Measuring a Safety Culture: Critical Pathway or Academic Activity?

he Institute of Medicine (IOM) identified six core needs in a health care system, the first of which was safety. 1 Furthermore, several IOM committees and others have identified the creation of a “culture of safety ” as the key institutional requirement to achieve safe medical care. 1–3 In this issue of the journal, Modak et al. 4 present an instrument that may help measure the extent to which a patient safety culture exists in an ambulatory setting. While these authors and others have done considerable work on defining and measuring a culture of safety in the hospital setting, 5,6 few have tackled the difficult task of measuring a safety culture in the ambulatory arena within the US health care system. Even in the hospital setting, where there has been more effort, the development of a culture of safety within all US hospitals has been spotty and, for some safety advocates, too slow. 7 There are many potential reasons for the poor progress in developing a culture of safety: confusion about the difference between safety and quality, concerns that increasing safety will further erode profits, or perhaps simply a lack of attention by institutional leaders. Whatever the reasons for the slow pace of transformation across the nation’s 5,000-plus hospitals, it is likely that this transformation will be even more difficult to achieve in the much larger and more diverse ambulatory setting. Thus, it is important to define and measure an ambulatory culture of safety. It is also difficult, perhaps impossible, to change beliefs, attitudes, knowledge, or actions (all components of a “culture”) without some form of feedback. Therefore, a necessary step in creating a culture of safety is to develop tools to measure the components of that culture. For those individuals and institutions that wish to truly improve the safety of the care they deliver, the creation and testing of tools such as the Safety Attitudes Questionnaire-Ambulatory (SAQ-A) version is critical. Beliefs, attitudes, and knowledge do not always lend themselves to clear-cut end points. Thus, we can expect to see more than one safety culture measuremen

Nursing opinion leadership: a preliminary model derived from philosophic theories of rational belief

Opinion leaders are informal leaders who have the ability to influence others' decisions about adopting new products, practices or ideas. In the healthcare setting, the importance of translating new research evidence into practice has led to interest in understanding how opinion leaders could be used to speed this process. Despite continued interest, gaps in understanding opinion leadership remain. Agent‐based models are computer models that have proven to be useful for representing dynamic and contextual phenomena such as opinion leadership. The purpose of this paper is to describe the work conducted in preparation for the development of an agent‐based model of nursing opinion leadership. The aim of this phase of the model development project was to clarify basic assumptions about opinions, the individual attributes of opinion leaders and characteristics of the context in which they are effective. The process used to clarify these assumptions was the construction of a preliminary nursing opinion leader model, derived from philosophical theories about belief formation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100132/1/nup12008.pd

The Patient‐Centered Medical Home and Patient Experience

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94450/1/hesr1429-sup-0001-Authormatrix.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/94450/2/hesr1429.pd

Medical oncology patients' preferences with regard to health care: development of a patient-driven questionnaire

BACKGROUND: To improve quality of care for cancer patients, it is important to have an insight on the patient's view on health care and on their specific wishes, needs and preferences, without restriction and without influence of researchers and health care providers. The aim of this study was to develop a questionnaire assessing medical oncology patients' preferences for health care based on their own input. PATIENTS AND METHODS: Items were generated using 10 focus group interviews with 51 cancer patients. A preliminary questionnaire was handed out to 681 patients of seven Dutch departments of medical oncology. Explorative factor analysis was carried out on the 386 returned questionnaires (response 57%). RESULTS: Focus group interviews resulted in a preliminary questionnaire containing 136 items. Explorative factor analysis resulted in a definitive questionnaire containing 123 items (21 scales and eight single items). Patients rated expertise, safety, performance and attitude of physicians and nurses as the most important issues in cancer care. CONCLUSION: This questionnaire may be used to assess preferences of cancer patients and to come to a tailored approach of health care that meets patients' wishes and needs

Defining and Measuring Successful Emergency Care Networks: A Research Agenda

The demands on emergency services have grown relentlessly, and the Institute of Medicine (IOM) has asserted the need for “regionalized, coordinated, and accountable emergency care systems throughout the country.” There are large gaps in the evidence base needed to fix the problem of how emergency care is organized and delivered, and science is urgently needed to define and measure success in the emerging network of emergency care. In 2010, Academic Emergency Medicine convened a consensus conference entitled “Beyond Regionalization: Integrated Networks of Emergency Care.” This article is a product of the conference breakout session on “Defining and Measuring Successful Networks”; it explores the concept of integrated emergency care delivery and prioritizes a research agenda for how to best define and measure successful networks of emergency care. The authors discuss five key areas: 1) the fundamental metrics that are needed to measure networks across time-sensitive and non–time-sensitive conditions; 2) how networks can be scalable and nimble and can be creative in terms of best practices; 3) the potential unintended consequences of networks of emergency care; 4) the development of large-scale, yet feasible, network data systems; and 5) the linkage of data systems across the disease course. These knowledge gaps must be filled to improve the quality and efficiency of emergency care and to fulfill the IOM’s vision of regionalized, coordinated, and accountable emergency care systems.ACADEMIC EMERGENCY MEDICINE 2010; 17:1297–1305 © 2010 by the Society for Academic Emergency MedicinePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79228/1/j.1553-2712.2010.00930.x.pd

Innovations in the Assessment of Transplant Center Performance: Implications for Quality Improvement

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74976/1/j.1600-6143.2009.02570.x.pd