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Background <p>In lower-middle-income countries (LMICs) like Pakistan, the high incidence and mortality of ischemic stroke pose significant challenges due to limited infrastructure and the scarcity of neurologists. Mobile health (mHealth) applications may bridge this gap by facilitating rapid and accurate diagnoses, which are critical for effective intervention. This study aims to describe the design, development, and initial testing phases of InstaDx, an android-based clinical decision support tool designed to assist neurology trainees and physicians in diagnosing ischemic stroke subtypes in high-volume, resource-constrained settings. The app aims to support neurology trainees in distinguishing stroke subtypes, a highly specialized task that requires knowledge of stroke pathophysiology, vascular anatomy, and the ability to interpret diagnostic imaging. The goal is to assist trainees in achieving diagnostic accuracy comparable to that of a vascular neurologist, thereby improving stroke diagnosis and care in LMICs where stroke specialists may not be readily available.</p> Results <p>InstaDx facilitates the diagnosis of ischemic stroke subtypes through a user-friendly interface, designed to function under constrained infrastructure conditions. Key features include offline capabilities, PDF versions of critical stroke scales, and flexible user-interface widgets, ensuring compatibility across diverse devices and screen sizes. The application employs alerts and dialogues to guide accurate data entry, with case processing times ranging from 5 to 7&#xa0;min. It also supports stroke risk stratification and diagnostic decision-making by incorporating laboratory findings to finalize the ischemic stroke subtype. Iterative testing phases—alpha (5 users), beta (10 users), and gamma (16 neurology residents)—led to significant enhancements, including layout adjustments, color scheme updates, and improvements to offline synchronization modules. Gamma testing with neurology residents highlighted the app’s potential to streamline the diagnostic process for ischemic stroke subtypes.</p> Conclusions <p>InstaDx represents a significant advancement in stroke care for LMICs, offering a scalable solution to overcome the challenges posed by limited availability of stroke specialists. The application’s design and testing phases indicate strong potential for enhancing stroke diagnosis and management, with further studies needed to evaluate its impact on clinical outcomes.</p>

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Development and initial implementation of InstaDx: a smartphone app for sub-type diagnosis of ischemic stroke

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月12日

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  • Saadia Sattar,
  • Wardah Kahlid,
  • Azmina Artani,
  • Syed Roohan Aamir,
  • Namrah Aziz,
  • Syed Zohaib,
  • Najeeya Khan,
  • Abdul Muqeet,
  • Fabiha Zaidi,
  • Nermeen Bashar,
  • Muhammad Usman,
  • Ambreen Gowani,
  • Shafquat Rozi,
  • Ayeesha Kamran Kamal

摘要

Background

In lower-middle-income countries (LMICs) like Pakistan, the high incidence and mortality of ischemic stroke pose significant challenges due to limited infrastructure and the scarcity of neurologists. Mobile health (mHealth) applications may bridge this gap by facilitating rapid and accurate diagnoses, which are critical for effective intervention. This study aims to describe the design, development, and initial testing phases of InstaDx, an android-based clinical decision support tool designed to assist neurology trainees and physicians in diagnosing ischemic stroke subtypes in high-volume, resource-constrained settings. The app aims to support neurology trainees in distinguishing stroke subtypes, a highly specialized task that requires knowledge of stroke pathophysiology, vascular anatomy, and the ability to interpret diagnostic imaging. The goal is to assist trainees in achieving diagnostic accuracy comparable to that of a vascular neurologist, thereby improving stroke diagnosis and care in LMICs where stroke specialists may not be readily available.

Results

InstaDx facilitates the diagnosis of ischemic stroke subtypes through a user-friendly interface, designed to function under constrained infrastructure conditions. Key features include offline capabilities, PDF versions of critical stroke scales, and flexible user-interface widgets, ensuring compatibility across diverse devices and screen sizes. The application employs alerts and dialogues to guide accurate data entry, with case processing times ranging from 5 to 7 min. It also supports stroke risk stratification and diagnostic decision-making by incorporating laboratory findings to finalize the ischemic stroke subtype. Iterative testing phases—alpha (5 users), beta (10 users), and gamma (16 neurology residents)—led to significant enhancements, including layout adjustments, color scheme updates, and improvements to offline synchronization modules. Gamma testing with neurology residents highlighted the app’s potential to streamline the diagnostic process for ischemic stroke subtypes.

Conclusions

InstaDx represents a significant advancement in stroke care for LMICs, offering a scalable solution to overcome the challenges posed by limited availability of stroke specialists. The application’s design and testing phases indicate strong potential for enhancing stroke diagnosis and management, with further studies needed to evaluate its impact on clinical outcomes.