A call to action to close the global digital divide in nursing: Clinical nursing information systems and standardized terminologies in low and middle-income countries
Animesh Ghimire
What the paper says
Clinical Nursing Information Systems (CNISs) and Standardized Nursing Terminologies (SNTs) significantly enhance the quality of care, promote interoperability, and enable measurable nursing outcomes. However, their adoption remains inconsistent, particularly in low- and middle-income countries (LMICs). This commentary reframes the existing gap as an issue of equity and systems design while providing a feasibility-prioritized roadmap tailored for LMICs. The article supports a sequenced approach that distinguishes between short-term actions and longer-term initiatives. Short-term actions include stabilizing infrastructure, developing open-source CNIS models, initiating terminology localization pilots, implementing essential data privacy safeguards, and providing targeted in-service training. In contrast, longer-term initiatives involve establishing national standards and exchanges, securing sustainable financing, cultivating leadership pipelines and curricula, and promoting cross-border interoperability and evaluation. Furthermore, it delineates various financing mechanisms-including concessional loans, performance-based grants, and collective procurement-while also addressing strategic considerations related to policy and governance frameworks. The commentary concludes with an explicit call to action: policymakers, donors, nursing leaders, educators, and vendors must collaborate to integrate structured nursing data into routine care and national platforms. Bridging this gap will render nursing work more visible, enhance decision support, and foster learning health systems within hospitals and communities worldwide.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.