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A multi-country study comparing typed to automatic speech recognition-based medical documentation speeds among Low- and Middle-Income Country Trained Clinicians

Olatunji, T.; Aka, C.; Okocha, C.; Katuka, G.; Tassallah, A.; Etori, N.; Ismaila, L.; Mateen, B. A.; Weintraub, R.

2025-05-13 health informatics
10.1101/2025.05.11.25327386 medRxiv
Show abstract

For decades, medical voice dictation and scribe services have boosted productivity in high-resource settings. Yet, they remain virtually absent in low- and middle-income countries (LMICs), where healthcare systems face physician shortages and heavier patient loads, but rely on outdated, paper-based workflows. Digital transformation efforts in these settings often overlook a critical barrier: the limited computer proficiency of overworked clinicians. While voice input is typically considered a suitable alternative that alleviates the additional cognitive burden from keyboard-based data entry, studies in high-resource settings report mixed findings on its efficiency. This study evaluates whether those findings hold in LMIC contexts. We assessed typing and dictation speeds among over 1,000 clinicians and health workers across 60+ hospitals in 15+ LMICs. Results reveal a median keyboard speed of just 21.4 words per minute (wpm), compared to dictation speeds of 4-5x faster on average (median 93 wpm). This significant speed improvement underscores the potential of speech recognition to reduce documentation burdens, improve workflow efficiency, and transform clinician experiences, evoking feelings of regret at the time lost to inefficient systems, and reinforcing the urgency of integrating voice solutions into LMIC digital health strategies.

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