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Financial transparency is based on concepts for valid, standardized information that is readily accessible and routinely disseminated to stakeholders. While Congress and others continuously ask for an accounting of public health investments, transparency remains an ignored concept. The objective of this study was to examine financial transparency practices in other industries considered as part of the public health system. Key informants, regarded as financial experts on the operations of hospitals, school systems, and higher education, were a primary source of information. Principal findings were that system partners have espoused some concepts for financial transparency beginning in the early 20th century--signifying an 80-year implementation gap for public health. Critical features that promote accountability included standardized data collection methods and infrastructures, uniform practices for quantitative analysis of financial performance, and credentialing of the financial management workforce. Recommendations are offered on the basis of these findings to aid public health to close this gap by framing a movement toward transparency. [ABSTRACT FROM AUTHOR]

In nursing research, once one has a solid design, one has still to think about a sampling strategy and implementation. Too often, the paraphernalia of inferential statistical reasoning is inappropriately deployed when the achieved sample can in no way be claimed to represent the drawn sample. Given the traditionally low rates of response in most nursing research (usually well under 90 per cent, and often unknown), there is a danger that perfectionist counsels would lead to an end to serious research. In this paper, Laurence Moseley and Donna Mead argue that such a nihilistic position is not necessary and that, instead, researchers should tailor their inferential analyses to the demands of any particular study. They argue that for many purposes, simple computations of both maximum and minimum population estimates are both defensible and useful. [ABSTRACT FROM AUTHOR]

This paper reports our experience of analysing what may well be one of the largest datasets gathered on nursing practice in the United Kingdom. The study produced both quantitative and qualitative data and a method had to be devised both for analysing each form of data and for relating the two. An inexpensive relational database was chosen for the purpose, and experience of using it is reported. Detailed examples are given. We look at the strengths and weaknesses of such a tool, and in general it received a positive evaluation. For many nursing research projects, it offers some advantages over a conventional statistical package, especially in the following areas: offering ease of use, and hence control of the data, by the domain (nursing) specialist; facilitating the analysis of free-text data; allowing the linking of free-text and structured questionnaire data; permitting the testing of conjectures which arise during analysis; handling varying amounts of data per case; providing non-redundant storage of data; permitting the association of machine-readable codes and human-readable labels; and encouraginhg an exploratory rather than merely analytical approach. [ABSTRACT FROM AUTHOR]

Auditing nursing practice is a time-consuming, error-prone task. Feedback to individuals is highly desirable but usually is not offered. This is particularly difficult in large-scale studies. In this study of 654 wards a new method was attempted. Structured questionnaires were analysed by a computer program and feedback reports generated automatically. Informal evaluations by the initial recipients are positive and the method seems worthy of future development. [ABSTRACT FROM AUTHOR]

Introduction: The concepts of causation and prediction are different, and have different implications for practice. This distinction is applied here to studies of the problem of student attrition (although it is more widely applicable)., Background: Studies of attrition from nursing courses have tended to concentrate on causation, trying, largely unsuccessfully, to elicit what causes drop out. However, the problem may more fruitfully be cast in terms of predicting who is likely to drop out., Methods: One powerful method for attempting to make predictions is rule induction. This paper reports the use of the Answer Tree package from SPSS for that purpose., Data: The main data set consisted of 3978 records on 528 nursing students, split into a training set and a test set. The source was standard university student records., Results: The method obtained 84% sensitivity, 70% specificity, and 94% accuracy on previously unseen cases., Discussion: The method requires large amounts of high quality data. When such data are available, rule induction offers a way to reduce attrition. It would be desirable to compare its results with those of predictions made by tutors using more informal conventional methods.

The Health Level 7 (HL7) Reference Information Model (RIM) was once incepted as an object oriented information model to harmonize the definition of HL7 messages across different application domains. On the heels of the hugely successful HL7 version 2, version 3 and the RIM has received significant attention and credit and in turn is increasingly subjected to criticism. In this paper the authors, who are among the chief designers of the RIM, respond to the major points that have been raised against the RIM in the published literature. We find that much of the criticism is based on misunderstandings and differences in point of view. We wish to advance the dialogue in the hope that when we account for those differences, effective critique may lead to real improvements of the standard.

We report the development of a brief and simple-to-complete clinical placement evaluation scale. Unlike many previous attempts to develop such tools, the one reported here gives reliable numerical scores with a firm empirical foundation. The scoring correlates well between three European countries: UK, Finland, and Germany.

An important, but often neglected, part of any research or audit exercise is the reporting back to participants of the results of that exercise. When feedback is made, it is often of a general, aggregated nature. Considerations of cost and psychological factors usually preclude feedback to individuals. As part of a larger study we have developed a prototype mechanism for providing such individual feedback. This was done by writing a computer program which automatically generated the report, using rules on how to interpret different patterns of responses to a questionnaire. Previous qualitative evaluation had shown a positive response from participating nurses. The current small-scale study reports a more formal evaluation. Participants who received reports on the degree to which their ward was practising primary nursing overwhelmingly found the reports readable, informative, encouraging, accurate and useful.