CClinicalTrials.gg
Status unknownNCT03345524Updated Nov 17, 2017

Predictive Analytics and Peer-Driven Intervention for Guideline-based Care for Sleep Apnea

An interventional study of Peer-Buddy System and Usual Care in Obstructive Sleep Apnea, sponsored by University of Arizona. Status unknown at 1 site in United States. Open to participants aged 21 Years to 85 Years. Per ClinicalTrials.gov, last updated 2017-11-17.

Sponsored by University of Arizona · Not applicable, Interventional, and Supportive care

The sponsor has not verified this record recently (last verified Nov 2017), so the status shown — last known as Not yet recruiting — may be out of date.
Phase
Not applicable
Study type
Interventional
Enrollment
145
Allocation
Randomized
Ages
21 Years to 85 Years
Sex
All
01

Study summary

Obstructive sleep apnea (OSA) is a prevalent condition that affects 7 to 12% of the US population and is characterized by repetitive collapse of the upper airway during sleep. Continuous positive airway pressure (CPAP) has been shown to be highly effective in the treatment of OSA, however, adherence is poor with up to 54% of patients being non-adherent to CPAP therapy by Medicare criteria, which has been attributed to inadequate patient education and support for CPAP therapy.

Poor treatment adherence in patients with OSA can lead to adverse health consequences, poor quality of life, and patient dissatisfaction. Poor treatment adherence may be due to lack of sufficient patient education, time delays in delivery of care, lack of adequate healthcare coordination, or difficulty accessing various healthcare providers across a front desk which serves as a "healthcare bottle-neck". Better efficiency in healthcare delivery, with greater connectivity through knowledgeable and trained peer volunteers and cheap cell-phones integrated by a smart telephone exchange may alleviate some of the care and communication burden faced by the healthcare system. Specifically, such community health education volunteers ("peer-buddies") who are experienced in managing their OSA may be able to impart knowledge and confidence to a recently diagnosed patient in a much more personalized manner than that of a group therapy session.

Read the detailed description

OSA affects 7 to 12% of the US population and is an independent risk factor for several clinical consequences such as systemic hypertension, cardiovascular disease, stroke, reduced HR-QOL, increased all-cause mortality, and motor vehicle accidents due to sleepiness. However, OSA and other sleep disorders are woefully underdiagnosed because of time constraints at the PCP's office. Such poor CPAP adherence is associated with increased risk for fatal and non-fatal cardiovascular events. CPAP therapy has been associated with up to 3-fold reduction in fatal and non-fatal cardiovascular events in both on-treatment analysis of RCTs and observational studies. CPAP therapy is associated with 7-fold reduction in sleepiness-related accidents. The overarching aim of this proposal is to institute a multi-level strategy aimed at improving guideline based care for OSA in populations with health disparities.

The overarching aim of the program of research is to eventually institute a multi-level strategy with interventions aimed at both providers and patients in order to improve guideline based care for OSA in populations with health disparities. Specifically, in order to address the under-diagnosis of OSA, an electronic health record (EHR) based predictive analytics system will be implemented. A similar EHR-based alert system with reflex order sets for initiating testing for OSA that the investigators have developed will enable PCPs to effectively diagnose and treat OSA. It was found that in a nationally representative dataset of \~220,000 patients, lower neighborhood income was associated with lower CPAP adherence. Considering the time and access-related barriers in the PCP office, it is believed that such socioeconomic status (SES) related differences in CPAP adherence needs to be addressed by culturally-competent peer educators (such as promotors) with OSA serving as "peer-buddies". In a recent multi-site RCT, it was found that CPAP adherence and patient satisfaction was improved by peer-driven intervention through an interactive voice response system (PDI-IVR; PCORI-IHS-1306-02505), whereby the peers shared their experiences with CPAP naïve patients and educated them about OSA and risks of CPAP nonadherence. Whether PDI-IVR can improve adherence in underserved population in low resource clinics is unclear. In this proposal, 110 CPAP naïve patients and 35 experienced peer-buddies will be recruited in from a large healthcare system that provides care for an underserved population with an excess burden of sleep disorders (Medicaid and dual-eligible Medicare beneficiaries). This study will address health disparities in the diagnosis and treatment of OSA using a patient-level educational intervention (PDI-IVR system) targeting patients and thereby promote health equity. This proposal will also inform future studies by gathering additional data on the effect of PDI-IVR on adherence to sleep study testing and CPAP adherence in an underserved population in low resource clinics.

Specific Aim #1: To test a peer-driven intervention with interactive voice response (PDI-IVR) system to improve adherence to sleep study testing in a lower socioeconomic population.

Hypothesis #1: A PDI-IVR support system will lead to greater adherence to sleep study testing in patients with OSA when compared to patients receiving conventional education.

Specific Aim #2: To test a peer-driven intervention with interactive voice response (PDI-IVR) system to improve CPAP treatment adherence in a lower socioeconomic population.

Hypothesis #2: A PDI-IVR support system will lead to greater adherence to CPAP therapy in patients with OSA when compared to patients receiving conventional education.

02

Conditions studied

  • Obstructive Sleep Apnea

Keywords

  • Obstructive Sleep Apnea
  • OSA
  • Peer-Buddies
  • CPAP
  • CPAP Adherence
03

Who can participate

Ages eligible
21 Years to 85 Years
Sexes eligible
All
Accepts healthy volunteers
No

Eligibility criteria

Inclusion Criteria for Subject:

  • Referral for sleep study testing for possible OSA
  • Medicaid and dual-eligible Medicare beneficiaries
  • Household income in the bottom national quartile of household median income

Inclusion Criteria for Peer Buddy:

  • Adherent to CPAP therapy (greater than or equal to 4 hours per night of CPAP use)
  • Willing to meet with peer-buddy on 2-4 occasions in-person
  • Has a cell phone or other reliable telephone line
  • Willing to undergo one-two training and orientation session(s) and pass a subsequent mock patient interaction

Exclusion Criteria for Subject:

  • Central sleep apnea (CSA)
  • Participation in another intervention-based research study
  • Patient's primary care provider refuses patient participation for medical instability

Exclusion Criteria for Peer Buddy:

  • Central sleep apnea (CSA)
  • Participation in another intervention-based research study
  • Patient's primary care provider refuses patient participation for medical instability
  • Major depression or other major psychiatric illness
  • Shift-worker or frequent out of town traveler
04

Study design

Phase
Not applicable
Primary purpose
Supportive care
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Double (Investigator, Outcomes assessor)
Enrollment
145 participants (estimated)

Study arms

  • Experimental
    Peer-buddy system

    Will meet with peer-buddy who will help with them with CPAP usage. Also will receive standard of care CPAP educational training

    Other: Peer-Buddy System

  • Active comparator
    Usual Care

    Will receive educational material at the same frequency that those in the experimental arm. Will also receive standard of care CPAP educational training.

    Other: Usual Care

Interventions

  • OtherPeer-Buddy System

    2-4 30-minute in person sessions with Peer Buddy (2 before and 2 after receiving CPAP) Standard of care CPAP educational training 8-10 phone conversations with Peer Buddy over 3 month period Subsequent 3 months use of phone system to contact Peer Buddy as needed

  • OtherUsual Care

    Standard of care CPAP educational training Educational Brochures and DVD videos mailed to participants (12 times)

05

What researchers measure

Primary outcomes

  1. Proportion of patients undergoing sleep study testing

    Difference between the proportion of patients in the peer-buddy arm from the proportion of patients in the conventional educational arm that follow-through and undergo sleep study testing.

    Time frame: Baseline

Secondary outcomes

  1. CPAP Adherence downloads

    All CPAP devices have internal adherence monitoring which can be downloaded using a computer cable, smart card, SD chip or wireless transmission. The objective, adherence information as 'mask-on' time for 6 months, number of nights used, cumulative hours used, average hours of CPAP use per night, and average number of hours per day of CPAP use will be derived. The proportion of days in which CPAP use was at least 4 hr (Medicare criterion) will also be utilized. Change in CPAP adherence over time will be assessed.

    Time frame: Day 30, Day 90, and Day 180

Other outcomes

  1. Functional Outcomes of Sleep Questionnaire (FOSQ)

    A condition-specific functional status measure designed to evaluate the impact of disorders of excessive sleepiness on activities of daily living. Lower global scores are associated with greater dysfunction. FOSQ has good to excellent test-retest reproducibility, internal consistency, with discriminate validity between those seeking medical attention for sleep disorders compared to normal subjects. Change in FOSQ over time will be assessed.

    Time frame: Baseline, Day 90, and Day 180

  2. Epworth Sleepiness Scale

    This scale measure daytime sleepiness. A measure of sleepiness that is administered as 8-item questionnaire of situational sleepiness on a 3-point scale. The sum of the points will yield the Epworth score which ranges from 0 to 24 and is essentially the sum of the scores for each of the 8-items that are scored from a range of 0 to 3. An Epworth Sleepiness Score that is greater than 10 is considered to signify excessive daytime sleepiness with a score of 24 signifying with worst possible score. The change in ESS over time will be measured.

    Time frame: Baseline, Day 90, and Day 180

  3. Systolic Blood Pressure

    Measured by experienced staff following international guidelines. Change in blood pressure over time will be assessed.

    Time frame: Baseline, Day 90, and Day 180

  4. Diastolic blood pressure

    Measured by experienced staff following international guidelines. Change in blood pressure over time will be assessed.

    Time frame: Baseline, Day 90, and Day 180

  5. Body Mass Index (BMI)

    A measure of body fat based on height and weight. Change in BMI over time will be assessed.

    Time frame: Baseline, Day 90, and Day 180

06

Study locations

1 site
07

References and documents

Publications

  • Punjabi NM. The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc. 2008 Feb 15;5(2):136-43. doi: 10.1513/pats.200709-155MG. PubMed 18250205 ↗
  • Marin JM, Agusti A, Villar I, Forner M, Nieto D, Carrizo SJ, Barbe F, Vicente E, Wei Y, Nieto FJ, Jelic S. Association between treated and untreated obstructive sleep apnea and risk of hypertension. JAMA. 2012 May 23;307(20):2169-76. doi: 10.1001/jama.2012.3418. PubMed 22618924 ↗
  • Peppard PE, Young T, Palta M, Skatrud J. Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med. 2000 May 11;342(19):1378-84. doi: 10.1056/NEJM200005113421901. PubMed 10805822 ↗
  • Nieto FJ, Young TB, Lind BK, Shahar E, Samet JM, Redline S, D'Agostino RB, Newman AB, Lebowitz MD, Pickering TG. Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study. Sleep Heart Health Study. JAMA. 2000 Apr 12;283(14):1829-36. doi: 10.1001/jama.283.14.1829. Erratum In: JAMA 2002 Oct 23-30;288(16):1985. PubMed 10770144 ↗
  • Peker Y, Carlson J, Hedner J. Increased incidence of coronary artery disease in sleep apnoea: a long-term follow-up. Eur Respir J. 2006 Sep;28(3):596-602. doi: 10.1183/09031936.06.00107805. Epub 2006 Apr 26. PubMed 16641120 ↗
  • Leung RS, Bradley TD. Sleep apnea and cardiovascular disease. Am J Respir Crit Care Med. 2001 Dec 15;164(12):2147-65. doi: 10.1164/ajrccm.164.12.2107045. No abstract available. PubMed 11751180 ↗
  • Yumino D, Wang H, Floras JS, Newton GE, Mak S, Ruttanaumpawan P, Parker JD, Bradley TD. Relationship between sleep apnoea and mortality in patients with ischaemic heart failure. Heart. 2009 May;95(10):819-24. doi: 10.1136/hrt.2008.160952. Epub 2009 Jan 8. PubMed 19131443 ↗
  • Yaggi HK, Concato J, Kernan WN, Lichtman JH, Brass LM, Mohsenin V. Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med. 2005 Nov 10;353(19):2034-41. doi: 10.1056/NEJMoa043104. PubMed 16282178 ↗
  • Weaver TE. Outcome measurement in sleep medicine practice and research. Part 1: assessment of symptoms, subjective and objective daytime sleepiness, health-related quality of life and functional status. Sleep Med Rev. 2001 Apr;5(2):103-128. doi: 10.1053/smrv.2001.0152. PubMed 12531049 ↗
  • Punjabi NM, Caffo BS, Goodwin JL, Gottlieb DJ, Newman AB, O'Connor GT, Rapoport DM, Redline S, Resnick HE, Robbins JA, Shahar E, Unruh ML, Samet JM. Sleep-disordered breathing and mortality: a prospective cohort study. PLoS Med. 2009 Aug;6(8):e1000132. doi: 10.1371/journal.pmed.1000132. Epub 2009 Aug 18. PubMed 19688045 ↗
  • Gami AS, Howard DE, Olson EJ, Somers VK. Day-night pattern of sudden death in obstructive sleep apnea. N Engl J Med. 2005 Mar 24;352(12):1206-14. doi: 10.1056/NEJMoa041832. PubMed 15788497 ↗
  • Teran-Santos J, Jimenez-Gomez A, Cordero-Guevara J. The association between sleep apnea and the risk of traffic accidents. Cooperative Group Burgos-Santander. N Engl J Med. 1999 Mar 18;340(11):847-51. doi: 10.1056/NEJM199903183401104. PubMed 10080847 ↗
  • Mulgrew AT, Nasvadi G, Butt A, Cheema R, Fox N, Fleetham JA, Ryan CF, Cooper P, Ayas NT. Risk and severity of motor vehicle crashes in patients with obstructive sleep apnoea/hypopnoea. Thorax. 2008 Jun;63(6):536-41. doi: 10.1136/thx.2007.085464. Epub 2008 Jan 30. PubMed 18234904 ↗
  • Redline S, Yenokyan G, Gottlieb DJ, Shahar E, O'Connor GT, Resnick HE, Diener-West M, Sanders MH, Wolf PA, Geraghty EM, Ali T, Lebowitz M, Punjabi NM. Obstructive sleep apnea-hypopnea and incident stroke: the sleep heart health study. Am J Respir Crit Care Med. 2010 Jul 15;182(2):269-77. doi: 10.1164/rccm.200911-1746OC. Epub 2010 Mar 25. PubMed 20339144 ↗
  • Rahaghi F, Basner RC. Delayed Diagnosis of Obstructive Sleep Apnea: Don't Ask, Don't Tell. Sleep Breath. 1999;3(4):119-124. doi: 10.1007/s11325-999-0119-z. PubMed 11898119 ↗
  • Flygare J, Parthasarathy S. Narcolepsy: let the patient's voice awaken us! Am J Med. 2015 Jan;128(1):10-3. doi: 10.1016/j.amjmed.2014.05.037. Epub 2014 Jun 12. PubMed 24931392 ↗
  • McEvoy RD, Antic NA, Heeley E, Luo Y, Ou Q, Zhang X, Mediano O, Chen R, Drager LF, Liu Z, Chen G, Du B, McArdle N, Mukherjee S, Tripathi M, Billot L, Li Q, Lorenzi-Filho G, Barbe F, Redline S, Wang J, Arima H, Neal B, White DP, Grunstein RR, Zhong N, Anderson CS; SAVE Investigators and Coordinators. CPAP for Prevention of Cardiovascular Events in Obstructive Sleep Apnea. N Engl J Med. 2016 Sep 8;375(10):919-31. doi: 10.1056/NEJMoa1606599. Epub 2016 Aug 28. PubMed 27571048 ↗
  • Weaver TE, Grunstein RR. Adherence to continuous positive airway pressure therapy: the challenge to effective treatment. Proc Am Thorac Soc. 2008 Feb 15;5(2):173-8. doi: 10.1513/pats.200708-119MG. PubMed 18250209 ↗
  • Martinez-Garcia MA, Campos-Rodriguez F, Catalan-Serra P, Soler-Cataluna JJ, Almeida-Gonzalez C, De la Cruz Moron I, Duran-Cantolla J, Montserrat JM. Cardiovascular mortality in obstructive sleep apnea in the elderly: role of long-term continuous positive airway pressure treatment: a prospective observational study. Am J Respir Crit Care Med. 2012 Nov 1;186(9):909-16. doi: 10.1164/rccm.201203-0448OC. Epub 2012 Sep 13. PubMed 22983957 ↗
  • Marin JM, Carrizo SJ, Vicente E, Agusti AG. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet. 2005 Mar 19-25;365(9464):1046-53. doi: 10.1016/S0140-6736(05)71141-7. PubMed 15781100 ↗
  • Javaheri S, Caref EB, Chen E, Tong KB, Abraham WT. Sleep apnea testing and outcomes in a large cohort of Medicare beneficiaries with newly diagnosed heart failure. Am J Respir Crit Care Med. 2011 Feb 15;183(4):539-46. doi: 10.1164/rccm.201003-0406OC. Epub 2010 Jul 23. PubMed 20656940 ↗
  • Findley L, Smith C, Hooper J, Dineen M, Suratt PM. Treatment with nasal CPAP decreases automobile accidents in patients with sleep apnea. Am J Respir Crit Care Med. 2000 Mar;161(3 Pt 1):857-9. doi: 10.1164/ajrccm.161.3.9812154. PubMed 10712333 ↗
  • Tregear S, Reston J, Schoelles K, Phillips B. Continuous positive airway pressure reduces risk of motor vehicle crash among drivers with obstructive sleep apnea: systematic review and meta-analysis. Sleep. 2010 Oct;33(10):1373-80. doi: 10.1093/sleep/33.10.1373. PubMed 21061860 ↗

Individual participant data

Plan to share: No

08

Registry details

Key details

Study ID
NCT03345524
Lead sponsor
University of Arizona
Collaborators
National Heart, Lung, and Blood Institute (NHLBI)
Responsible party
Sairam Parthasarathy (Professor of Medicine, University of Arizona) — Principal investigator
First posted
Nov 17, 2017
Start date
Nov 17, 2017 (estimated)
Primary completion
Oct 11, 2018 (estimated)
Completion
Oct 11, 2018 (estimated)
Last update
Nov 17, 2017

Study contacts

Sairam Parthasarathy, MD
Contact
sparthasarathy@deptofmed.arizona.edu
520-626-6109

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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