Improving chronic care management post stroke management and education using the smartphone
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Improving Chronic Care Management: Post-stroke Management and Education Using the Smartphone. Presented by: Anthony Sterns, PhD Kent State University Co-authors: Greta Lax, Harvey L. Sterns, PhD The University of Akron Kyle Allen, DO, Sue Hazelett, RN, MS Summa Health System.

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Improving Chronic Care Management: Post-stroke Management and Education Using the Smartphone

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Improving Chronic Care Management: Post-stroke Management and Education Using the Smartphone

Presented by: Anthony Sterns, PhDKent State University

Co-authors:

Greta Lax, Harvey L. Sterns, PhD

The University of Akron

Kyle Allen, DO, Sue Hazelett, RN, MS

Summa Health System


Overview of the Technology

  • A complete SmartPhone-based data gathering system for

    • medication

    • physical

    • behavioral

    • and attitudinal data collection

  • The system consists of:

    • Web-based management

    • iPhone application

    • Pillbox Case

  • The system provides:

    • Surveying

    • Reminders

    • Activities

    • Tracking

    • Integration with EMR

    • Output for Analysis


Overview

  • Environmental Press Model

    • User Centered Design

    • Theory of Empowerment

  • Application for Post-stroke

  • How we apply to stroke prevention program

    • Medication Adherence

    • Health Education

    • Monitoring

  • Design

  • Results

  • Questions


User-centered design

  • Needs

  • Capabilities

  • Limitations

  • Environmental Press

    • (Lawton, 1991)

Person

Performance

Place

Mayhorn, C., & Sterns, A. (2006). Perfecting the Handheld Computer for Older Adults: From Cognitive Theory to Practical Application. Cognitive Technology, 12(1), 15-21.


Bandura’s Theory of Empowerment

Fear Does Not

Change Behavior

Efficacy Does

or Belief in Ability to Control Behavior

Lead to

Behavior Change

Behavior Change


Medication Adherence

  • Poor adherence

    • Behavioral disease (Johnson and Bootman, 1995)

    • Correct adherence 26-59% (Malhotra et al., 2001)

    • 76% of patients errors in 3 months (Bedell et al., 2000)

    • ~50% of ER visits for 60+ year olds is non-adherence for CV meds (Chia, Schlenk, and Dunbar-Jacob, 2006)

  • Causes

    • 71% due to forgetfullness (Kidder, Park, Hertzog, and Morrell, 1997)

    • 33% fail to follow directions correctly

    • Scheduled appointments missed 20-50% (DiMetteo et al., 1993).

Sterns, A. A. & Mayhorn, C. B. (2006). Persuasive pillboxes: Improving medication adherence with personal digital assistants. Y. de Kort and W. I. Jsselsteijn (Eds.), Persuasive Technologies, LNCS v. 3962, New York, NY: Springer Publishing


Cognitive Prosthesis

  • Prospective memory support

  • Knowledge activation

  • Our previous research provides evidence of:

    • Improving medication adherence

    • Link between specialists

    • Feedback to better direct medication regimens.

(Sterns, 2005; Sterns and Mayhorn, 2006)


Why Stroke Recovery and Prevention

  • Primarily affects older adults

  • Stroke is challenging and expensive to treat

  • Is the leading cause of disability

  • Third leading cause of death in the U.S.

    (American Heart Assoc. [AMA], 2007; 2006)


Post Stroke Management Care Model

  • Education – Understand risk factors

  • Maintenance of function

    • – ADLs, IADLs, exercise

  • Medication Appropriateness

  • Medication Adherence

  • Monitoring


Post Stroke Management Care Model

Education – Understand risk factors

Maintenance of function – ADLs, IADLs, exercise

Medication Appropriateness

Medication Adherence

Monitoring


Experimental Design

Post-test

Use-Test

Stroke Knowledge

ADL/IADLs

(@2-months)

N=10

RandomAssignment

Recruiting on

Stroke Unit

Pre-test

Use-Test

Stroke Knowledge

Med Reconciliation

ADL/IADLs

N=10


In Hospital Use Test

  • Talked through 18 Steps

  • Use all interface elements

    • Home button

    • Slide

    • Icon

    • +

    • Numbers

    • Screen slip

    • Cylinders

    • Letters

Ranked:

3 – first try

2 – 2nd try

1 – with demo

0 – unable to do

Sterns, A. A., Lax, G, Sterns, H., Allen, K, Hazelet, S., and Fosnight, S. (Nov., 2009). Improving Chronic Care Management: An iPhone Application for Post-Stroke Recovery. Part of a symposium on Technology presented at the 62nd annual meeting of the Gerontological Society of America, Atlanta, GA.


Gain in Stroke Knowledge

N=20


Compliance

  • Education

    • 88% Compliance with 1-month curriculum

    • 94% Compliance if exclude outlier (100% nc)

    • 89% correct on education quizzes

  • Surveys

    • Mood (2x daily) – 61%, 72% excluding 2 outliers

    • Exercise (daily) – 54%, 63% excluding outlier

    • ADL/IADL (weekly) – 57%, 61% without outlier

  • Medication

    • 70% compliance with confirmation to alerts

    • 83% compliance if exclude outlier (100% nc)


What’s Next

  • Multi-model Data

    • Behavioral

      • Motion (Exercise: Nike+)

      • Taking Medication (iRx Reminder)

    • Attitudinal

      • Mood Assessment (Anger, Depression, Happiness

      • Wellness (Stiffness, Pain)

    • Cognitive

      • Reaction Time Tests

      • Fluid Tests

    • Physical (Heart Rate, Skin Temperature)

    • Environmental (Location, Ambient Light, Temperature)


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