Nursing Minimum Datasets in Long-Term Care Settings: Scoping Review.

Area of Science:

• Nursing Informatics
• Health Services Research
• Data Standardization

Background:

• Standardized data collection is essential for nursing research, data comparison, and leveraging technological advancements in healthcare.
• Nursing minimum datasets (NMDSs) are key tools for achieving structured data collection in the health sector.

Purpose of the Study:

• To conduct a scoping review presenting the current state of research on nursing minimum datasets (NMDSs) within long-term care settings.
• To identify and analyze existing NMDS projects, their characteristics, and their application in long-term care.

Main Methods:

• A comprehensive literature search was performed across PubMed, CINAHL, Embase, and DPLA databases up to September 2024.
• Included articles underwent double-review screening and qualitative content analysis, supplemented by citation tracking and manual searches.
• Narrative synthesis was employed to consolidate findings from 36 selected sources representing 9 NMDS projects.

Main Results:

• The review identified 36 sources related to 9 NMDS projects, with a peak in publications between 2004-2015 and increased relevance noted from 2022-2024.
• The United States leads in NMDS research (44% of sources), with identified datasets categorized as patient, interpersonal, or institutional data.
• While numerous initiatives exist, few are fully developed or operational, indicating a gap between conceptualization and implementation.

Conclusions:

• NMDS initiatives are gaining importance due to digitalization and legislative changes, particularly in Europe.
• Current NMDS primarily capture patient data, with limited attention to nursing interventions, outcomes, and patient perspectives.
• A need exists for standardized descriptions, scientifically usable content, legal frameworks, and increased collaboration among stakeholders to advance NMDS development and utilization.