SafeHands

Client

  • MCGL

Sector

  • Public Health

Healthcare-acquired infections remain a critical challenge in hospital settings, with hand hygiene representing the most effective preventive measure. Despite this established knowledge, global compliance rates average only 38.7%. Traditional supervision methods such as direct observation and manual feedback have proven to be resource-intensive and susceptible to bias. Often, they create barriers to behavioural change especially in resource scare settings such as labour rooms in hospitals.

The SafeHands project employed human-centered design to understand this implementation gap and explore how AI could support hand hygiene compliance in Indian public hospitals. Implemented between June 2021 and June 2022, the initiative installed an AI-enabled system called VajraHands (developed by DataKalp) across seven district and sub-district hospitals in Chhattisgarh, Jharkhand, and Madhya Pradesh.

Research questions

The project focuses largely on three interconnected objectives:

  • Understand how hand hygiene is practiced within public health settings, including structural, knowledge-based, and motivational factors shaping compliance.
  • Explore the potential of AI-enabled feedback systems in improving adherence to WHO handwashing protocols.
  • Co-develop digital and non-digital interventions grounded in actual user needs and institutional contexts.

Methodology

Foundational research

Quicksand, with support from Jhpeigo and DataKalp, conducted qualitative research with 30+ stakeholders across labour room staff cadres and management levels through remote in-depth interviews, followed by field observations, and focused group discussions. The team approached the development of research tools by relying on storytelling instead of emphasising  on technical terminology. This decision was shaped by the formative research that indicated low data literacy and limited time between different tasks.

To synthesise the findings from primary research, the team applied the Manoff Group's Toolkit for Behaviour Integration. This toolkit became central in understanding the factors impacting two distinct behaviours in the handwashing patterns of staff members: uptake of VajraHands and adherence to WHO protocols. These factors were prioritized based on importance and feasibility, some key barriers included surveillance concerns, confusing interface design and decision logic, as well as technical inconsistencies. However, the research also pointed towards some enabling factors, most importantly—that labour room in-charges could train teams using real-time feedback, and duration information to encourage self-monitoring.

Co-design process

Following research synthesis, brainstorming sessions with stakeholders were organized to ideate on behavior change frameworks. A vital development were the concept cards used for qualitative research to help interviewees visualise potential interventions, based on feedback gathered from the hospital sites.  The design team took the intervention ideas that staff responded positively to during concept testing and checked them against the behavioral factors—the barriers and enablers—identified during research. This ensured that the redesigned interface and complementary activities directly addressed the real obstacles and motivations affecting handwashing compliance.

VajraHands 2.0

Interface

Rather than providing retrospective feedback after handwash completion, the new interface adopted a sequential model where users performed each step as it appeared on screen. Custom animated GIFs were replaced with static graphics, and red crosses appeared instantly for incorrect steps, in contrast with the old interface that indicated errors after completion of handwash.

A "SafeHands Sakhi" mascot also provided encouragement, adapting from observations indicating that health workers rely heavily on peer learning. Visual tools—enlarged step demonstrations, real-time progress feedback along with educational screensavers—and replaced instructions in Hindi were used to create effective communication between staff members and the tech tool.

The launch of VajraHands 2.0 was complemented by an orientation for the staff and management at all sites These complementary activities, on the other hand, became imperative in addressing larger organisational and motivational factors which included adult learning principles, interactive activities, and video resources.

New interface - feedback displayed during a handwash

Differentiated intervention groups

Group A: Training of Trainers (ToT) sessions equipped selected staff and management to conduct peer learning on hand hygiene and team cohesion using provided resource kits. Management participated in regular meetings discussing performance reports and establishing targets. Facilities collected patient feedback on ward hand hygiene. A six-week competition offered rewards based on compliance and improvement points.

Group B (Lean): Received orientation and performance reports only.

This stratification enabled assessment of inclusion, cohesion, and varied accountability mechanisms—meetings, self-driven targets, patient feedback, and rewards—on hand hygiene outcomes.

Implications

The SafeHands project demonstrates both potential and limitations of AI-enabled behavior change systems in resource-constrained settings. VajraHands proved most effective when integrated with human-mediated supervision rather than operating as standalone solution. The transition from version 1.0 to 2.0 illustrates how interface design and decision logic transparency fundamentally shape user trust and adoption.

Hospital context created differential effects: larger facilities serving broader geographical areas faced greater challenges maintaining protocol adherence under time pressure. While performance visibility generated initial behavior change, sustainability demanded sustained management commitment and integration into institutional quality assurance processes. The research establishes groundwork for scaling AI-enabled systems while highlighting necessary conditions: responsive interface design, integration with existing infrastructure, management capacity building, and attention to power dynamics within hierarchical health systems.

Related

Case Study

How AI and Human-Centred Design Improved Hand Washing in Public Hospitals

SafeHands

Leveraging Human-Centered Design and AI Systems for Behaviour Change in Health