159 research outputs found
Informal caregiver decision-making factors associated with technology adoption and use in home health care: A systematic scoping review
Technology systems to alleviate the burden of managing patient’s health at home are increasing. The home is a unique place where chronic disease self-management is often performed by informal caregivers. Informal caregivers provide up to 80% of in‐home care to dementia patients. Yet, how caregivers make decisions about adopting a specific technology has not been thoroughly explored. This review mapped evidence on decision-making factors associated with technology adoption and use by caregivers for patients at home. This study followed the recommendations for performing systematic scoping reviews that were developed by members of the Joanna Briggs Institute. Four electronic databases (PubMed, Medline, CINAHL, and Embase) were searched using both medical subject headings (MeSH terms) and key words. A total of 6 papers were included for data synthesis. The scope of the technology types and patient diagnoses explored in the included studies has been mapped. Factors such as information, comprehension, motivation, time, perceived burden, and perceived caregiving competency were found to affect whether to adopt caregiver decision-making regarding on the use of technology when caring for patients at home. There are other factors uniquely springing from the patient and technology as well as shared issues between caregivers and patient or caregivers and technology. Informal caregiver decision-making on technology adoption can have a considerable impact on patient care at home. This systematic scoping review found that although some factors depend on technology type and patient diagnosis, there were some common factors across the research. Those factors can be carefully considered in referring technology use for caregivers. Further, more focused study in this under-investigated area is much needed
Nurse documentation of sexual orientation and gender identity in home healthcare: A text mining study
Ambiguity Uncertainty and Risk: Reframing the task of suicide risk assessment and prevention in acute in-patient mental health
The work of the National Confidential Inquiry into Suicide by People with Mental Illness has served to draw attention to the issue of suicide amongst users of mental health services including inpatient and provided the basis for a series of recommendations aimed at improving practice (Appleby et al., 2001, NIMHE 2003). Such recommendations include further training on risk assessment for practitioners. However, representing the problem of suicide as one which can be 'managed' by risk assessment particularly quantitative actuarial approaches implicitly misrepresents the phenomena of suicidality as something which can predicted and therefore managed may be inherently unpredictable at the level of the individual over the short term. We need instead to acknowledge that our work with service users who may be contemplating suicide embraces and acknowledges both uncertainty and ambiguity and seeks to assess risk phenomenologically at the level of the individual such that by understanding their reasons for living and dying we can work in partnership with them to find hope
How, for Whom, and in Which Contexts or Conditions Augmented and Virtual Reality Training Works in Upskilling Health Care Workers: Realist Synthesis
BACKGROUND: Using traditional simulators (eg, cadavers, animals, or actors) to upskill health workers is becoming less common because of ethical issues, commitment to patient safety, and cost and resource restrictions. Virtual reality (VR) and augmented reality (AR) may help to overcome these barriers. However, their effectiveness is often contested and poorly understood and warrants further investigation. OBJECTIVE: The aim of this review is to develop, test, and refine an evidence-informed program theory on how, for whom, and to what extent training using AR or VR works for upskilling health care workers and to understand what facilitates or constrains their implementation and maintenance. METHODS: We conducted a realist synthesis using the following 3-step process: theory elicitation, theory testing, and theory refinement. We first searched 7 databases and 11 practitioner journals for literature on AR or VR used to train health care staff. In total, 80 papers were identified, and information regarding context-mechanism-outcome (CMO) was extracted. We conducted a narrative synthesis to form an initial program theory comprising of CMO configurations. To refine and test this theory, we identified empirical studies through a second search of the same databases used in the first search. We used the Mixed Methods Appraisal Tool to assess the quality of the studies and to determine our confidence in each CMO configuration. RESULTS: Of the 41 CMO configurations identified, we had moderate to high confidence in 9 (22%) based on 46 empirical studies reporting on VR, AR, or mixed simulation training programs. These stated that realistic (high-fidelity) simulations trigger perceptions of realism, easier visualization of patient anatomy, and an interactive experience, which result in increased learner satisfaction and more effective learning. Immersive VR or AR engages learners in deep immersion and improves learning and skill performance. When transferable skills and knowledge are taught using VR or AR, skills are enhanced and practiced in a safe environment, leading to knowledge and skill transfer to clinical practice. Finally, for novices, VR or AR enables repeated practice, resulting in technical proficiency, skill acquisition, and improved performance. The most common barriers to implementation were up-front costs, negative attitudes and experiences (ie, cybersickness), developmental and logistical considerations, and the complexity of creating a curriculum. Facilitating factors included decreasing costs through commercialization, increasing the cost-effectiveness of training, a cultural shift toward acceptance, access to training, and leadership and collaboration. CONCLUSIONS: Technical and nontechnical skills training programs using AR or VR for health care staff may trigger perceptions of realism and deep immersion and enable easier visualization, interactivity, enhanced skills, and repeated practice in a safe environment. This may improve skills and increase learning, knowledge, and learner satisfaction. The future testing of these mechanisms using hypothesis-driven approaches is required. Research is also required to explore implementation considerations
Variation in National Clinical Audit Data Capture:Is Using Routine Data the Answer?
National Clinical Audit (NCA) data are collected from all National Health Service providers in the UK, to measure the quality of care and stimulate quality improvement initatives. As part of a larger study we explored how NHS providers currently collect NCA data and the resources involved. Study results highlight a dependence on manual data entry and use of professional resources, which could be improved by exploring how routine clinical data could be captured more effectively
Clinical decision making in the recognition of dying: a qualitative interview study
Background:
Recognising dying is an essential clinical skill for general and palliative care professionals alike. Despite the high importance, both identification and good clinical care of the dying patient remains extremely difficult and often controversial in clinical practice. This study aimed to answer the question: “What factors influence medical and nursing staff when recognising dying in end-stage cancer and heart failure patients?”
Methods:
This study used a descriptive approach to decision-making theory. Participants were purposively sampled for profession (doctor or nurse), specialty (cardiology or oncology) and grade (senior vs junior). Recruitment continued until data saturation was reached. Semi-structured interviews were conducted with NHS medical and nursing staff in an NHS Trust which contained cancer and cardiology tertiary referral centres. An interview schedule was designed, based on decision-making literature. Interviews were audio-recorded and transcribed and analysed using thematic framework. Data were managed with Atlas.ti.
Results:
Saturation was achieved with 19 participants (7 seniors; 8 intermediate level staff; 4 juniors). There were 11 oncologists (6 doctors, 5 nurses) and 8 cardiologists (3 doctors, 5 nurses). Six themes were generated: information used; decision processes; modifying factors; implementation; reflecting on decisions and related decisions. The decision process described was time-dependent, ongoing and iterative, and relies heavily on intuition.
Conclusions:
This study supports the need to recognise the strengths and weaknesses of expertise and intuition as part of the decision process, and of placing the recognition of dying in a time-dependent context. Clinicians should also be prepared to accept and convey the uncertainty surrounding these decisions, both in practice and in communication with patients and carers
Exploring variation in the use of feedback from national clinical audits : a realist investigation
BACKGROUND: National Clinical Audits (NCAs) are a well-established quality improvement strategy used in healthcare settings. Significant resources, including clinicians' time, are invested in participating in NCAs, yet there is variation in the extent to which the resulting feedback stimulates quality improvement. The aim of this study was to explore the reasons behind this variation. METHODS: We used realist evaluation to interrogate how context shapes the mechanisms through which NCAs work (or not) to stimulate quality improvement. Fifty-four interviews were conducted with doctors, nurses, audit clerks and other staff working with NCAs across five healthcare providers in England. In line with realist principles we scrutinised the data to identify how and why providers responded to NCA feedback (mechanisms), the circumstances that supported or constrained provider responses (context), and what happened as a result of the interactions between mechanisms and context (outcomes). We summarised our findings as Context+Mechanism = Outcome configurations. RESULTS: We identified five mechanisms that explained provider interactions with NCA feedback: reputation, professionalism, competition, incentives, and professional development. Professionalism and incentives underpinned most frequent interaction with feedback, providing opportunities to stimulate quality improvement. Feedback was used routinely in these ways where it was generated from data stored in local databases before upload to NCA suppliers. Local databases enabled staff to access data easily, customise feedback and, importantly, the data were trusted as accurate, due to the skills and experience of staff supporting audit participation. Feedback produced by NCA suppliers, which included national comparator data, was used in a more limited capacity across providers. Challenges accessing supplier data in a timely way and concerns about the quality of data submitted across providers were reported to constrain use of this mode of feedback. CONCLUSION: The findings suggest that there are a number of mechanisms that underpin healthcare providers' interactions with NCA feedback. However, there is variation in the mode, frequency and impact of these interactions. Feedback was used most routinely, providing opportunities to stimulate quality improvement, within clinical services resourced to collect accurate data and to maintain local databases from which feedback could be customised for the needs of the service
A Predictive Risk Model for Infection-Related Hospitalization among Home Healthcare Patients
Infection prevention is a high priority for home healthcare (HHC) but tools are lacking to identify patients at highest risk for developing infections. The purpose of this study was to develop and test a predictive risk model to identify HHC patients at risk of an infection-related hospitalization or emergency department visit. A non-experimental study using secondary data was conducted. The Outcome and Assessment Information Set linked with relevant clinical data from 112,788 HHC admissions in 2014 were used for model development (70% of data) and testing (30%). A total of 1,908 patients (1.69%) were hospitalized or received emergency care associated with infection. Stepwise logistic regression models discriminated between individuals with and without infections. Our final model, when classified by highest risk of infection, identified a high portion of those who were hospitalized or received emergent care for an infection while also correctly categorizing 90.5% of patients without infection. The risk model can be used by clinicians to inform care planning. This is the first study to develop a tool for predicting infection risk that can be used to inform how to direct additional infection control intervention resources on high-risk patients, potentially reducing infection related hospitalizations, emergency department visits, and costs
Developing a community of digital nurse and midwife researchers
Despite nurses and midwives taking on digital leadership roles and influencing the future of healthcare, there is a scarcity of research in the United Kingdom on the development of their roles and processes.
In this workshop, we will discuss digital nursing leaders and their roles within academic communities. We will also consider the strategies to adopt to link into existing research networks and how to investigate the paradigm shift in nursing and midwifery catalysed by information technology.
In our discussion, we will increase awareness of the research capabilities of the digital nursing and midwifery workforce. Hosting the workshop will help support a proposal for an ongoing project that enhances digital nursing and midwifery research skills and networks. The workshop will provide a platform for a digital nursing and midwifery research community of practice.
Using patient-generated health data in clinical practice: how timing influences its function in rheumatology outpatient consultations
ObjectiveUtilizing patient-generated health data (PGHD) in clinical consultations and informing clinical and shared decision-making processes has the potential to improve clinical practice but has proven challenging to implement. Looking at consultations between people with rheumatoid arthritis (RA) and rheumatologists, this study examines when and how daily PGHD was discussed in outpatient consultations.MethodsWe conducted a secondary qualitative analysis of 17 audio-recorded research outpatient consultations using thematic and interactional approaches.ResultsClinicians decided when to look at the PGHD and what symptoms to prioritise during the consultation. When PGHD was introduced early in consultations, it was usually used to invite patients to collaborate (elicit new information). When introduced later, PGHD was used to corroborate patient accounts and to convince the patient about proposed actions and treatments. Clinicians occasionally disregarded PGHD if it did not fit into their clinical assessment.ConclusionThe time that PGHD is introduced may influence how PGHD is used in consultations. Further research is needed to understand how best to empower patients to discuss PGHD.Practice ImplicationsEducating patients and clinicians about the importance of timing and strategies when using PGHD in consultations may help promote shared decision-making
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