Nursing students as agents of change: Empowering patients using mobile technology for health promotion. Presented by Sally Britnell, School of Health Care Practice, AUT University, at HINZ 2014, 11 November 2014, 12pm, Plenary Room 2

1. +
Sally Britnell
Lecturer
AUT University
Students as Agents of Change: Empowering
patients using mobile technology in health
promotion

2. +
Acknowledgements
 Project Leader
 Sally Britnell
 CFLAT Advisor
 Vickel Naryan
 Writing
 Sally Britnell
 Jo Conaglen
 Susan Johns
 Data Collection
 Glennis Best
 Sally Britnell
 Susan Johns
 Caroline McKinney
 Faith Reed
 Jaga Maya Shrestha-Ranjit
 Kay Shannon
 Annie Tatton
Funding for this project was provided by the Centre for Learning and Teaching
at AUT University in 2013

3. +
Common Cardiovascular Diseases
in New Zealand
Cerebrovascular
Disease
Damage to blood vessels
supplying the brain
Heart Attack
Coronary Heart Disease
Damage to blood vessels
supplying the heart
Stroke
Background

4. +
Cardiovascular Disease in
New Zealand
 Cardiovascular Disease
(CVD) is the leading
cause of death in NZ.
 30% of deaths are
related to CVD.
 Every 90 minutes a New
Zealander dies from
CVD relared illness.
Background
Annual risk of CVD related
death for those > 40 years of
2,074,900
622,470
age
No Risk Risk of Death from CVD

5. +
Cardiovascular disease is often
preventable
Risk
Factors
Lifestyle
Changes
Background
Requires Patient
Education

6. +
The Problem
 AUT University nursing students provide a health
assessments at workplaces in Auckland.
 Patients have variable health literacy.
 Tools and resources need to accommodate a wide
range of learning styles and needs.
 Education needs to be individualised to each patient.
Problem

7. +
Solution
 Allow facilitated exploration of individual patient
information “on the spot”.
Tablet with
Pocket Wi-
Fi
Heart
Health
Forecast
Tool
Individual,
Guided,
Interactive
Learning
 Multiple modalities:
 interactive
 graphical
 spoken
 written
Strategy

8. +
Methods
AUT University
Ethics Approval
(Part of a larger
study)
Theoretical and
practical training for
students and staff
Students coached
to use Heart Health
Forecast online tool
(New Zealand
Heart Foundation)
Students provided
health assessments
in workplaces
Data Analysis using
SPSS using
descriptive
statistics
Anonymous patient
and student survey
distributed and
returned
Methods

9. +
Health Assessment’s In Action
A written release was gained from those pictured in the below photos and
returned by the photographer to AUT University (Marketing). These photographs
have also been published in two suburban newspapers.
Victoria Lelo
Takes a sample of blood
Wes Namizono & Aleshia Sneap
Explanation of Cardiovascular
Risk with a patient
Patient
Education

10. +
Return Rates
 Surveys were distributed to all students and patients:
 504 patients
 130 students
 Surveys were returned by:
 125 patients (24.8%)
 61 Students (46.9%)
 Students completed an online survey.
 Patients could complete this online or via prepaid post.
Results

11. +
Demographics (Patients)
Age
< 20 years 2 1.6%
21 - 30 years 21 16.8%
31 - 40 years 44 35.2%
41 - 50 years 27 21.6%
51 - 60 years 20 16.0%
> 60 years 4 3.2%
Not specified 7 5.6%
Ethnicity
NZ Eurpean 59 47.2%
Asian / Indian 24 19.2%
Pacific 20 16.0%
Maori 16 12.8%
MEELA 2 1.6%
Other European 4 3.2%
Gender
Female 78 62.4%
Male 46 36.8%
not valid 1 0.8%
Results

12. +
Demographics (Students)
Age
< 20 years 30 49.2%
21 - 30 years 23 37.7%
31 - 40 years 3 4.9%
41 - 50 years 4 6.6%
51 - 60 years 0 0.0%
> 60 years 0 0.0%
Not Specified 1 1.6%
Ethnicity
NZ Eurpean 29 47.5%
Asian / Indian 18 29.5%
Pacific 8 13.1%
Maori 3 4.9%
MEELA 1 1.6%
Other European 2 3.3%
Gender
Female 57 93.4%
Male 4 6.6%
not valid 0 0.0%
Results

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Usefulness of the Heart Health
Forecast Tool to students
 40 students
(66.6%)
indicated.
 mean (SD) score
of 7.9 (1.8)
12
10
8
6
4
2
0
Usefulness mobile access to the Heart
Health Forecast Tool (Students)
1 2 3 4 5 6 7 8 9 10
n
1 = not useful - 10 = very useful
Results

14. +
Usefulness of the Heart Health
Forecast Tool for patients
 50 patients
(40.0%)
 mean (SD) score
of 8.5 (1.6)
30
25
20
15
10
5
0
Usefulness mobile access to the Heart
Health Forecast Tool (Patients)
1 2 3 4 5 6 7 8 9 10
n
1 = not useful - 10 = very useful
Results

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Patient Knowledge
 Self rated knowledge
of own health (0 to 10
or no knowledge to
very knowledgeable)
 Mean difference score
(paired t-test) of 1.8
(SD 1.9, 95% CI 1.5 -
2.1, P < 0.0001)
30
25
20
15
10
5
0
Patient Knowledge
-3 -2 -1 0 1 2 3 4 5 6 7 8
n
Knowledge After - Knowledge Before
Results

16. +
Student use of resources to educate
patients
Results
Resources Used Most Useful
Heart Health Forecast Online Tool 33 54.1% 20 33.3%
Blood Pressure Chart 31 50.8% 8 13.3%
BMI Chart or Wheel 27 44.3% 4 6.7%
Peak Flow Chart 24 39.3% 3 5.0%
Blood Test Results 20 32.8% 11 18.3%
Patient Information Pamphlets 13 21.3% 15 25.0%
Cardiovascular Risk Chart 11 18.0% 5 8.3%
Other 13 21.3% 10 16.7%

17. +
Readiness to learn
Many patients want to learn about their
health
Top two reasons why patients chose to have
a health assessment:
 lipid and blood sugar testing (36.8%),
general interest / check up (24.0%).
Discussion

18. +
Mobile technology can improve
patient outcomes
Literature suggests mobile technology
leads to increased knowledge
Discussion
Increased
Knowledge
Ability to
Change
Improved Health
Outcomes

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Patients as active recipients of
health information
Online
Information
Patient
Knowledge
Clinician
Knowledge
Validated
Information
Patient
Treatment
Patient
Knowledge
Discussion
Traditional
Healthcare
Recent
Healthcare

20. +
Risk of information that is not
validated
 A plethora of online health information is available.
 Literature recognises risk of un-validated information.
Discussion
http://www.topnews.in/health/online-self-diagnosis-poses-health-risk-210075
Do patients have the
expertise to interpret
available health
information alone?
How does this affect health
outcomes?

21. +
Engagement versus Distraction
 Explanation of
technology can reduce
distraction
Discussion
 Studies have shown an
increase patient
engagement when using
mobile technology to
learn
Clinician
Technology
Patient
Distraction

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Point of Difference
This study used health care professional
facilitated online learning with patients
 Current literature predominantly self directed
online patient education.
 Research sparse for health care professional
facilitated online patient education using mobile
technology.
Discussion

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Internet Connectivity
Students reported what stopped them using
the Heart Health Forecast tool online (top
three):
 “Wi-Fi” connectivity (26.2%)
 “not working” (9.8%)
 “website down” (1.6%)
 Analysis of exact connectivity problem limited
due to survey design
Discussion

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Conclusion
 Students and patients found mobile technology and
online tools useful in patient education for
cardiovascular risk.
 Patient knowledge of their health increased after
facilitated education using mobile technology to
display the HHF from the New Zealand Heart
Foundation.
Conclusion

25. +
Future Research
 Staff interaction with technology in patient education
 Engagement in lifestyle change and patient
outcomes after online education intervention
 Communication styles when working with technology
to educate patients
Anecdotal observations
 Students communication became more facilitative
between patient and student using this tool.

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Questions Thank You
Contact: Sally Britnell - sally.britnell@aut.ac.nz
Questions
 Please note that a scientific report accompanies this
presentation