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NCT Number: NCT07500532

Evaluation of the Medentum Diagnostik Platform for Pediatric ENT Conditions and Asthma

This study evaluates the diagnostic performance, usability, and clinical utility of the Medentum Diagnostik platform, a multisensor device with integrated software and artificial intelligence, in pediatric patients with asthma and ENT conditions. Participants will be assigned to either home-based use of the Diagnostik platform with telehealth-supported clinician evaluation or standard in-person care.

The primary objective is to assess agreement between AI-generated diagnoses and clinician diagnoses obtained during study encounters, including telehealth evaluations in the Diagnostik arm and in-person evaluations in the standard-of-care arm. Secondary objectives include evaluating agreement between AI-generated diagnoses and independent research team diagnoses, as well as assessing usability, patient and caregiver satisfaction, healthcare utilization, and clinical outcomes such as asthma control and symptom resolution.

This study will also evaluate differences in healthcare utilization, including in-person visits, emergency care use, and time to diagnosis and treatment, between study groups.

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Key information

Age range

3 year–17 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

El Rio Health System

Tuscon, Arizona, 85745, United States

Location status: Recruiting

Location contact

Erin Dougherty, Masters Degree

CONTACT

[email protected]

520-670-3909

About this study

Study Design and Methodology

This study is a randomized, controlled clinical trial designed to evaluate the diagnostic performance, usability, and clinical utility of the Medentum Diagnostik platform in pediatric patients with asthma and ear, nose, and throat (ENT) conditions, including acute otitis media and pharyngitis .

Participants will be randomized to one of two groups:

  • home-based use of the Diagnostik platform with telehealth-supported clinician evaluation (intervention arm), or
  • standard-of-care clinical evaluation via in-person or telehealth visits without use of the Diagnostik platform (control arm).

The study duration is 6 months. Intervention participants will use the Diagnostik platform during symptomatic episodes and for monthly monitoring (asthma patients), while control participants will receive routine clinical care. Follow-up data will be collected through platform data, medical record review, and patient-reported outcomes.

Intervention and Data Collection

Participants in the intervention arm will use the Diagnostik platform, which integrates a smartphone application with a multifunctional medical device, including a digital stethoscope, otoscope, thermometer, and pulse oximeter, to collect clinical data at home .

During symptomatic episodes, participants will:

Record lung sounds using the digital stethoscope Capture images of the ear or throat Enter symptom data and complete relevant questionnaires (e.g., Asthma Control Test) Measure vital signs, including temperature, heart rate, and oxygen saturation

The platform's AI algorithms will analyze these data to generate a preliminary diagnostic assessment (e.g., presence or absence of wheeze, acute otitis media, pharyngitis). Intervention participants will then undergo a telehealth consultation with a clinician who will review the collected data, consider the AI-generated assessment, and establish a clinical diagnosis.

Participants in the control arm will receive standard clinical care, including in-person or telehealth evaluations, during which clinicians will make diagnoses based on routine clinical assessment and testing.

Primary Outcome Assessment

The primary objective is to assess agreement between AI-generated diagnoses and clinician diagnoses obtained during study encounters. Clinician diagnoses will be established via telehealth evaluation in the intervention arm and via standard-of-care evaluation (in-person or telehealth) in the control arm.

Diagnostic agreement will be evaluated separately for asthma and ENT conditions. Lung sounds will be assessed for the presence or absence of wheeze, and ear/throat images will be evaluated for acute otitis media and pharyngitis. Agreement between AI and clinician diagnoses will be quantified using percent agreement and Cohen's kappa.

Secondary and Exploratory Assessments

Secondary analyses will include evaluation of agreement between AI-generated diagnoses and research team diagnoses. Research diagnoses will be established by independent clinicians, including pediatric pulmonologists, based on blinded review of lung sound recordings and ear/throat images collected using the Diagnostik platform.

Additional secondary outcomes will include usability, patient and caregiver satisfaction, healthcare utilization, and clinical outcomes such as symptom days, asthma control, rescue inhaler use, and time to symptom resolution. Healthcare utilization measures will include in-person visits, emergency department visits, and time to diagnosis and treatment.

Exploratory analyses will assess the performance of the AI system across clinical conditions and care settings.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age: Patients between the ages of 4 and 17 years (asthma) and 3-17 years (ENT)
  • Diagnosis:

o Asthma patients: Diagnosed with mild-to-moderate and severe persistent asthma according to Global Initiative for Asthma (GINA) guidelines, with a history of symptoms or exacerbations requiring medical intervention (prior prednisone course and/or albuterol for >24 hours in context of acute wheezing episode) in the past 12 months. ENT patients: Diagnosed with common ENT conditions such as acute otitis media (AOM) or strep pharyngitis in the prior year. Diagnosis must be based on established clinical guidelines.

  • Technology access: Must have access to a smartphone, tablet, or other device capable of running the Medentum Diagnostik platform app and access to Wifi or cellular service.
  • Care access: Must be receiving routine care from University of Arizona or associated clinics in Arizona and have active health insurance
  • Consent: Must have parental or guardian consent for participation, as well as child assent when appropriate.(all children ≥7 yrs)

Exclusion criteria

  • Other medical conditions: Patients with additional chronic lung diseases (such as cystic fibrosis) requiring complex specialist care will be excluded. cerebral palsy, neurodevelopmental conditions, congenital heart disease. Patients with complex chronic conditions or chronic ENT conditions requiring complex specialist care will be excluded.
  • Recent surgical/complex ENT medical history: Patients who have had tympanostomy tubes or tonsillectomy/adenoidectomy, patients with chronic ENT conditions including chronic suppurative or serous otitis media
  • Recent medical history: Patients who have experienced severe asthma exacerbations requiring hospitalization or intensive treatment in the past 4 weeks
  • Comorbidities: Patients with speech delays, hearing impairments, or cognitive impairments that may affect their ability to use the Diagnostik platform accurately will be excluded.
  • Non-compliance risk: Patients or families that are unable to follow study instructions, comply with follow-up visits, or properly use the Medentum platform will be excluded.

Treatment and study plan

Diagnostik home-based platform: multisensor device, software application, and artificial-intelligence algorithms that predict diagnosis of AOM and strep pharyngitis

Device

Diagnostik home-based platform: multisensor device, software application, and artificial-intelligence algorithms that predict diagnosis of AOM and strep pharyngitis

Diagnostik home-based platform: multisensor device, software application, and artificial-intelligence algorithms that predict diagnosis of wheeze/asthma exacerbation

Device

Diagnostik home-based platform: multisensor device, software application, and artificial-intelligence algorithms that predict diagnosis of wheeze/asthma exacerbation

Routine Asthma Management (in-person and telehealth visits)- Control Group

Other
  • Patients randomized to the control group will receive standard care through routine in-office visits or telehealth visits.
  • Patients in the control group will visit the clinic whenever they experience symptoms related to their asthma condition or any other non-respiratory, non-ENT medical condition.
  • Telehealth visits will be offered as per routine and determined by the medical provider.
  • Asthma patients will undergo a physical exam, and other lab studies (e.g. Covid, strep tests) as determined by the provider to aid in diagnosis and treatment plan. The medical provider will make a diagnosis based on these routine in-office or telehealth assessments.
  • Control group patients will have routine well-care in-office follow-ups at a frequency as determined by their routine provider.

Routine ENT Management (in-person and telehealth visits)- Control Group

Other
  • Patients randomized to the control group will receive standard care through routine in-office visits or telehealth visits.
  • Patients in the control group will visit the clinic whenever they experience symptoms related to their ENT condition or any other non-respiratory, non-ENT medical condition.
  • Telehealth visits will be offered as per routine and determined by the medical provider.
  • ENT patients will undergo a physical exam, and other lab studies (e.g. Covid, strep tests) as determined by the provider to aid in diagnosis and treatment plan. The medical provider will make a diagnosis based on these routine in-office or telehealth assessments.
  • Control group patients will have routine well-care in-office follow-ups at a frequency as determined by their routine provider.

Primary outcomes

  1. Diagnostic concordance between AI and physician/clinician

    Time frame: 6 months

    Arms and Interventions: Participants will be randomized to (1) home-based use of the Diagnostik device with telehealth-supported clinician evaluation or (2) in-clinic standard-of-care evaluation.

    Primary Outcome: Agreement between AI-generated diagnosis and clinician diagnosis obtained during the study encounter. Clinician diagnosis will be determined via telehealth evaluation in the Diagnostik arm and in-person standard-of-care evaluation in the control arm. Participants will use the Diagnostik device to collect lung auscultation recordings via digital stethoscope and capture ear or throat images. AI algorithms will assess lung sounds for presence or absence of wheeze and images for acute otitis media and pharyngitis. Clinicians will establish diagnoses based on their respective evaluation modality. Agreement between AI and clinician diagnoses will be assessed separately for asthma and ENT conditions using percent agreement and Cohen's kappa. A concordance rate ≥85% is anticipated.

Secondary outcomes

  1. Agreement between AI-generated diagnosis and research team diagnosis.

    Time frame: 6 months

    The research diagnosis will be established by an independent panel of clinicians, including pediatric pulmonologists, based on blinded review of lung sound recordings and ear/throat images collected using the Diagnostik device. Agreement will be assessed separately for asthma and ENT conditions using percent agreement and Cohen's kappa. Sensitivity and specificity may also be calculated.

  2. Usability: Net Promoter Score

    Time frame: 6 months

    Usability assessed using standardized questionnaires evaluating ease of use, patient satisfaction, Net Promoter Score (NPS), and technical difficulties encountered during platform use. NPS is scored from 0 to 100, with higher scores indicating greater user satisfaction. Questionnaires will be administered at 3 and 6 months. Additional measures will include convenience-related outcomes such as time from symptom onset to diagnosis and treatment, distance traveled, and wait times. We anticipate NPS of >70.

  3. Emergency Room Visit

    Time frame: 6 months

    Utilization outcome: Compare emergency room visit for ENT or asthma condition between the control standard of care, and at-home Diagnostik groups.

  4. Unscheduled medical visit for asthma or ENT condition

    Time frame: 6 months

    Healthcare utilization measured as the number of unscheduled in-person visits for asthma or ENT symptoms, including urgent care and emergency room visits, compared between study groups. Additional measures include symptom days, asthma control days, time to symptom resolution, rescue inhaler use, Asthma Control Test (ACT) scores, and complication rates.

  5. Asthma Control Test Score

    Time frame: 6 months

    Team will assess Asthma Control Test (ACT) standardized scores between the two groups

  6. Symptom Days

    Time frame: 6 months

    The team will measure the number of days of asthma/ENT symptoms between the two groups.

  7. Frequency of Rescue Inhaler Use

    Time frame: 6 months

    The team will measure the frequency of rescue inhaler use between the control and intervention asthma groups.

Study contacts

Contact information is provided by the study sponsor or research team.

Starla Kiser, Medical Degree

CONTACT

[email protected]

276-212-1863

Sponsors and collaborators

Lead sponsor

Medentum Innovations

Industry

Collaborators

  • El Rio Community Health Center
  • National Institutes of Health (NIH)
  • University of Arizona

Registry information

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Mar 30, 2026
Registry last updated
Mar 30, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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