Classifying clinical decision making:interpreting nursing intuition, heuristics and medical diagnosis

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.

Staying in nursing:what factors determine whether nurses intend to remain employed?

Aim. To test a model of eight thematic determinants of whether nurses intend to remain in nursing roles. Background. Despite the dramatic increase in the supply of nurses in England over the past decade, a combination of the economic downturn, funding constraints and more generally an ageing nursing population means that healthcare organizations are likely to encounter long-term problems in the recruitment and retention of nursing staff. Design. Survey. Method. Data were collected from a large staff survey conducted in the National Health Service in England between September-December 2009. A multi-level model was tested using MPlus statistical software on a sub-sample of 16,707 nurses drawn from 167 healthcare organizations. Results. Findings were generally supportive of the proposed model. Nurses who reported being psychologically engaged with their jobs reported a lower intention to leave their current job. The perceived availability of developmental opportunities, being able to achieve a good work-life balance and whether nurses' encountered work pressures were also influencing factors on their turnover intentions. However, relationships formed with colleagues and patients displayed comparatively small relationships with turnover intentions. Conclusion. The focus at the local level needs to be on promoting employee engagement by equipping staff with the resources (physical and monetary) and control to enable them to perform their tasks to standards they aspire to and creating a work environment where staff are fully involved in the wider running of their organizations, communicating to staff that patient care is important and the top priority of the organization. © 2012 Blackwell Publishing Ltd.

Classifying clinical decision making:a unifying approach

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

The effect of ward design on the well-being of post-operative patients

Changes in the design of hospital wards have usually been determined by architects and members of the nursing and medical professions; the views and preferences of patients have seldom been sought directly. The Hospital Anxiety and Depression scale and the Disturbance Due to Hospital Noise questionnaire were administered to 64 female patients on bay and Nightingale wards together with a questionnaire designed for this study. Perceptions of social and physical factors of ward design were examined, and their relationship to psychological well-being and sleep patterns. The results show that the bay ward seemed to offer a more favourable environment for patients but some of the disadvantages of bay wards are balanced by better staffing levels and better and more modern facilities. Visibility to nurses was lower on the bay ward. The Nightingale ward was perceived as significantly noisier than the bay ward and noise levels were significantly correlated to anxiety scores. Paradoxically the increase in noise levels appeared to improve the perceived level of privacy on the Nightingale ward. Seventy-five per cent of patients were found to prefer the bay ward design, and since neither design appears to have major disadvantages their continued introduction should be encouraged. However, recommendations are made concerning the optimizing of patients' well-being within the bay ward setting.

Study of management decision making by ward sisters in a hospital and the effects on decision making after the implementation of a decision support sytem

This thesis considers management decision making at the ward level in hospitals especially by ward sisters, and the effectiveness of the intervention of a decision support system. Nursing practice theories were related to organisation and management theories in order to conceptualise a decision making framework for nurse manpower planning and deployment at the ward level. Decision and systems theories were explored to understand the concepts of decision making and the realities of power in an organisation. In essence, the hypothesis was concerned with changes in patterns of decision making that could occur with the intervention of a decision support system and that the degree of change would be governed by a set of `difficulty' factors within wards in a hospital. During the course of the study, a classification of ward management decision making was created, together with the development and validation of measuring instruments to test the research hypothesis. The decision support system used was rigorously evaluated to test whether benefits did accrue from its implementation. Quantitative results from sample wards together with qualitative information collected, were used to test this hypothesis and the outcomes postulated were supported by these findings. The main conclusion from this research is that a more rational approach to management decision making is feasible, using information from a decision support system. However, wards and ward sisters that need the most assistance, where the `difficulty' factors in the organisation are highest, benefit the least from this type of system. Organisational reviews are needed on these identified wards, involving managers and doctors, to reduce the levels of un-coordinated activities and disruption.

The potential for pharmacists to manage children attending emergency departments

AIM: There have been concerns about maintaining appropriate clinical staff levels in Emergency Departments in England.1 The aim of this study was to determine if Emergency Department attendees aged from 0-16 years could be managed by community pharmacists or hospital independent prescriber pharmacists with or without further advanced clinical practice training. METHOD: A prospective, 48 site, cross-sectional, observational study of patients attending Emergency Departments (ED) in England, UK was conducted. Pharmacists at each site collected up to 400 admissions and paediatric patients were included in the data collection. The pharmacist independent prescribers (one for each site) were asked to identify patient attendance at their Emergency Department, record anonymised details of the cases-age, weight, presenting complaint, clinical grouping (e.g. medicine, orthopaedics), and categorise each presentation into one of four possible categories: CP, Community Pharmacist, cases which could be managed by a community pharmacist outside an ED setting; IP-cases that could be managed at ED by a hospital pharmacist with independent prescriber status; IPT, Independent Prescriber Pharmacist with additional training-cases which could be managed at ED by a hospital pharmacist independent prescriber with additional clinical training; and MT, Medical Team only-cases that were unsuitable for the pharmacist to manage. An Impact Index was calculated for the two most frequent clinical groupings using the formula: Impact index=percentage of the total workload of the clinical grouping multiplied by the percentage ability of pharmacists to manage that clinical group. RESULTS: 1623 out of 18,229 (9%) attendees, from 45 of the 48 sites, were children aged from 0 to 16 years of age (median 8 yrs, range 0-16), 749 were female and 874 were male. Of the 1623 admissions, 9% of the cases were judged to be suitable for clinical management by a community pharmacist (CP), 4% suitable for a hospital pharmacist independent prescriber (IP), 32% suitable for a hospital independent pharmacist prescriber with additional training (IPT); and the remaining 55% were only suitable for the Medical Team (MT). The most frequent clinical groups and impact index for the attendees were General Medicine=10.78 and orthopaedics=10.60. CONCLUSION: Paediatric patients attending Emergency Departments were judged by pharmacists to be suitable for management outside a hospital setting in approximately 1 in 11 cases, and by hospital independent prescriber pharmacists in 4 in 10 cases. With further training, it was found that the total proportion of cases that could be managed by a pharmacist was 45%. The greatest impact for pharmacist management occurs in general medicine and orthopaedics.

Advanced mean field methods:theory and practice

A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.