Real-World Deployment of an Ethical AI-Assisted Tele-Ultrasound Platform for Endometriosis Diagnosis in the Brazilian Public Health System: The EndoConnect Alpha Case Study and Its Evolution into the NAM-Endora Framework (Preprint)

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Abstract

BACKGROUND Endometriosis affects 10 % of reproductive-age women globally, with diagnostic delays of 7–10 years in Brazil’s SUS. Digital platforms offer promise, but few are ethically designed with AI for low-resource settings. OBJECTIVE To report real-world deployment of EndoConnect Alpha in SUS primary care, evaluate usability/acceptability, and describe its evolution into the NAM-Endora ethical AI framework. METHODS Applied methodological study. EndoConnect Alpha (React.js + Firebase) deployed in 10 SUS units (Ceará). n = 60 (45 patients, 15 professionals). Instruments: SUS, TAM, engagement metrics, clinical-psychosocial outcomes. Ethics CAAE 82094924.8.0000.5049. INPI BR5120250005556-0. RESULTS SUS 88.9 ± 9.8 (excellent); TAM 91.4.57/5. Trail completion 79 %. Pain reduction 23 % (VAS p=0.02), therapy adherence +17 %, anxiety −14 %. Strong SUS-TAM correlation (ρ=0.76, p<0.001). CONCLUSIONS EndoConnect Alpha is feasible and impactful in SUS. NAM-Endora provides scalable ethical AI governance for LMICs. Multicenter validation planned. CLINICALTRIAL Not applicable (formative research)
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Abstract

Background: Endometriosis affects 10 % of reproductive-age women globally, with diagnostic delays of 7–10 years in Brazil’s SUS. Digital platforms offer promise, but few are ethically designed with AI for low-resource settings.

Objective

To report real-world deployment of EndoConnect Alpha in SUS primary care, evaluate usability/acceptability, and describe its evolution into the NAM-Endora ethical AI framework.

Methods

Applied methodological study. EndoConnect Alpha (React.js + Firebase) deployed in 10 SUS units (Ceará). n = 60 (45 patients, 15 professionals). Instruments: SUS, TAM, engagement metrics, clinical-psychosocial outcomes. Ethics CAAE 82094924.8.0000.5049. INPI BR5120250005556-0.

Results

SUS 88.9 ± 9.8 (excellent); TAM 91.4.57/5. Trail completion 79 %. Pain reduction 23 % (VAS p=0.02), therapy adherence +17 %, anxiety −14 %. Strong SUS-TAM correlation (ρ=0.76, p<0.001).

Conclusions

EndoConnect Alpha is feasible and impactful in SUS. NAM-Endora provides scalable ethical AI governance for LMICs. Multicenter validation planned. Clinical Trial: Not applicable (formative research) Citation Request queued. Please wait while the file is being generated. It may take some time. Copyright © The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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Outcome instruments

VAS-pain

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endometriosis

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last seen: 2026-08-03T06:04:05.111620+00:00
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