The probability sampling techniques used for quantitative studies are rarely appropriate when conducting qualitative research. This article considers and explains the differences between the two approaches and describes three broad categories of naturalistic sampling: convenience, judgement and theoretical models. The principles are illustrated with practical examples from the author's own research.

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Objective. To review the quantitative instruments available to health service researchers who want to measure culture and cultural change. Data Sources. A literature search was conducted using Medline, Cinahl, Helmis, Psychlit, Dhdata, and the database of the King's Fund in London for articles published up to June 2001, using the phrase ''organizational culture.'' In addition, all citations and the gray literature were reviewed and advice was sought from experts in the field to identify instruments not found on the electronic databases. The search focused on instruments used to quantify culture with a track record, or potential for use, in health care settings. Data Extraction. For each instrument we examined the cultural dimensions addressed, the number of items for each questionnaire, the measurement scale adopted, examples of studies that had used the tool, the scientific properties of the instrument, and its strengths and limitations. Principal Findings. Thirteen instruments were found that satisfied our inclusion criteria, of which nine have a track record in studies involving health care organizations. The instruments varied considerably in terms of their grounding in theory, format, length, scope, and scientific properties. Conclusions. A range of instruments with differing characteristics are available to researchers interested in organizational culture, all of which have limitations in terms of their scope, ease of use, or scientific properties. The choice of instrument should be determined by how organizational culture is conceptualized by the research team, the purpose of the investigation, intended use of the results, and availability of resources.

There is some evidence to suggest that organisational culture may be a relevant factor in health care performance, yet articulating the nature of that relationship proves difficult. Simple relationships such as 'strong culture leads to good performance' are not supported by this review. Instead, the evidence suggests a more contingent relationship, in that those aspects of performance valued within different cultures may be enhanced within organisations that exhibit those cultural traits. A striking finding is the difficulty in defining and operationalising both 'culture' and 'performance' as variables that are conceptually and practically distinct. Considerably greater methodological ingenuity will be required to unravel the relationship(s) between organisational culture(s) and performance(s). Current policy prescriptions, which seek service improvements through cultural transformation, are in need of a more secure evidential base.

Before we can take steps to improve the quality of health care, we need to define what quality care means. This article describes how to make best use of available evidence and reach a consensus on quality indicators

There are several potential gains from the public disclosure of performance data, but use of the information by provider organizations for quality improvement may be the most productive area for further research.

Worldwide, policymakers, health system managers, practitioners and researchers struggle to use evidence to improve policy and practice. There is growing recognition that this challenge relates to the complex systems in which we work. The corresponding increase in complexity-related discourse remains primarily at a theoretical level. This paper moves the discussion to a practical level, proposing actions that can be taken to implement evidence successfully in complex systems. Key to success is working with, rather than trying to simplify or control, complexity. The integrated actions relate to co-producing knowledge, establishing shared goals and measures, enabling leadership, ensuring adequate resourcing, contributing to the science of knowledge-to-action, and communicating strategically.

The traditional separation of the producers of research evidence in academia from the users of that evidence in healthcare organisations has not succeeded in closing the gap between what is known about the organisation and delivery of health services and what is actually done in practice. As a consequence, there is growing interest in alternative models of knowledge creation and mobilisation, ones which emphasise collaboration, active participation of all stakeholders, and a commitment to shared learning. Such models have robust historical, philosophical and methodological foundations but have not yet been embraced by many of the people working in the health sector. This paper presents an emerging model of participation, the Researcher-in-Residence. The model positions the researcher as a core member of a delivery team, actively negotiating a body of expertise which is different from, but complementary to, the expertise of managers and clinicians. Three examples of in-residence models are presented: an anthropologist working as a member of an executive team, operational researchers working in a front-line delivery team, and a Health Services Researcher working across an integrated care organisation. Each of these examples illustrates the contribution that an embedded researcher can make to a service-based team. They also highlight a number of unanswered questions about the model, including the required level of experience of the researcher and their areas of expertise, the institutional facilitators and barriers to embedding the model, and the risk that the independence of an embedded researcher might be compromised. The Researcher-in-Residence model has the potential to engage both academics and practitioners in the promotion of evidence-informed service improvement, but further evaluation is required before the model should be routinely used in practice.