Introduction Hospital organizational performance has been largely defined by administrative data comprised of tangible financial records. Though important, the hospital environment of care is arguably represented by multiple inter-professional and intangible factors that influence patient outcomes that are not costdriven but service-oriented. The researcher introduces controllable, behavioral internal factors that measure effectiveness, efficiency, and equity within the hospital environment of care based on simple solutions that optimize professional relationships. In the absence of uniform standards, understanding the relationships between clinical (e.g., nurses) and non-clinical caregiver occupations (e.g., BMETs) in the hospital environment of care is vital to determining best practices that improve patient outcomes. However, the BMET is under-represented in research despite evidence that validates their indirect impact on patient outcomes through their medical equipment duties (Needleman, Kurtzman, and Kizer, 2007). In order to fill this research gap, the purpose of this study is to understand the relationships among organizational performance indicators and level of quality in a hospital environment of
care from the perspective of the biomedical engineering technician. Survey Development Using Organizational Performance Theory The Biomedical (BEI) Engineering Survey was
Interdepartmental
develo ped, analyzed for statistical reliability (overall Cronbach Alpha = 0.905; all study constructs administered Cronbach to a ? > 0.7), number and of select
biomedical engineering technicians (BMETs) via electronic access to Survey Monkey during January 2011. The BEI survey (Figure 1) and measurement models for hospital level of quality utilized the Assessment Measurement Classes of Organizational Performance—Structure-Process-Outcome (S-P-O) (Donabedian, 1988) (Figure 2). Responses were gauged on a five point Likert scale ranging from 1- (strongly agree) to 5- (strongly disagree). The 39 questionnaire items were associated with the three latent variables or constructs. First, the predictor variables of Structural Complexity has four scale factors (Organizational Culture-OC, Level of