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Cost, Evidence and Comparative Effectiveness Research Data in Benefit Design – An Exploratory Study Harald Schmidt Fellow Kolleg Forschergruppe Uni Münster Research Associate LSE Health Fellow , Kolleg Forschergruppe, Uni Münster , Research Associate, LSE Health Nuffield Trust, H3 March 11

Harald Schmidt: Research data in benefit design

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Page 1: Harald Schmidt: Research data in benefit design

Cost, Evidence and Comparative Effectiveness Research Data in Benefit Design –An Exploratory Study

Harald SchmidtFellow Kolleg Forschergruppe Uni Münster Research Associate LSE HealthFellow, Kolleg Forschergruppe, Uni Münster, Research Associate, LSE Health

Nuffield Trust, H3 March 11

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Objectives

• With CER push: (how) will public and private payers consider value in benefit design? g

• Implementation mechanisms: what’s feasible and fair?

• Within vs across disease prioritizations: potential?

• What role for public engagement?

• Patient Centered Outcomes Research Institute (PCORI): how can it help maximize CER benefits?

Page 3: Harald Schmidt: Research data in benefit design

Objectives

• With CER push: (how) will public and private payers consider value in benefit design? g

• Implementation mechanisms: what’s feasible and fair?

• Within vs across disease prioritizations: potential?

• What role for public engagement?

• Patient Centered Outcomes Research Institute (PCORI): how can it help maximize CER benefits?

Page 4: Harald Schmidt: Research data in benefit design

Two examples

Prostate cancer management, Plavix/Effient trial: Policy spectrum:Policy spectrum: • Provide all options – physician/patient judgment• Differential copays /Value Based Insurance Design (VBID)p y g ( )• Other steering (information, counseling…) • Deny coverage/access• Other -> Consensus: no ban, but shared decision making and use of

info Over time move down the ladder (3 5 Y)info. Over time, move down the ladder (3-5 Y)

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Copays and VBID/’top-up’ payments

Pro: • “employers need it simple” branded/generic concept clear and y g

accepted, signaling effectCon: • blunt & potentially unfair (Newhouse/RAND)• blunt & potentially unfair (Newhouse/RAND),• operationalizability: “just good for low hanging fruit”? Key: • robustness of evidence, admin cost, feasibility (co-pays used

or not… payers vs payer/provider systems)• Fairness within group (Plavix): don’t penalize victims of• Fairness within group (Plavix): don t penalize victims of

genetic lottery • Fairness across groups: Who and why? (diabetics….)• Instead of drugs: focus on choice of providers, wellness

incentives

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Fellowship meetings and travel opptand VBID/’top up’ paymentsand VBID/ top-up payments Sept: Orientation & qualitative methods / NYCNov: CMWF Intl Symposium / DCNov: CMWF Intl Symposium / DC Jan: IHI/CMWF Fellow Summit / BostonFeb: Policy mtg / DCy gMay: Canada tripJune: final reporting seminar / NYC

Research related travel…

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