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Record W3172321909 · doi:10.2196/26059

Design, Development, and Evaluation of a Telemedicine Platform for Patients With Sleep Apnea (Ognomy): Design Science Research Approach

2021· article· en· W3172321909 on OpenAlexvenueno aff
Pavankumar Mulgund, Raj Sharman, Daniel I. Rifkin, Sam Marrazzo

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTelemedicineChatbotUsabilitySleep apneaMedicinePopulationComputer scienceMedical emergencyHealth careWorld Wide WebHuman–computer interaction

Abstract

fetched live from OpenAlex

BACKGROUND: With an aging population and the escalating cost of care, telemedicine has become a societal imperative. Telemedicine alternatives are especially relevant to patients seeking care for sleep apnea, with its prevalence approaching one billion cases worldwide. Increasing awareness has led to a surge in demand for sleep apnea care; however, there is a shortage of the resources and expertise necessary to cater to the rising demand. OBJECTIVE: The aim of this study is to design, develop, and evaluate a telemedicine platform, called Ognomy, for the consultation, diagnosis, and treatment of patients with sleep apnea. METHODS: Using the design science research methodology, we developed a telemedicine platform for patients with sleep apnea. To explore the problem, in the analysis phase, we conducted two brainstorming workshops and structured interviews with 6 subject matter experts to gather requirements. Following that, we conducted three design and architectural review sessions to define and evaluate the system architecture. Subsequently, we conducted 14 formative usability assessments to improve the user interface of the system. In addition, 3 trained test engineers performed end-to-end system testing to comprehensively evaluate the platform. RESULTS: Patient registration and data collection, physician appointments, video consultation, and patient progress tracking have emerged as critical functional requirements. A telemedicine platform comprising four artifacts-a mobile app for patients, a web app for providers, a dashboard for reporting, and an artificial intelligence-based chatbot for customer onboarding and support-was developed to meet these requirements. Design reviews emphasized the need for a highly cohesive but loosely coupled interaction among the platform's components, which was achieved through a layered modular architecture using third-party application programming interfaces. In contrast, critical findings from formative usability assessments focused on the need for a more straightforward onboarding process for patients, better status indicators during patient registration, and reorganization of the appointment calendar. Feedback from the design reviews and usability assessments was translated into technical improvements and design enhancements that were implemented in subsequent iterations. CONCLUSIONS: Sleep apnea is an underdiagnosed and undertreated condition. However, with increasing awareness, the demand for quality sleep apnea care is likely to surge, and creative alternatives are needed. The results of this study demonstrate the successful application of a framework using a design science research paradigm to design, develop, and evaluate a telemedicine platform for patients with sleep apnea and their providers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.044
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.379
GPT teacher head0.564
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2021
Admission routes1
Has abstractyes

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