Disclosures

Dr. Spertus discloses that he is a founder of Health Outcomes Sciences (www.h-outcomes.com) that disseminates and supports the PRISM tool.

All other authors – None

Management of COI – A complete raw set of data and analytic code provided to Harvard Clinical Research Institute for independent verification of all study results.

Testing Evidence-Based,Individualized Informed Consent Forms

to Improve Patients' Experiences with PCI

John Spertus MD MPH, Richard Bach MD, Charles Bethea MD,Adnan Chhatriwalla MD, Jeptha P. Curtis MD, Elizabeth Gialde RN,

Mayra Guerrero MD, Kensey Gosch MS, Philip Jones MS, Aaron Kugelmass MD, Bradley M. Leonard MD, Edward J. McNulty MD, Marc Shelton MD,

Henry H. Ting MD MBA, and Carole Decker RN PhD

Funding: AHA/PRT/David and Stevie Spina Outcomes Research Center, NHLBI R01- HL096624Disclosures: Dr. Spertus has equity in Health Outcomes Sciences (www.h-outcomes.com)

AHA Late Breaking Clinical Trials – November 14, 2011

Conceptualizing an Improved Consent Process

PCI Patients

Informed Consent

Patient Factors:- Socio-demographics- Clinical Factors- Disease Severity

Feedback of Predicted Outcomes

DES

BMS

Outcomes: • Restenosis• Need for DAPT

Medical Decision-making

PCI Complications:

•Bleeding•Death

Informing Patients

Shared Decision-making:

- Therapeutic options- Evidence of benefit- Patient preferences

Requires Delivering Evidence-based Prediction Models

ePRISM: Clinical Risk Modeling at the Point-of-Care

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Risk Models Decision Support Tools

Valid Risk Models for PCI Outcomes

ACC NCDR Mortality Model– Built on 588,398 procedures at 465 sites– J Am Coll Cardiol 2010; 55:1923-32

ACC NCDR Bleeding Risk Model– Built on 302,152 procedures at 440 sites– Circ Cardiovasc Intervent 2009; 2: 222-9

ACC NCDR 1-year Target Vessel Revascularization Model for DES and BMS– Built on 27,107 procedures in all Massachusetts hospitals– Circulation 2011; 124: 1557-64

Implementing PRISM Informed Consents

Study Design

Design: 9-center pre/post survey of patients’experiences with traditional

vs. PRISM-generated consent forms

Outcomes:

– Do patients engage in the consent process?

» Do they read the consents? Do they understand them?

– Is there effective ‘knowledge transfer’ of risks/benefits of PCI?

» Are patients aware of risks of bleeding? Death?

– Do patients participate in shared medical decision-making?

» Do they discuss stent type with their doctors? Participate in the decision?

********

Henry Ford Hospital Detroit, MI

Mayra Guerrero, MDMayra Guerrero, MD

**

Baylor HealthPlano Heart Hospital

Plano, TXBradley Leonard, MDBradley Leonard, MD

Washington UniversityBarnes-Jewish Hospital

St. Louis, MORichard Bach, MDRichard Bach, MD

**

Bay State Medical CenterSpringfield, MA

Aaron Kugelmass, MDAaron Kugelmass, MD

Yale New Haven HospitalNew Haven, CTJeptha Curtis, MDJeptha Curtis, MD

****

Prairie HeartSt. John’s Hospital

Springfield, ILMarc Shelton, MDMarc Shelton, MD

Kaiser-PermanenteSan Francisco, CA

Ed McNulty, MD

**

**

**

Mayo ClinicRochester, MNHenry Ting, MDHenry Ting, MD

Integris Heart HospitalOklahoma City, OK

Charles Bethea, MDCharles Bethea, MD

Sites Participating in PRISM Study

Site Enrollment, Characteristics & Process

HospitalA B C D E F G H I

Number of patients surveyedOriginal consentPRISM consent

101101

100101

6543

6265

6651

6862

4121

3939

4844

Reading level (School grade)Original consentPRISM consent

15.78.6

11.09.0

9.59.0

12.59.1

12.79.14

12.39.5

9.78.0

13.79.1

13.19.0

Number of interventionalists 23 19 21 5 52 12 11 15 17

PRISM replaced original form

Baseline Characteristics

590 surveyed with original consents, 527 with PRISM

Comparable in >30 demographic, literacy/numeracy and comorbidity characteristics, except…

More PRISM patients with – History of prior smoking (42% vs. 33%, p=0.006)– History of depression (10% vs. 5%, p=0.001)– Stable CAD (51% vs. 34%, p<0.001)

All differences adjusted for in hierarchical models

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Per

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Original ConsentOriginal Consent PRISM ConsentPRISM Consent

100100

Percent of Patients Who Reviewed the Consent FormPercent of Patients Who Reviewed the Consent Form

Study averageIndividual sites

Large Site Variability

Required statistical analyses to be site-adjusted

Patients’ Experiences of the Consent Process

0%10%20%30%40%50%60%70%80%90%

100%

Reviewed consentform

Completelyunderstood theinformation*

Consent was easy toread*

Original Consent (n=590) PRISM Consent (n=527)

p=0.04

p=0.04 p=0.01

*Among those who reviewed consentAll p-values from hierarchical models adjusting for site

Knowledge Transfer

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Correctly identifiedpurpose of the procedure

Recalled being told %risk of death

Recalled being told %risk of bleeding

Original Consent (n=590) PRISM Consent (n=527)

p=0.02 p=0.09 p=0.08

All p-values from full, site-adjusted models

Discussed Stent Type with Doctor before Treatment

0%

20%

40%

60%

80%

100%

Discussed Stent Type with Doctor

Original Consent (n=590) PRISM Consent (n=527)

Average OR = 2.7, p=0.02

All p-values from full, site-adjusted models

Participation in Shared Decision-MakingWho Should Decide your Treatment? Who Decided to Use a DES or BMS?

p=0.43 p=0.05

All p-values from full, site-adjusted models

Limitations

Non-randomized study– Difficult given fundamental changes in structure/process of

care

Which components of PRISM consents – lower reading level, individualized risks – lead to outcomes unknown

Site characteristics associated with benefit unknown– Ongoing qualitative research on implementation

Conclusions

It is feasible to implement evidence-based decision aids within the routine flow of patient care

Personalized, evidence-based consents support…– Improved informed consent

– Better knowledge transfer

– More engagement in shared decision-making

Marked variability in benefits observed across sites– The consent form is only 1 component of the consent process

Future Directions

Define impact on treatment and outcomes– Do they support more rational of drug eluting stents?– Do they reverse the risk-treatment paradox in bleeding

management?

Extend this paradigm to other conditions– Shared decision-making tools for stable CAD treatment

– Other medical conditions – orthopedics, cancer, etc.