Pharmacoepidemiology, LASER Analytica

Assistant Professor (courtesy) of Healthcare Policy and Research, Weill Cornell Medical College

CADTH Symposium

Ottawa, Canada

24 April 2017

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Device Characteristics

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IMD Example: Stents

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Medical Device Lifecycles

> Lifecycle of medical devices << drugs

• Different regulatory landscape

• Iterative improvements of existing technologies

> Incremental changes to device and procedure are common

• Improve performance/overcoming shortcomings

> Devices may be on market for a short period before being

discontinued or replaced

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Medical Devices “Systems”

> Devices can be marketed as individual, separate

components or as “systems”

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Identifying IMDs

> Administrative claims data

• Procedure codes (e.g. ICD-9, CPT-4 codes)

• Varying granularity

• Device-specific information generally lacking

> Electronic healthcare records

• Additional device/procedure information potentially

available (in addition to procedure codes)

• Lack of standardization/limited follow-up

> Device registries

• Detailed device/procedure/clinical data

• Smaller population/limited follow-up

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What are the implications?

> Unobserved heterogeneity

• Multiple versions of device in population

• Multiple combinations of components of a device in a

population

• Differences in safety/effectiveness

> Stratify by device (manufacturer, design, lot, version) or

combinations

• Too few patients/too little data to study all permutations

of a device or combinations of device systems

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Characteristics of Providers

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Role of Provider

> Operator skill and learning curve

• Related to procedural complexity

• Affect patient outcomes (short- and long-term)

• Affect choice of treatment

> Intervention setting

• Affect choice of treatment

• Affect patient outcomes

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0

0.5

1

1.5

2

2.5

3

3.5

Mo

rtal

ity

Ris

k (%

) 30-Day Mortality Risk and Past-Year

Physician CAS Volume

CAS Volume 0 1-4 5-9 10-19 20-24 ≥25

p-value for trend: <0.0001

Ref: Jalbert JJ et al. Circ Cardiovasc Qual Outcomes 2015;8(6 Suppl 3):S81-9.

Adjusted RR Ref 0.80 0.74 0.60 0.52 0.46 (0.62-1.04) (0.56-0.97) (0.46-0.80) (0.34-0.80) (0.33-0.65)

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0

0.5

1

1.5

2

2.5

3

3.5

Mo

rtal

ity

Ris

k (%

)

CAS Volume <10 10-19 20-39 ≥40

p-value for trend: < 0.0001

Adjusted RR 1.0 0.81 0.74 0.54 (0.63-1.04) (0.58-0.93) (0.42-0.71)

30-Day Mortality Risk and Past-Year

Hospital CAS Volume

Ref: Jalbert JJ et al. Circ Cardiovasc Qual Outcomes 2015;8(6 Suppl 3):S81-9.

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CAS vs. CEA with Different Levels of

Adjustment

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Proportion of CEA Procedures in HRRs

Performed in Hospitals with

<20 Past-Year CEA (2007 – 2008)

HRR = Hospital Referral Regions

From the Dartmouth atlas of health care

http://www.dartmouthatlas.org/data/region/

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Proportion of CAS Procedures in HRRs

Performed in Hospitals with <20 Past-Year CAS

(2007 – 2008)

HRR = Hospital Referral Regions

From the Dartmouth atlas of health care

http://www.dartmouthatlas.org/data/region/

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What are the implications?

> Real-world IMD performance

• Affected by operator and hospital proficiency

• Proficiency can be diverse in real-world settings

> Need to understand role of provider

• Describe volume-outcome relationship

• Adjust (potentially) for provider proficiency

• Consider other provider characteristics

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Thank you to collaborators/mentors

> Art Sedrakyan, MD, PhD – Weill Cornell Medical College

> Soko Setoguchi, MD, PhD – Duke Clinical Research

Institute and Brigham and Women’s Hospital/Harvard

Medical School

> Natasha Chen, PhD – Brigham and Women’s

Hospital/Harvard Medical School

> Hiraku Kumamaru, MD, ScD – Harvard Medical School

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Thank you for your attention

jessica.jalbert@la-ser.com

jjj2001@med.cornell.edu