Improving chronic care management post stroke management and education using the smartphone
This presentation is the property of its rightful owner.
Sponsored Links
1 / 16

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


  • 150 Views
  • Uploaded on
  • Presentation posted in: General

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.

Download Presentation

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

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Improving chronic care management post stroke management and education using the smartphone

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

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

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

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

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

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

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

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

Post Stroke Management Care Model

  • Education – Understand risk factors

  • Maintenance of function

    • – ADLs, IADLs, exercise

  • Medication Appropriateness

  • Medication Adherence

  • Monitoring


Post stroke management care model1

Post Stroke Management Care Model

Education – Understand risk factors

Maintenance of function – ADLs, IADLs, exercise

Medication Appropriateness

Medication Adherence

Monitoring


Experimental design

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

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

Gain in Stroke Knowledge

N=20


Compliance

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

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)


  • Login