An Investment Decision-Making Process for Investments in Clinical ICT Systems in Public Health Care Organizations
Research output: Book/Report › Doctoral thesis › Collection of Articles
|Publisher||Tampere University of Technology|
|Number of pages||141|
|Publication status||Published - 28 Oct 2016|
|Publication type||G5 Doctoral dissertation (article)|
|Name||Tampere University of Technology. Publication|
The results show that investment decision-making in a public health care organization should begin with an analysis of the alternative technologies and their operational potential (technology variable). Decision-making should particularly emphasize three factors: standards, the integration potential of the system and the strategic fit with the health care organization’s strategy. These should form the basis of the financial analysis of the investment, which is then made using a modified capital budgeting method. The decision-making process should continue with ensuring that other important variables are taken into account. Legislation and the organization’s culture are variables, which should be considered before making the final decision to invest in a clinical ICT system. Since these variables might also affect the technology variable, the financial analysis might need to be re-visited during the decision-making process.
This dissertation identifies the use of the contingency theory in clinical IT investment decisions in a public health care organization from a management accounting perspective. It also analyzes the contingency variables which may contribute to the investment analysis when investing in clinical IT in a public health care organization. Future research will be needed in order to identify the relationship between health care organizations’ management accounting systems and investment decision-making process. In addition, the contingency theory should be future tested to provide more insight into how the independent variables interact with each other.
- clinical ICT investment, investment decision, contingency theory, contingency variables, public health care