Telemonitoring and Sleep Apnea: 

Effect on CPAP Adherence

Carl J. Stepnowsky, Jr., Ph.D.

Health Services Research & Development Unit, Veterans Affairs San 

Diego Healthcare System &

Department of Medicine, UCSD

cstepnowsky@ucsd.edu

VIReC Cyberseminar, May 15, 2012
Overview

• Background on sleep apnea and CPAP therapy

• Overview of telehealth studies in sleep apnea

• Presentation of two CPAP telemonitoring 

studies
Introduction to OSA

• OSA = Obstructive Sleep Apnea

– Repetitive cessations of breath during sleep

– Comprised of apneas and hypopneas

– AHI = apneas + hypopneas/hour of sleep

• OSA is associated with serious cardiovascular and 

psychosocial co-morbidities, and with increased rates 

of mortality

• >80% of all Sleep Clinic diagnoses are OSA

• OSA is a prevalent chronic disease

– 2-4% middle aged adults; ~30-40% older adults
Introduction to CPAP Therapy

• CPAP = continuous 

positive airway pressure 

therapy 

• Comprised of flow 

generator, hose, and 

mask

• Prescribed for use 

whenever asleep

• Gold-standard therapy

• Fixed, bi-level, autoadjusting
Background

• Obstructive sleep apnea historically has been 

underdiagnosed

• Large emphasis on diagnosis

– Many factors (increased awareness, increased capacity) 

resulting in increased numbers of OSA patients

• Evolving emphasis on treatment initialization & follow-up

• Medicare 90-day rule has had large recent influence

Stepnowsky & Moore, 2004; Flemons et al, 2004
CPAP Adherence Rates

• Continuous positive airway pressure (CPAP) therapy adherence 

rates generally considered suboptimal

– 75-80% of OSA patients give CPAP a try

– ~50% continue to use at one year

– Of those that continue to use, mean use=3-4hrs/nt

• CPAP prescribed for use all night, every night, including naps

• Majority of patients are engaging in partial use patterns
CPAP Adherence Patterns

• Consistent and inconsistent users can be distinguished 

within the first week (Weaver et al, 1997; Aloia et al 2007)

• Adherence in week 1 associated with:

– adherence at 6 months (Aloia et al 2007)

• Adherence at 1 mo is associated with:

– adherence at 3 months (Kribbs et al, 1993)

– adherence at 6 months (Reeves-Hoche et al, 1994)

• Adherence at 3 mo is associated with:

– adherence at 22 months(McArdle et al, 1999)
CPAP Adherence – First 2 Weeks

Figure 2: CPAP adherence over first 14 days

Data from 

Usual Care 

group from 

recent study

Drop of >50% 

in first 2 

weeks of use

CPAP Use Pattern- Summary

• Adherence use patterns seem to be established early 

in the treatment initialization process

• Use patterns are variable; they tell a story

• This variability is important to monitor over time 

because it can help inform when to intervene when 

tracked prospectively

• Technologically, we can do this

• Key issue: current system is not well set up to take 

advantage of it
Interventional Studies

• Educational 

– Provision of pamphlets, group education

• Clinical Support

– Provision of additional telephone/clinic visits with focus on therapeutic 

changes/advice

• Behavioral Change

– Motivational Enhancement, Cognitive-Behavioral Therapy, Self-Management, etc.

• Health information technology

– Telemedicine, Telephone-linked care
Health Buddy Study

• Home telehealth device

• Intervention consisted of 

branching questions

– Symptom management

– Health behavior

– Knowledge

• No difference in adherence

– 4.2 vs. 4.3 hrs/nt

Health Buddy Appliance, Health 

Hero Network, Palo Alto, CA

Taylor et al, 2006
Video Teleconferencing (VTC) 

Study

• Sample: non-adherent patients 

over prior 3 mos

• Randomized to VTC or control 

(vitamin placebo)

• VTC group had higher 

adherence (90% vs. 44%; 

p=0.03)

• >4hrs/nt on >9 out of 14 nights

Video phone, 8x8, Inc, Santa 

Clara, CA

Smith et al, 2006
Interactive Voice Response: TLCCPAP Study

• Full-Scale Study

– Incorporation of motivational enhancement

– RCT of Telephone-linked Care (TLC)-CPAP vs. attention control

• n=100+ per group

– Weekly phone calls in 1 mo; monthly thereafter

– 12 mo study, with assessment at 6 mos

– 2.4 vs. 1.5 hrs/nt at 6 mos

• Of concern: magnitude of use

Sparrow et al, 2010
Our Work
CPAP Telemonitoring System

+ =

Resmed

AutoSet Spirit

ResTraxx

wireless module

AutoSet + 

ResTraxx

Data transmitted via pager/cell network next 

day in “store & forward” manner
CPAP Telemonitoring Using ResTraxx Data 

Center (RDC): 

• Demographics – background data

• Prescription – allows for setting of thresholds

• Monitoring – calendar format reporting of data

• Compliance

• Only provider access (i.e., no patient access)
ResTraxx Data Center - Prescription
ResTraxx Data Center Calendar
Provider 

Treatment 

Algorithm:

Green/green 

pathway

I.

Set-up

Go to 

Step III

- Daily use meets or exceeds 

daily threshold

- Mask leak and AHI within 

normal limits

Monitor usage / 

efficacy data daily

- Confirm wireless 

module attached and 

powered on

-Begin monitoring

- Set-up new pt in ResTraxx

- Enter thresholds for minimal 

daily use, AHI and mask leak

- CPAP instruction

- Educate patient

Stage

- Use, leak and AHI within 

normal limits

- Continue monitoring weekly 

adherence and efficacy data

Monitor usage / 

efficacy data weekly

- Use, leak and AHI within 

normal limits

- Continue monitoring weekly 

adherence and efficacy data

Red / 

Yellow 

Pathway

Monitor usage / 

efficacy data every 

other day

II.

Week 1

III.

Week 2

IV.

Weeks 3,4

Go to 

Step IV

V.

Months 

2 & 3

Red / Yellow 

Pathway

Red / 

Yellow 

Pathway

Monitor usage / 

efficacy data weekly 

for remainder of study - Use, leak and AHI within 

normal limits

- Continue monitoring weekly 

adherence and efficacy data

Red / 

Yellow 

Pathway

Go to 

Step V
Provider 

Treatment 

Algorithm:

Red/yellow 

pathway

Low 

Adherence

CPAP Red-Yellow Pathway

Consider:

- Side effects

- Claustrophobia

- Difficulty breathing

Assess Problem

High Leak High AHI 

Assess Problem

See 

Intervention 

Matrix

Consider:

-Mask

-Nasal/Oral

-Pressure

Consider:

- Pressure too low

- APAP trial

Increase 

Pressure

Assess Problem

See 

Intervention 

Matrix

Continue Monitoring
Study 1 – CPAP Telemonitoring

• Examined effect of CPAP telemonitoring on 

improving CPAP adherence

– Provider had access to CPAP adherence and efficacy 

data

– Could act proactively

– No specific intervention on the patient-side (i.e., 

clinical support study)

Stepnowsky et al, 2007
Methods

• Randomized trial comparing two groups:

– Usual clinical care (UCC)

– Enhanced clinical care (ECC)

• 20 patients per group

• ECC receive tailored feedback from clinical 

staff based on wireless data collection

• Participants were followed for 2 months
CPAP Data Measurement

• Objective measurement of both adherence 

and efficacy data

– Adherence – amount of time treatment was worn 

at the prescribed pressure

– Efficacy

• AHI – CPAP unit is able to measure the AHI while the 

device is worn

• Leak – measure of the amount of air leak; to the extent 

that leak is high, treatment less efficacious
UCC vs. 

ECC

OSA Diagnosis

CPAP Prescription Ordered

CPAP Set-up

Clinical Process Enhanced Clinical Care (ECC) Usual Clinical Care (UCC)

Follow-up #1 1 week Phone Call Follow-up #2 1 month Clinic Visit Data download

CPAP Set-up CPAP Follow-up (+)

Introduction to CPAP CPAP set-up Introduction to CPAP CPAP set-up

Follow-up #3 2 month Clinic Visit Data download Provider access to monthly data Follow-up #1 1 week Phone Call Follow-up #2 1 month Clinic Visit Data download Follow-up #3 2 month Clinic Visit Data download Provider access to daily data
Clinical Care Differences

• Both ECC and UCC have data access

– ECC – Daily data access

– UCC – Monthly data access

• ECC providers can proactively intervene

– UCC providers limited to time points

– However, patients could always call/drop-in

• Key difference was essentially in that first 30 

day period.
Sample Characteristics*

Variable Mean SD Range

Age 59 14.3 23-80

Body Mass Index (kg/m2) 32.8 5.7 26.0-45.9

Apnea-Hypopnea Index 

(AHI)

39 16.8 20.7-93.7

Oxygen Desat Index (ODI) 43.4 20.1 16.5-89.3

CPAP pressure (cm H2O) 10.3 1.6 8-13

Epworth Sleepiness Scale 12.6 5.8 4-23

FOSQ* 13.8 3.8 6.2-19.3

27

* There were no significant differences on any of these sample characteristic variables 

between the 2 groups
Data on Adherence, AHI and Mask Leak by 

Overall Group and Intervention Arms

Total Sample Usual Clinical Care Enhanced Clinical 

Care

Mean SD Range Mean SD Range Mean 

SD

Range

Adherence 

(hrs/night)*

3.5 2.1 0.2 – 6.8 2.8 2.2 0.2 – 6.2 4.1 1.8 .01 – 6.8

AHI (e/hr) 6.8 5.3 .14 – 25.6 8.8 5.7 3.4 – 25.6 4.8 4.0 .14 – 13.3

Mask Leak 

(l/sec)

.44 .36 .05 – 2.2 .50 .47 .05 – 2.2 .38 .18 .17 - .82

% Nights 

with CPAP 

Use (>0)*

65 31% 0-100% 60 32% 5-100% 78 22% 24-98%

% Nights 

with > 

4hrs/nt

44 32% 0-93% 37 34% 0-89% 52 27% 0-93%

Note: * p<0.10 (trend); ** p<0.05 28
Results: Adherence level (in hrs/nt) 

by Group

2.8

4.1

0

1

2

3

4

5

Usual Enhanced

Adherence

29

p-value=0.07
Results: Mean Leak by Group

0.5

0.38

0

0.1

0.2

0.3

0.4

0.5

0.6

Usual Enhanced Mask Leak (l/sec)

30
Conclusions

Trend for both greater CPAP adherence levels and 

lower mask leak levels in ECC relative to UCC 

All patients had acceptable leak levels and AHI levels, 

on average, over the 2-month intervention period

Overall, enhanced clinical care patients were satisfied 

with their care, are very likely to continue to use CPAP, 

and were not concerned about wireless monitoring of 

their CPAP data
Study 2: Telemonitoring + 

Interactive Website

• Develop and evaluate a CPAP adherence 

intervention using the internet

• Key features:

– Telemonitoring of CPAP adherence and efficacy data

– Feeding that data back to both patients and providers

– Creating online resource for participants
Methods

• Randomized, controlled trial comparing two groups:

– Usual Care (UC)

– Patient-Centered Collaborative Care (PC3) – emphasize 

collaboration between provider and patient

• 120 patients per group

• Recruited from UCSD Sleep Clinic

– Supplemented by word-of-mouth referrals

• Inclusion criteria: AHI>10
OSA Diagnosis

CPAP Prescription Ordered

CPAP Set-up

Clinical Process Patient- Centered Collaborative Care (PC3) Usual Care (UC)

Follow-up #1 1 week Phone Call Follow-up #2 1 month Clinic Visit Data download

CPAP Set-up CPAP Follow-up (+)

Introduction to CPAP CPAP set-up Introduction to CPAP CPAP set-up

Follow-up #3 2 month Clinic Visit Data download Provider access to monthly data Follow-up #1 1 week Phone Call Follow-up #2 1 month Clinic Visit Data download Follow-up #3 2 month Clinic Visit Data download Provider access to daily data

UC 

vs. 

PC3
Chronic Illness Care - IOM

• What patients with chronic illnesses need:

– A “continuous, healing relationship”

– Regular assessments of how they are doing

– Effective clinical management

– Information and ongoing support for self-management 

– Shared care plan

– Active, sustained follow-up

Crossing the Quality Chasm, Institute of Medicine (IOM), 2001
PC3 based in large part on the 

Chronic Care Model
Provider Side:

CPAP Telemonitoring System

+ =

ResMed AutoSet Spirit ResTraxx wireless 

module

AutoSet + ResTraxx

• Data transmitted via cellular network next day in “store & 

forward” manner (ie, not real-time)

• Other similar systems include Encore Anywhere (Philips 

Respironics)
Model of Wireless CPAP 

Telemonitoring
Patient Side: PC3 Website

• Interactive website designed to “off-load” 

those tasks that tend to be repetitive to 

provider:

– Learning Center – OSA and CPAP

– Reference Manual 

• Add interactive components:

– My Charts

– Troubleshooting Guide
PC3 Website Login
PC3 Website Homepage
Learning Center
Charts Page
CPAP Adherence data
CPAP Residual AHI Data
CPAP Leak Data
Troubleshooting & Manual
Sample Baseline 

Characteristics

Variable Both Groups PC3 *

(N=126)

Usual Care* 

(N=114)

P-value

Mean ± SD Mean ± SD Mean ± SD

Age 52.1 ± 13.3 52.2 ± 13.0 51.9 ± 13.6 NS

Body Mass Index 

(kg/m2)

32.4 ± 8.0 32.1 ± 8.3 32.8 ± 7.8 NS

Apnea-Hypopnea 

Index (AHI)

36.5 ± 25.9 36.3 ± 24.9 36.6 ± 27.0 NS

Epworth 

Sleepiness Scale

10.6 ± 5.3 10.7 ± 5.2 10.5 ± 5.4 NS

* No significant differences between UC and PC3 groups
CPAP Adherence level between UC and 

PC3 at 2-months

1

2

3

4

5

UC PC3

CPAP Adherence (hrs/nt)

p-value=.016; d-index = 0.34
CPAP Adherence level between UC and 

PC3 at 4-months

p-value =.035; d-index = 0.30 

1

2

3

4

5

UC PC3

CPAP Adherence (hrs/nt)
Nightly Use Rates over first 90 days

0.0

1.0

2.0

3.0

4.0

5.0

6.0

n1 n11 n21 n31 n41 n51 n61 n71 n81

UC

PC3
Outcome Measures – 2 

months

Variable Both Groups PC3 

(N=126)

Usual Care 

(N=114)

P-value

Mean ± SD Mean ± SD Mean ± SD

Epworth 

Sleepiness Scale

8.5 ± 5.4 8.9 ± 5.3 8.1 ± 5.5 NS

Sleep Apnea 

Quality of Life

2.4 ± 1.1 2.5 ± 1.0 2.4 ± 1.2 NS

CES-D* 8.5 ± 5.4 8.9 ± 5.3 8.1 ± 5.5 NS

Patient 

Satisfaction

1.7 ± 1.2 1.7 ± 1.1 1.8 ±1.3 NS

*CES-D=Center for Epidemiological Studies-Depression
Outcome Measures – 4 

months

Variable Both Groups PC3 

(N=126)

Usual Care 

(N=114)

P-value

Mean ± SD Mean ± SD Mean ± SD

Epworth 

Sleepiness Scale

6.5 ± 4.2 7.1 ± 4.5 5.7 ± 3.6 NS

Sleep Apnea 

Quality of Life

2.3 ± 1.1 2.4 ± 1.1 2.2 ± 1.2 NS

CES-D 7.9 ± 5.2 8.6 ± 5.5 7.1 ± 4.9 NS

Patient 

Satisfaction

1.8 ± 1.2 1.7 ± 1.1 1.9 ±1.3 NS

*CES-D=Center for Epidemiological Studies-Depression
Study 3 – in progress

• Four-group design:

– CPAP Telemonitoring

– Individualized Self-Management

– Telemonitoring + Self-Management

– Usual Care
Conclusions

• CPAP telemonitoring has provided the basis for several of our studies

– Allows for timely objective data review 

– Provides the basis for productive interactions between patient and 

provider

• The PC3 intervention has the potential to help improve CPAP 

adherence in clinical settings

• The ~1hr/nt difference held at both 2-mo and 4-mo time points
Conclusions

• CPAP adherence interventions based on health IT have potential to 

be cost effective relative to more labor-intensive interventions

• May be useful as part of a stepped care plan

• Patient engagement with health IT tools is variable: consider 

incentives/rewards

• Future studies would do well to include forums and other peer 

support, as well as electronic communication with provider

• “Tool” vs. clinical issue/process
Acknowledgements

• Project team and Colleagues:

– Zia Agha, MD, VASDHS & UCSD

– Sonia Ancoli-Israel, PhD, UCSD

– Jose Loredo, MD, VASDHS & UCSD

– Matthew Marler, PhD

– Allen Gifford, MD, VA Boston &Tufts

– Christine Edwards, BA

– Tania Zamora, BA

– Phil Rios, B.S.

– Karen Bartku

• UCSD Sleep Clinic Staff

• AHRQ 1R18HS017426-01; VA IIR 07-163; VA San Diego Research Service; 

Veteran’s Medical Research Foundation; UCSD Calit2.
Questions?

cstepnowsky@ucsd.edu

carl.stepnowsky@va.gov