Uncertainty inclusion in budgeting technology adoption at a hospital level: evidence from a multiple case study.
OBJECTIVE
The shortage of resources for healthcare has risen the quest for more rational models and practices for technology selection at a hospital level. Uncertainty is a critical issue. This paper aims to shed first light on this issue through an investigation on the content and the process of budgeting technology adoption with respect to uncertainty.


METHODS
An exploratory multi-case study was carried out to gain a better understanding of the current practice of technology assessment at a hospital level. Five Italian hospitals were selected. Key informants from the budget committees have been interviewed with a structured questionnaire based on the results of an electronic literature search.


RESULTS
Five domains of uncertainty have been identified. They have been deployed in a list of 15 relevant issues that should be reviewed during the budget process. The hospitals in the sample cope with these issues in a peculiar manner. Organisational uncertainty is broadly overcome. Reporting about technology performance after the adoption is missing.


CONCLUSIONS
Policy makers should facilitate hospitals: (a) to develop a multi-disciplinary and evidence based practice for technology selection, (b) to assess and manage uncertainty, and (c) to build a reporting system regarding technology performance in order to build fair practices for technology selection and support continuous learning.
Lettieri
Emanuele
E
Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milan, Italy. emanuele.lettieri@polimi.it
D002017:Budgets / Q000458:organization & administration*; D003659:Decision Making, Organizational; D004059:Diffusion of Innovation; D005377:Financial Management, Hospital; D006740:Hospital Administrators; D006801:Humans; D007407:Interviews as Topic; D007558:Italy; D013677:Medical Laboratory Science / Q000191:economics*; D019982:Organizational Case Studies; D013673:Technology Assessment, Biomedical; D035501:Uncertainty