Background: Health care organizations increasingly strive to deliver care that is both evidence based and patient centered. Although often complementary, fundamental contradictions may exist between these goals, and the organizational culture and infrastructure necessary to be successful in one domain may inherently diminish performance in the other. Purpose: We assessed the relationship between evidence-based practice (EBP) and patient-centered care (PCC) by seeking to identify specific behavioral and process mechanisms, along with organizational characteristics that distinguish medical centers that are able to provide inpatient care that is both evidence based and patient centered from those where performance is either mixed or low in both domains. Methodology/Approach: We analyzed interview data from 142 employees at 12 Veterans Affairs Medical Centers selected based on EBP and PCC performance (high, low, or mixed) using a priori constructs consistent with organizational literature, as well as emergent themes. Results: We confirmed that tensions may arise when attempting to deliver both EBP and PCC and found unique characteristics of organizations that do both well. High-performing sites exhibited organizational cultures of empowerment where both EBP and PCC expectations were emphasized; provided formal and informal institutional supports and structures with regard to PCC and EBP; and fostered multidisciplinary, multidirectional approaches to care and communication that facilitated delivery of both EBP and PCC. Conclusions and Practice Implications: Organizations that excel in providing both EBP and PCC exhibit unique characteristics and processes. Recognizing that some characteristics such as culture are difficult to change, these findings nonetheless highlight areas that could be enhanced by medical centers striving to deliver care that is both evidence based and patient centered.

A growing line of research indicates a positive relationship between a healthcare organization's culture and various performance measures. In these studies, a key cultural characteristic is the emphasis placed on teamwork. None of the studies, however, have examined teamwork culture relative to patient satisfaction, which is now 1 of the most widely used performance measures for healthcare organizations. This study investigated the relationship between teamwork culture of hospitals and patient reports of their satisfaction with the care they received. The study setting was the Veterans Health Administration (VHA), Department of Veterans Affairs. The study sample consisted of 125 VHA hospitals for which independent and valid sources of data for culture and patient satisfaction were obtained. Each hospital's culture was assessed relative to 4 dimensions: teamwork, entrepreneurial, bureaucratic, and rational. Patient satisfaction data were available for both inpatient and outpatient settings. Results from multivariate regression analyses indicated a significant and positive relation between teamwork culture and patient satisfaction for inpatient care, and a significant and negative relation between bureaucratic culture and patient satisfaction for inpatient care. Additional analyses revealed an almost 1 standard deviation difference in patient satisfaction scores between hospitals in the top third and bottom third of the distribution for the teamwork culture measure. Study results suggest that hospitals and possibly other healthcare organizations should strive to develop a culture emphasizing teamwork and deemphasizing those aspects of bureaucracy that are not essential to assuring efficiency and quality care.

The authors conducted 4 studies to construct a multidimensional measure of perceptions of organization personality. Results of the first 2 studies suggest that (a) 5 broad factors are sufficient to capture the structure of organization personality perceptions, (b) real-world organizations differ on personality profiles, and (c) personality trait inferences are related to organizational attraction. Results of a 3rd study suggest that personality trait inferences assessed in 1 sample are related lo ratings of organizational attractiveness by a 2nd sample. Finally, results of a 4th study suggest that the measure is sensitive to experimental manipulations of organizational descriptions. Implications and suggestions for the use of this measure in future research are discussed.

Survey response rate is regarded as a key data-quality indicator, yet response rate is not necessarily predictive of nonresponse bias. Our study objective was to use a high-response-rate survey to assess nonresponse bias across successive waves. This survey of healthcare leaders utilized a web-based, self-report format with an initial invitation and four nonrespondent follow-ups. Across five waves, comparisons were made for demographic and facility characteristics, proportion of items completed, and distribution of three question types: factual reports of customized categorical responses; single-item evaluations using five-point Likert scales; and multi-item scales, across four- or five-point Likert scales. The overall response rate was 95 percent (118/124); waves did not differ by demographic and facility characteristics or missing data. Across waves, there were no significant differences between responses to two factual report questions or the single- or multi-item scale measures of attitudes. According to a “what-if” analysis of cumulative results by wave, the same conclusions would have been reached if data collection had been halted at earlier points in time. Precision and statistical power increased as number of respondents accumulated by wave. The high response rate facilitated studying the impact of nonresponse bias by wave. Although high response rates are desirable because of precision and power, as survey fatigue increases, absolute thresholds representing “adequate” response rates may be less realistic. Results from “low” response-rate surveys should be considered on their merits, as they may accurately represent attitudes of the population. Therefore, low response rates should not be cited as reasons to dismiss results as uninformative.