Sufficiency and relevance of information for inpatients in general ward settings: a qualitative exploration of information exchange between patients and nurses

Background  Information exchange as part of shared decision-making is widely discussed in research and policy literature as a means of improving patient involvement in treatment and care. To date information exchange between patients and nurses has not been explored in ward contexts.  Objective  To explore the sufficiency of, and intentions behind, information exchanged by patients and nurses in surgical and medical ward settings using a recognised model of shared decision-making.  Design  A multiple-case study design was used. Data were collected from 19 cases. Each case comprised one patient, the nurses interacting with that patient, the interactions between them, and their perceptions about the interactions.  Settings  The study was undertaken across six surgical, six medical and one rehabilitation ward in a large teaching hospital in the United Kingdom.  Participants  Purposive sampling was used to first recruit nurses and then patients. Inclusion criteria included nurses registered with the Nursing and Midwifery Council, and patients who had been in hospital for more than 24 hours and who could consent to participating. Twenty-two nurses and 19 patients participated.  Methods  Interactions from 19 cases were observed and audio-recorded. Individual interviews with patients and nurses followed, and were related to, the observed interactions.  Results  Patients and nurses perceived they had exchanged sufficient information for their own needs including patient involvement, due to: information being shared previously and on an ongoing basis; having asked all their questions; therapeutic patient/nurse relationships; and, nurses speaking in lay terms. In contrast, the observational data suggested that insufficient information was exchanged between patients and nurses due to: lost opportunities for sharing information; paternalistic practice; and withholding information.  Conclusion  The elements of information exchange within a recognised model of shared decision-making do not adequately fit with patient/nurse interactions in ward settings. Participants generally perceived they had given and received enough information for their own needs. Therefore, the ways in which patients and nurses currently interact, could remain as they are. Policymakers should be aware of the varying contexts where healthcare staff work, and should promote information exchange and shared decision-making more strategically. Due to the complexities of patient/nurse interactions, consideration should be given to situation and context when applying these findings to practice

A Descriptive Survey to Identify the Skill and Information Needs of Hospital Based Multidisciplinary Mental Health Staff in the Move to Community Care

Mental Health care was changing from a segregational hospital-based service to an integrational community-based service. The Government policy documents that were setting the community care objectives indicated that staff would require further education as a result of the changes (DoH, 1994; DoH, 1993; DoH, 1989a; SHHD, 1988). However the documents did not indicate what education was required. Furthermore a search of the mental health literature in the UK did not reveal any empirical studies of sufficient size and methodological rigor to identify what education was required. Literature from the USA in mental health and from learning disabilities and general nursing in the UK suggested that mental health staff moving into the community would need to leam more skills and gain more knowledge in order to be effective. This study aimed to identify and describe the skill and information needs of a multidisciplinary population of mental health staff in the movement from a hospital-based working environment to a community-based working environment. In order to describe the skill and information needs four research questions were posed. The questions addressed issues of identification of the current educational preparation of staff; identification of the current skills and skills required for community practice and identification of the knowledge possessed by some multidisciplinary mental health staff about community care changes. Questionnaires were distributed to the population of mental health care workers in one Scottish Health Board (n=695) and a 36% response rate achieved. A volunteer subsample of 20 questionnaire respondents were interviewed to enrich and clarify data from questionnaires. Data analysis revealed a diversity of skills was possessed by mental health staff. However, it was concluded that hospital based mental health staff needed to leam more skills and gain more knowledge to transfer to community based posts. This study makes a positive start in identifying the skill and information needs of a population of mental health care staff moving to a community-based working environment. However, as a consequence of the low response rate the findings are considered tentatively. Conclusions and recommendations have implications for service purchasers, providers, professionals and clients

Developing and Evaluating Complex Interventions: Enhancing the Role of Qualitative Research

The use of qualitative research methods alongside randomized controlled trials of health-care interventions have the potential to contribute to the development and evaluation of both complex and other health interventions. Qualitative evaluations of interventions are rarely reported but can provide insight into the intervention process, and the feasibility and acceptability of the intervention, to improve and adapt interventions

Commercial gaming devices for stroke upper limb rehabilitation: the stroke survivor experience

Introduction Approximately 30% of stroke survivors experience an upper limb impairment, which impacts on participation and quality of life. Gaming devices (Nintendo Wii) are being incorporated into rehabilitation to improve function. We explored the stroke survivor experience of gaming as an upper limb intervention. Methods Semi-structured, individual interviews with stroke survivors living within the UK were completed. Interviews were audio-recorded, transcribed verbatim and analysed using Framework methods. Transcripts were coded and summarised into thematic charts. Thematic charts were refined during analysis until the final framework emerged. Results We captured experiences of 12 stroke survivors who used Nintendo Wii. Gaming devices were found to be acceptable for all ages but varying levels of enthusiasm existed. Enthusiastic players described gaming as having a positive impact on their motivation to engage in rehabilitation. For some, this became a leisure activity, encouraging self-practice. Non-enthusiastic players preferred sports to gaming. Conclusion An in-depth account of stroke survivor experiences of gaming within upper limb rehabilitation has been captured. Suitability of gaming should be assessed individually and stroke survivor abilities and preference for interventions should be taken into consideration. There was no indication that older stroke survivors or those with no previous experience of gaming were less likely to enjoy the activity

ADePT (algorithm for decision-making after pilot and feasibility trials): a decision aid for progression from feasibility study to main trial

Background: Complex intervention guidance advocates pilot trials and feasibility studies as part of a phased approach to development, testing and evaluation of healthcare interventions. In this paper an example of a feasibility study and pilot trial for a randomised controlled trial (RCT) of pelvic floor muscle training for prolapse is used to explore challenges for progression to main trial. Methods: A four-centre feasibility study including pilot trial aiming to randomise 50 women with prolapse of any type or stage and who had had a pessary successfully fitted. We used published methodological categories to classify and analyse the problems that arose in our feasibility study. Subsequently we sought to locate potential solutions that might minimise the trade-off between an explanatory and pragmatic main trial. Results: The feasibility study pointed to significant potential problems in relation to participant recruitment, features of the intervention, acceptability of the intervention to participants and outcome measurement. Finding minimal evidence to support our decision-making regarding the transition from feasibility work to a trial, we developed an algorithm (ADePT; Algorithm for Decision-making after Pilot and feasibility Trials) which we subsequently used as a guide. The algorithm sought to: 1) encourage systematic identification and appraisal of problems and potential solutions; 2) improve transparency of decision-making processes; and 3) reveal tensions that exist between choices which lead to a pragmatic versus explanatory trial. Conclusions: We have developed a decision-support tool that may aid future researchers to identify the most appropriate solutions to problems identified within pilot and feasibility studies

Does the socioeconomic background of pregnant women make a difference to their perceptions of antenatal care? : a qualitative case study

Socioeconomically deprived women are at greater risk of adverse pregnancy outcomes. To counteract this, attention tends to focus around access (equality) of services. Yet access may not equate with the meaningfulness (equity) of services for women from different socioeconomic backgrounds. Without understanding equity we are not in a position to plan appropriate and equitable care. This study aimed to determine pregnant women's perceptions of the current antenatal provision and to determine if women from the extremes of socioeconomic background perceived their antenatal care differently. Longitudinal interviews were undertaken with multiple, comparative antenatal case studies between January 2007 and April 2009. Cases were primigravida women from ‘least deprived’ (n=9) and ‘most deprived’ (n=12) geographical areas as identified by the Scottish Index of Multiple Deprivation (SIMD 2006). The data were analysed using case study replication analysis. Analysis of categorical data from the sample groups indicated they were less diverse than might have been expected in terms of age and education. However in the key variables of housing tenure, potential income and socioeconomic status based on area of residence, the groups were indicative of the SIMD target populations. The preliminary analysis showed that the sample groups considered the initial General Practitioner contact to be less than adequate and the subsequent utility of antenatal education to be based on self perceived relevance. The substantive analysis showed little difference in access to antenatal services between the ‘least’ and ‘most’ deprived groups but perception of care differed. A key difference concerned the level of ‘engagement’ (defined as personalisation and active involvement in care, power and relationships and health literacy). Using these concepts, engagement was present in most of the ‘least deprived’ group and almost none of the ‘most deprived’ group. In comparison with women from affluent areas, more deprived women described less evidence of: personal connection to their own care; shared decision making; and perceived value in relation to the written educational aspects of antenatal care. In terms of the preliminary analysis, the results suggest that utility of educational material may need to be reviewed to ensure it is relevant to specific needs. Without this relevance, key information may be missed. The substantive analysis suggests that for women from socioeconomically deprived areas, access may be a less useful indicator than engagement when assessing quality of antenatal services. The lack of engagement perceived by those who are most deprived suggests that equity of service has yet to be attained for those who are most in need. Future research needs to be directed to the potential reasons that may undermine equity and engagement in women from lower socioeconomic areas.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Scottish Ambulance Service New Clinical Response Model

Evaluation suggests new model accurately identifies patients in greatest need through emergency 999 calls

Stroke patients' informal caregivers: Patient, caregiver, and service factors that affect caregiver strain

Background and Purpose: Research has revealed that caring for a stroke patient can result in caregiver strain and a myriad of other difficulties for caregivers. This study aims to identify the level of strain experienced by caregivers in the early months after stroke and to assess the relationship between caregiver strain and caregiver characteristics, patient characteristics, and service inputs. Methods: Stroke patients were identified through a random stratified sample of general practices. Patients were asked to identify their principal informal caregiver. Strain was measured with the Caregiver Strain Index, and all data were collected from caregivers at 1, 3, and 6 months after the patient's stroke. Multiple regression analysis was used to examine the factors associated with caregiver strain. Results: Six months after stroke, 37% of caregivers were experiencing considerable strain. The amount of time a caregiver spent helping a stroke patient, the amount of time the caregiver spent with the patient, and the caregiver's health were all significantly associated with the level of strain experienced. Although none of the services or patient factors tested in this study were consistently associated with strain, an indicator of stroke severity was significant at each time point. Conclusions: Caregivers are experiencing strain, which has implications for research and service provision. Service providers need to identify caregivers at risk of greater strain and to help caregivers work through situations that services cannot alter. Research is needed to identify services that are effective in strain alleviation. Future research should also aim to identify the interface between patient characteristics and strain, burden, and depression and particularly to assess the caregiver's perception of these relationships

NCRM report for SAS

Executive Summary The Scottish Ambulance Service (SAS) responds to around 1.8 million calls per year, including responses to 700,000 emergency and unscheduled incidents. Of these responses, over 500,000 are received through the 999 call service. SAS transfers around 90,000 patients between hospitals each year and responds to over 150,000 urgent requests for admission, transfer and discharge from GPs and hospitals (SAS, 2015). In 2017 SAS began to implement a new clinical response model (NCRM). The aims of the NCRM are to: - Save more lives by more accurately identifying patients with immediately life-threatening conditions, such as cardiac arrest; - Safely and more effectively send a matched resource first time to all patients based on their clinical need. The University of Stirling, commissioned to carry out an independent evaluation of the NCRM using data provided by SAS and NHS Information Services Division (ISD), considered the following questions: 1. Are patients with Immediately Life Threatening (ILT) conditions more quickly and accurately identified? 2. Are more lives saved as a consequence of the best available resources being dispatched to the patient? 3. Are improved clinical outcomes achieved if the matched resources are sent first time for patients with non-ILT conditions? Methods A quantitative analysis was conducted comparing SAS data on response to 999 calls from a pre-NCRM implementation time-period (January 2016) and a post-implementation time-period (January 2017 and January 2018). NHS ISD linked additional data from the Unscheduled Care Data Mart (UCDM) to the SAS data. UCDM contains emergency department data (ED) and data from the National Records of Scotland (NRS) for mortality data. Data were examined for the purple code (the highest risk category of call to the 999 service) and within the purple category, those patients in cardiac arrest. The same analyses were conducted for the remaining colour codes and a selection of clinical categories within these colour codes: breathing difficulties (red), stroke (amber) and falls (yellow). Key Findings Interpreting this data It should be noted that data is taken from only three (and in some cases two) time points and only from the month of January. While this does allow some relevant comparisons between the years, the findings cannot be generalised to the whole year and the whole time-period in question (January 2016 – January 2018). In addition, call volume was approximately 9% higher in 2018 compared to 2017 and 2016 (which were similar) with over 4,000 more calls in January 2018. Further analysis of the data using data from each month, as well as individual-level data (rather than it being aggregated), would allow much more robust and relevant evidence of change and the impact on the service and patients. 1. Are patients with Immediately Life Threatening (ILT) conditions more quickly and accurately identified? Patients with ILT conditions (purple calls) would appear to be more accurately identified post-NCRM with a noticeable increase in patients coded with ILT conditions by 2018. The time to respond to ILT conditions was slightly longer (but not statistically significant). Speed Resource allocation was used as an indicator of speed of identification. We found that resource allocation (and in turn response times) did not differ significantly between January 2016 (pre-NCRM) and January 2017 (post-NCRM introduction) for ILT (purple) calls. However, there was a longer time to allocate resources (i.e. identify) purple calls in 2018 compared to 2016 and this was statistically significant. For all other colour codes, 2017 and 2018 resource allocation were also significantly slower than 2016 (except amber 2017 calls) as expected with a priority-based system. Call handlers were provided with further training and development in the process of triage over the course of 2016 onwards, with the aim of more accurately allocating patients into the most appropriate category, and therefore it was to be expected that time to allocate resources and identification into the correct category would take longer. Accuracy Comparing 2016 (pre-NCRM) and 2017 (post-NCRM introduction) outcomes data, we found that sensitivity (correctly identifying a purple, ILT condition) was higher in 2017 compared to 2016, but specificity (correctly identifying a non-ILT condition) was lower in 2017. Overall accuracy (the likelihood of being correctly identified as either ILT or non-ILT) was not different between the two-time points. Similar results were also seen for the cardiac arrest cases within the purple calls. 2. Are more lives saved as a consequence of the best available resources being dispatched to the patient? Survival for purple-coded patients is markedly lower with respect to all other causes (as one would expect) and reflects that purple-coded calls/conditions are a unique category (in terms of risk of death) and represent the majority of incidents where patients face an immediate threat to life (ILT). The risk of death across the other colour codes is small in comparison and therefore differences of survival seem to exist only for the purple-coded patients. The cardiac arrest rate within the purple coded is around 53%. Survival analysis for all patients within the purple code and specifically for those affected by cardiac arrest are considered next. There seems to be a considerable (~20%) increase in survival for all purple-coded patients comparing January 2016 to January 2017, which is constant over time from time 0 (confirmed dead when the ambulance arrives at the scene) to 30 days post-call. When comparing January 2016 to January 2018 for the same group, survival also increased (~10%). The number of lives saved, 30 days post-call, in patients with ILT conditions in January 2016 (pre-NCRM) was 32 (14.2% of purple calls), and in post-NCRM in January 2017 was 134 (28.6% of purple calls) and in January 2018 was 182 (26.6% of purple calls). Although the numbers of patients with ILT conditions has increased, the data from the specificity and sensitivity analysis (Table 14) shows that there is no difference in false positive rates between the years. This suggests that the acuity of these patients remains very high and that the increase in volume represents patients correctly identified with the highest requirement for immediate response. Therefore, the increase in survival probability with those with ILT conditions is not likely to be caused by artificial inflation caused by conservative allocation of patients with ILT conditions to the purple code but rather by appropriate allocation and intervention(s) to those patients at risk from death due to ILT conditions. In terms of the 2018 survival probability being lower than in 2017, it is possible that the higher call-load in 2018 has limited the impact previously seen in 2017. Continued monitoring of these data is needed to identify how mortality has been impacted by the NCRM over the longer-term. 3. Are improved clinical outcomes achieved if the matched resources are sent first time for patients with non-ILT conditions? Overall survival for all non-ILT codes (Red, Amber, Yellow and Green) was similar, as noted above (where purple calls carry much higher risk of death). For these codes there was also no clear difference in survival in 2017 versus 2016 or 2018 versus 2016. Breathing difficulty (a sub-set of the red calls) seems to have worsened between 2016 and 2017, with 451 patients having a decrease in survival from 3% to 6%, with the gap widening as time passes. However, by 2018, survival was at 2016 levels despite the number of incidents (n=2044) back to the levels seen in 2016 (n=2018). No differences between years seem to be present for stroke or falls. Data on further clinical outcomes were not available within this dataset to analyse in any further detail. Conclusions By January 2018 the number of incidents (n=52,871) had increased by 9% when compared to January 2016 (n=48,544), amounting to over 4000 more incidents in 2018 than seen in 2016 or 2017. During this time of high demand in 2017 and particularly 2018, the NCRM does accurately identify patients who have the greatest need for services from SAS. The NCRM’s identification and triage of patients into triage categories, although taking time for the call handler and dispatching system, can get the ambulance and its crew to patients with the greatest need and this has improved the survival of those with immediate life-threatening conditions. Those with lower acuity needs are responded to but in a longer time period as expected when using a priority-based system (but with no apparent impact on survival). These conclusions are reached in the context of analysing aggregated data over three fairly short time-periods and further research over a longer time frame, with longitudinal data on individual cases, would further improve the evidence base for the NCRM