A study of outcomes measures in forensic mental health

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.

Cues and knowledge structures used by mental-health professionals when making risk assessments

Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

Knowledge engineering for mental-health risk assessment and decision support

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.

Medication error in mental health:implications for primary care

Medication errors are associated with significant morbidity and people with mental health problems may be particularly susceptible to medication errors due to various factors. Primary care has a key role in improving medication safety in this vulnerable population. The complexity of services, involving primary and secondary care and social services, and potential training issues may increase error rates, with physical medicines representing a particular risk. Service users may be cognitively impaired and fail to identify an error placing additional responsibilities on clinicians. The potential role of carers in error prevention and medication safety requires further elaboration. A potential lack of trust between service users and clinicians may impair honest communication about medication issues leading to errors. There is a need for detailed research within this field.

Medication errors in older people with mental health problems:a review

Objective - To review and summarise published data on medication errors in older people with mental health problems. Methods - A systematic review was conducted to identify studies that investigated medication errors in older people with mental health problems. MEDLINE, EMBASE, PHARMLINE, COCHRANE COLLABORATION and PsycINFO were searched electronically. Any studies identified were scrutinized for further references. The title, abstract or full text was systematically reviewed for relevance. Results - Data were extracted from eight studies. In total, information about 728 errors (459 administration, 248 prescribing, 7 dispensing, 12 transcribing, 2 unclassified) was available. The dataset related almost exclusively to inpatients, frequently involved non-psychotropics, and the majority of the errors were not serious. Conclusions - Due to methodology issues it was impossible to calculate overall error rates. Future research should concentrate on serious errors within community settings, and clarify potential risk factors.

Quality of life, stress and mental health in parents of children with parentally diagnosed food allergy compared to medically diagnosed and healthy controls

Background. Food allergy is related to poorer quality of life (QoL) and mental health of caregivers. Many parents diagnose food allergy in their child without seeking medical care and there is limited research on this group. This study investigated parental QoL and mental health in parents of children with parent-diagnosed food allergy (PA), medically diagnosed food allergy (MA), and a control group with no allergy (NA). Methods. One hundred and fifty parents from a general population completed validated measures of QoL, anxiety, depression, and stress. Results. Parents of children with food allergy (PA or MA) reported higher stress, anxiety, and depression than the control group (all ). Parents of children with MA reported poorer food allergy related QoL compared to parents of children with PA (); parents of children with PA reported poorer general QoL compared to parents of children with MA (). Conclusion. Parents of children with food allergy have significantly poorer mental health compared to healthy controls, irrespective of whether food allergy is medically diagnosed or not. It is important to encourage parents to have their child medically tested for food allergy and to recognise and refer for psychological support where needed.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge. © 2007 Informa UK Ltd All rights reserved.

Handling varying amounts of missing data when classifying mental-health risk levels

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.

Understanding data collection behaviour of mental health practitioners

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.

Mental health pharmacists views on shared decision-making for antipsychotics in serious mental illness

Background People diagnosed with serious mental illnesses (SMIs) such as schizophrenia and bipolar affective disorder are frequently treated with antipsychotics. National guidance advises the use of shared decision-making (SDM) in antipsychotic prescribing. There is currently little data on the opinions of health professionals on the role of SDM. Objective To explore the views and experiences of UK mental health pharmacists regarding the use of SDM in antipsychotic prescribing in people diagnosed with SMI. Setting The study was conducted by interviewing secondary care mental health pharmacists in the UK to obtain qualitative data. Methods Semi-structured interviews were recorded. An inductive thematic analysis was conducted using the method of constant comparison. Main outcome measure Themes evolving from mental health pharmacists on SDM in relation to antipsychotic prescribing in people with SMI. Results Thirteen mental health pharmacists were interviewed. SDM was perceived to be linked to positive clinical outcomes including adherence, service user satisfaction and improved therapeutic relations. Despite more prescribers and service users supporting SDM, it was not seen as being practised as widely as it could be; this was attributed to a number of barriers, most predominantly issues surrounding service user’s lacking capacity to engage in SDM and time pressures on clinical staff. The need for greater effort to work around the issues, engage service users and adopt a more inter-professional approach was conveyed. Conclusion The mental health pharmacists support SDM for antipsychotic prescribing, believing that it improves outcomes. However, barriers are seen to limit implementation. More research is needed into overcoming the barriers and measuring the benefits of SDM, along with exploring a more inter-professional approach to SDM.

Global Mental Health: Five Areas for Value-Driven Training Innovation.

OBJECTIVE: In the field of global mental health, there is a need for identifying core values and competencies to guide training programs in professional practice as well as in academia. This paper presents the results of interdisciplinary discussions fostered during an annual meeting of the Society for the Study of Psychiatry and Culture to develop recommendations for value-driven innovation in global mental health training. METHODS: Participants (n = 48), who registered for a dedicated workshop on global mental health training advertised in conference proceedings, included both established faculty and current students engaged in learning, practice, and research. They proffered recommendations in five areas of training curriculum: values, competencies, training experiences, resources, and evaluation. RESULTS: Priority values included humility, ethical awareness of power differentials, collaborative action, and "deep accountability" when working in low-resource settings in low- and middle-income countries and high-income countries. Competencies included flexibility and tolerating ambiguity when working across diverse settings, the ability to systematically evaluate personal biases, historical and linguistic proficiency, and evaluation skills across a range of stakeholders. Training experiences included didactics, language training, self-awareness, and supervision in immersive activities related to professional or academic work. Resources included connections with diverse faculty such as social scientists and mentors in addition to medical practitioners, institutional commitment through protected time and funding, and sustainable collaborations with partners in low resource settings. Finally, evaluation skills built upon community-based participatory methods, 360-degree feedback from partners in low-resource settings, and observed structured clinical evaluations (OSCEs) with people of different cultural backgrounds. CONCLUSIONS: Global mental health training, as envisioned in this workshop, exemplifies an ethos of working through power differentials across clinical, professional, and social contexts in order to form longstanding collaborations. If incorporated into the ACGME/ABPN Psychiatry Milestone Project, such recommendations will improve training gained through international experiences as well as the everyday training of mental health professionals, global health practitioners, and social scientists.

Operational Stress Injuries: Impact on Family Mental Health and Well-being

This study was part of a larger scoping review and environmental scan conducted for Veterans Affairs Canada on the effects of operational stress injuries (OSIs) on the mental health and wellbeing of Veterans’ families. This paper focuses broadly on the relationships between combat (and/or deployment more generally), OSIs (primarily post-traumatic stress disorder (PTSD)), and the family. Based on the scoping review, the paper finds that existing research investigates the impacts of a Veteran’s OSI on the family, but also how various aspects of the family (such as family functioning, family support, etc.) can impact a Veteran living with an OSI.

The mental health and wellbeing of first generation migrants: a systematic-narrative review of reviews

Background
First generation migrants are reportedly at higher risk of mental ill-health compared to the settled population. This paper systematically reviews and synthesizes all reviews on the mental health of first generation migrants in order to appraise the risk factors for, and explain differences in, the mental health of this population.
Methods
Scientific databases were searched for systematic reviews (inception-November 2015) which provided quantitative data on the mental ill-health of first generation migrants and associated risk factors. Two reviewers screened titles, abstracts and full text papers for their suitability against pre-specified criteria, methodological quality was assessed.
Results
One thousand eight hundred twenty articles were identified, eight met inclusion criteria, which were all moderate or low quality. Depression was mostly higher in first generation migrants in general, and in refugees/asylum seekers when analysed separately. However, for both groups there was wide variation in prevalence rates, from 5 to 44 % compared with prevalence rates of 8–12 % in the general population. Post-Traumatic Stress Disorder prevalence was higher for both first generation migrants in general and for refugees/asylum seekers compared with the settled majority. Post-Traumatic Stress Disorder prevalence in first generation migrants in general and refugees/ asylum seekers ranged from 9 to 36 % compared with reported prevalence rates of 1–2 % in the general population. Few studies presented anxiety prevalence rates in first generation migrants and there was wide variation in those that did. Prevalence ranged from 4 to 40 % compared with reported prevalence of 5 % in the general population. Two reviews assessed the psychotic disorder risk, reporting this was two to three times more likely in adult first generation migrants. However, one review on the risk of schizophrenia in refugees reported similar prevalence rates (2 %) to estimates of prevalence among the settled majority (3 %). Risk factors for mental ill-health included low Gross National Product in the host country, downward social mobility, country of origin, and host country.
Conclusion
First generation migrants may be at increased risk of mental illness and public health policy must account for this and influencing factors. High quality research in the area is urgently needed as is the use of culturally specific validated measurement tools for assessing migrant mental health.