The objective of this dissertation is to systematize the investment decision-making process to ensure the financial performance and investment are in line with the organization’s existing operating environment when investing in clinical ICT systems in a public health care organization.
The financial analysis for investment decisions should also consider other variables beyond costs (Brown, 2005; Sintonen, 2007; Yates, 2009) and be supplemented with the relevant factors. The relevant factors contributing to the cost analysis of a clinical ICT system (including telemedicine) investment are factors such as the quality of care (Rosenstein, 1999), patient experience, including the time savings for the patient, the organization’s internal process improvements (Sims, 1999;
Lamminen et al., 2006; Remenyi et al., 2007), and the organization learnings (Lamminen et al., 2006).
Compared to many other industries, the health care industry has been relatively slow to adopt ICT (Kaplan, 1997; Shortliffe, 2005; Sistrom, 2005; Christensen and Remler, 2007; Christensen and Remler, 2009). Today, health care organizations are constantly seeking innovative use of ICT, such as telemedicine, mobile health and e-service in order to improve their processes (Sethi and King, 1994; Wootton, 2009). Specific issues such as the costs associated with hardware and software, availability of broadband and mobile networks, development of user interfaces, and ongoing maintenance costs are evident in the ICT investment decision-making process (Wootton, 2009).
However, in the investment decision, it is more difficult to evaluate the financial value related to the ongoing development of technology, the present level of standardization and interconnectivity (Goroll et al., 2009; Jha et al., 2009; Lorenzi et al., 2009). In a public health care organization, the administrative management prepares investment proposals while politicians make the final decision (Kurunmäki, 1999).
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Therefore, the first research question can be formulated as follows:
Research question 1: Which contingency factors will, with reasonable accuracy, contribute to the investment decision-making process when selecting a clinical ICT system in public health care?
According to the contingency theory, the efficiency of decision-making depends on a number of aspects, such as the amount of relevant information and decision quality and acceptance, within a specific situation (Vroom and Yetton, 1973). The contingency theory connotes a conditional association of two or more independent variables with a dependent outcome (Drazin and Van de Ven, 1985). The fit is understood as a positive impact on performance, and the research task is then to explain variations in performance in terms of interaction effects between context and structure (Gerdin and Greve, 2004). However, if the factors that affect decision-making when investing in clinical ICT systems are linked to the purposes of use, the appropriate design of the decision-making model may not be understood without reference to their actual usage.
In public health care, the evaluation process concerning different ICT systems has to be transparent.
The factors affecting the final decision already need to be identified at the beginning of the process.
The overall performance of the investment decision is dependent on contextual variables, variables which have financial value and which can be part of the cost analysis, as well as variables whose exact financial value is hard to assess.
The contingency theory explains the circumstances in which a relevant set of variables being considered in a decision-making process coincides with the actual parameters relevant to the process. A contingency-based investment decision approach would give a more balanced view of the various parameters employed and help ensure the performance of the clinical ICT investment decision.
The contingency theory approach is a viable tool since the selection of a clinical ICT system in a public health care organization is influenced by internal and external constraints. The theory seeks to understand which external factors, such as preferences of the surrounding community (Barry and Chaiken, 2003), in particular have an impact on the organization's operations or which internal factors must be taken into account for an optimal investment. The effectiveness of a decision depends on a balance of how important the decision is from an external variables point of view, and how well the new clinical ICT system is compatible with the organization’s internal processes and strategy. Changing the nature of one factor will alter the relationship with the other variable. When
analyzing investments in a public health care context, it is also important to consider the special features of a non-profit organization (Leväsvirta, 1999, p. 92).
Therefore, the second research question can be formulated as follows:
Research question 2: Which contextual variables will, with sufficient accuracy, enhance the performance of clinical ICT system investments in public health care?
Cost savings are not always the main reason for investing in clinical ICT. An improvement in service quality also has a significant role in the investment decision. Since the investment should either produce cost savings or improve service quality, both aspects need to be considered in the financial calculations. While investment theories mainly emphasize quantitative appraisals, there is no self-evident methodology for a contextual analysis of ICT systems beyond financial considerations (Pirttivaara, 2010). Health care organizations should evaluate the suitability of their ICT investments (Remenyi et al., 2007) in terms of indirect costs and benefits (Sorenson et al., 2008).
In a public health care organization, all investment decisions have to be based on factors which are openly communicated in advance to all stakeholders. The entire decision-making process also needs to be open and transparent. However, factors such as client experience and organizational learning are usually very difficult to express in financial terms, and therefore their inclusion adds considerable uncertainty also regarding investment calculations.
Together, these research questions address the problem of how to design an investment decision-making model that is able to take the different financial and non-financial factors into account. The lack of a structured method to conceptualize the complex environment seems to lead to a situation where decisions are often based on intuition and recommendation by trusted parties. While this more intuitive line of work may produce good results, it has its obvious risks. This problem becomes more acute as today's ICT systems are becoming complex and intertwined, and an increasing amount of specialist knowledge is needed to understand the essentials.
The contingency approach is not commonly applied to the study of decision-making, but it was chosen to be evaluated in this study due to its main proposition that the structure and process of an organization must fit its context in order to be effective (Drazin and Van de Ven, 1985). The theory acknowledges the complexity and uncertainties behind decisions.
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