Research Design (RD)

Any successful attempt to integrate information communication technology (ICT) into existing institutional structures must begin with an evaluation of the current status of the institution, followed by a plan for improvement (Govender, 2011). Research design is the plan that is followed to conduct the research (B. L. Berg, 2004, 2007). According to Hevner and Chatterjee (2010), the design science research paradigm is highly relevant to information systems (IS) research because it directly addresses two of the key issues of the discipline (Hevner & Chatterjee, 2010): the central, albeit controversial, role of the IT artefact in IS research (Benbasat & Zmud, 2003; W. J. Orlikowski & Iacono,

2001; Weber, 1987) and the perceived lack of professional relevance of IS research (Benbasat & Zmud, 1999). Design science, as conceptualized by Simon (1996), supports a pragmatic research paradigm that calls for the creation of innovative artefacts to solve real-world problems (Simon, 1969). Thus, design science research combines a focus on the IT artefact with a high priority on relevance in the application domain. The design science paradigm has its roots in engineering and the sciences of the artificial (Simon, 1969). It is fundamentally a problem-solving paradigm. It seeks to create innovations that define the ideas, practices, technical capabilities, and products through which the analysis, design, implementation, and use of information systems can be effectively and efficiently accomplished. Design science research in IS addresses what are considered to be wicked problems (Hevner & Chatterjee, 2010). That is, those problems characterized by: (1) unstable requirements and constraints based on ill- defined environmental contexts, (2) complex interactions among subcomponents of the problem, (3) inherent flexibility to change design processes as well as design artefacts (i.e., malleable processes and artefacts), (4) a critical dependence upon human cognitive abilities (e.g., creativity) to produce effective solutions, and (5) a critical dependence upon human social abilities (e.g., teamwork) to produce effective solutions.

The case study method is adopted in the current research, which aims to “illuminate the general by looking at the particular” (Denscombe, 2007). The purpose is not to over generalize an isolated investigation, but to gain some insights from which certain wider implications may be assumed. Case studies are the most common types of qualitative method used in information sciences and technologies research (B. L. Berg, 2004, 2007). Typically, the researcher studies a case or a variety of real-world organizations that utilize information sciences and technologies. Conclusions are then drawn regarding their impacts on the organizational context (B. L. Berg, 2004, 2007).

The concept of ontology was used to evaluate the current status of the institution. Ontology describes the nature of reality, followed by a plan for improvement according to the knowledge acquired from the study. Epistemology in research design (RD) involves learning through building and organizing steps and processes to improve performance (Creswell, 2007; Vaishnavi, et al., 2007). The successful integration of health information technology into hospitals (“health providers”) will result in the early detection of infectious disease outbreaks around the country, improved tracking of chronic disease management, healthcare evaluation (Sinha, 2010; Wu, et al., 2006; Yusof, Kuljis, Papazafeiropoulou, & Stergioulas, 2008), and quality information that can be compared with “axiology,” a philosophical perspective that studies values and value judgments (Creswell, 2007; Vaishnavi, et al., 2007).

This study adopts the qualitative research approach using case study. Data collection techniques, such as interview and observation, are also adopted. The need to use different techniques for data collection arises from the ethical need to confirm the validity and reliability of the processes (B. L. Berg, 2004, 2007), to ask subjects to identify factors that affect technology acceptance with regard to collaboration in sharing information among specialists within the selected Egyptian hospital, and to determine the main obstructions in technology adoption with regard to collaboration in sharing information among specialists. Furthermore, this study intends to develop a proposed CHIMS model (see Figure 2.8 in Chapter 2) to improve collaboration among specialists with regard to health information sharing in the hospital environment based on privacy preservation. Figure 3.2 shows the research science design framework.

Figure 3.2: Research Science Design Framework

Figure 3.2 shows the research science design framework for this study. The research science design framework includes three stages: (1) the environment defines the problem space (Simon, 1969) in which the phenomena of interest resides. For IS research, it is composed of people, organizations, and their existing or planned technologies (Silver, Markus, & Beath, 1995). In it are the goals, tasks, problems, and opportunities that define business needs as they are perceived by people within the organization. Such perceptions are shaped by the roles, capabilities, and characteristics of people within the organization. Organization needs are assessed and evaluated within the context of organizational strategies, structure, culture, and existing business processes. They are positioned relative to existing technology infrastructure, applications, communication architectures, and development capabilities. Framing research activities to address organization needs assures research relevance (Hevner & Chatterjee, 2010). Design science addresses research through the building and

Relevance

Environment IS Researcha Knowledge Base

Relevance Rigor

People Medical Staff

(i.e. institute dean,hospital manger,doctors,researchers, medical informatics experts)

Organization Selected Egyptian Hospitals

Technology Development Collaborative HISs application Develop CHIMS Evaluate Case Study Foundation CHIMS Model Methodology Qualitative Data Analysis Business Needs Applicable Knowledge Application in the

evaluation of artefacts designed to meet the identified business need. The goal of design science research is utility. The knowledge base provides the raw materials from and through which IS research is accomplished. The knowledge base is composed of foundations and methodologies. Prior IS research and results from reference disciplines provide foundational theories, frameworks, instruments, constructs, models, methods, and instantiations used in the develop/build phase of a research study. Methodologies provide guidelines used in the evaluate phase. Rigor is achieved by appropriately applying existing foundations and methodologies. The following sections discuss the Research Science Design stages in detail.