DEFINING THE EVIDENCE
FOR PERSONAL
CONNECTED HEALTH
AND RESEARCH GAPSJohn Sharp, MSSA
Personal Connected Health Alliance
And Kent State University
Personal Connected Health
• Patient-facing devices and technology, promising to
support patients in their proactive, self-management
efforts
• Enabled by apps and devices, pervasive mobile networks
and innovation
Outline
• Literature Review
• Topical review of the evidence
• Intervention types
• Research issues
• Solutions
Table 1: Criteria for article selectionSelection Exclusion
Peer-reviewed journal
Published after 01/01/2013
Measurement health outcomes
as part of the study
Published in peer-reviewed
journal
Editorials or policy statements
Validation or usability of a new
technology
Technology designed to enhance
communication or performance for
health care providers (no patient
involvement)
Cost analysis with no health
outcomes
Process evaluation
Review or meta-analysis
Design and testing of new
technology
Study protocols (no results)
Sample size less than 100
individuals
Summary of systematic review results
Functional Theme Description Number of studies
Remote Patient Monitoring
Quantitative data collection on patient health indicators such as blood pressure, weight, or blood sugar
9
Behavior change/self-care
Interventions intended to encourage behavior change and motivation to make healthy choices
34 studies (35 publications)
Remote counseling and mental health
Interventions providing advice, guidance or qualitative monitoring by health professionals through technology in the patient’s home (telemedicine, video conferencing)
10 studies (12 publications)
Total 53 studies (56 publications)
Summary of Remote Patient
Monitoring publications
First Author
Pub
Year Title Location Population
Outcome
measurements Sample Size
Agboola,S.1 2015
Heart failure remote monitoring: evidence from the retrospective
evaluation of a real-world remote monitoring program North America
Patients with heart
failure
Mortality and
hospitalizations 348
Akar,J. G.2 2015
Use of Remote Monitoring Is Associated With Lower Risk of
Adverse Outcomes Among Patients With Implanted Cardiac
Defibrillators North America
Patients w
implantable cardio-
defibrillators
All-cause mortality
and re-
hospitalization 37742
Albini,F.3 2016
An ICT and mobile health integrated approach to optimize
patients' education on hypertension and its management by
physicians: The Patients Optimal Strategy of Treatment(POST) pilot
study Europe
Hypertensive patients
w high blood
pressure, av age 57
Blood pressure
values 690
Ishani,A.4 2016
Telehealth by an Interprofessional Team in Patients With CKD: A
Randomized Controlled Trial North America
Patients with chronic
kidney disease
Mortality and
hospitalizations 601
Kim,Y. N. 5 2015
RCT to assess the effectiveness of remote patient monitoring and
physician care in reducing office blood pressure Asia
Patients with
hypertension
Blood pressure
values 374
Moffet,H. 6 2015
In-Home Telerehabilitation Compared with Face-to-Face
Rehabilitation After Total Knee Arthroplasty: A Noninferiority
Randomized Controlled Trial North America
Patients recovering
from total knee
arthroplasty Osteoarthritis score 205
Ong,M.K. 7 2016
Effectiveness of Remote Patient Monitoring After Discharge of
Hospitalized Patients With Heart Failure: The Better Effectiveness
After Transition -- Heart Failure (BEAT-HF) Randomized Clinical
Trial North America
Patients over 50
recovering from heart
failure
Re-hospitalization
rates 1437
Shea,S. 8 2013
Social impact analysis of the effects of a telemedicine intervention
to improve diabetes outcomes in an ethnically diverse, medically
underserved population North America
Adults over 55 with
diabetes
Glycated hemoglobin
levels 1665
Upatising,B. 9 2013
Effects of home telemonitoring on transitions between frailty
states and death for older adults: a randomized controlled trial North America
Adults over 60 with
high risk of
hospitalization Frailty score 205
Topical review of the evidence
• Wellness
• Prevention programs/coaching
• Chronic conditions
• Mental health
Wellness
• Fitness trackers – steps, distance, heart rate
• employee wellness program can increase the number of steps and
time spent walking,6 but demonstrating prevention of disease and
reduction of healthcare costs is more of a challenge.
• Diet
• modest evidence that app-based interventions to improve diet,
physical activity and sedentary [behaviors] can be effective. Multi-
component interventions appear to be more effective.
Wellness
• Sleep tracking
• some validation studies of sleep trackers. These point to strengths
and limitations in sleep estimates produced by personal health
monitoring devices, requiring further study.
Secondary Prevention
• Digital Diabetes Prevention Programs
• significant weight loss, improved glucose control and lower total
cholesterol at 12 months
• return on investment for digital behavioral counseling for
prediabetes and cardiovascular disease to be break even at three
years
Remote Cardiac Monitoring
• Mobile ECG
• After cardiac surgery - a non-invasive, inexpensive, convenient and
feasible way to monitor for AF recurrence in post-cardiac surgery
patients
• Hypertension monitoring
• demonstrated a significant reduction both in the overall costs and in
the number of days of hospitalization over two years
Pain Control
Transcutaneous electrical nerve stimulation device was
shown effective in reducing low back pain resulting in
reduced pain interference with walking ability and sleep,
and greater pain relief
Behavioral Health
• One of the studies reviewed indicated that self-monitoring
of mood can boost overall emotional self-awareness
• Substance abuse
• systematic review found that the majority of studies provided
support for the efficacy of mHealth in reducing substance use.
• The main analysis found that smartphone interventions
had a moderate positive effect on depressive symptoms,
with no indication of publication bias affecting these
findings. However, our subgroup analyses found that the
effects of smartphone interventions were substantially
larger when compared to inactive (g=0.56) than active
(g=0.22) control conditions.
• http://onlinelibrary.wiley.com/doi/10.1002/wps.20472/full
Research Issues
• Unique challenges
• Resistance from providers
• Speed of technological change
• Regulatory challenges
• Possible solutions
• There was little evidence of differences in health care costs or
utilization as a result of the intervention.
• we found evidence that the control and intervention groups
were equivalent with respect to most health care utilization
outcomes.
• This result suggests there are not large short-term increases or
decreases in health care costs or utilization associated with
monitoring chronic health conditions using mobile health or
digital medicine technologies.
• Among secondary outcomes there was some evidence of
improvement in health self-management which was
characterized by a decrease in the propensity to view health
status as due to chance factors in the intervention group
Research Issues
Asthma Mobile Health Study – lack of rigor
The platform enabled prospective collection of longitudinal,
multidimensional data, but was limited by
• selection bias,
• low retention rates,
• reporting bias, and
• data security.
Designing randomized control trials in
Connected Health• What is the mechanism of effect in personal connected
health — does monitoring itself produce change or only
monitoring plus incentives plus coaching?
• What can we learn from psychology and behavioral
economics?
• Does behavior change require ‘patient activation’ or a
motivation to change?
• Can results be generalized from one app or device to
another?
http://jamanetwork.com/journals/jama/fullarticle/2553448
Conclusions and Relevance Among young adults with a BMI between
25 and less than 40, the addition of a wearable technology device to a
standard behavioral intervention resulted in less weight loss over 24 months.
Devices that monitor and provide feedback on physical activity
may not offer an advantage over standard behavioral weight loss approaches.
Negative or Inconclusive ResultsClinical trials can contribute knowledge about both efficacy
and mechanisms of action.
• Efficacy concerns whether the intervention is “better” than
a control, such as standard of care; mechanisms concern
how the intervention produces desired outcomes — its
hypothesized causal pathways.
• For pharmacotherapies, after years of bench research, a
new drug’s action pathways are typically understood well
enough that a clinical trial can both test efficacy and
generate evidence about causal mechanisms
Device Issues
• By the time the results are published, the device is
outdated and no longer available
• Device accuracy needs to be validated and the subjects
should be questioned about whether they are using other
consumer-grade personal connected health technology
• Signal vs noise – e.g., home cardiac monitoring
Research Challenges
• Lifestyle intervention studies are difficult to blind and avoid
bias
• Defining a hypothesis that includes the causal pathway
(such as active self-monitoring versus passive). The
causal relationship related to technology use also has the
potential to be confounded by the use of reminders and
rewards as part of the study design.
Solutions
Study categories
1) investigating how technologies can replace, enhance or
supplement traditional healthcare provider-patient
interactions
2) investigating how technologies can create new
opportunities for users to act independently in making
healthy lifestyle choices
Solutions
• Studies that strive to understand the underlying
psychology of motivation and behavior change in lifestyle
choices will remain relevant
• Society of Behavioral Medicine
– Digital Health Council
Developing and Evaluating Digital
Interventions to Promote Behavior
Change in Health and Healthcare
• JMIR 2017 article addressed:
• Pace and efficiency
• Engagement
• Theory
• Evaluation of effectiveness
• Evaluation of Cost effectiveness
• Regulation, ethics and information governance
Recommendations
• Increase the size of studies in personal
connected health to enhance the body of
meaningful evidence, working
collaboratively if necessary.
• Develop and disseminate consensus-based
guidelines for research methodology in
personal connected health, working with
experts from across the field.
Recommendations (continued)
• As part of developing consensus-based
guidelines for research methodology, consider
ways to accelerate research without
compromising the quality of results.
• Endeavor to validate apps and devices in
comparative studies.
• Fund studies exploring new ways for individuals
to act independently to improve their health using
personal connected health technologies.
Network of Digital Evidence
www.nodehealth.org
• Combine the rigor of Evidence Based Medicine (EBM)
with emerging healthcare technologies to help create
evidence-based digital medicine.
• Sharing Info on Digital Medicine Pilots
• Standardizing practices for adoption
• Supporting multi-site trials and collaborations
New Terminology
• Digital Therapeutics
• medication augmentation
e.g., medication adherence app, smart pillbox
• medication replacement
e.g., virtual coaching, diabetes prevention programs
• https://www.technologyreview.com/s/604053/can-digital-
therapeutics-be-as-good-as-drugs/
• Using digital tools in research, e.g., continuous monitoring or
symptom checkers, QOL surveys
Digital Biomarkers
• Objective, quantifiable measures of biology or health
collected and measured through digital devices
• Digital Biomarkers Journal
https://www.karger.com/Journal/Home/271954
• Section for the Network of Digital Evidence
Coauthors
• Sarah Cunard Chaney, MPH, MSc, Research Analyst,
Personal Connected Health Alliance
• Janna Guinen, Senior Program Advisor, Personal
Connected Health Alliance
• Patricia Mechael, PhD, MHS, Executive Vice President,
Personal Connected Health Alliance
• Download white paper:
http://www.pchalliance.org/resources