Ontological clarity and comprehension in health data models

Conceptual modeling forms an important part of systems analysis. If this is done incorrectly or incompletely, there can be serious implications for the resultant system, specifically in terms of rework and useability. One approach to improving the conceptual modelling process is to evaluate how well the model represents reality. Emergence of the Bunge-Wand-Weber (BWW) ontological model introduced a platform to classify and compare the grammar of conceptual modelling languages. This work applies the BWW theory to a real world example in the health arena. The general practice computing group data model was developed using the Barker Entity Relationship Modelling technique. We describe an experiment, grounded in ontological theory, which evaluates how well the GPCG data model is understood by domain experts. The results show that with the exception of the use of entities to represent events, the raw model is better understood by domain experts

Leadership clarity and team innovation in health care

The relationships among leadership clarity (i.e., team members' consensual perceptions of clarity of and no conflict over leadership of their teams), team processes, and innovation were examined in health care contexts. The sample comprised 3447 respondents from 98 primary health care teams (PHCTs), 113 community mental health teams (CMHTs), and 72 breast cancer care teams (BCTs). The results revealed that leadership clarity is associated with clear team objectives, high levels of participation, commitment to excellence, and support for innovation. Team processes consistently predicted team innovation across all three samples. Team leadership predicted innovation in the latter two samples, and there was some evidence that team processes partly mediated this relationship. The results imply the need for theory that incorporates clarity and not just style of leadership. For health care teams in particular, and teams in general, the results suggest a need to ensure leadership is clear in teams when innovation is a desirable team performance outcome. © 2003 Elsevier Inc. All rights reserved.

Getting the most out of multidisciplinary teams: a multi-sample study of team innovation in health care

Driven by the assumption that multidisciplinarity contributes positively to team outcomes teams are often deliberately staffed such that they comprise multiple disciplines. However, the diversity literature suggests that multidisciplinarity may not always benefit a team. This study departs from the notion of a linear, positive effect of multidisciplinarity and tests its contingency on the quality of team processes. It was assumed that multidisciplinarity only contributes to team outcomes if the quality of team processes is high. This hypothesis was tested in two independent samples of health care workers (N = 66 and N = 95 teams), using team innovation as the outcome variable. Results support the hypothesis for the quality of innovation, rather than the number of innovations introduced by the teams.

Spatially clustered associations in health GIS

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources and Web services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial mashups to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and correlation of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. Spatial entropy index HSu for the ScankOO analysis of the hypothetical dataset using a vicinity which is fixed by the number of points without distinction between their labels. (The size of the labels is proportional to the inverse of the index) In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

Spatially clustered associations in health related geospatial data

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources an dWeb services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial ‘mashups’ to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and ‘correlation’ of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

An evaluative analysis of the practice of teamwork in Health and Personal Social Services

This report describes the practice of teamwork as expressed in case conferences for care of the elderly and evaluates the effectiveness of case conferences in their contribution to care. The study involved the observation of more than two hundred case conferences in sixteen locations throughout the West Midlands, in which one thousand seven hundred and three participants were involved. Related investigation of service outcomes involved an additional ninety six patients who were interviewed in their homes. The pu`pose of the study was to determine whether the practice of teamwork and decision-making in case conferences is a productive and cost effective method of working. Preliminary exploration revealed the extent to which the team approach is part of the organisational culture and which, it is asserted, serves to perpetuate the mythical value of team working. The study has demonstrated an active subscription to the case conference approach, yet has revealed many weaknesses, not least of which is clear evidence that certain team members are inhibited in their contribution. Further, that the decisional process in case conferences has little consequence to care outcome. Where outcomes are examined there is evidence of service inadequacy. This work presents a challenge to professionals to confront their working practices with honesty and with vision, in the quest for the best and most cost effective service to patients.