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Objectives To assess the feasibility of capturing older care home residents’ quality of life (QoL) in digital social care records and the construct validity (hypothesis testing) and internal consistency (Cronbach’s alpha) of four QoL measures.Design Cross-sectional data collected in wave 1 of the DACHA (Developing resources And minimum dataset for Care Homes’ Adoption) study, a mixed-methods pilot of a prototype minimum dataset (MDS).Setting Care homes (with or without nursing) registered to provide care for older adults (>65 years) and/or those living with dementia. All homes used a digital record system from one of two suppliers.Participants Data were extracted from 748 residents. All permanent residents, aged 65 years or older, were eligible to participate, including those lacking capacity to consent. Temporary residents and residents in their last weeks of life were excluded.Outcome measures and analysis The English language versions of Adult Social Care Outcomes Toolkit (ASCOT)-Proxy-Resident, ICEpop CAPability measure for Older people (ICECAP-O), EQ-5D-5L proxy and the QUALIDEM were added to the digital record. As there have not been any previous studies of the structural validity of the English language version of the QUALIDEM, ordinal exploratory factor analysis (EFA) was applied for this measure only. Feasibility (% missing by software provider and measure), % floor/ceiling effects (>15% at lower/upper end of the scales), convergent or divergent construct validity (criterion of >75% of hypotheses accepted) and internal consistency (Cronbach’s alpha ≥0.7) were assessed for all four measures.Results The ordinal EFA of QUALIDEM did not replicate the findings of previous research. A six-factor (36 item) solution was proposed and used in all subsequent analyses. There were low rates of missing data (

Introduction Health and care data are routinely collected about care home residents in England, yet there is no way to collate these data to inform benchmarking and improvement. The Developing research resources And minimum data set for Care Homes’ Adoption and use study has developed a prototype minimum data set (MDS) for piloting.Methods and analysis A mixed-methods longitudinal pilot study will be conducted in 60 care homes (approximately 960 residents) in 3 regions of England, using resident data from cloud-based digital care home records at two-time points. These will be linked to resident and care home level data held within routine National Health Service and social care data sets. Two rounds of focus groups with care home staff (n=8–10 per region) and additional interviews with external stakeholders (n=3 per region) will explore implementation and the perceived utility of the MDS. Data will be assessed for completeness and timeliness of completion. Descriptive statistics, including percentage floor and ceiling effects, will establish data quality. For validated scales, construct validity will be assessed by hypothesis testing and exploratory factor analysis will establish structural validity. Internal consistency will be established using Cronbach’s alpha. Longitudinal analysis of the pilot data will demonstrate the value of the MDS to each region. Qualitative data will be analysed inductively using thematic analysis to understand the complexities of implementing an MDS in care homes for older people.Ethics and dissemination The study has received ethical approval from the London Queen’s Square Research Ethics Committee (22/LO/0250). Informed consent is required for participation. Findings will be disseminated to: academics working on data use and integration in social care, care sector organisations, policy makers and commissioners. Findings will be published in peer-reviewed journals. Partner NIHR Applied Research Collaborations, the National Care Forum and the British Geriatrics Society will disseminate policy briefs.

Introduction Care homes provide nursing and social care for older people who can no longer live independently at home. In the UK, there is no consistent approach to how information about residents’ medical history, care needs and preferences are collected and shared. This limits opportunities to understand the care home population, have a systematic approach to assessment and documentation of care, identifiy care home residents at risk of deterioration and review care. Countries with standardised approaches to residents’ assessment, care planning and review (eg, minimum data sets (MDS)) use the data to understand the care home population, guide resource allocation, monitor services delivery and for research. The aim of this realist review is to develop a theory-driven understanding of how care home staff implement and use MDS to plan and deliver care of individual residents.Methods and analysis A realist review will be conducted in three research stages.Stage 1 will scope the literature and develop candidate programme theories of what ensures effective uptake and sustained implementation of an MDS.Stage2 will test and refine these theories through further iterative searches of the evidence from the literature to establish how effective uptake of an MDS can be achieved.Stage 3 will consult with relevant stakeholders to test or refine the programme theory (theories) of how an MDS works at the resident level of care for different stakeholders and in what circumstances. Data synthesis will use realist logic to align data from each eligible article with possible context–mechanism–outcome configurations or specific elements that answer the research questions.Ethics and dissemination The University of Hertfordshire Ethics Committee has approved this study (HSK/SF/UH/04169). Findings will be disseminated through briefings with stakeholders, conference presentations, a national consultation on the use of an MDS in UK long-term care settings, publications in peer-reviewed journals and in print and social media publications accessible to residents, relatives and care home staff.PROSPERO registration number CRD42020171323; this review protocol is registered on the International Prospective Register of Systematic Reviews.