Introduction: The Growing Need for Standardized Nursing Data in Long-Term Care
As populations age and care needs become more complex, long-term care facilities—from nursing homes to rehabilitation centers—face a surge in data requirements. Nursing minimum datasets (NMDSs) are designed to provide a standardized, uniform set of nursing information that supports multiple data users in the health system. Originating from Werley and colleagues’ concept of a minimum set of items with clear definitions, NMDSs aim to describe nursing care, enable cross-setting comparisons, and drive policy and research within digital health ecosystems.
This scoping review examines NMDS initiatives specifically in long-term care settings. It situates NMDSs within Europe’s demographic shifts, the systemic push toward digital records, and legislative efforts to harmonize data use for quality improvement and research. The review also highlights challenges—especially data validity, completeness, and comparability—that influence the reliability of conclusions drawn from NMDS analyses.
Why NMDSs Matter in Long-Term Care
The long-term care sector requires reliable, standardized data to plan staffing, allocate resources, and monitor resident outcomes. NMDSs can help illuminate what constitutes effective nursing care across residential homes and rehabilitation facilities, support population-level research, and inform policy decisions. The COVID-19 pandemic exposed gaps in data infrastructure, underscoring the urgency of interoperable datasets. Countries like Germany illustrate how digital health legislation can promote NMDS adoption, integrate electronic health records, and enable data access for research while maintaining privacy and security.
However, for NMDSs to deliver on their promise, elements must be valid, consistently documented, and retrievable from patient records. Inconsistent or missing data undermine cross-country comparisons and hinder evidence-based improvements in care quality.
What NMDS Initiatives Exist in Long-Term Care?
Across the literature, NMDS projects in long-term care include country-specific datasets, cross-national adaptations, and topic-focused datasets supporting research and practice. The United States hosts a foundational NMDS with ongoing relevance, while the United Kingdom has advanced the Developing Resources and Minimum Data Set for Care Homes’ Adoption (DACHA) study to improve data accessibility and interoperability in care homes. Canada and Germany also contribute through rehabilitation-specific datasets and core data elements aligned with broader national initiatives, such as the MII core dataset and related intersectoral repositories.
Recent work often centers on translating or adapting existing U.S. NMDSs for other health systems, as well as creating context-specific items for long-term inpatient settings. A notable pattern is the emphasis on standardization rather than reinventing the wheel, with a focus on ensuring that NMDS content supports both clinical care and research needs.
What Do NMDSs Contain in Long-Term Care?
To categorize the contents, researchers typically follow a three-part model: patient data, interpersonal data, and institutional data. The majority of elements in many NMDSs center on patient data—demographics, diagnoses, functional status, cognitive and psychosocial factors, and patient goals. Interpersonal data covers nursing interventions, orders, and outcomes linked to care plans. Institutional data includes staffing, facility characteristics, and admission/discharge information. While patient data often dominate, there is a growing call to elevate nursing-specific data and residents’ expressed needs to ensure a more holistic view of care and outcomes.
Discrepancies across datasets in what constitutes “nursing data” reflect varying national definitions of nursing and differences in how care is documented. Harmonizing terminology and definitions is critical to making NMDSs comparable and useful for cross-site learning, policy development, and international research.
Recommendations for Effective NMDS Implementation
The literature groups recommendations into four categories: overall, clinical, research, and managerial. Key threads include:
- Overall: pursue uniform documentation standards, involve care residents in development, and ensure NMDS data can inform policy while protecting privacy.
- Clinical: engage clinicians in results interpretation, train staff on standardized coding and the patient voice, and foster multidisciplinary collaboration.
- Research: focus on aging populations, improve international comparability, and bridge practice and research to enhance knowledge transfer.
- Managerial: strengthen collaboration between nursing leadership and medical directors to translate data into care improvements and resource planning.
Limitations and Future Directions
As a scoping review, the evidence base includes diverse article types with varying methodological rigor. Not all NMDSs have publicly available item lists, and some datasets are older or region-specific. Going forward, researchers should emphasize validating NMDS elements, expanding resident-centered data, and developing an interoperable, legally anchored framework that supports both care delivery and research across long-term care settings.
Conclusion: Toward a Shared Vision for NMDSs in Long-Term Care
NMDSs offer a roadmap for standardized nursing documentation in long-term care, supporting better care planning, research, and policy decisions. Achieving broad, international utility requires consensus on core nursing data elements, robust validation, stakeholder involvement, and alignment with digital health legislation. As long-term care continues to modernize, NMDSs will be a foundational tool for data-driven nursing excellence.
