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Healthcare Renunciation in Respiratory Chronic Disease and Treatment Compliance (OBSERVE)

Grenoble Alpes University Hospital Center (CHU) logo

Grenoble Alpes University Hospital Center (CHU)

Status

Completed

Conditions

Respiratory Failure
Obstructive Sleep Apnea

Study type

Observational

Funder types

Other

Identifiers

NCT03591250
2017-A02831-52 (Other Identifier)
38RC17.321

Details and patient eligibility

About

Health care renunciation is a factor that can alter patients' health status and increase the costs of its support.

To date, there is no national data on the renunciation of care. This study will initially characterize the different forms of health care renunciation in patients with chronic respiratory diseases, treated with continuous positive airway pressure (CPAP) or non-invasive ventilation (NIV) , and analyze it impact on treatment compliance and health processes.

The follow-up of these patients during 5 years will define renunciation trajectories (transition from the state of "renouncing" to "non-renouncing" and vice versa) and their impact on treatment compliance.

The investigators hypothesize that a patient becoming renounced on a given treatment also decreases his treatment compliance (CPAP or NIV ).

The impact of the renunciation trajectory on the patient's follow-up in terms of hospitalizations and deaths will also be studied.

Full description

A questionnaire of health care renunciation will be administered to the patient at Day 0 and each year during 5 years, to determine whether or not he has given up one or more care in the last 12 months.

The compliance to the CPAP or NIV will be extracted from the database of the Health care provider (AGIR à dom).

The primary outcome is to determine the impact of health care renunciation on treatment compliance and overall health care processes.

The analysis of the primary outcome (compliance) will be performed using a simple or generalized linear model (based on its observed distribution). Variables most associated with compliance will be introduced into a multivariate model, including healthcare renunciation variables.

For the secondary objective (identifying the determinants of cessation of health care) a first approach based on unsupervised learning will make it possible to classify patients according to homogeneous profiles on the basis of the different information collected.

A classical multivariate analysis using a hierarchical logistic regression model will quantify the weight of the different determinants in the renunciation of care. Finally, an exploratory approach based on structural equation models based on latent variables will be implemented to establish the direct and indirect relationships of the different qualitative determinants collected in the questionnaires on caregiving.

Regarding the longitudinal approach, this will be the subject of several analysis steps. Firstly, on an annual basis, a descriptive analysis will be carried out to investigate the determinants of the cessation of care according to the status of patients (renouncing or not renouncing) the previous year. Regarding the five-year follow-up, mixed models will be used to identify different trajectories of patients with regard to the renunciation of care from the initial follow-up and to study their impact on the prognosis at 5 years in terms of deaths and number hospitalizations

Enrollment

1,083 patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Male or female over 18 years old
  • Patient with respiratory failure or obstructive sleep apnea
  • Treated with CPAP, NIV therapy for at least 12 months
  • Home monitoring by AGIR a dom
  • Voluntary patient to participate in research after adequate information and delivery of the information note
  • Patient affiliated with social security or beneficiary of such a scheme

Exclusion criteria

  • Pregnant, lactating or parturient woman
  • Person deprived of liberty by judicial or administrative decision, person subject to a measure of legal protection (patient under tutorship or curatorship) Article L1121-8

Trial contacts and locations

3

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Central trial contact

Sebastien SB Bailly, PharmD/PhD; Jean Louis JP Pepin, MD/PhD

Data sourced from clinicaltrials.gov

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