Introduction and Background
Nursing minimum datasets (NMDSs) are defined as a minimum set of information items with uniform definitions and categories that address the essential dimensions of nursing care across diverse health care settings. In long-term care (LTC) — including residential homes, nursing homes, and rehabilitation facilities for older adults — NMDSs aim to standardize documentation, facilitate cross-setting comparisons, and support data-driven decision making. This scoping review maps the international landscape of NMDS initiatives in LTC, highlights what data are collected, and synthesizes recommendations for development and use.
As populations age, LTC facilities face growing complexity of care needs. The COVID-19 pandemic underscored gaps in data infrastructure and the need for interoperable, well-documented nursing data. Jurisdictions such as Germany have moved to legislate digital health strategies that encourage data sharing and better use of electronic health records (EHRs). Against this backdrop, NMDSs are positioned as tools to improve care quality, inform staffing, guide research, and shape policy.
Need for NMDSs in Long-Term Care
The LTC sector requires structured, comparable data to support evidence-based care, workforce planning, and resource allocation. NMDSs help ensure that essential nursing information — from patient data to nursing actions and institutional context — is consistently captured. Reliable NMDS data enable researchers to study trends, benchmark performance, and validate care outcomes, which in turn can justify investments in staff development and quality improvement initiatives. Standardized data are also critical for national and cross-border research collaborations and for evaluating the impact of digital health infrastructures on care processes.
Prior Work and Initiatives
Historically, NMDS work began in the United States in the 1990s with follow-on translations and adaptations across countries. Notable initiatives include the UK’s effort to develop a minimum data set for care homes (the DACHA program) to improve data accessibility and interoperability, as well as international projects that translated or adapted the U.S. NMDS for different settings. Beyond LTC, there have been LMDS/NDS efforts focused on specialized topics such as nutrition, falls prevention, and diabetes interventions. These projects demonstrate both the potential and the challenges of cross-national standardization, especially when nursing practice definitions vary by country and care setting.
In Canada and Europe, efforts have included rehabilitation-specific datasets and intersectoral data repositories that integrate nursing data with medical data. The literature reveals a spectrum of NMDS contents, with a strong emphasis on patient demographics, health status, and clinical diagnoses in line with Werley’s framework, while interpersonal and institutional data (nursing interventions, care plans, staffing, and facility characteristics) are variably represented. The divergence in content highlights the ongoing need for consensus on core nursing elements that are meaningful for care planning and research alike.
Contents of NMDSs in LTC
Using Werley et al.’s structural model, NMDSs are categorized into three top areas: patient data, interpersonal data, and institutional data. In LTC datasets, patient data commonly cover demographics, physiological and psychosocial measures, functional status, and residents’ goals and preferences. Interpersonal data include nursing diagnoses, interventions, outcomes, and care coordination. Institutional data capture facility characteristics such as size, staffing, admissions, and discharge information. A persistent theme is the predominance of patient-centered data, with nursing-specific measures and residents’ voices variably represented, depending on the dataset and country.
Recommendations and Practical Implications
Across studies, four overarching recommendation domains emerge: overall, clinical, research, and managerial. Overall guidance calls for uniform data definitions and item standardization to enable meaningful comparisons and policy-relevant insights. Clinically, there is emphasis on incorporating the patient voice, engaging multidisciplinary teams, and providing staff with training in standardized data capture. Research-oriented recommendations stress improving international comparability, bridging research and practice, and focusing on older adult populations to enhance the relevance of findings. Managerial guidance advocates collaboration between clinical leaders and administrators to translate NMDS outputs into care improvements and resource planning, as well as broad abstraction of core nursing data to support public health and inform electronic systems development.
Discussion and Current Relevance
The review suggests that NMDSs in LTC are increasingly relevant in the context of digital health and policy evolution. The push for data interoperability, resident-centered care, and data-driven governance aligns with the needs of LTC providers facing aging populations and complex care needs. National and regional policies are likely to accelerate NMDS adoption, but success hinges on stakeholder involvement in development, clear item definitions, and robust data governance. The limited presence of detailed LTC-specific data elements beyond patient status in some datasets indicates areas for future refinement, particularly in nursing outcomes and resident experiences.
Limitations
This scoping review encompasses a broad range of sources with variable methodological quality and reporting. Not all NMDSs have available full-text documentation, and original datasets are described unevenly across publications. Consequently, direct comparisons of content are constrained, and some findings reflect secondary reporting rather than primary data item sets.
Conclusions
NMDSs offer a strategic route to standardized nursing data in long-term care, supporting care quality, workforce planning, and health system learning. While older datasets emphasized patient data, there is growing recognition of incorporating residents’ needs and experiences. The path forward involves collaborative development of core nursing elements, alignment with international standards, and deliberate attention to governance, privacy, and data quality to realize the full benefits of NMDSs in long-term care settings.
