Improving HIV Medication Adherence Using Mobile Health Technology

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

Print

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

0.1

0.2

0.3

0.4

0.5

0.6

0.7

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

[email protected]

Fiona Smythe Vice President, Strategy

[email protected]

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