Clinical trial NCT05064579: Towards an Algorithmic Approach to Asthma Management: Collaborative Definition of Algorithm Objectives With Families
Official title: Towards an Algorithmic Approach to Asthma Management: Collaborative Definition of Algorithm Objectives With Families
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Childhood Asthma
Keywords: Childhood asthma
Algorithms for managing childhood asthma
Big data
Artificial intelligence
Lead sponsor: Assistance Publique - Hôpitaux de Paris
Sponsor class: OTHER
First posted: 2021-10-01
Enrollment: 307
Sex: ALL
Minimum age (years): 8
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Participants will be recruited in hospitals in the Ile-de-france region

Brief summary: Using "big data" and artificial intelligence techniques, it becomes possible to envision algorithms for managing childhood asthma on a daily basis.

In order to develop such tools, it is necessary to determine with asthma stakeholders (children, parents, doctors) the parameters that future algorithms should seek to maximize / minimize.

The main objective of the study is to quantify the respective importance of each of the goals that children with asthma, parents, and their doctors seek to achieve when taking / supervising / prescribing a background therapy.

Detailed description: Using "big data" and artificial intelligence techniques, it becomes possible to envision algorithms for managing childhood asthma on a daily basis.

In order to develop such tools, it is necessary to determine with asthma stakeholders (children, parents, doctors) the parameters that future algorithms should seek to maximize / minimize.

The main objective of the study is to quantify the respective importance of each of the goals that children with asthma, parents, and their doctors seek to achieve when taking / supervising / prescribing a background therapy.

To do this, parents and children fill out a paper questionnaire, which is completed by their doctor, when they come to the hospital for consultation, hospitalization, or to perform lung function tests.

Concerning children and parents, these questionnaires include a part aimed at prioritizing each person's objectives and a second part collecting general information regarding their characteristics (age, sex, asthma history, etc.).

Eligibility criteria: Inclusion Criteria:

* Minor patients aged 8 years to 17 years and 11 months inclusive with a diagnosis of asthma made by a doctor and a basic treatment for asthma
* Holders of parental authority for patients meeting the above criteria
* Doctors caring for children with asthma
* Information and non-opposition of holders of parental authority and minor patients to participate in the study

Exclusion Criteria:

* Refusal to participate in the study
* Difficulties in French writing and / or speaking

Primary outcomes:
measure: Mean score attributed to each goal
timeFrame: Day 0
Secondary outcomes:
measure: Correlation of goals between respondents
timeFrame: Day 0
Other outcomes:
Locations:
city: Boulogne-Billancourt
country: France
facility: Hôpital Ambroise Paré
city: Colombes
country: France
facility: Hôpital Louis Mourier
city: Paris
country: France
facility: Hôpital Trousseau-Allergologie pédiatrique
city: Paris
country: France
facility: Hôpital Trousseau-Pneumologie pédiatrique
city: Paris
country: France
facility: Hôpital Necker-Enfants Malades
city: Paris
country: France
facility: Hôpital Robert Debré
Study officials:
affiliation: Assistance Publique - Hôpitaux de Paris
name: David Drummond, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Masrour O, Personnic J, Amat F, Abou Taam R, Prevost B, Lezmi G, Gonsard A, Nathan N, Pirojoc A, Delacourt C, Wanin S, Drummond D. Objectives for algorithmic decision-making systems in childhood asthma: Perspectives of children, parents, and physicians. Digit Health. 2024 Feb 21;10:20552076241227285. doi: 10.1177/20552076241227285. eCollection 2024 Jan-Dec.