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

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

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03345524
Enrollment
145
Registered
2017-11-17
Start date
2017-11-17
Completion date
2018-10-11
Last updated
2017-11-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Obstructive Sleep Apnea

Keywords

Obstructive Sleep Apnea, OSA, Peer-Buddies, CPAP, CPAP Adherence

Brief 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.

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.

Interventions

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)

Sponsors

National Heart, Lung, and Blood Institute (NHLBI)
CollaboratorNIH
University of Arizona
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
DOUBLE (Investigator, Outcomes Assessor)

Masking description

Will be blinded to subjects group assignment

Intervention model description

Randomized Controlled Trial

Eligibility

Sex/Gender
ALL
Age
21 Years to 85 Years
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Proportion of patients undergoing sleep study testingBaselineDifference 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.

Secondary

MeasureTime frameDescription
CPAP Adherence downloadsDay 30, Day 90, and Day 180All 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.

Other

MeasureTime frameDescription
Systolic Blood PressureBaseline, Day 90, and Day 180Measured by experienced staff following international guidelines. Change in blood pressure over time will be assessed.
Functional Outcomes of Sleep Questionnaire (FOSQ)Baseline, Day 90, and Day 180A 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.
Body Mass Index (BMI)Baseline, Day 90, and Day 180A measure of body fat based on height and weight. Change in BMI over time will be assessed.
Diastolic blood pressureBaseline, Day 90, and Day 180Measured by experienced staff following international guidelines. Change in blood pressure over time will be assessed.
Epworth Sleepiness ScaleBaseline, Day 90, and Day 180This 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.

Countries

United States

Contacts

Primary ContactSairam Parthasarathy, MD
sparthasarathy@deptofmed.arizona.edu520-626-6109

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026