improving hiv medication adherence using mobile health technology
TRANSCRIPT
IMPROVING HIV MEDICATION ADHERENCE USING MOBILE HEALTH TECHNOLOGY
Fiona Smythe I mscripts Eric Sredzinski, Pharm.D, AAHIVP I Avella Specialty Pharmacy
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PERCENT OF RETAIL PRESCRIPTIONS ABANDONED, REJECTED AND REASONS FOR REJECTIONS, 2013
DISTRIBUTION OF PAYER REJECTION REASONS IN SELECTED CLASSES
Almost 10% of the 3.6 billion retail prescriptions written by physicians are NOT dispensed to patients
Prescription Abandonment and Payer Rejections
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• Patient Characteristics • Health beliefs • Quality of life/Health status • Understanding of disease/Therapy • Psychological state • Social support • SES status • Forgetfulness and lifestyle factors
• Disease characteristics
PREDISPOSING FACTORS
• Complexity of regimen • Food interaction
• Side Effects of regimen • Schedule of regimen • Cost of drug • Cost of side-effects of treatment • Cost of follow-up care
TREATMENT FACTORS
POSSIBLE INTERVENTIONS POSSIBLE INTERVENTIONS
Fig 1. Schematic of factors and barriers involved in adherence to targeted OAMs and possible ways to improve adherence.
ADHERENCE
& PERSISTENCE
• Identify degree of adherence • Use assessment tools • Ask about barriers • Keep an open non-confrontational dialogue
• Increase patient education at every visit • Provide literature on side effects • Refer to support groups, websites, and disease specific organizations
• Involve physicians, nurses, pharmacists and family members
• Multi-disciplinary approach • The patient has a “team”
• Address Costs • Use available assistance programs • Help patients apply for necessary benefits
• Make sure refills are ordered in time • Consider initiating nurse-led phone calls to
assess adherence, side-effects and any barriers • Encourage tools to help with adherence
• Pill boxes, alarms, calendars, daily routines
SYSTEM FACTORS • Interaction with M.D. • Interaction with nurse • Ease of drugs • Satisfaction with care
Barriers to Adherence
4 Cochrane Review, Oct, 2005; Transplantation (2007;83:858-873) Blood (2007;109:58-60)
Disease Rates of non-adherence
Epilepsy 30% to 50%
Arthritis 50% to 71%
Hypertension 40% (average)
Diabetes 40% to 50%
Oral Contraceptives 8%
HRT 57%
Asthma 20%
Kidney Transplant 35.6%
Heart Transplant 14.5%
Liver Transplant 6.7%
CML (Imatinib) 25%
COMPLIANCE DECLINES WITH TIME
Benchmark Adherence Rates
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Study population size Rates of adherence
N=17,573 patients from 33 studies 55% adherent
N=540 patients from 1 cohort 32.78% adherent
N=3,140 patients from 22 US studies 53% Adherence defined as- 85-100% MPR or viral suppression of <50 - <500 copies/ml
N=862 ART naïve patients 36% discontinued therapy
ARV Adherence
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Adapted from Maggiolo et al. Clin Infect Dis. 2005;40:158-63. NNRTI = nonnucleoside reverse transcriptase inhibitor; PI = protease inhibitor.
Relation Between Adherence and Treatment Failure
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$1.8 Billion HIV
$105.4 BILLION TOTAL
AVOIDABLE COSTS BY DISEASE
IMS Institute for Healthcare Informatics, 2013
$44 Billion Hypercholesterolemia
$24.6 Billion Diabetes
$18.6 Billion Hypertension
$15.5 Billion Osteoporosis
$1 Billion Congestive heart failure
HIV Cost of Non-Adherence
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Living with HIV: Patient Story
9 http://www.ncbi.nlm.nih.gov/pubmed/19866536 http://www.ncbi.nlm.nih.gov/pubmed/16846321
BEHAVIOR AGE PRACTICES
Common Causes of Non-Adherence in HIV Populations
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Source: http://pando.com/2014/03/17/validic-wants-to-send-your-health-data-straight-to-hospital/ http://www.informationweek.com/mobile/mobile-health-market-to-reach-$26b-by-2017/d/d-id/1110964? http://www.pmlive.com/pharma_news/digital_health_charge_led_by_millennials_in_the_us_669123 The Accenture Connected Health Pulse Survey, 2012 & Mobile Health Market Report 2011–2016
4.3 million mobile health application downloads daily
$26 billion predicted 2017 worldwide mHealth market revenue for associated services and hardware
66% of people would use a mobile app to manage a heart condition
72% of patients want to refill prescriptions on their phone
Patients Want mHealth
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Overview of the Tool
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Timely two-way messaging
Create an experience that is intuitive, easy to use and adds value for patients
Real-time notifications provide behavioral “nudges”
Build on existing habits • Reinforce good behavior • Small, incremental modifications
Customized messaging based on behavior
Stringent privacy practices • Double-opt in text registration • Data masking
Employing Best Practices
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Pharmacy Management
System
Patient Portal
Mobile Pharmacy App
360 visibility into patient data
Integrations between the dispensing system, patient portals and mobile pharmacy apps
Real-time data provides insight into behavior
Understand risk and design interventions with predictive analytics
mHealth Strategies in Specialty Pharmacy
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To open: hold down tab & turn
Get o
ur mobile app:
avella.com/appE-mails
avella.com on mobile
Pill bottles
Fax
In-store display
Rollout Strategy: Marketing Touch Points
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PRIMARY OBJECTIVES
• Proving efficacy of mobile to increase adherence • Decreasing operational burden • Validating systems integration
BARRIERS • High consumer expectations set by retail apps • HIPAA/HITECH, TCPA • Strong feelings of “What’s in it for me” require intensive patient education • Getting app onto patient’s phone & getting them to use it
ASSUMPTIONS • Multi-faceted program using mobile health • Impact of mobile-optimized adherence tools • Replicable for other hard-to-manage populations
A Clinical Study Tests These Assumptions
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• On- and off-platform cohorts
• Brand name ARVs of interest
• Retrospective cohort PDC and survival analysis
Atripla, Complera, Intelence, Isentress, Kaletra, Norvir, Reyataz, Stribild, Trizivir, Truvada
On-platform = 224 (10.6%) Off-platform/control = 1,896 (89.4%)
• Study period of 12 months
• Possible self-selection bias
Methodology
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Female 14%
Male 85%
Non-defined
Female 20%
Male 80%
ON-PLATFORM OFF-PLATFORM
GENDER
Female 14%
Male 85%
Did not self-identify/identify
as male or female 1%
Female 20%
Male 80%
Demographics
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ON-PLATFORM OFF-PLATFORM
AGE Demographics
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< 1 year (97%)
>1 year (3%)
TIME SINCE PLATFORM REGISTRATION
Turned on 221 (99%)
Turned off 3 (1%)
REFILL REMINDER PREFERENCE
Measurements of Success: Platform Engagement
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Zero 0 (0%)
One 11 (5%)
Two 173 (78%)
Three 37 (17%)
NUMBER OF ACTIVE NOTIFICATION METHODS
None 0%
In-app notification
47%
Text Message
43%
Email 10%
NOTIFICATION METHOD PREFERENCE
Measurements of Success: Platform Engagement
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0.85 0.86 0.87 0.88 0.89
0.9 0.91 0.92 0.93
Off Platform On Platform
PDC
Off Platform On Platform
N=1,896
N=224
Measurements of Success: Improved Patient Adherence
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0
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0.8
0.9
1
0 10 20 30 68 85 97 111 123 134 151 163 173
Pro
porti
on o
f Pat
ient
s on
The
rapy
Days to Discontinuation
PATIENT DISCONTINUATION BY PLATFORM USAGE
Off-Platform
On-Platform
Patients on-platform were 2.9 times more likely to remain on therapy
Measurements of Success: Patient Discontinuation
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Patients with PDC => 90%
Measurements of Success: High Viral Suppression Loads
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OPPORTUNITIES TO OPTIMIZE ADHERENCE TOOLS THROUGH MOBILE HEALTH • Peer support forums • Feedback through surveys • Adverse event reporting • Financial assistance based on perceived need • Secure messaging, chat, or video • Delivery of educational material • Clinical trials – Researchkit • Interfacing with EMR or patient portals • Patient ownership and control of data • Predictive analytics and interventions
Source: Fierce Mobile Healthcare
APPS WILL BECOME MORE DISEASE SPECIFIC • Deliver relevant information
based on condition and behavior
Continuous Improvement: The Road Ahead for Mobile Adherence
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Eric Sredzinski, Pharm.D. AAHIVP - EVP, Clinical Affairs & Quality Assurance Pharmacy Program Director, ADAP
Fiona Smythe Vice President, Strategy
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