title: An analysis of the adoption of managerial innovation: cost accounting systems in hospitals.
abstract: The adoption of new medical technologies has received significant attention in the hospital industry, in part, because of its observed relation to hospital cost increases. However, few comprehensive studies exist regarding the adoption of non-medical technologies in the hospital setting. This paper develops and tests a model of the adoption of a managerial innovation, new to the hospital industry, that of cost accounting systems based upon standard costs. The conceptual model hypothesizes that four organizational context factors (size, complexity, ownership and slack resources) and two environmental factors (payor mix and interorganizational dependency) influence hospital adoption of cost accounting systems. Based on responses to a mail survey of hospitals in the Chicago area and AHA annual survey information for 1986, a sample of 92 hospitals was analyzed. Greater hospital size, complexity, slack resources, and interorganizational dependency all were associated with adoption. Payor mix had no significant influence and the hospital ownership variables had a mixed influence. The logistic regression model was significant overall and explained over 15% of the variance in the adoption decision.
authors.affiliation: Rush-Presbyterian-St Luke's Medical Center, Chicago, IL, USA.
authors.forename: G L
authors.initials: GL
authors.lastname: Glandon
authors.forename: M A
authors.initials: MA
authors.lastname: Counte
mesh_terms: D000066:Accounting / Q000379:methods* / Q000706:statistics & numerical data; D002641:Chicago; D003361:Cost Allocation / Q000379:methods* / Q000706:statistics & numerical data; D003625:Data Collection; D004059:Diffusion of Innovation; D005377:Financial Management, Hospital / Q000706:statistics & numerical data / Q000639:trends*; D006302:Health Services Research; D017721:Hospital Costs; D016015:Logistic Models; D017146:Models, Organizational; D009936:Organizational Innovation / Q000191:economics*; D012044:Regression Analysis