Current Issue : April - June Volume : 2019 Issue Number : 2 Articles : 6 Articles
Background: Patient falls, the most common safety events resulting in adverse patient outcomes, impose\nsignificant costs and have become a great burden to the healthcare community. Current patient fall reporting\nsystems remain in the early stage that is far away from reaching the ultimate goal toward a safer healthcare.\nAccording to the Kirkpatrick model, the key challenge in reaction, learning, behavior and results is the realization of\nlearning stage due to the lack of knowledge management, sharing and growing mechanism.\nMethods: Based on the key contributing factors defined by AHRQ Common Formats 2.0, a hierarchical list of\ncontributing factors for patient falls was established by expert review and discussion. Using the list as an\ninfrastructure, we designed and developed a novel reporting system, where a strategy to identify contributing\nfactors is intended to provide reporters knowledge support, in the form of similar cases and potential solutions. A\nsurvey containing two scenarios was conducted to evaluate the learning effect of our system.\nResults: In both scenarios, potential solutions recommended by the system were annotated with correct\ncontributing factors, and presented only when the corresponding factors were identified from the query report or\nselected by the user. The five experts show substantial consistency (Fleissâ?? kappa > 0.6) and high agreement\n(ranging between fully agree and mostly agree) in the assessment of the three perspectives of the system, which\nverifies the effectiveness of the proposed knowledge support toward sharing and learning through the novel\nreporting system.\nConclusions: This study proposed a profile of contributing factors that could measure the similarity of patient\nsafety events. Based on the profile, a knowledge-based reporting and learning system was developed to bridge the\ngap between surveillance, reporting, and retrospective analysis in the fall management circle. The system holds\npromise in improving event reporting toward better and safer healthcare....
Background: Nurses can often be key frontline healthcare professionals\nworking in remote and rural settings due to resource constraints including an\nacute shortage of medical practitioners. The provision of regular and appropriate\nContinuing Professional Development (CPD) to support nurses to be\nable to provide effective health care therefore becomes even more significant\nin these settings. Engagement and â??buy inâ? from relevant stakeholders at an\norganisational level is a critical step to ensure CPD provision for nurses. Objectives:\nThe overall aim was to achieve consensus on CPD for registered\nnurses working in remote and rural settings among key stakeholders using\nthe Nominal Group Technique (NGT). The objectives were to identify stakeholdersâ??\nperspectives on the priorities for CPD training for registered nurses;\nthe preferred modes of delivery for CPD and perceived barriers and facilitators\nfor CPD access. Methods: NGT was used as a qualitative method with\nkey organisational stakeholders in several iterative stages in the form of a\nworkshop. Results: 22 senior healthcare professionals involved in medical\nand nursing education representing north, northeast, central India and the\nstate of Karnataka in South India participated in the workshop. Three key\nfindings emerged from this study: priorities of CPD; preferred modes of CPD\ndelivery; barriers and facilitators to CPD access. Conclusion: Engagement\nwith key stakeholders to identify CPD priorities can help facilitate strategic\nplanning and provision of relevant and accessible CPD programmes for\nnurses working within remote and rural health care contexts in India....
Background: Nosocomial infections are among the most common complications in hospitals. A major part is\ncaused by multidrug-resistant organisms (MDRO). MRSA is still the most prominent and frequent MDRO. The early\ndetection of carriers of multidrug-resistant bacteria is an effective measure to reduce nosocomial infections caused by\nMDRO. For patients who are planning to go to the hospital, an outpatient screening for MDRO and pre-hospital\ndecolonization is recommended. However, the effectiveness of such pre-admission MDRO management in preparation\nfor a planned hospital stay has not yet been sufficiently scientifically examined from an economic perspective.\nMethods: A decision tree will be used to develop scenarios for MDRO screening and treatment in the context of the\noutpatient and inpatient sectors using MRSA-positive patients as an example. Subsequently, the expected costs for the\nrespective strategy are presented.\nResults: The decision tree analysis shows that the expected costs of outpatient MRSA management are 8.24 Euro and that\nof inpatient MRSA management are 672.51 Euros.\nConclusion: The forward displacement of the MRSA screening to the ambulatory sector and any subsequent\noutpatient decolonization for patients with a planned hospitalization is the most cost-effective strategy and should\nbecome a standard benefit. Excluding opportunity costs, the expected costs of inpatient MRSA management are 54.94 Euros....
Background: Access to palliative care is a key quality metric which most healthcare organizations strive to improve.\nThe primary challenges to increasing palliative care access are a combination of physicians over-estimating patient\nprognoses, and a shortage of palliative staff in general. This, in combination with treatment inertia can result in a\nmismatch between patient wishes, and their actual care towards the end of life.\nMethods: In this work, we address this problem, with Institutional Review Board approval, using machine learning\nand Electronic Health Record (EHR) data of patients. We train a Deep Neural Network model on the EHR data of\npatients from previous years, to predict mortality of patients within the next 3-12 month period. This prediction is\nused as a proxy decision for identifying patients who could benefit from palliative care.\nResults: The EHR data of all admitted patients are evaluated every night by this algorithm, and the palliative care team\nis automatically notified of the list of patients with a positive prediction. In addition, we present a novel technique\nfor decision interpretation, using which we provide explanations for the modelâ??s predictions.\nConclusion: The automatic screening and notification saves the palliative care team the burden of time consuming\nchart reviews of all patients, and allows them to take a proactive approach in reaching out to such patients rather then\nrelying on referrals from the treating physicians....
Background: Common measures used to describe preventive treatment effects today are proportional, i.e. they\ncompare the proportions of events in relative or absolute terms, however they are not easily interpreted from the\npatientâ??s perspective and different magnitudes do not seem to clearly discriminate between levels of effect\npresented to people.\nMethods: In this randomised cross-sectional survey experiment, performed in a Swedish population-based sample\n(n = 1041, response rate 58.6%), the respondents, aged between 40 and 75 years were given information on a\nhypothetical preventive cardiovascular treatment. Respondents were randomised into groups in which the\ntreatment was described as having the effect of delaying a heart attack for different periods of time (Delay of\nEvent, DoE): 1 month, 6 months or 18 months. Respondents were thereafter asked about their willingness to initiate\nsuch therapy, as well as questions about how they valued the proposed therapy.\nResults: Longer DoE:s were associated with comparatively greater willingness to initiate treatment. The proportions\naccepting treatment were 81, 71 and 46% when postponement was 18 months, 6 months and 1 month\nrespectively. In adjusted binary logistic regression models the odds ratio for being willing to take therapy was 4.45\n(95% CI 2.72â??7.30) for a DoE of 6 months, and 6.08 (95% CI 3.61â??10.23) for a DoE of 18 months compared with a\nDoE of 1 month. Greater belief in the necessity of medical treatment increased the odds of being willing to initiate\ntherapy.\nConclusions: Lay peopleâ??s willingness to initiate preventive therapy was sensitive to the magnitude of the effect\npresented as DoE. The results indicate that DoE is a comprehensible effect measure, of potential value in shared\nclinical decision-making....
Background: Thirty-day hospital readmissions represent an international challenge leading to increased prevalence\nof adverse events, reduced quality of care and pressure on healthcare serviceâ??s resources and finances. There is a\nneed for a broader understanding of hospital readmissions, how they manifest, and how resources in the primary\nhealthcare service may affect hospital readmissions. The aim of the study was to examine how nurses and nursing\nhome leaders experienced the resource situation, staffing and competence level in municipal healthcare services,\nand if and how they experienced these factors to influence hospital readmissions.\nMethod: The study was conducted as a comparative case study of two municipalities affiliated with the same hospital,\nchosen for historical differences in readmission rates. Nurses and leaders from four nursing homes participated in focus\ngroups and interviews. Data were analyzed within and across cases.\nResults: The analysis resulted in four common themes, with some variation in each municipality, describing nursesâ??\nand leadersâ?? experience of the nursing home resource situation, staffing level and competence and their perception of\nfactors affecting hospital readmissions. The nursing home patients were described as becoming increasingly complex\nwith a subsequent need for increased nurse competence. There was variation in competence and staffing between\nnursing homes, but capacity building was an overall focus. Economic limitations and attempts at saving\nthrough cost-cutting were present, but not perceived as affecting patient care and the availability of medical\nequipment. Several factors such as nurse competence and staffing, physician coverage, and adequate communication\nand documentation, were recognized as factors affecting hospital readmissions across the municipalities.\nConclusion: Several factors related to nursesâ?? and leadersâ?? experience of the resource situation, staffing and\ncompetence level were suggested to affect hospital readmissions and the municipalities were similar in their\nanswers regarding these factors. Patients were perceived as more complex with higher patient mortality forcing longterm\nnursing homes to shift towards an acute care or palliative function, and short-term nursing homes to function as\nâ??small hospitalsâ?, requiring higher nurse competence. Staffing, competence and physician coverage did not seem to have\nadjusted to the new patient group in some nursing homes....
Loading....