Clinical trial NCT04322162: Addressing Sleep Apnea Post-Stroke/TIA
Official title: Addressing Sleep Apnea Post-Stroke (ASAP)
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Ischemic Stroke
Transient Ischemic Attack (TIA)
Obstructive Sleep Apnea
Keywords: Ischemic stroke
Transient ischemic attack (TIA)
Stepped-wedge trial
Implementation Science
Hybrid Type I
Quality Improvement
Systems Redesign
Champion
External Facilitation
Audit and feedback
Local Adaptation
Obstructive Sleep Apnea
Polysomnography
Sustainability
Business-case
Lead sponsor: VA Office of Research and Development
Sponsor class: FED
First posted: 2020-03-26
Enrollment: 6
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: SEQUENTIAL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: Effectively identifying and treating risk factors for ischemic stroke and transient ischemic attack (TIA) is important to patients, their family members, and healthcare systems. While obstructive sleep apnea (OSA) is a known risk factor for stroke and TIA that is present in more than 70% of stroke/TIA survivors, testing for OSA is infrequently performed for patients and within healthcare systems. The Addressing Sleep Apnea Post-Stroke/TIA (ASAP) study intends to improve rates of guideline-recommended OSA testing and treatment through local quality improvement initiatives (QI) conducted within and across 6 VA Medical Centers. ASAP will also determine the impact of these local QI initiatives on rates of OSA diagnosis, OSA treatment, recurrent vascular events, and hospital readmissions.

Detailed description: Approximately 11,000 Veterans present to a VAMC annually with an acute ischemic stroke or TIA. The cornerstone of secondary stroke/TIA prevention includes delivering timely, guideline-concordant vascular risk factor management. Over the past decade, OSA has been recognized as a potent, underdiagnosed, and inadequately treated cerebrovascular risk factor. OSA is very common among patients with stroke/TIA with a prevalence of 60-80%. Despite being highly prevalent, 70-80% of patients with OSA are neither diagnosed nor treated. Untreated OSA has been associated with poor outcomes among patients with cerebrovascular disease including higher mortality and worse functional status. The mainstay of OSA therapy is positive airway pressure (PAP). PAP reduces recurrent vascular events, improves neurological symptoms and functional status among stroke/TIA patients with OSA. The evidence favoring neurological recovery is strongest when interventions are applied early post-stroke/TIA. Guidelines recommend diagnosing and treating OSA for stroke and TIA patients; however, within VHA, very few stroke or TIA patients receive OSA screening. This guideline recommendation was informed in part by clinical trials utilizing an acute OSA assessment protocol developed and implemented by the investigators' group. To address the observed gap in care, the investigators propose a Hybrid Type I, randomized, stepped-wedge trial at 6 VAMCs to increase the rate of timely, guideline-concordant diagnosis and treatment of OSA among Veterans with ischemic stroke/TIA and thereby reduce recurrent vascular events and hospital readmissions. The investigators will identify matched control sites for each ASAP implementation site to examine temporal trends in outcomes among non-intervention sites. For example, the investigators will use administrative data to examine the use of polysomnography across stroke/TIA patients in the VA system and compare changes in matched controls versus the intervention sites on the diagnostic rate. The same adjustment approach will be used for ASAP intervention sites and for control sites.

Eligibility criteria: Inclusion Criteria:

As recruitment was at the facility-level, an ASAP a VAMCS had to have \>50 stroke/TIA admissions per year and have at least 1.0 FTE staff dedicated to systems redesign

* The sites were chosen because they are diverse in terms of geography and sleep infrastructure

  * Local site investigators and their care teams will identify patients eligible for the QI intervention, specifically patients with ischemic stroke/TIA without a prior diagnosis of OSA

Exclusion Criteria:

* VAMCs were excluded if they had \<=50 stroke/TIA admissions per year and did not have at least 1.0 FTE staff dedicated to systems redesign
* Local site investigators and their care teams will prioritize the protection of patients from harm and use their clinical expertise in identifying patients who would not be candidates for PAP therapy

  * e.g., palliative care/hospice, inability to use PAP therapy \[e.g., orofacial injury\], or contraindication to PAP \[e.g., inability to clear secretions\]

Primary outcomes:
measure: Facility-level OSA diagnostic rate
timeFrame: 30-day
Secondary outcomes:
measure: Facility-level treatment rate
timeFrame: 30-day
measure: Facility-level recurrent vascular event rate
timeFrame: 90-day
measure: Facility-level all-cause readmission rate
timeFrame: 90-day
measure: Facility-level treatment rate (Positive airway pressure and non-positive airway pressure treatments)
timeFrame: 30-day
Other outcomes:
measure: Implementation Outcome - Adaptation
timeFrame: Measured throughout active implementation and sustainability periods
measure: External Facilitation
timeFrame: Measured throughout active implementation and sustainability periods
measure: Audit and Feedback
timeFrame: Measured throughout active implementation and sustainability periods
measure: Sustainability - mixed methods analysis
timeFrame: Measured throughout sustainability period
measure: Sustainability - Program Sustainability Assessment Tool (PSAT)
timeFrame: Measured prior to and at the end of active implementation period and at the end of the sustainability period
Locations:
city: West Haven
country: United States
facility: VA Connecticut Healthcare System West Haven Campus, West Haven, CT
state: Connecticut
city: Indianapolis
country: United States
facility: Richard L. Roudebush VA Medical Center, Indianapolis, IN
state: Indiana
Study officials:
affiliation: VA Connecticut Healthcare System West Haven Campus, West Haven, CT
name: Jason Jonathon Sico, MD MHS
role: PRINCIPAL_INVESTIGATOR
affiliation: Richard L. Roudebush VA Medical Center, Indianapolis, IN
name: Dawn M. Bravata, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Diaz MM, Hu X, Fenton BT, Kimuli I, Lee A, Lindsey H, Bigelow JK, Maiser S, Altalib HH, Sico JJ. Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward. BMC Neurol. 2020 Jan 31;20(1):42. doi: 10.1186/s12883-020-1627-5.
citation: Sico JJ, Sarwal A, Benish SM, Busis NA, Cohen BH, Das RR, Finsilver S, Halperin JJ, Kelly AG, Meunier L, Phipps MS, Thirumala PD, Villanueva R, von Gaudecker J, Bennett A, Shenoy AM. Quality improvement in neurology: Neurology Outcomes Quality Measurement Set. Neurology. 2020 Jun 2;94(22):982-990. doi: 10.1212/WNL.0000000000009525. Epub 2020 May 12. No abstract available.
citation: Patel K, Nussbaum E, Sico J, Merchant N. Atypical case of Miller-Fisher syndrome presenting with severe dysphagia and weight loss. BMJ Case Rep. 2020 May 27;13(5):e234316. doi: 10.1136/bcr-2020-234316.
citation: Arling G, Perkins A, Myers LJ, Sico JJ, Bravata DM. Blood Pressure Trajectories and Outcomes for Veterans Presenting at VA Medical Centers with a Stroke or Transient Ischemic Attack. Am J Med. 2022 Jul;135(7):889-896.e1. doi: 10.1016/j.amjmed.2022.02.012. Epub 2022 Mar 12.
citation: Miech EJ, Perkins AJ, Zhang Y, Myers LJ, Sico JJ, Daggy J, Bravata DM. Pairing regression and configurational analysis in health services research: modelling outcomes in an observational cohort using a split-sample design. BMJ Open. 2022 Jun 7;12(6):e061469. doi: 10.1136/bmjopen-2022-061469.
citation: Sico JJ, Koo BB, Perkins AJ, Burrone L, Sexson A, Myers LJ, Taylor S, Yarbrough WC, Daggy JK, Miech EJ, Bravata DM. Impact of the coronavirus disease-2019 pandemic on Veterans Health Administration Sleep Services. SAGE Open Med. 2023 May 3;11:20503121231169388. doi: 10.1177/20503121231169388. eCollection 2023.
citation: Waddell KJ, Myers LJ, Perkins AJ, Sico JJ, Sexson A, Burrone L, Taylor S, Koo B, Daggy JK, Bravata DM. Development and validation of a model predicting mild stroke severity on admission using electronic health record data. J Stroke Cerebrovasc Dis. 2023 Sep;32(9):107255. doi: 10.1016/j.jstrokecerebrovasdis.2023.107255. Epub 2023 Jul 18.