3. 3
Patient Involvement in Research
We are being asked to do more with less
Decrease in availability of funds for research
Increase in stakeholder demand for real-world data post-approval
Timelines are being cut
Why we need it…
5. 5
Patient Involvement in Research
Innovation potential for research
Why we need it…
Faster
Enrollment
Increased
Retention
Decreased
Costs
Upfront study design more patient-friendly
Recruitment and retention activities relevant to patients
Patient outreach to supplement recruitment
Patient engagement during study (and beyond)
Remote visits (hybrid virtual study designs)
6. 6
Direct-to-Patient Innovation
*Patient protocol
assessment for
feedback on:
• I/E criteria
• Barriers &
facilitating
messages
*Supplemental
patient
recruitment
*Retention
* Pre-registration
* Alumni
communities
* Direct
recruitment of
patients (no
sites)
* On-line patient
consent &
screening
* Capture of ePRO
data
*Direct outreach to
patients
*Online consent
and ePRO
*Patient consent
for medical record
access
*Patient provision
of DNA or blood
sample
* Device integration
(all without sites)
*Direct patient
outreach & pre-
qualification
*Physician visit for
screening &
randomization
*Remote visits with
ePRO; in-person
visits for physician
endpoints or risk
*Would work well
for pragmatic
trials
Clinical Study
Support
Observational
PRO Data
Observational
PRO+EMR+Lab
+Device
Hybrid Virtual
Clinical Trials
Now Next
8. 8
Balance to Direct-to-Patient
Benefits
> More rapid study launch and
shortened timelines
> Decreased costs compared to
the physician-centric model
> Strong patient interest in method
- Helping others
- Alignment of patient incentives
- Comprehensive condition
monitoring and tracking
> Patient perspective directly
provided
Limitations
> Questions about data quality
- Verification of patient diagnosis
- Self-reported data
- Length of recall
- Lack of randomization
> No physician involvement
> Regulatory requirements in
process of being defined in some
countries
9. 9
Future: Virtual Research
Driving greater efficiencies through direct patient engagement
• Rapid and Efficient Enrollment
> Direct-to-patient recruitment
> On-line screening and consent
• Continued patient engagement
> Retention activities
> Remote lost to follow-up tracking
• Next stage in patient involvement = virtual consent and/or remote patient visits
> Reduces site and patient burden
> Reduces investigator grant fees
> Reduces site monitoring visits
11. 11
Case Study Example:
Burden of Illness in MS Walking Ability
• Walking impairment was associated with
increased falls and severe falls led to
hospitalization/ER use and doctor’s visits
• Objective:
• To assess the clinical,
psychological and economic
impact of differences in walking
ability in patients with MS
• Approach:
• 346 US patients with MS
completed an on-line study in 2
weeks
– PDDS=0: 106 (31%)
– PDDS of >0: 240 (69%)
• Walking ability was significantly
linked to increased:
– Falls
– Depression
– Absenteeism
– Activity restriction
Conclusions
Background Findings Related to Falls
Compliance with Daily Diary (n=74 Subjects)
14%
62%
50%
0%
50%
100%
PDDS 0 PDDS 3 PDDS 4
% of Patients that “Sometimes” Fall
Because of MS by PDDS Score
2% 2%
11% 16%
32% 27%
0%
50%
100%
Hospital / ER Doctor's Office
Resource Utilization for Severe Falls by
PDDS Score
PDDS 0 PDDS 3 PDDS 4
Source: Sidovar M, Horowicz-Mehler N, Hawryluk E, Cascade E, McCarthy S: Patient-Reported Burden of Walking
Impairment in Multiple Sclerosis. ISPOR June 2012.
12. 12
Case Study Example:
PRO + Chart Data in US Gout Patients
• Although concerns exist regarding the
validity of self-reported diagnosis, this
PRO+MR pilot shows nearly all (37 of
38) charts confirm patient data
• Objective: To collect patient-reported
outcomes (PRO) and medical record
(MR) data
• Approach: MediGuard.org members
were invited to participate based upon
treatment or diagnosis in their profile
• Interested members screened based
on self-reported diagnosis and
willingness to release medical records
(electronic and paper signature)
• OHIS contacted physicians and
obtained participant charts
• Results:
• 42 of 50 paper release forms returned
• 38 of 50 charts retrieved (28
electronic, 10 paper)
Conclusions
Background Findings
35 21
0 5 10 15 20 25 30 35
Diagnosis Treatment Missing
% Match from PRO to MR
Medical Records
Source: Cascade E, Marr P; Tuttle D, Winslow M: Patient-Reported Outcomes (PRO) and Medical Record Data (MR) in
Observational Study Designs: Results from a Direct-to-Patient Pilot Study in Gout. ISPOR June 2012.
13. 13
Case Study Example:
Measuring UK Real-World Outcomes
• Quintiles patient consent & connectivity
provide opportunity for intervention
• PRO+EMR environment serves as
foundation for intervention evaluation
• Objective: Build a UK data-rich
environment to measure outcomes
• Approach: Conducted study to
demonstrate PRO+EMR link with
SAIL data warehouse in Wales, UK
• In 6 weeks, recruited 240
cholesterol patients who
completed PRO assessments and
consented to share identifiers
• Identifiers provided to NHS Wales
to create pseudo-identifier bridge
into SAIL data warehouse
o PRO data combined with
electronic data stored in SAIL at
Swansea Univ. for all Wales
Conclusions
93% 98%
0%
25%
50%
75%
100%
Patients
(224 of 240)
Diagnosis
(89 of 91)
Background Findings
% Match from PRO to EMR Wales, UK
Source: Cascade E, Nixon M, Ford D, Brooks C, Heaven M: Combining Electronic Health Records and Patient-Reported
Information in the UK: Preliminary Results from the WASPS (Wales SAIL + PRO Study) . ISPOR June 2012.
14. 14
Case Study Example:
Evidence-based Program Design
• Data-driven patient framework
serves as the foundation for
program design
• Design includes continuous
program evaluation component
• Objective: Build HTN engagement
program around deep
understanding of patient drivers
• Approach: Surveyed >350 patients
in UK, DE, ES, IT to support design:
• Behavioral segments
o Control: External / Internal
o Emotion: Positive / Negative
o Agency/Action: High / Low
• Validated patient-reported
outcomes instruments used to
evaluate adherence, treatment
satisfaction, and other drivers of
engagement
• Communication preferences:
Content, Message, Frequency
Results
51%
39% 39%
24% 23% 21%
13%
8%
0%
20%
40%
60%
IPH EPL EPH IPL INH ENH ENL INL
% Perfect Adherence by Segment
Background Findings
Source: Cascade E, Cousins F, Connor U, Sandy R: Variance in Medication Adherence by Patient Behavioral Segment: A Multi-
Country Study in Hypertension . ISPOR June 2012.
