CPAP Population Management

The investigators propose a study to formally compare two Continuous Positive Airway Pressure (CPAP) follow-up pathways: 1) Usual care - follow-up visits reflect standard care practice and we rely on patients to reach out to us if they are struggling with therapy (there will be no active outreach); 2) Case Management - in addition to "Usual Care" visits, patients CPAP use will be monitored and further encounters may be initiated with "struggler" CPAP users while "successful" users are passively followed. The investigators will evaluate measures of CPAP adherence, patient engagement and cost-effectiveness for the duration of 1 year. Our hypothesis is that "Case Management" will improve CPAP adherence and cost-effectiveness compared to "Usual Care". The investigators also hypothesize that targeting "strugglers" only in a management by exception (MBE) approach will be equally effective, but require less personnel time compared to targeting "all" patients.

Untreated obstructive sleep apnea (OSA) increases patient risks and burden on the healthcare system due to its high prevalence, impact on cardiovascular health, and daytime symptoms that cause deficits on daytime functioning. The yearly economic cost of OSA in Australia, with a population of about 25 million, is estimated to be $21 billion. Unfortunately, the effectiveness of continuous positive airway pressure (CPAP) therapy on improving patient and population outcomes is limited by suboptimal adherence with literature generally reporting adherence rates of 50-70% (defined by Medicare as ≥70% nights used ≥4 hours). The development of technology-based solutions is critical towards improving adherence, and this includes the use of remote patient monitoring, automation, and population management tools. Current CPAP devices are now wirelessly connected (eg, via cellular) which enables remote access by sleep medicine providers to access patient usage. Fox et al demonstrated the utility of remote monitoring in a randomized trial. New CPAP users that were remotely identified to have suboptimal use (and underwent a telephone encounter with a sleep medicine provider) showed significantly better 3 month CPAP use compared to the control group without monitoring (321 minutes versus 207 minutes; p<0.0001). Our center also performed a randomized trial (Tele-OSA study) in which a similar process was applied but the monitoring and patient feedback was automated. Patients with <4 hours use for 3 nights in a row were automatically sent messages (typically via SMS text) encouraging use. The investigators demonstrated the cost-effectiveness of this automated approach (Auto-Monitoring), which resulted in improved CPAP adherence without an increase in manual intervention with a provider. Population management platforms capable of automatically risk stratifying patients (eg, automatically identifying poor users) may be another cost-effective technology-based tool by enabling a "management by exception" (MBE) follow-up process. This process concentrates provider effort on patients most at need by allowing providers to passively observe successful users and actively intervene only in CPAP strugglers. In our center, the investigators intend to implement this population management process by identifying CPAP strugglers at 1 month, 2 month, and 3 months after therapy initiation although impact on outcomes is unknown. Time Motion Pilot Our center proceeded with a preliminary implementation of this automated MBE process and performed a time motion study comparing time required to deliver care utilizing the population management process with automated risk stratification versus a non-automated process. The tasks performed were as follows: 1) Risk stratification (identifying patients with moderate-severe OSA), assessing CPAP Adherence (identifying those with >50% nights used at least 4 hours), telephone encounter (to troubleshoot issues with CPAP use), and documentation. The investigators demonstrated an 83% reduction in time required to follow-up a similar population of new CPAP users at any given time point (eg, 1 month, 2 months, etc.) While the results of this pilot (unpublished data) demonstrates significant improvement in care delivery efficiency, the impact on adherence remains unclear. Population Management Study The investigators propose a study to formally compare two CPAP follow-up pathways: 1) Usual care - a control group utilizing standard care practices with no active outreach; 2) Case Management - in addition to "Usual Care", other encounters may be initiated with CPAP strugglers while successful users are passively followed.

Case Management (CM), Management by Exception, Continuous Positive Airway Pressure (CPAP), CPAP Adherence, Auto-monitoring, Patient Engagement, Patient Acceptance, Cost-Effective

Patients will receive Auto-Monitoring text messages. The Auto-Monitoring tool that will be used is a function within Somnoware (Somnoware, Inc.) patient management platform, which is the national KP benchmarked platform for sleep management software. Fixed scheduled follow-up visits will be scheduled at 1-month (telephone encounter), 3-months (in-person or video encounter), and 1-year (in-person or video encounter). This sequence of follow-up visits reflects current real-world practice. Patients are eligible for additional visits when self-initiated. Sleep questionnaires will be delivered at 1, 3, and 6 months and at 1 year.

Patients will undergo the same follow-up process as described in the Usual Care Pathway. A population CM dashboard (Somnoware, Inc.) will be used to automatically identify PAP strugglers (defined as <70% nights with ≥4 hours use during the preceding month) for 1 year. Video encounters will be triggered for these select patients for troubleshooting. Additionally, throughout this 1-year period, Q1 window of <70% nights >4 hours will trigger a phone call and at the discretion of the case manager convert to video or in-person encounter for troubleshooting. CPAP Follow-Up Questionnaire will also be delivered to patient at 3 months and 1 year.

Population management platforms capable of automatically risk stratifying patients (eg, automatically identifying poor users) may be another cost-effective technology-based tool by enabling a "management by exception" (MBE) follow-up intervention. This intervention concentrates provider effort on patients most at need by allowing providers to passively observe successful users and actively intervene only in CPAP strugglers. Therefore, in addition to "Usual Care" we will implement this population management process by identifying CPAP strugglers only and further follow-up encounters will be triggered for these select patients for troubleshooting. Additionally, throughout the 1-year period, Q1 window of <70% nights >4 hours will trigger a phone call and at the discretion of the sleep provider convert to video or in-person encounter for troubleshooting. CPAP Follow-Up Questionnaire will also be delivered to patient at 3 months and 1 year.

Evaluate the cost-effectiveness of each arm by evaluating the number, estimated time and cost per encounter.

Evaluate measures of patient acceptance, engagement and satisfaction with Case Management intervention and care experience

Inclusion Criteria: Kaiser Permanente member Moderate-Severe Obstructive Sleep Apnea diagnosis (AHI4%≥15 on home sleep apnea test [Nox T3 or WatchPAT] or polysomnography (in-lab study) PAP therapy clinically recommended and prescribed for home therapy of OSA Adults (age ≥ 18 years) Exclusion Criteria: Chronic respiratory failure requiring bilevel PAP ventilatory support or addition of oxygen supplementation. Prior use of PAP prescribed for home therapy. Inability wirelessly connect patient's PAP device.

The Economic Cost of Sleep Disorders in Australia. Sleep Health Foundation. Deloitte Access Economics. 2010.

Kribbs NB, Pack AI, Kline LR, Smith PL, Schwartz AR, Schubert NM, Redline S, Henry JN, Getsy JE, Dinges DF. Objective measurement of patterns of nasal CPAP use by patients with obstructive sleep apnea. Am Rev Respir Dis. 1993 Apr;147(4):887-95. doi: 10.1164/ajrccm/147.4.887.

Iftikhar IH, Valentine CW, Bittencourt LR, Cohen DL, Fedson AC, Gislason T, Penzel T, Phillips CL, Yu-sheng L, Pack AI, Magalang UJ. Effects of continuous positive airway pressure on blood pressure in patients with resistant hypertension and obstructive sleep apnea: a meta-analysis. J Hypertens. 2014 Dec;32(12):2341-50; discussion 2350. doi: 10.1097/HJH.0000000000000372.

Iftikhar IH, Hoyos CM, Phillips CL, Magalang UJ. Meta-analyses of the Association of Sleep Apnea with Insulin Resistance, and the Effects of CPAP on HOMA-IR, Adiponectin, and Visceral Adipose Fat. J Clin Sleep Med. 2015 Apr 15;11(4):475-85. doi: 10.5664/jcsm.4610.

Fox N, Hirsch-Allen AJ, Goodfellow E, Wenner J, Fleetham J, Ryan CF, Kwiatkowska M, Ayas NT. The impact of a telemedicine monitoring system on positive airway pressure adherence in patients with obstructive sleep apnea: a randomized controlled trial. Sleep. 2012 Apr 1;35(4):477-81. doi: 10.5665/sleep.1728.