BACKGROUND: Older adults are at high risk of developing delirium in the emergency department (ED); however, it is under-recognized in routine clinical care. Lack of detection and treatment is associated with poor outcomes, such as mortality. Performance measures (PMs) are needed to identify variations in quality care to help guide improvement strategies. The purpose of this study is to gain consensus on a set of quality statements and PMs that can be used to evaluate delirium care quality for older ED patients.
METHODS: A 3-round modified e-Delphi study was conducted with ED clinical experts. In each round, participants rated quality statements according to the concepts of importance and actionability, then their associated PMs according to the concept of necessity (1-9 Likert scales), with the ability to comment on each. Consensus and stability were evaluated using a priori criteria using descriptive statistics. Qualitative data was examined to identify themes within and across quality statements and PMs, which went through a participant validation exercise in the final round.
RESULTS: Twenty-two experts participated, 95.5% were from west or central Canada. From 10 quality statements and 24 PMs, consensus was achieved for six quality statements and 22 PMs. Qualitative data supported justification for including three quality statements and one PM that achieved consensus slightly below a priori criteria. Three overarching themes emerged from the qualitative data related to quality statement actionability. Nine quality statements, nine structure PMs, and 14 process PMs are included in the final set, addressing four areas of delirium care: screening, diagnosis, risk reduction and management.
CONCLUSIONS: Results provide a set of quality statements and PMs that are important, actionable, and necessary to a diverse group of clinical experts. To our knowledge, this is the first known study to develop a de novo set of guideline-based quality statements and PMs to evaluate the quality of delirium care older adults receive in the ED setting.

UNASSIGNED: Surgical site infections (SSIs) are among the most common healthcare-associated infections occurring following 1%-3% of all surgical procedures. Their rates are the highest following abdominal surgery. They are still associated with increased morbidity and healthcare costs despite the advancement in the medical field. Many risk factors for SSIs following abdominal surgery have been identified. The aim of this study is to comprehensively assess these risk factors as published in peer-reviewed journals.
UNASSIGNED: A systematic review was conducted with accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.
UNASSIGNED: The databases for search were PubMed and Cochrane Library, in addition to reference lists. Studies were retrieved and assessed for their quality. Data were extracted in a designed form, and a stratified synthesis of data was conducted to report the significant risk factors.
UNASSIGNED: Patients undergoing general abdominal surgery.
UNASSIGNED: The intervention of general abdominal surgery.
UNASSIGNED: To identify and assess the risk factors for SSI following abdominal surgery.
UNASSIGNED: Literature search yielded 813 articles, and the final screening process identified 11 eligible studies. The total number of patients is 11 996. The rates of SSI ranged from 4.09% to 26.7%. Nine studies were assessed to be of high quality, the remaining two studies have moderate quality. Stratified synthesis of data was performed for risk factors using summary measures (OR/risk ratio, 95% CI, and p value). Male sex and increased body mass index (BMI) were identified as significant demographic risk factors, and long operative time was among the major significant procedure-related risk factors.
UNASSIGNED: Male sex, increased BMI, diabetes, smoking, American Society of Anesthesiologists classification of >2, low albumin level, low haemoglobin level, preoperative hospital stay, long operative time, emergency procedure, open surgical approach, increased wound class, intraoperative blood loss, perioperative infection, perioperative blood transfusion, and use of drains are potential independent risk factors for SSI following abdominal surgery.

UNASSIGNED: This study aimed to develop the actual pathway to reporting and information transfer in operating theatres in relation to medical technology malfunction/failure. This with the aim of understanding the differences with the pathway published by NHS Improvement and identification of points for improvement.
UNASSIGNED: This is a qualitative study involving stakeholder interviews with doctors, nurses, manufacturers, medical device safety officer and Medicines and Healthcare products Regulatory Agency.
UNASSIGNED: Data were collected on reporting pathway used in operating theatres. Clinical staff who took part worked in different trusts throughout UK while manufacturers provided devices in UK and EU/USA.
UNASSIGNED: Semistructured interviews were completed with 15 clinicians and 13 manufacturers. Surveys were completed by 38 clinicians and 5 manufacturers. Recognised methods of pathway development were used. The Lean Six Sigma principles adapted to healthcare were used to develop suggestions for improvement.
UNASSIGNED: To identify the differences between the set pathway to reporting and information transfer to what is occurring on a day-to-day basis as reported by staff. Identify points in the pathway where improvements could be applied.
UNASSIGNED: The developed pathway demonstrated great complexity of the current reporting system for medical devices. It identified numerous areas that give rise to problems and multiple biases in decision making. This highlighted the core issues leading to under-reporting and lack of knowledge on device performance and patient risk. Suggestions for improvement were deduced based on end user requirements and identified problems.
UNASSIGNED: This study has provided a detailed understanding of the key problem areas that exist within the current reporting system for medical devices and technology. The developed pathway sets to address the key problems to improve reporting outcomes. The identification of pathway differences between \'work as done\' and \'work as imagined\' can lead to development of quality improvements that could be systematically applied.

UNASSIGNED: To examine the current state of unique device identifier (UDI) implementation, including barriers and facilitators, among eight health systems participating in a research network committed to real-world evidence (RWE) generation for medical devices.
UNASSIGNED: Mixed methods, including a structured survey and semistructured interviews.
UNASSIGNED: Eight health systems participating in the National Evaluation System for health Technology research network within the USA.
UNASSIGNED: Individuals identified as being involved in or knowledgeable about UDI implementation or medical device identification from supply chain, information technology and high-volume procedural area(s) in their health system.
UNASSIGNED: Interview topics were related to UDI implementation, including barriers and facilitators; UDI use; benefits of UDI adoption; and vision for UDI implementation. Data were analysed using directed content analysis, drawing on prior conceptual models of UDI implementation and the Exploration, Preparation, Implementation, Sustainment framework. A brief survey of health system characteristics and scope of UDI implementation was also conducted.
UNASSIGNED: Thirty-five individuals completed interviews. Three of eight health systems reported having implemented UDI. Themes identified about barriers and facilitators to UDI implementation included knowledge of the UDI and its benefits among decision-makers; organisational systems, culture and networks that support technology and workflow changes; and external factors such as policy mandates and technology. A final theme focused on the availability of UDIs for RWE; lack of availability significantly hindered RWE studies on medical devices.
UNASSIGNED: UDI adoption within health systems requires knowledge of and impetus to achieve operational and clinical benefits. These are necessary to support UDI availability for medical device safety and effectiveness studies and RWE generation.

UNASSIGNED: Brain tumours lead to significant morbidity including a neurocognitive, physical and psychological burden of disease. The extent to which they impact the multiple domains of health is difficult to capture leading to a significant degree of unmet needs. Mobile health tools such as Vinehealth have the potential to identify and address these needs through real-world data generation and delivery of personalised educational material and therapies. We aimed to establish the feasibility of Vinehealth integration into brain tumour care, its ability to collect real-world and (electronic) patient-recorded outcome (ePRO) data, and subjective improvement in care.
UNASSIGNED: A mixed-methodology IDEAL stage 1 study.
UNASSIGNED: A single tertiary care centre.
UNASSIGNED: Six patients consented and four downloaded and engaged with the mHealth application throughout the 12 weeks of the study.
UNASSIGNED: Over a 12-week period, we collected real-world and ePRO data via Vinehealth. We assessed qualitative feedback from mixed-methodology surveys and semistructured interviews at recruitment and after 2 weeks.
UNASSIGNED: 565 data points were captured including, but not limited to: symptoms, activity, well-being and medication. EORTC QLQ-BN20 and EQ-5D-5L completion rates (54% and 46%) were impacted by technical issues; 100% completion rates were seen when ePROs were received. More brain cancer tumour-specific content was requested. All participants recommended the application and felt it improved care.
UNASSIGNED: Our findings indicate value in an application to holistically support patients living with brain cancer tumours and established the feasibility and safety of further studies to more rigorously assess this.

BACKGROUND: Abdominal aortic aneurysms (AAA) are often identified incidentally on imaging studies. Patients and/or providers are frequently unaware of these AAA and the need for long-term follow-up. We sought to evaluate the outcome of a nurse-navigator-run AAA program that uses a natural language processing (NLP) algorithm applied to the electronic medical record (EMR) to identify patients with imaging report-identified AAA not being followed actively.
METHODS: A commercially available AAA-specific NLP system was run on EMR data at a large, academic, tertiary hospital with an 11-year historical look back (January 1, 2010, to June 2, 2021), to identify and characterize AAA. Beginning June 3, 2021, a direct link between the NLP system and the EMR enabled for real-time review of imaging reports for new AAA cases. A nurse-navigator (1.0 full-time equivalent) used software filters to categorize AAA according to predefined metrics, including repair status and adherence to Society for Vascular Surgery imaging surveillance protocol. The nurse-navigator then interfaced with patients and providers to reestablish care for patients not being followed actively. The nurse-navigator characterized patients as case closed (eg, deceased, appropriate follow-up elsewhere, refuses follow-up), cases awaiting review, and cases reviewed and placed in ongoing surveillance using AAA-specific software. The primary outcome measures were yield of surveillance imaging performed or scheduled, new clinic visits, and AAA operations for patients not being followed actively.
RESULTS: During the prospective study period (January 1, 2021, to December 30, 2021), 6,340,505 imaging reports were processed by the NLP. After filtering for studies likely to include abdominal aorta, 243,889 imaging reports were evaluated, resulting in the identification of 6495 patients with AAA. Of these, 2937 cases were reviewed and closed, 1183 were reviewed and placed in ongoing surveillance, and 2375 are awaiting review. When stratifying those reviewed and placed in ongoing surveillance by maximum aortic diameter, 258 were 2.5 to 3.4 cm, 163 were 3.5 to 3.9 cm, 213 were 4 to 5 cm, and 49 were larger than 5 cm; 36 were saccular, 86 previously underwent open repair, 274 previously underwent endovascular repair, and 104 were other. This process yielded 29 new patient clinic visits, 40 finalized imaging studies, 29 scheduled imaging studies, and 4 AAA operations in 3 patients among patients not being followed actively.
CONCLUSIONS: The application of an AAA program leveraging NLP successfully identifies patients with AAA not receiving appropriate surveillance or counseling and repair. This program offers an opportunity to improve best practice-based care across a large health system.

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BACKGROUND: The observation of a feeding by a professional is important to strengthen breastfeeding. The Bristol Breastfeeding Assessment Tool (BBAT) was translated into Spanish and validated.
METHODS: Translation and back-translation of the original scale was done. Six pediatricians and six pediatric nurses collaborated. At the newborn\'s first visit, a feeding was observed and the pediatrician and nurse scored the BBAT scale independently. The nurse also scored the LATCH Breastfeeding Assessment (LATCH) and each mother filled out the Breastfeeding Self-Efficacy Scale (BSES-SF). Mothers were appointed a week later and the nurse re-scored the BBAT.
RESULTS: A total of 62 mothers participated. There was good internal consisitency for the BBAT (Cronbach\'s alpha = 0.83 in the assessment made by the nurses and Cronbach\'s alpha = 0.79 in the assessment made by the pediatricians). Inter-rater consistency showed an intra-class correlation coefficient of 0.91, while for the test-retest was 0.67. Concurrent validity with the BSES-SF scale was good and with the LATCH scale very good. The factor analysis showed the one-dimensional character of the scale and a good homogeneity of the 4 items (positioning = 0.771, attachment = 0.852, sucking = 0.856 and swallowing = 0.679).
CONCLUSIONS: The scale obtained in Spanish shows good reliability and validity. The BBAT is an easy-to-use tool that allows breastfeeding assessment and determines the aspects that need to be improved.

BACKGROUND: The Quality of Interactions Schedule (QuIS) is an observational tool to assess the quality of staff-patient interactions in a healthcare context. QuIS is a promising measure for the evaluation of compassionate care, particularly where care is being delivered to patient populations, such as older people, who may be excluded from self-completion data collection methods. This study investigates the content validity of QuIS in identification of negative staff-patient interactions in acute care.
METHODS: Staff-patient interactions (n = 1598) on adult inpatient units with a high proportion of older patients in two UK National Health Service hospitals were observed and rated using QuIS. When rating interactions as negative quality, observers recorded brief field notes to explain the rating. Content analysis was used to develop categories of negative interaction type. These categories were compared with the QuIS negative interaction definitions.
RESULTS: Eighty-eight negative ratings were accompanied by a field note that could be used in the analysis. Five interaction categories were identified: Patient calls for help, call not acknowledged; Staff focused on task and appear to ignore/not hear patient; Patient-led interactions appear dismissed or ignored; Patient prevented from doing something without explanation; Staff interact with each other or talk to relatives, not including patient. There was clear association between the derived categories and QuIS guidance for negative ratings.
CONCLUSIONS: These findings support the validity of QuIS data in relation to measurement of interaction quality in acute care settings. Extending the research to a wider range of settings would be useful.

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