India AI Impact Summit 2026

building-ai-readiness-and-digital-competency-among-frontline-health-workers-in-india

6 min read

TRACK:Human Capital
SPEAKERS
  • Dr Valerie Jean Laloo, MBBS, MD, State Health Systems Resource Centre (SHSRC), Meghalaya
  • Dr. Amnesty LeFevre, PhD MHS, University of Cape Town and Johns Hopkins School of Public Health
  • Dr. Diwakar Mohan, PhD MPH MD MBBS, Johns Hopkins School of Public Health
  • Dr. Karthik Adapa, IAS, Digital Health, WHO-SEARO
  • Dr. Marbabiang Syiemlieh, PhD, Gender Studies & Social Work, The State Health System Resource Centre (SHSRC), Meghalaya
  • Dr. Mayank Date, MPH BDS, The Johns Hopkins Bloomberg School of Public Health
  • Dr. Nayanjeet Chaudhury, MBBS MD MPH, State Health Systems Resource Centre (SHSRC), Meghalaya
  • Dr. Osama Ummer MPH BAMS, Digital health innovations and health systems Research
  • Dr. Sampath Kumar, IAS, Health & Family Welfare, Government of Meghalaya
  • Mebanialam Tang, MA, The State Health Systems Resource Center (SHSRC), Meghalaya
  • Nishanlang Khonglah, MA BE, The State Health Systems Resource Center (SHSRC), Meghalaya
  • Smt. Shyamashree Das, The Gates Foundation India Country Office
SESSION OVERVIEW

This interactive workshop brings together public health leaders to build consensus on measuring digital access, use, and skills among frontline health workers. Participants will explore AI readiness frameworks, co-design skill metrics for frontline health workers and healthcare providers, and evaluate assessment methods. The session concludes with practical recommendations for scalable, context-aware digital skills measurement across regional and national health workforces.

VIDEO RECORDING

Building AI Readiness and Digital Competency Among Frontline Health Workers in India

Abstract

The workshop gathered public‑health leaders, academics, and development partners to examine how AI‑driven tools can be introduced responsibly among India’s frontline health workforce. Participants reviewed the current health‑system gaps in Meghalaya, explored global digital‑competency frameworks, mapped the competencies required by various health‑worker cadres (including ASHAs, ANMs, and village health councils), and co‑designed a measurement pathway that blends tool development, cognitive testing, and field surveys. The session concluded with concrete recommendations for scaling a context‑aware digital‑skill assessment across the state and, ultimately, the nation.

Detailed Summary

  • Welcomed participants, clarified that the session would be interactive rather than a lecture.
  • Emphasised that digital tools (EHRs, tele‑medicine, real‑time surveillance, AI‑supported decision making) are now essential for delivering equitable health services.
  • Stressed that technology alone cannot transform health systems; the “real strength” lies in people who are competent, confident, and ethically grounded.

2. Contextual Challenges in Meghalaya (Dr Sampath Kumar)

  • Highlighted the state’s high maternal mortality rate (≈ 3 × national average) and the fact that 25 % of villages are hard‑to‑reach.
  • Described the historic “top‑down” approach: massive national programs were implemented without empowering frontline workers, leading to low ownership and ineffective use of data.
  • Asserted that a shift in identity—viewing frontline workers as problem‑solvers rather than mere implementers—is pivotal.

3. Vision of “State Capability” (Dr Sampath Kumar)

  • Introduced a 2020 framework aimed at building state capability through:
    1. Decentralised leadership at the frontline.
    2. Data‑driven motivation (using real‑time data to demonstrate impact).
    3. Adaptive leadership – handing problem‑solving authority back to local providers.
  • Called the approach a “mission‑economy” where the state’s transformative power lies in its people.

4. Digital‑Competency Rationale (Ms Shama Shridas)

  • Announced an MOU with the Government of Meghalaya that originally focused on digital health, now expanding to AI.
  • Stated that AI tools are entering “center stage” and that competence is the core prerequisite for safe, effective adoption.
  • Illustrated that existing apps (e.g., the ASHAs’ incentive‑management app) are evolving to include decision‑support, stock‑management, and referral features.
  • Argued that competency mapping must be granular because frontline workers are heterogeneous (different cadres, literacy levels, and work contexts).

5. Conceptual Foundations of Digital Competency (Dr Amnesty Le‑Fevre)

  • Distinguished digital literacy (knowledge of technologies) from digital competency (confident, critical, responsible application).
  • Presented the DIGCOMP framework (five domains, multiple competency areas) and the ITU digital‑skills indicator as global reference points.
  • Noted limitations of these tools for mobile‑first, low‑resource populations, prompting the creation of a digital‑access‑and‑use index tailored to India.

6. Mapping Competencies for Health‑Worker Cadres (Dr Diwakar Mohan)

  • Described a four‑step process: tool development → implementation → analysis → use.
  • Showed how domain‑specific, functional/technical, and behavioural competencies were identified for four cadres (ANMs, MLHPs, staff nurses, medical officers).
  • Provided a workflow simulation (e.g., a woman in third‑stage labor) to illustrate where digital tasks (recording vitals, reporting, referral) intersect with clinical duties.
  • Emphasised that digital skills are integral, not optional, for every point of care interaction.

7. Extending the Mapping to Village Health Councils (VHCs) (Dr Marbabiang Syiemlieh)

  • Explained that VHCs (≈ 6 700 across Meghalaya) act as the bridge between the health system and communities, with ≥ 50 % women among 10‑member executive committees.
  • Described their role in outcome‑based budgeting (OBB), ensuring community priorities shape health‑planning and resource allocation.
  • Outlined a digital‑competency assessment pipeline for VHCs:
    1. Map core and digital competencies.
    2. Analyse existing app‑derived data.
    3. Conduct surveys on meeting attendance, tool usage, etc.
    4. Classify VHCs by functionality level.
    5. Co‑design a performance scorecard and feedback loop to strengthen leadership and ownership.

8. Tool Development & Cognitive Testing (Dr Osama Ummer & Dr Mayank Date)

  • Reported that cognitive testing (qualitative rounds) was used to ensure survey items were understood in the local worldview.
  • Compared self‑report, observed skills, and mixed methods; participants favoured a mixed approach, with a slight preference for observation.
  • Highlighted a pilot survey in another Indian state showing:
    • Gender disparities in digital skill levels.
    • Under‑reporting of skills was more common than over‑reporting; participants often failed to demonstrate skills they claimed to possess.
  • Discussed specific challenges for ASHAs (low literacy, heavy workload, long travel distances) that affect digital‑skill measurement.

9. Turning Data into Action (Dr Nishanlang Khonglah)

  • Suggested using the collected data to:
    • Build monitoring‑and‑evaluation dashboards.
    • Guide resource allocation (targeted training, hardware provision).
    • Create composite indices or skill‑specific scores depending on the policy question.
  • Emphasised the need to tailor measurement techniques to the respondent’s context and the specific competencies being examined.

10. WHO Perspective – Bottom‑Up Competency Building (Dr Karthik Adapa)

  • Stressed that global digital‑health strategies often start at the top of the health‑system pyramid; Meghalaya’s approach flips this by beginning with frontline workers.
  • Noted the burden on ASHAs (≈ 90–120 passwords for different tools) and the risk of “mission‑bureaucracy” fatigue without proper competence.
  • Highlighted WHO’s commitment to scaling this model beyond Meghalaya to other Indian states and South‑Asian countries.

11. Closing Remarks & Takeaways (Dr Valerie Laloo & Panel)

  • Reiterated that the workshop laid the foundation for AI‑ready health systems by establishing a systematic digital‑competency framework.
  • Acknowledged Gates Foundation, WHO, University of Cape Town, Johns Hopkins, and Meghalaya Government for collaborative leadership.
  • Invited participants to join the ongoing journey of assessment, evaluation, and implementation.

Key Takeaways

  • Frontline empowerment is essential: AI and digital tools can only improve health outcomes when frontline workers are competent, motivated, and trusted.
  • State‑capability framework: Meghalaya’s 2020 framework links decentralized leadership, data‑driven motivation, and adaptive problem‑solving to build AI readiness.
  • Digital‑competency mapping must be granular: Separate domain‑specific, functional, behavioural, and digital competencies for each cadre (ASHAs, ANMs, nurses, doctors).
  • Use of global standards with local adaptation: DIGCOMP and ITU indicators provide a baseline, but a mobile‑first, context‑aware digital‑access index is required for India’s heterogeneous settings.
  • Iterative tool development: Cognitive testing, mixed self‑report/observational methods, and pilot surveys ensure measurement tools resonate with local realities.
  • Evidence of skill gaps: Pilot data reveal gender disparities and frequent under‑reporting of digital skills, underscoring the need for targeted training.
  • Village Health Councils are pivotal: Embedding digital competency assessment within VHCs strengthens community‑state linkages, improves budgeting relevance, and fosters local ownership.
  • Data‑driven action: Collected competency data should feed into dashboards, resource‑allocation models, and tailored capacity‑building programs.
  • Bottom‑up approach aligns with WHO strategy: Starting with frontline workers rather than physicians ensures sustainable AI integration across the health system.
  • Scalable collaboration: The partnership among state government, Gates Foundation, WHO, and academic institutions creates a replicable model for other Indian states and the broader region.

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