WLSACONVERGENCE SUMMIT

EVALUATING POCKET PATH® AN MHEALTH INTERVENTION FOR SELF-MANAGEMENT OF CHRONIC ILLNESS USING A RIGOROUS TRIAL DESIGN IN A REAL-WORLD CLINICAL SETTING TECHNOLOGIESANNETTE DEVITO DABBS RN,

PHDUNIVERSITY OF PITTSBURGHSCHOOL OF NURSING

Evaluating Pocket PATH® an mHealth Intervention for Self-Management of Chronic Illness using a Rigorous Trial Design

in a Real-World Clinical Setting

Annette DeVito Dabbs RN, PhDUniversity of Pittsburgh

School of Nursing

Wireless Health 2014October 30, 2014

Background

• To promote better health outcomes people with chronic illnesses are– expected to be actively engaged in care– perform self-management activities

• adhering to the regimen• performing self-monitoring• detecting and reporting condition changes

in a timely manner

• Performance of these behaviors is less than ideal and effective interventions to promote self-management behaviors are lacking

mHealth Technologies

• Hold promise for assisting patients to be informed, active participants in self-management

• Currently ~ 40,000 health-related mobile apps

(Am Assoc Med Colleges, 2012)

• However, real-world, clinical trial evidence is lacking…the following questions remain:– Do mHealth technologies actually engage

patients in the performance of self-management?

– Does performance of self-management behaviors improve health outcomes?

To answer these questions…

• Review the early design and testing of Pocket PATH® an mHealth intervention for self-management of chronic illness

• Report results from a recent full-scale RCT• Discuss future implications

Phase 1a: Prototype Design & Testing

UCD laboratory setting

Phase I b: Prototype Design & Testing

Field Setting

DeVito Dabbs, et al. (2009). Computers, Informatics, Nursing. 27(3): 175.

Pilot RCTPocket PATH v Standard Care

• N= 30, 2 month f/u period• Pocket PATH® more efficacious in

promoting early self-management behaviors and QOL

• Evidence for full scale trial

DeVito Dabbs, et al. (2009). Clinical Transplantation, 23:537.

Smartphones with custom

• data recording• graphing• decision-support

to assist LTRs to perform self-management behaviors

Pocket PATH®

Personal Assistant for Tracking Health

Pocket PATH ® Features

RCT to Evaluate Effect of Pocket PATHon Self-Management and Health Outcomes

Evaluate Patient EngagementData not shared with clinicians

Design: • Prospective, longitudinal, 2-group • Full Scale RCT • Pocket PATH® versus standard care

Methods

Analyses• Intent to treat• Assessments at 2, 6 and 12 months

– between group differences at baseline & at each time point

– modeled group effect controlling for time and unbalanced covariates

354 Assessed for Eligibility

102 Assigned to Usual Care

Group 102 Received Intervention as

Assigned 0 Did not

Receive Assigned Intervention

201 RandomizedFlow Diagram (N = 201)

Baseline Characteristics

Pocket PATH (n= 99) Std Care (n=102)

Socio-Demographics

Gender, % male 52.5% 57.8% Age, years, median (q1, q3) 62 (51,67) 62 (51,68) Marital status, % married 74.7% 68.6% Race, % white 92.9% 89.2% Education, % ≥ high school 92.9% 95.1% Employment, % yes 15.2% 7.8% Computer use, % yes 83.8% 79.4%

Clinical Characteristics    

Underlying disease, % Obstructive 54.5% 45.1% Procedure % Single 19.2% 17.6% ICU LOS, days median (q1, q3) 4 (3,11) 7 (3,14) Hospital LOS, days median (q1, q3) 24 (16,38) 33 (21,49)** Re-intubated, % yes 17.2% 29.4% * Discharge destination, % home 89.9% 83.3%* p< .05 ** p < .001 unbalanced covariates

FindingsSelf-Management Outcomes

Self-Monitoring

0-2 mos 2-6 mos 6-12 mos0%

20%

40%

60%

80%

100%

Pocket PATH (n=99)STD Care (n=102)

Followup Period

Pe

rce

nt

Da

ys

GEE: OR = 3.66 (95% CI 2.06-6.51, p<.001)

Adhering to Regimen

GEE: OR = 1.98 (95% CI 1.19—3.28, p<.01)

0-2 mos 2-6 mos 6-12 mos0%

20%

40%

60%

80%

100%

Pocket PATH (n=99)

STD Care (n=102)

Followup Period

Pe

rce

nta

ge

of

Hig

he

r A

dh

ere

rs

Detecting and Reporting Critical Condition Changes

0 20 40 60 80 1000

20

40

60

80

100

Pocket PATH

# Detected

# R

ep

ort

ed

0 20 40 60 80 1000

20

40

60

80

100

STD Care

# Detected

# R

ep

ort

ed

GEE for Detecting Critical Values: OR = 3.10 (95% CI 1.37-7.01, p<.01) GEE for Appropriate Reporting: OR = 9.54 (95% CI 3.85-23.62, p<.001)

FindingsHealth Outcomes

Percentage of Patients Re-Admitted to Hospital over 12 months

0-2 mos 2-6 mos 6-12 mos 0-12 mos0%

20%

40%

60%

80%

100%

Pocket PATH (n=99)STD Care (n=102)

Followup Period

Pe

rce

nt

Re

ho

sp

ita

lize

d

GEE: OR = .91 (95% CI .59 -1.4, p = .655)

Survival over 12 months

88.9% v. 92.2% at 12 monthsLog Rank (Mantel-Cox): Chi2 = .131 (p= .717)

Conclusions • Pocket PATH was used by patients with chronic

illness, following a complex regimen

• Self-Management behaviors

– Significantly better adhering, self-monitoring,

detecting and reporting in Pocket PATH group

at all time points

– Performance declined in both groups overtime

• Health Outcomes No significant between group

differences ****even with higher reporting of

critical condition changes

Pocket PATH RCT

Limitations• Single-center• Narrow range of

variation in selected health outcomes in year 1

Implications• Examine

mediators/moderators of effects

• Enhance intervention to reduce decline overtime

• Consider other tx populations and chronic illness

• Next step: Combine patient self-management with clinician support

Acknowledgements

Collaborators: Mary Amanda Dew, Brad Myers,

Mi-Kyung Song, Ruosha Li, Jill Aubrecht, Rachelle Zomak, Mohammad Alrawashdeh,

Joespeh Pilewski, Christian BermudezU of Pittsburgh, CMU, UNC-Chapel Hill, UPMC

Funding: NIH: R01 NR010711

Thank you and questions

WLSACONVERGENCE SUMMIT

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