Strategic Planning of Identification Technologies in Healthcare Processes: a Model and a Real Case

摘要

Automatic Identification and Data Capture (AIDC) solutions are key to safety and traceability of clinical processes in healthcare organizations. This is also confirmed by the number of cases found in surveys. Nevertheless, solutions implemented by providers often target specific processes and don't exploit the value of synergies between different application fields: this because they do not follow a systemic vision of investments planning. In this paper we addressed this issue and developed a model for the evaluation of AIDC technologies projects in healthcare. This model identifies and rates fundamental and means objectives of AIDC technologies implementations, and then guides the assessment of the value exploited by applications investigating user's feedback as a proxy of actual goals reached by applications. The model proves a valuable tool both in setting strategic priorities, and in assessing state-of-the-art implementations in an organization. The model was first applied by Fondazione Politecnico di Milano to evaluate current RFId technology initiatives at the National Cancer Institute in Milan.