10 resultados para Mental health--Patients--South Carolina

em Aston University Research Archive


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Risk assessment is crucial for developing risk management plans to prevent or minimize mental health patients' risks that will impede their recovery. Risk assessments and risk management plans should be closely linked. Their content and the extent to which they are linked within one Trust is explored. There is a great deal of variability in the amount and detail of risk information collected by nurses and how this is used to develop risk management plans. Keeping risk assessment information in one place rather than scattered throughout patient records is important for ensuring it can be accessed easily and linked properly to risk management plans. Strengthening the link between risk assessment and management will help ensure interventions and care is tailored to the specific needs of individual patients, thus promoting their safety and well-being. Thorough risk assessment helps in developing risk management plans that minimize risks that can impede mental health patients' recovery. Department of Health policy states that risk assessments and risk management plans should be inextricably linked. This paper examines their content and linkage within one Trust. Four inpatient wards for working age adults (18-65 years) in a large mental health Trust in England were included in the study. Completed risk assessment forms, for all patients in each inpatient ward were examined (n= 43), followed by an examination of notes for the same patients. Semi-structured interviews took place with ward nurses (n= 17). Findings show much variability in the amount and detail of risk information collected by nurses, which may be distributed in several places. Gaps in the risk assessment and risk management process are evident, and a disassociation between risk information and risk management plans is often present. Risk information should have a single location so that it can be easily found and updated. Overall, a more integrated approach to risk assessment and management is required, to help patients receive timely and appropriate interventions that can reduce risks such as suicide or harm to others. © 2011 Blackwell Publishing.

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Background Medicines reconciliation-identifying and maintaining an accurate list of a patient's current medications-should be undertaken at all transitions of care and available to all patients. Objective A self-completion web survey was conducted for chief pharmacists (or equivalent) to evaluate medicines reconciliation levels in secondary care mental health organisations. Setting The survey was sent to secondary care mental health organisations in England, Scotland, Northern Ireland and Wales. Method The survey was launched via Bristol Online Surveys. Quantitative data was analysed using descriptive statistics and qualitative data was collected through respondents free-text answers to specific questions. Main outcomes measure Investigate how medicines reconciliation is delivered, incorporate a clear description of the role of pharmacy staff and identify areas of concern. Results Forty-two (52 % response rate) surveys were completed. Thirty-seven (88.1 %) organisations have a formal policy for medicines reconciliation with defined steps. Results show that the pharmacy team (pharmacists and pharmacy technicians) are the main professionals involved in medicines reconciliation with a high rate of doctors also involved. Training procedures frequently include an induction by pharmacy for doctors whilst the pharmacy team are generally trained by another member of pharmacy. Mental health organisations estimate that nearly 80 % of medicines reconciliation is carried out within 24 h of admission. A full medicines reconciliation is not carried out on patient transfer between mental health wards; instead quicker and less exhaustive variations are implemented. 71.4 % of organisations estimate that pharmacy staff conduct daily medicine reconciliations for acute admission wards (Monday to Friday). However, only 38 % of organisations self-report to pharmacy reconciling patients' medication for other teams that admit from primary care. Conclusion Most mental health organisations appear to be complying with NICE guidance on medicines reconciliation for their acute admission wards. However, medicines reconciliation is conducted less frequently on other units that admit from primary care and rarely completed on transfer when it significantly differs to that on admission. Formal training and competency assessments on medicines reconciliation should be considered as current training varies and adherence to best practice is questionable.

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Outcomes measures, which is the measurement of effectiveness of interventions and services has been propelled onto the health service agenda since the introduction of the internal market in the 1990s. It arose as a result of the escalating cost of inpatient care, the need to identify what interventions work and in what situations, and the desire for effective information by service users enabled by the consumerist agenda introduced by Working for Patients white paper. The research reported in this thesis is an assessment of the readiness of the forensic mental health service to measure outcomes of interventions. The research examines the type, prevalence and scope of use of outcomes measures, and further seeks a consensus of views of key stakeholders on the priority areas for future development. It discusses the theoretical basis for defining health and advocates the argument that the present focus on measuring effectiveness of care is misdirected without the input of users, particularly patients in their care, drawing together the views of the many stakeholders who have an interest in the provision of care in the service. The research further draws on the theory of structuration to demonstrate the degree to which a duality of action, which is necessary for the development, and use of outcomes measures is in place within the service. Consequently, it highlights some of the hurdles that need to be surmounted before effective measurement of health gain can be developed in the field of study. It concludes by advancing the view that outcomes research can enable practitioners to better understand the relationship between the illness of the patient and the efficacy of treatment. This understanding it is argued would contribute to improving dialogue between the health care practitioner and the patient, and further providing the information necessary for moving away from untested assumptions, which are numerous in the field about the superiority of one treatment approach over another.

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Mental-health risk assessment practice in the UK is mainly paper-based, with little standardisation in the tools that are used across the Services. The tools that are available tend to rely on minimal sets of items and unsophisticated scoring methods to identify at-risk individuals. This means the reasoning by which an outcome has been determined remains uncertain. Consequently, there is little provision for: including the patient as an active party in the assessment process, identifying underlying causes of risk, and eecting shared decision-making. This thesis develops a tool-chain for the formulation and deployment of a computerised clinical decision support system for mental-health risk assessment. The resultant tool, GRiST, will be based on consensual domain expert knowledge that will be validated as part of the research, and will incorporate a proven psychological model of classication for risk computation. GRiST will have an ambitious remit of being a platform that can be used over the Internet, by both the clinician and the layperson, in multiple settings, and in the assessment of patients with varying demographics. Flexibility will therefore be a guiding principle in the development of the platform, to the extent that GRiST will present an assessment environment that is tailored to the circumstances in which it nds itself. XML and XSLT will be the key technologies that help deliver this exibility.

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Background: Medication discrepancies are common when patients cross organisational boundaries. However, little is known about the frequency of discrepancies within mental health and the efficacy of interventions to reduce discrepancies. Objective: To evaluate the impact of a pharmacy-led reconciliation service on medication discrepancies on admissions to a secondary care mental health trust. Setting: In-patient mental health services. Methods: Prospective evaluation of pharmacy technician led medication reconciliation for admissions to a UK Mental Health NHS Trust. From March to June 2012 information on any unintentional discrepancies (dose, frequency and name of medication); patient demographics; and type and cause of the discrepancy was collected. The potential for harm was assessed based on two scenarios; the discrepancy was continued into primary care, and the discrepancy was corrected during admission. Logistic regression identified factors associated with discrepancies. Main outcome measure: Mean number of discrepancies per admission corrected by the pharmacy technician. Results Unintentional medication discrepancies occurred in 212 of 377 admissions (56.2 %). Discrepancies involving 569 medicines (mean 1.5 medicines per admission) were corrected. The most common discrepancy was omission (n = 464). Severity was assessed for 114 discrepancies. If the discrepancy was corrected within 16 days the potential harm was minor in 71 (62.3 %) cases and moderate in 43 (37.7 %) cases whereas if the discrepancy was not corrected the potential harm was minor in 27 (23.7 %) cases and moderate in 87 (76.3 %) cases. Discrepancies were associated with both age and number of medications; the stronger association was age. Conclusions: Medication discrepancies are common within mental health services with potentially significant consequences for patients. Trained pharmacy technicians are able to reduce the frequency of discrepancies, improving safety. © 2013 Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie.

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Background: Patient involvement in health care is a strong political driver in the NHS. However in spite of policy prominence, there has been only limited previous work exploring patient involvement for people with serious mental illness. Aim: To describe the views on, potential for, and types of patient involvement in primary care from the perspectives of primary care health professionals and patients with serious mental illness. Design of study: Qualitative study consisting of six patient, six health professional and six combined focus groups between May 2002 and January 2003. Setting: Six primary care trusts in the West Midlands, England. Method: Forty-five patients with serious mental illness, 39 GPs, and eight practice nurses participated in a series of 18 focus groups. All focus groups were audiotaped and fully transcribed. Nvivo was used to manage data more effectively. Results: Most patients felt that only other people with lived experience of mental illness could understand what they were going through. This experience could be used to help others navigate the health- and social-care systems, give advice about medication, and offer support at times of crisis. Many patients also saw paid employment within primary care as a way of addressing issues of poverty and social exclusion. Health professionals were, however, more reluctant to see patients as partners, be it in the consultation or in service delivery. Conclusions: Meaningful change in patient involvement requires commitment and belief from primary care practitioners that the views and experiences of people with serious mental illness are valid and valuable.

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Aim: To explore current risk assessment processes in general practice and Improving Access to Psychological Therapies (IAPT) services, and to consider whether the Galatean Risk and Safety Tool (GRiST) can help support improved patient care. Background: Much has been written about risk assessment practice in secondary mental health care, but little is known about how it is undertaken at the beginning of patients' care pathways, within general practice and IAPT services. Methods: Interviews with eight general practice and eight IAPT clinicians from two primary care trusts in the West Midlands, UK, and eight service users from the same region. Interviews explored current practice and participants' views and experiences of mental health risk assessment. Two focus groups were also carried out, one with general practice and one with IAPT clinicians, to review interview findings and to elicit views about GRiST from a demonstration of its functionality. Data were analysed using thematic analysis. Findings Variable approaches to mental health risk assessment were observed. Clinicians were anxious that important risk information was being missed, and risk communication was undermined. Patients felt uninvolved in the process, and both clinicians and patients expressed anxiety about risk assessment skills. Clinicians were positive about the potential for GRiST to provide solutions to these problems. Conclusions: A more structured and systematic approach to risk assessment in general practice and IAPT services is needed, to ensure important risk information is captured and communicated across the care pathway. GRiST has the functionality to support this aspect of practice.

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One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

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Failure to detect patients at risk of attempting suicide can result in tragic consequences. Identifying risks earlier and more accurately helps prevent serious incidents occurring and is the objective of the GRiST clinical decision support system (CDSS). One of the problems it faces is high variability in the type and quantity of data submitted for patients, who are assessed in multiple contexts along the care pathway. Although GRiST identifies up to 138 patient cues to collect, only about half of them are relevant for any one patient and their roles may not be for risk evaluation but more for risk management. This paper explores the data collection behaviour of clinicians using GRiST to see whether it can elucidate which variables are important for risk evaluations and when. The GRiST CDSS is based on a cognitive model of human expertise manifested by a sophisticated hierarchical knowledge structure or tree. This structure is used by the GRiST interface to provide top-down controlled access to the patient data. Our research explores relationships between the answers given to these higher-level 'branch' questions to see whether they can help direct assessors to the most important data, depending on the patient profile and assessment context. The outcome is a model for dynamic data collection driven by the knowledge hierarchy. It has potential for improving other clinical decision support systems operating in domains with high dimensional data that are only partially collected and in a variety of combinations.

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Background. The Scale for Psychosocial Factors in Food Allergy (SPS-FA) is based on the biopsychosocial model of health and was developed and validated in Chile to measure the interaction between psychological variables and allergy symptoms in the child. We sought to validate this scale in an English speaking population and explore its relationship with parental quality of life, self-efficacy, and mental health. Methods. Parents (n = 434) from the general population in the UK, who had a child with a clinical diagnosis of food allergy, completed the SPS-FA and validated scales on food allergy specific parental quality of life (QoL), parental self-efficacy, and general mental health. Findings. The SPS-FA had good internal consistency (alphas = .61-.86). Higher scores on the SPS-FA significantly correlated with poorer parental QoL, self-efficacy, and mental health. All predictors explained 57% of the variance in SPS-FA scores with QoL as the biggest predictor (β = .52). Discussion. The SPS-FA is a valid scale for use in the UK and provides a holistic view of the impact of food allergy on the family. In conjunction with health-related QoL measures, it can be used by health care practitioners to target care for patients and evaluate psychological interventions for improvement of food allergy management.