A decision support tool for supporting individuals living with long-term conditions make informed choices: LTC-Choices tool for continuous healthcare

An increasing number of individuals are now living with some form of chronic, long-term condition (LTC). The holistic perspective of LTCs makes it important to acknowledge that priorities and decisions are in fluctuation over the course of an individual’s life. The landscape of digital healthcare is full of information systems that capture individuals’ health data, clinical guidelines and/or advice on health conditions, which taken together can help create a comprehensive overview of suitable lifestyle choices to optimise health and well-being. Despite this, there is no evidence of existing frameworks to support individuals living with LTCs from a continuum of care perspective. In this paper, we propose such a multidimensional model for a decision support tool – LTC-Choices. This tool was developed from existing work conducted by the authors around use of multicriteria to support health decisionmaking. We illustrate how LTC-Choices can be implemented using the example of individuals living post-stroke

An exploration of how domains of quality of care relate to overall care experience

Purpose: To determine the relative influence of the different domains of healthcare quality from the Care Experience Feedback Improvement Tool and identify key predictors of healthcare quality from the patients’ perspective. Measurement is necessary to determine whether quality of healthcare is improving. The Care Experience Feedback Improvement Tool was developed as a brief measure of patient experience. It is important to determine the relative influence of the different domains of healthcare quality to further clarify how the Care Experience Feedback Improvement Tool can be used and identify key predictors of healthcare quality from the patients’ perspective. Methods: 802 people with a healthcare experience during the previous 12 months were telephoned to complete the Care Experience Feedback Improvement Tool questions and an additional eleven-point global rating of patient experience. To estimate the influence of different domains of healthcare quality on patient overall ratings of quality of healthcare experience, we regressed the overall rating of patient experience with each component of quality (safety, effectiveness, timely, caring, enables system navigation and person-centred). Findings: We found that all of the domains of the Care Experience Feedback Improvement Tool, influenced patient experience ratings of healthcare quality. Specifically, results show the degree of influence, the impact of demographics and how high scores for overall rating of patient experience can be predicted. Originality: Our findings suggest that all of the Care Experience Feedback Improvement Tool domains are important in terms of capturing the wholeness of the patient experience of healthcare quality to direct local quality improvement

Electronic swallowing intervention package to support swallowing function in patients with head and neck cancer: development and feasibility study

Background: Many patients undergoing treatment for head and neck cancer (HNC) experience significant swallowing difficulties, and there is some evidence that swallowing exercises may improve outcomes, including quality of life. This feasibility study developed an evidence-based, practical Swallowing Intervention Package (SiP) for patients undergoing chemo-radiotherapy (CRT) for HNC. As part of the study, an electronic version of SiP (e-SiP) was concurrently developed to support patients to self-manage during treatment. This paper reports on the e-SiP component of this work. Objective: To develop and conduct preliminary evaluation of an electronic support system (e-SiP) for patients undergoing CRT for head and neck cancer. Methods: The study involved health professionals and patients who were undergoing CRT for head and neck cancer. The scoping stage of e-SiP development involved investigated the potential usefulness of e-SiP, exploring how e-SiP would look and feel and what content would be appropriate to provide. Patient and carer focus groups and a health professionals’ consensus day were used as a means of data gathering around potential e-SiP content. A repeat focus group looked at an outline version of e-SIP and informed the next stage of its development around requirements for tool. This was followed by further development and a testing stage of e-SiP involved the coding of a prototype which was then evaluated using a series of steering group meetings, semi-structured interviews with both patients and health care professionals, and analysis of e-SiP log data. Results: Feedback from focus groups and health professional interviews was very positive and it was felt e-SiP use would support and encourage patients in conducting their swallowing exercises. However, of the ten patients offered e-SIP, only two opted to use it. For these patients, aspects of the e-SIP application were considered useful, in particular the ease of keeping a diary of exercises performed. Interviews with users and non-users suggested significant barriers to its use. Most significantly the lack of flexibility of platform on which e-SiP could be accessed appeared a dominant factor in deterring e-SiP use. Conclusions: Results suggest a need for further research to be conducted around the implementation of e-SiP. This involves evaluating how e-SiP can be better integrated into usual care, and through patient training and staff engagement, can be seen as a beneficial tool to help support patients in conducting swallowing exercises

Improving the sustainability of hospital-based interventions: a study protocol for a systematic review

Introduction Sustaining effective interventions in hospital environments is essential to improving health outcomes, and reducing research waste. Current evidence suggests many interventions are not sustained beyond their initial delivery. The reason for this failure remains unclear. Increasingly research is employing theoretical frameworks and models to identify critical factors that influence the implementation of interventions. However, little is known about the value of these frameworks on sustainability. The aim of this review is to examine the evidence regarding the use of theoretical frameworks to maximise effective intervention sustainability in hospital-based settings in order to better understand their role in supporting long-term intervention use. Methods and analysis Systematic review. We will systematically search the following databases: Medline, AMED, CINAHL, Embase and Cochrane Library (CENTRAL, CDSR, DARE, HTA). We will also hand search relevant journals and will check the bibliographies of all included studies. Language and date limitations will be applied. We will include empirical studies that have used a theoretical framework (or model) and have explicitly reported the sustainability of an intervention (or programme). One reviewer will remove obviously irrelevant titles. The remaining abstracts and full-text articles will be screened by two independent reviewers to determine their eligibility for inclusion. Disagreements will be resolved by discussion, and may involve a third reviewer if required. Key study characteristics will be extracted (study design, population demographics, setting, evidence of sustained change, use of theoretical frameworks and any barriers or facilitators data reported) by one reviewer and cross-checked by another reviewer. Descriptive data will be tabulated within evidence tables, and key findings will be brought together within a narrative synthesis. Ethics and dissemination Formal ethical approval is not required as no primary data will be collected. Dissemination of results will be through peer-reviewed journal publications, presentation at an international conference and social media

Evaluation of a digital consultation and self-care advice tool in primary care: a multi-methods study

Digital services are often regarded as a solution to the growing demands on primary care services. Provision of a tool offering advice to support self-management as well as the ability to digitally consult with a General Practitioner (GP) has the potential to alleviate some of the pressure on primary care. This paper reports on a Phase II, 6-month evaluation of eConsult, a web-based triage and consultation system that was piloted across 11 GP practices across Scotland. Through a multi-method approach the evaluation explored eConsult use across practices, exposing both barriers and facilitators to its adoption. Findings suggest that expectations that eConsult would offer an additional and alternative method of accessing GP services were largely met. However, there is less certainty that it has fulfilled expectations of promoting self-help. In addition, low uptake meant that evaluation of current effectiveness was difficult for practices to quantify. The presence of an eConsult champion(s) within the practice was seen to be a significant factor in ensuring successful integration of the tool. A lack of patient and staff engagement, insufficient support and lack of protocols around processes were seen as barriers to its success

Particle Swarm Optimisation for learning Bayesian Networks

This paper discusses the potential of Particle Swarm Optimisation (PSO) for inducing Bayesian Networks (BNs). Specifically, we detail two methods which adopt the search and score approach to BN learning. The two algorithms are similar in that they both use PSO as the search algorithm, and the K2 metric to score the resulting network. The difference lies in the way networks are constructed. The CONstruct And Repair (CONAR) algorithm generates structures, validates, and repairs if required, and the REstricted STructure (REST) algorithm, only permits valid structures to be developed. Initial experiments indicate that these approaches produce promising results when compared to other BN learning strategies

Economic Impact Study: United Methodist Community House Expansion

In 2019, United Methodist Community House (UMCH) commissioned IFF, a real estate consulting firm, to perform a strategic facility plan. This strategic plan’s needs assessment included the following: A new senior center, expanded child development center, and relocation of administrative offices. Seidman Research Office at Grand Valley State University was retained by UMCH to perform an economic assessment of the IFF strategic facility plan. This economic assessment will: (A) evaluate the economic impact of construction of proposed senior center; (B) evaluate the economic impact of UMCH operations; (C) evaluate the economic impact of expanded child development center; and (D) quantify the economic impact of the new senior center (magnet effect)

Economic Impact Study: Grand Rapids Public Museum Proposed Redesign and Expansion

The Grand Rapids Public Museum (GRPM) has formalized a proposal to renovate and expand the current building (built in 1994). The proposed redesign and expansion include: A $39.8M addition to the south end of the building; Expanding rental space to accommodate larger groups and allow multiple events simultaneously; Different pricing strategies for each floor of the museum

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

Developing SASSA: a Soil Analysis Support System for Archaeologists

A constant problem for field archaeologists is the need for familiarity with the core concepts of a diverse range of specialist disciplines. Soils and sediments are an integral part of archaeological sites, yet the teaching of soils in archaeology degrees is variable and many archaeologists complain they are lacking in the confidence and skills required to describe and interpret the deposits they excavate. SASSA (Soil Analysis Support System for Archaeologists) is a free-to-use, internet based system designed to familiarise archaeologists with the concepts and possibilities offered by geoarchaeology (the scientific study of soils and sediments). SASSA consists of two core components: the knowledge base and field tool. The ‘front-end’ of the website is the knowledge base; this uses Wiki technology to allow users to add their own content and encourage dialogue between archaeologists and geoarchaeologists. Whilst the field tool uses an XML data structure and decision tree, decision support system to guide the user through the process of describing and interpreting soils and sediments. SASSA is designed for use on both ‘static’ (PC) and ‘mobile’ (PDA and laptop) hardware in order to provide in-situ field support as well as offering office-based ‘reference book style’ help. This article introduces the aims of SASSA, presents SASSA as a user might experience it, and discusses the computing technology used to construct the system