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Background Computerised decision support systems (CDSS) are widely used by nurses and allied health professionals but their effect on clinical performance and patient outcomes is uncertain. Objectives Evaluate the effects of clinical decision support systems use on nurses’, midwives’ and allied health professionals’ performance and patient outcomes and sense-check the results with developers and users. Eligibility criteria Comparative studies (randomised controlled trials (RCTs), non-randomised trials, controlled before-and-after (CBA) studies, interrupted time series (ITS) and repeated measures studies comparing) of CDSS versus usual care from nurses, midwives or other allied health professionals. Information sources Nineteen bibliographic databases searched October 2019 and February 2021. Risk of bias Assessed using structured risk of bias guidelines; almost all included studies were at high risk of bias. Synthesis of results Heterogeneity between interventions and outcomes necessitated narrative synthesis and grouping by: similarity in focus or CDSS-type, targeted health professionals, patient group, outcomes reported and study design. Included studies Of 36,106 initial records, 262 studies were assessed for eligibility, with 35 included: 28 RCTs (80%), 3 CBA studies (8.6%), 3 ITS (8.6%) and 1 non-randomised trial, a total of 1318 health professionals and 67,595 patient participants. Few studies were multi-site and most focused on decision-making by nurses (71%) or paramedics (5.7%). Standalone, computer-based CDSS featured in 88.7% of the studies; only 8.6% of the studies involved ‘smart’ mobile or handheld technology. Care processes – including adherence to guidance – were positively influenced in 47% of the measures adopted. For example, nurses’ adherence to hand disinfection guidance, insulin dosing, on-time blood sampling, and documenting care were improved if they used CDSS. Patient care outcomes were statistically – if not always clinically – significantly improved in 40.7% of indicators. For example, lower numbers of falls and pressure ulcers, better glycaemic control, screening of malnutrition and obesity, and accurate triaging were features of professionals using CDSS compared to those who were not. Evidence limitations Allied health professionals (AHPs) were underrepresented compared to nurses; systems, studies and outcomes were heterogeneous, preventing statistical aggregation; very wide confidence intervals around effects meant clinical significance was questionable; decision and implementation theory that would have helped interpret effects – including null effects – was largely absent; economic data were scant and diverse, preventing estimation of overall cost-effectiveness. Interpretation CDSS can positively influence selected aspects of nurses’, midwives’ and AHPs’ performance and care outcomes. Comparative research is generally of low quality and outcomes wide ranging and heterogeneous. After more than a decade of synthesised research into CDSS in healthcare professions other than medicine, the effect on processes and outcomes remains uncertain. Higher-quality, theoretically informed, evaluative research that addresses the economics of CDSS development and implementation is still required. Future work Developing nursing CDSS and primary research evaluation. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in Health and Social Care Delivery Research; 2023. See the NIHR Journals Library website for further project information. Registration PROSPERO 1 [number: CRD42019147773]. Plain language summary Computerised decision support systems (CDSS) are software or computer-based technologies providing advice to professionals making clinical decisions – for example, which patients to treat first in emergency departments. CDSS improve some doctors’ decisions and patients’ outcomes, but we don’t know if they improve nurses’, midwives’ and therapists’ or other staff decisions and patient outcomes. Research into, and health professionals’ use of, technology – for example, in video consultations – has grown since the last relevant systematic review in 2009. We systematically searched electronic databases for research measuring how well nurses, midwifes and other therapists/staff followed CDSS advice, how CDSS influence their decisions, how safe CDSS are, and their financial costs and benefits. We interviewed CDSS users and developers and some patient representatives from a general practice to help understand our findings. Of 35 relevant studies – from 36,106 initially found – most (71%) focused on nurses. Just over half (57%) involved hospital-based staff, and three-quarters (75%) were from richer countries like the USA or the UK. Research quality had not noticeably improved since 2009 and all studies were at risk of potentially misleading readers. CDSS improved care in just under half (47%) of professional behaviours, such as following hand-disinfection guidance, working out insulin doses, and sampling blood on time. Patient care – judged using outcomes like falls, pressure ulcers, diabetes control and triage accuracy – was better in 41% of the care measured. There wasn’t enough evidence to judge CDSS safety or the financial costs and benefits of systems. CDSS can improve some nursing and therapist decisions and some patient outcomes. Studies mostly measure different behaviours and outcomes, making comparing them hard. Theories explaining or predicting how decision support systems might work are not used enough when designing, implementing or evaluating CDSS. More research into the financial costs and benefits of CDSS and higher-quality evidence of their effects are still needed. Whether decision support for nurses, midwives and other therapists reliably improves decision-making remains uncertain.

Background Quality of life and care varies between and within the care homes in which almost half a million older people live and over half a million direct care staff (registered nurses and care assistants) work. The reasons are complex, understudied and sometimes oversimplified, but staff and their work are a significant influence. Objective(s) To explore variations in the care home nursing and support workforce; how resident and relatives’ needs in care homes are linked to care home staffing; how different staffing models impact on care quality, outcomes and costs; how workforce numbers, skill mix and stability meet residents’ needs; the contributions of the care home workforce to enhancing quality of care; staff relationships as a platform for implementation by providers. Design Mixed-method (QUAL-QUANT) parallel design with five work packages. WP1 – two evidence syntheses (one realist); WP2 – cross-sectional survey of routine staffing and rated quality from care home regulator; WP3 – analysis of longitudinal data from a corporate provider of staffing characteristics and quality indicators, including safety; WP4 – secondary analysis of care home regulator reports; WP5 – social network analysis of networks likely to influence quality innovation. We expressed our synthesised findings as a logic model. Setting English care homes, with and without nursing, with various ownership structures, size and location, with varying quality ratings. Participants Managers, residents, families and care home staff. Findings Staffing’s contribution to quality and personalised care requires: managerial and staff stability and consistency; sufficient staff to develop ‘familial’ relationships between staff and residents, and staff–staff reciprocity, ‘knowing’ residents, and skills and competence training beyond induction; supported, well-led staff seeing modelled behaviours from supervisors; autonomy to act. Outcome measures that capture the relationship between staffing and quality include: the extent to which resident needs and preferences are met and culturally appropriate; resident and family satisfaction; extent of residents living with purpose; safe care (including clinical outcomes); staff well-being and job satisfaction were important, but underacknowledged. Limitations Many of our findings stem from self-reported and routine data with known biases – such as under reporting of adverse incidents; our analysis may reflect these biases. COVID-19 required adapting our original protocol to make it feasible. Consequently, the effects of the pandemic are reflected in our research methods and findings. Our findings are based on data from a single care home operator and so may not be generalised to the wider population of care homes. Conclusions Innovative and multiple methods and theory can successfully highlight the nuanced relationship between staffing and quality in care homes. Modifiable characteristics such as visible philosophies of care and high-quality training, reinforced by behavioural and relational role modelling by leaders can make the difference when sufficient amounts of consistent staff are employed. Greater staffing capacity alone is unlikely to enhance quality in a cost-effective manner. Social network analysis can help identify the right people to aid adoption and spread of quality and innovation. Future research should focus on richer, iterative, evaluative testing and development of our logic model using theoretically and empirically defensible – rather than available – inputs and outcomes. Study registration This study is registered as PROSPERO CRD42021241066 and Research Registry registration: 1062. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/144/29) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 8. See the NIHR Funding and Awards website for further award information. Plain language summary This study was about the relationship between staffing and quality in care homes. Almost half a million older people live in care homes in England. Why quality of care and quality of life for residents vary so much between and within homes is unknown, but staff and the ways they work are likely to be important. Researching staffing and quality is difficult: quality means different things to different people and a lot of things shape how quality feels to residents, families and staff. In the past, researchers have oversimplified the problem to study it and may have missed important influences. We took a more complex view. In five interlinked work packages, we collected and analysed: (1) research journal articles; (2) national data from different care homes; (3) data from a large care organisation to look at what it is about staffing that influences quality; (4) reports and ratings of homes from the Care Quality Commission; and (5) we looked at the networks between staff in homes that shape how quality improvement techniques might spread. We used theories about how our findings might be linked to plan for this data collection and analysis. The results were combined into something called a ‘logic model’ – a diagram and explanation that make it easier for managers, researchers and people interested in care homes to see how staffing influences quality. Staffing considerations that might improve quality include: not swapping managers too much; having sufficient and consistent staff for family-like relationships in homes and putting residents’ needs first; supporting staff and giving them freedom to act; and key staff leading by example. Research examining care home quality should capture those aspects that mean the most to residents, their families and staff. Scientific summary Background An estimated 425,000 older people in England live in 18,000 care homes: with nursing, without nursing, or dual registered homes. They are some of the oldest and the most vulnerable people in society. Resident dependency levels and care needs are often similar in homes with and without nursing – but their workforces differ significantly. In homes with nursing care, registered nurses (RNs) are employed to provide clinical care and supervise care delivery, mainly from a large workforce of non-registered care assistants. Care homes without nursing comprise only social care staff or care assistants. The NHS provides health care – including nursing care – as required; for example, supporting specialist care for residents at the end of life. Staffing profiles and establishments vary between providers and so studying care homes and their workforce is complex. Conceptually, quality is similarly complex; it is contested, contingent, contextualised, dynamic and often deeply personal. Two dimensions of quality require consideration in care homes: quality of care and quality of life. While care home staff and their work are likely determinants of quality, research into the staffing–quality relationship is comparatively scant. Measuring quality often focuses on clinical outcomes, such as pressure ulcer prevalence, falls or medication errors. Many studies are in North American long-term care and the few English studies’ primary focus has been on staff turnover and quality and working conditions and quality. Our mixed-methods study addresses some of the theoretical gaps and methodological challenges associated with understanding staffing’s relationship to quality. Using established theory we focused on the structures, processes and outcomes of quality. Our aim of investigating workforce models of nursing and care support in care homes that effectively benefit residents, relatives and staff was addressed through six objectives, which were the focus of five linked work packages (WP). Objectives Describe variations in the characteristics of the care home nursing and support workforce (WP1). Identify the dependency and needs of residents and relatives in care homes and their association with care home staffing (WP2, WP3). Examine how different care home staffing models (including new roles) impact on quality of care, resident outcomes and NHS resources (WP1, WP2, WP3). Explain how care home workforce (numbers, skill mix and stability) might meet the dependency and needs of residents (WP1, WP2, WP3, WP4). Explore and understand the contributions of the nursing and support workforce (including innovations in nursing and support roles) in care homes to enhance quality of care (WP1, WP4). Translate methods used for modelling the relationships between staffing and quality to provide a platform for sector-wide implementation (WP5). Methods A mixed-method (QUAL-QUANT) parallel design built around Donabedian’s theoretical framework of structures, processes and outcomes was the basis for our exploration of the relationship between care home staffing and quality. The coronavirus disease 2019 (COVID-19) pandemic meant some deviation from our original protocol was necessary. Work package 1 (WP1) was two evidence reviews: a systematic review synthesising 36 studies of care home staff perceptions of their roles and responsibilities in promoting quality; a realist review (n = 66 studies) then developed evidence and theory-based explanations of how care home staff behaviours promote quality of care and quality of life, why and in what circumstances. Work packages 2 and 3 used routinely collected measures of staffing and examined their relationship to quality. WP2 was a cross-sectional observational study, modelling the relationship between care quality – as measured in Care Quality Commission (CQC) inspection reports – and care home workforce characteristics from the National Minimum Data Set for Social Care (NMDS-SC). WP3 analysed routinely collected longitudinal data measures of workforce, nurse-sensitive indicators of care quality, resident characteristics and home characteristics from a large corporate care home provider over 42 months. A cost analysis from a provider perspective was also undertaken. Work package 4 used documentary analysis of 30 purposively sampled, publicly available, inspection reports from the English national quality regulator (CQC) from homes rated as outstanding or inadequate to examine (1) how staffing structures influenced quality and (2) the care processes that explain the relationship between staffing and quality. In WP5, care homes (n = 11) were purposively sampled and social network analysis (SNA) using questionnaires and roster name generation was used to map the self-reported advice and influence relationships present in care homes. To assess homes’ readiness for innovation and work-related barriers to adoption of our (translated) findings, eight managers completed an adapted version of the Normalisation MeAsure Development questionnaire (NoMAD) questionnaire – an operationalised instrument of Normalisation Process Theory. Public and stakeholder involvement and engagement We worked closely with the public and stakeholders throughout, from question formulation through to synthesis. Two advisory groups were formed: (1) a resident and relative group and (2) a care home manager group. The study steering committee (SSC) contained key stakeholders – including relatives – to provide oversight and guidance. These mechanisms ensured perspectives other than the research team informed and improved research design and implementation and prompted wider conversations and learnRNing that benefited the research. Ethics approval Work package 2 and WP3 were approved (2 August 2017) by the Social Care Research Ethics Committee (17/WM/0232). WP5 was approved (21 June 2019) by the University of Leeds, Faculty of Medicine and Health, Ethics and Governance Committee (HREC 18-028). Findings The five linked WP findings were synthesised using a logic model to explain what is likely to work, why and how, and the interactions between structures, processes and outcomes important for the staffing–quality relationship. Managerial stability was important: care homes with a manager in-post in the 12 months prior to a CQC inspection were more likely to be rated as good or outstanding (WP2). Managers made those workforce decisions necessary for meeting residents’ care and safety needs (WP4). Managers of care homes rated good or outstanding had authority and flexibility to secure the workforce they judged necessary (WP4). Cohesive working relationships between managers and their corporate senior management team or owner helped managers enact their decisions (WP4). Higher staff-to-bed ratios were associated with a greater chance of a good or outstanding CQC inspection score (WP2). More care from RNs was associated with fewer falls with fractures, urinary tract infections (UTIs) and medication errors (WP3). Use of agency nurses to cover for staff sickness or unfilled vacancies was not associated with more falls, infections or pressure ulcers, but was associated with more medication errors (WP3). Simply increasing nursing input is unlikely to be a cost-effective way of reducing adverse incidents in care homes (WP3). WP4 (and WP1ii) identified the importance of having ‘sufficient’ staff to meet residents’ needs and preferences and improve outcomes. But detail of how staffing levels were determined by managers and consistent use of tools to support professional judgement about staffing (WP4) was lacking. Staff stability and minimising agency staff use were perceived as necessary conditions for quality (WP4). Having experienced care staff, that is, staff in post for 5 years, was likely to improve quality, as measured by ratings (WP2). A stable workforce was also associated with skills and competence (WP1i, WP1ii, WP4). Opportunities for staff induction, training and continuing professional development, alongside staff supervision, were extensive in care homes rated as outstanding (WP4). High staff turnover reduced opportunities for developing broader staff skills and competence, narrowing it to staff induction and mandatory training (WP4). Staffing consistency was important for organising care and work (WP1i, WP1ii, WP4). Larger homes were less likely to be rated positively (WP2). Other WPs highlighted the importance of team size (not home size) as a lever for promoting quality (WP1i, WP1ii, WP4). Small groups of linked residents and staff (5–15 residents per staff member based on level of resident dependency) promoted familiarity, communication and a family-like environment for cultivating relationships (WP1ii). Establishing these family-like relationships and ‘knowing’ residents promoted personalisation of resident care (WP1i), encouraging staff to go beyond purely assisting residents with physical tasks, towards addressing wider social and emotional needs (WP1ii). The reviews (WP1i, WP1ii) highlight where the requisite roles and responsibilities of the workforce might help achieve this. Developing relationships based on consultation – with families, professionals outside the home and residents – to support residents was a feature of homes rated as outstanding (WP1i, WP1ii, WP4). These relationships informed care planning and personalisation of care (WP1i). Relationships between staff and families also legitimised family involvement in care to support quality (WP1ii). Unit-level supervisors that role modelled relationship building were important levers for realising team ambitions of relationship-based quality (WP1ii, WP4). Staffing consistency was important for teamworking. In care homes rated outstanding, staff reported working together and supporting each other towards a collective vision of care and support (WP4). Staff that felt supported, valued and – with (managerial) ‘permission’ – able to prioritise residents’ needs, adapted and adopted behaviours promoting residents’ expressing preferences for care (WP1ii, WP4). More autonomy in day-to-day work, with associated accountability, led to greater staff engagement and satisfaction (WP1ii, WP4). Team reciprocity was linked to open communication, information exchange, advice and influence (WP1ii, WP5). Reciprocity encouraged teams to draw on each other’s knowledge and skills to promote individualised care and enhance quality (WP1i, WP1ii, WP4). Combining written and verbal staff communication was a feature in homes rated as outstanding and linked to better resident care (WP4). Visible unit-level supervisors – not always managers – fostered teamworking. They also minimised conflicts, enabling team reciprocity and relationships (WP1ii). Social networks can promote or hinder the behavioural mechanisms influencing quality (WP5). Networks that were interconnected, dense or cohesive, built around strong advice and influence relationships, had higher chances of implementing change associated with innovation around quality (WP5). The care home manager – as opinion leader (i.e. providing most advice and influence and receiving most advice and influence) – was pivotal in implementing innovation-related change (WP5). Leadership and management behaviours promoted resident-centred approaches; ensured effective communication; promoted staff confidence; offered practical and emotional support and recognition to staff; and encouraged diversity (WP1ii). Staff feeling valued was linked to greater staff commitment and contribution to quality (WP4). A managerially endorsed philosophy of care (valuing residents and staff) encouraged the staff behaviours needed for individualised resident care (WP1ii, WP4). Based on our analysis, measuring the following resident outcomes would provide a more meaningful picture of the relationship between staffing and quality: the extent to which resident needs and preferences are met (and culturally appropriate) (WP1i, WP1ii, WP4); resident and family satisfaction (WP1i, WP1ii, WP4); residents living with purpose to promote their quality of life and well-being (WP1i, WP1ii, WP4); and safe care for residents (including clinical outcomes) (WP1i, WP1ii, WP2, WP3, WP4). Staff well-being and job satisfaction were important outcomes which influenced quality as experienced by residents. Conclusions Our study makes a novel and important contribution to understanding the importance of the relationship between staff, their work and behaviours and quality in care homes. We have attempted to shift the debate away from a reductionist picture of numbers of staff and their relationship to clinical indicators, towards a more nuanced recognition of the ways in which staff in the right amounts and with the right behaviours can meet resident’s needs and preferences. Staffing needs to be stable, skilled and competent to realise the benefits of person-focused organisation of care, and enhanced teamworking. Leadership, reward and recognition of staff and a shared philosophy of care provide needed context for the relationships required to improve quality as experienced by residents. Our findings will be useful for people and organisations making policy and delivering services that want to work towards the best ways to deploy and support quality in care homes using their most valuable resource: their staff. Implications for social care Understanding that numbers of staff alone are a necessary but not sufficient condition for care home quality. Quality improves in homes when more care is provided by RNs. Simply introducing ‘more’ staff (particularly RNs) is unlikely to be a cost-effective way of reducing adverse incidents in care homes. Quality relies on the who, what and how of staffing arrangements and organisation of work. Leadership is key, influencing how organisational resources are used to promote the environments and cultures needed for quality-promoting relationships to flourish. Realising and supporting the potential of the staffing resource (clinical, care, social and cultural skills and competence) are essential for quality. Opportunities for learning and development demonstrate an organisation values staff and may support staff retention. A focus on the structures that support staffing consistency (stability, skill and competence) is important for influencing processes (the organisation of care and teamworking) and outcomes for residents and staff. Developing transparent approaches that enable care home managers to effectively judge and make decisions about staffing levels is crucial for safe and appropriate care for residents. Reciprocal relationships, beyond the immediate care team and including residents, their families and health and social care professionals promote quality. Leadership and management behaviours influence staff commitment and thus their contribution to quality. A ‘visible’ unit supervisor and staff who ‘connect’ and influence the team are essential for quality and innovation in care homes. Implications for research Future research should: Unpack the contribution of direct care support workforce (including care assistants, senior care assistants and nursing associates) working at different levels of skills and competence to care home quality. Explore how training for care assistants, senior care assistants and nursing associates contributes to improving quality. Consider differences for temporary (i.e. step-up or step-down care) versus permanent (i.e. long-term placement) care home residents. Explore how resident population levels of dependency are related to quality. Use innovative methods to capture quality in ways that recognise individual stakeholder views, values, expectations and preferences and address both quality of care and quality of life. Develop robust social network interventions to change network structures to enhance reciprocity and advice and influence relationships to embed innovations for enhancing quality. Consider machine learning methods for analysis of routine data because these methods are better able to identify non-linear relationships between staffing and care quality indicators than traditional regression analysis in order to better identify minimum adequate staffing levels. Use methods to promote more accurate modelling of the staffing–quality relationship through data linkage. Further test and develop our logic model. Study registration This study is registered as PROSPERO CRD42021241066 and Research Registry registration: 1062. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/144/29) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 8. See the NIHR Funding and Awards website for further award information.

Abstract Introduction Growing numbers of older patients occupy hospital beds despite being ‘medically fit’ for discharge. These Delayed Transfers of Care amplify inefficiencies in care and can cause harm. Delayed transfer because of family or patient choice is common; yet, research on patient and family perspectives is scarce. To identify barriers to, and facilitators of, shorter hospital stays, we sought to understand older people's and caregivers' thoughts and feelings about the benefits and harms of being in hospital and the decisions made at discharge. Methods A multimethod qualitative study was carried out. Content analysis was carried out of older people's experiences of health or care services submitted to the Care Opinion online website, followed by telephone and video interviews with older people and family members of older people experiencing a hospital stay in the previous 12 months. Results Online accounts provide insight into how care was organized for older people in the hospital, including deficiencies in care organization, the discharge process and communication, as well as how care was experienced by older people and family members. Interview‐generated themes included shared meanings of hospitalization and discharge experiences and the context of discharge decisions including failure in communication systems, unwarranted variation and lack of confidence in care and lack of preparation for ongoing care. Conclusion Poor quality and availability of information, and poor communication, inhibit effective transfer of care. Communication is fundamental to patient‐centred care and even more important in discharge models characterized by limited assessments and quicker discharge. Interventions at the service level and targeted patient information about what to expect in discharge assessments and after discharge could help to address poor communication and support for improving discharge of older people from hospital. Patient or Public Contribution The Frailty Oversight Group, a small group of older people providing oversight of the Community Aging Research 75+ study, provided feedback on the research topic and level of interest, the draft data collection tools and the feasibility of collecting data with older people during the COVID‐19 pandemic. The group also reviewed preliminary findings and provided feedback on our interpretation.

Abstract Background People living in care homes have experienced devastating impact from COVID-19. As interventions to prevent the transmission of COVID-19 are developed and evaluated, there is an urgent need for researchers to agree on the outcomes used when evaluating their effectiveness. Having an agreed set of outcomes that are used in all relevant trials can ensure that study results can be compared. Objective The aim of the study was to develop a core outcome set (COS) for trials assessing the effectiveness of pharmacological and non-pharmacological interventions for preventing COVID-19 infection and transmission in care homes. Methods The study used established COS methodology. A list of candidate outcomes was identified by reviewing registered trials to evaluate interventions to prevent COVID-19 in care homes. Seventy key stakeholders participated in a Delphi survey, rating the candidate outcomes on a nine-point scale over two rounds, with the opportunity to propose additional outcomes. Stakeholders included care home representatives (n = 19), healthcare professionals (n = 20), people with personal experience of care homes (n = 7), researchers (n = 15) and others (n = 9). Outcomes were eligible for inclusion if they met an a priori threshold. A consensus meeting with stakeholders resulted in agreement of the final outcome set. Results Following the Delphi and consensus meeting, twenty-four outcomes were recommended for inclusion. These are grouped across four domains of infection, severity of illness, mortality, and ‘other’ (intervention specific or life impact). Due to the considerable heterogeneity between care homes, residents, and interventions, the relevance and importance of outcomes may differ between trial contexts. Intervention-specific outcomes would be included only where relevant to a given trial, thus reducing the measurement burden. Conclusion Using a rapid response approach, a COS for COVID-19 prevention interventions in care homes has been developed. Future work should focus on identifying instruments for measuring these outcomes, and the interpretation and application of the COS across different trial contexts. Beyond COVID-19, the outcomes identified in this COS may have relevance to other infectious diseases in care homes, and the rapid response approach may be useful as preparation for future pandemics.

Abstract Background Health practitioners from different professions, and with differing competencies, need to collaborate to provide quality care. Competencies in interprofessional working need developing in undergraduate educational preparation. This paper reports the protocol for a systematic review of self-report instruments to assess interprofessional learning in undergraduate health professionals’ education. Methods We will search PubMed, Web of Science, CINAHL and ERIC from January 2010 onwards. A combination of search terms for interprofessional learning, health professions, psychometric properties, assessment of learning and assessment tools will be used. Two reviewers will independently screen all titles, abstracts and full-texts. Potential conflicts will be resolved through discussion. Quantitative and mixed-methods studies evaluating interprofessional learning in undergraduate health professions education (e.g. medicine, nursing, occupational and physical therapy, pharmacy and psychology) will be included. Methodological quality of each reported instrument, underpinning theoretical frameworks, and the effects of reported interventions will be assessed. The overall outcome will be the effectiveness of instruments used to assess interprofessional competence. Primary outcomes will be the psychometric properties (e.g. reliability, discriminant and internal validity) of instruments used. Secondary outcomes will include time from intervention to assessment, how items relate to specific performance/competencies (or general abstract constructs) and how scores are used (e.g. to grade students, to improve courses or research purposes). Quantitative summaries in tabular format and a narrative synthesis will allow recommendations to be made on the use of self-report instruments in practice. Discussion Many studies use self-report questionnaires as tools for developing meaningful interprofessional education activities and assessing students’ interprofessional competence. This systematic review will evaluate both the benefits and limitations of reported instruments and help educators and researchers (i) choose the most appropriate existing self-report instruments to assess interprofessional competence and (ii) inform the design and conduct of interprofessional competency assessment using self-report instruments. Systematic review registration Open Science Framework [ https://osf.io/vrfjn ].

Objective Computerised clinical decision support systems (CDSS) are an increasingly important part of nurse and allied health professional (AHP) roles in delivering healthcare. The impact of these technologies on these health professionals’ performance and patient outcomes has not been systematically reviewed. We aimed to conduct a systematic review to investigate this.Materials and methods The following bibliographic databases and grey literature sources were searched by an experienced Information Professional for published and unpublished research from inception to February 2021 without language restrictions: MEDLINE (Ovid), Embase Classic+Embase (Ovid), PsycINFO (Ovid), HMIC (Ovid), AMED (Allied and Complementary Medicine) (Ovid), CINAHL (EBSCO), Cochrane Central Register of Controlled Trials (Wiley), Cochrane Database of Systematic Reviews (Wiley), Social Sciences Citation Index Expanded (Clarivate), ProQuest Dissertations & Theses Abstracts & Index, ProQuest ASSIA (Applied Social Science Index and Abstract), Clinical Trials.gov, WHO International Clinical Trials Registry (ICTRP), Health Services Research Projects in Progress (HSRProj), OpenClinical(www.OpenClinical.org), OpenGrey (www.opengrey.eu), Health.IT.gov, Agency for Healthcare Research and Quality (www.ahrq.gov). Any comparative research studies comparing CDSS with usual care were eligible for inclusion.Results A total of 36 106 non-duplicate records were identified. Of 35 included studies: 28 were randomised trials, three controlled-before-and-after studies, three interrupted-time-series and one non-randomised trial. There were ~1318 health professionals and ~67 595 patient participants in the studies. Most studies focused on nurse decision-makers (71%) or paramedics (5.7%). CDSS as a standalone Personal Computer/LAPTOP-technology was a feature of 88.7% of the studies; only 8.6% of the studies involved ‘smart’ mobile/handheld-technology.Discussion CDSS impacted 38% of the outcome measures used positively. Care processes were better in 47% of the measures adopted; examples included, nurses’ adherence to hand disinfection guidance, insulin dosing, on-time blood sampling and documenting care. Patient care outcomes in 40.7% of indicators were better; examples included, lower numbers of falls and pressure ulcers, better glycaemic control, screening of malnutrition and obesity and triaging appropriateness.Conclusion CDSS may have a positive impact on selected aspects of nurses’ and AHPs’ performance and care outcomes. However, comparative research is generally low quality, with a wide range of heterogeneous outcomes. After more than 13 years of synthesised research into CDSS in healthcare professions other than medicine, the need for better quality evaluative research remains as pressing.

Intraventricular hemorrhage (IVH) is a severe complication of preterm birth associated with cerebral palsy, intellectual disability, and commonly, accumulation of cerebrospinal fluid (CSF). Histologically, IVH leads to subependymal gliosis, fibrosis, and disruption of the ependymal wall. Importantly, expression of aquaporin channels 1 and 4 (AQP1 and AQP4) regulating respectively, secretion and absorption of cerebrospinal fluids is altered with IVH and are associated with development of post hemorrhagic hydrocephalus. Human cord blood derived unrestricted somatic stem cells (USSCs), which we previously demonstrated to reduce the magnitude of hydrocephalus, as having anti-inflammatory, and beneficial behavioral effects, were injected into the cerebral ventricles of rabbit pups 18 h after glycerol-induced IVH. USSC treated IVH pups showed a reduction in ventricular size when compared to control pups at 7 and 14 days (both, P < 0.05). Histologically, USSC treatment reduced cellular infiltration and ependymal wall disruption. In the region of the choroid plexus, immuno-reactivity for AQP1 and ependymal wall AQP4 expression were suppressed after IVH but were restored following USSC administration. Effects were confirmed by analysis of mRNA from dissected choroid plexus and ependymal tissue. Transforming growth factor beta (TGF-β) isoforms, connective tissue growth factor (CTGF) and matrix metalloprotease-9 (MMP-9) mRNA, as well as protein levels, were significantly increased following IVH and restored towards normal with USSC treatment (P < 0.05). The anti-inflammatory cytokine Interleukin-10 (IL-10) mRNA was reduced in IVH, but significantly recovered after USSC injection (P < 0.05). In conclusion, USSCs exerted anti-inflammatory effects by suppressing both TGF-β specific isoforms, CTGF and MMP-9, recovered IL-10, restored aquaporins expression towards baseline, and reduced hydrocephalus. These results support the possibility of the use of USSCs to reduce IVH consequences in prematurity.

Background: The Health and Social Care Act 2012 (Great Britain. Health and Social Care Act 2012. London: The Stationery Office; 2012) has mandated research use as a core consideration of health service commissioning arrangements. We evaluated whether or not access to a demand-led evidence briefing service improved the use of research evidence by commissioners, compared with less intensive and less targeted alternatives. Design: Controlled before-and-after study. Setting: Clinical Commissioning Groups (CCGs) in the north of England. Main outcome measures: Change at 12 months from baseline of a CCG’s ability to acquire, assess, adapt and apply research evidence to support decision-making. Secondary outcomes measured individual clinical leads’ and managers’ intentions to use research evidence in decision-making. Methods: Nine CCGs received one of three interventions: (1) access to an evidence briefing service; (2) contact plus an unsolicited push of non-tailored evidence; or (3) an unsolicited push of non-tailored evidence. Data for the primary outcome measure were collected at baseline and 12 months post intervention, using a survey instrument devised to assess an organisation’s ability to acquire, assess, adapt and apply research evidence to support decision-making. In addition, documentary and observational evidence of the use of the outputs of the service was sought and interviews with CCG participants were undertaken. Results: Most of the requests were conceptual; they were not directly linked to discrete decisions or actions but were intended to provide knowledge about possible options for future actions. Symbolic use to justify existing decisions and actions were less frequent and included a decision to close a walk-in centre and to lend weight to a major initiative to promote self-care already under way. The opportunity to impact directly on decision-making processes was limited to work to establish disinvestment policies. In terms of impact overall, the evidence briefing service was not associated with increases in CCGs’ capacity to acquire, assess, adapt and apply research evidence to support decision-making, individual intentions to use research findings or perceptions of CCGs’ relationships with researchers. Regardless of the intervention received, at baseline participating CCGs indicated that they felt that they were inconsistent in their research-seeking behaviours and their capacity to acquire research remained so at follow-up. The informal nature of decision-making processes meant that there was little or no traceability of the use of evidence. Limitations: Low baseline and follow-up response rates (of 68% and 44%, respectively) and missing data limit the reliability of these findings. Conclusions: Access to a demand-led evidence briefing service did not improve the uptake and use of research evidence by NHS commissioners compared with less intensive and less targeted alternatives. Commissioners appear to be well intentioned but ad hoc users of research. Future work: Further research is required on the effects of interventions and strategies to build individual and organisational capacity to use research. Resource-intensive approaches to providing evidence may best be employed to support instrumental decision-making. Comparative evaluation of the impact of less intensive but targeted strategies on the uptake and use of research by commissioners is warranted. Funding: The National Institute for Health Research Health Services and Delivery Research programme.

Background: The establishment of the Collaborations for Leadership in Applied Health Research and Care (CLAHRCs) was the culmination of a number of policy initiatives to bridge the gap between evidence and practice. CLAHRCs were created and funded to facilitate development of partnerships and connect the worlds of academia and practice in an effort to improve patient outcomes through the conduct and application of applied health research. Objectives: Our starting point was to test the theory that bringing higher education institutions and health-care organisations closer together catalyses knowledge mobilisation. The overall purpose was to develop explanatory theory regarding implementation through CLAHRCs and answer the question ‘what works, for whom, why and in what circumstances?’. The study objectives focused on identifying and tracking implementation mechanisms and processes over time; determining what influences whether or not and how research is used in CLAHRCs; investigating the role played by boundary objects in the success or failure of implementation; and determining whether or not and how CLAHRCs develop and sustain interactions and communities of practice. Methods: This study was a longitudinal realist evaluation using multiple qualitative case studies, incorporating stakeholder engagement and formative feedback. Three CLAHRCs were studied in depth over four rounds of data collection through a process of hypothesis generation, refining, testing and programme theory specification. Data collection included interviews, observation, documents, feedback sessions and an interpretive forum. Findings: Knowledge mobilisation in CLAHRCs was a function of a number of interconnected issues that provided more or less conducive conditions for collective action. The potential of CLAHRCs to close the metaphorical ‘know–do’ gap was dependent on historical regional relationships, their approach to engaging different communities, their architectures, what priorities were set and how, and providing additional resources for implementation, including investment in roles and activities to bridge and broker boundaries. Additionally, we observed a balance towards conducting research rather than implementing it. Key mechanisms of interpretations of collaborative action, opportunities for connectivity, facilitation, motivation, review and reflection, and unlocking barriers/releasing potential were important to the processes and outcomes of CLAHRCs. These mechanisms operated in different contexts including stakeholders’ positioning, or ‘where they were coming from’, governance arrangements, availability of resources, competing drivers, receptiveness to learning and evaluation, and alignment of structures, positions and resources. Preceding conditions influenced the course and journey of the CLAHRCs in a path-dependent way. We observed them evolving over time and their development led to the accumulation of different types of impacts, from those that were conceptual to, later in their life cycle, those that were more direct. Conclusions: Most studies of implementation focus on researching one-off projects, so a strength of this study was in researching a systems approach to knowledge mobilisation over time. Although CLAHRC-like approaches show promise, realising their full potential will require a longer and more sustained focus on relationship building, resource allocation and, in some cases, culture change. This reinforces the point that research implementation within a CLAHRC model is a long-term investment and one that is set within a life cycle of organisational collaboration. Funding: The National Institute for Health Research Health Services and Delivery Research programme.

BackgroundSocial network analysis (SNA) has been widely used across a range of disciplines but is most commonly applied to help improve the effectiveness and efficiency of decision making processes in commercial organisations. We are utilising SNA to inform the development and implementation of tailored behaviour-change interventions to improve the uptake of evidence into practice in the English National Health Service. To inform this work, we conducted a systematic scoping review to identify and evaluate the use of SNA as part of an intervention to support the implementation of change in healthcare settings.Methods and findingsWe searched ten bibliographic databases to October 2011. We also searched reference lists, hand searched selected journals and websites, and contacted experts in the field. To be eligible for the review, studies had to describe and report the results of an SNA performed with healthcare professionals (e.g. doctors, nurses, pharmacists, radiographers etc.) and others involved in their professional social networks. We included 52 completed studies, reported in 62 publications. Almost all of the studies were limited to cross sectional descriptions of networks; only one involved using the results of the SNA as part of an intervention to change practice.ConclusionsWe found very little evidence for the potential of SNA being realised in healthcare settings. However, it seems unlikely that networks are less important in healthcare than other settings. Future research should seek to go beyond the merely descriptive to implement and evaluate SNA-based interventions.