A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. (18th October 2010)

• Record Type: Journal Article
• Authors: Sittig, Dean F; Singh, Hardeep
• Is Part Of: Quality & safety in health care. Volume 19(2010)Supplement 3
• Page Start: i68
• Page End: i74
• Publication Date: 2010-10-18
• Subjects: Human factors -- information technology
• DOI: 10.1136/qshc.2010.042085
• Languages: English
• ISSNs: 1475-3898

Abstract

Abstract : Background: Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). Method: This manuscript introduces an eight-dimensional model specifically designed to address the sociotechnical challenges involved in design, development, implementation, use and evaluation of HIT within complex adaptive healthcare systems. Discussion: The eight dimensions are not independent, sequential or hierarchical, but rather are interdependent and inter-related concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the 'language' of clinical applications. The human–computer interface includes all aspects of the computer that users can see, touch or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developer to end user, including potential patient-users. Workflow and communication are the processes or steps involved in ensuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organisational features (eg, policies, procedures and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation.