Coping with information silos: An examination of the medication management process in residential aged care facilities (RACFs)

The aim of this study was to examine the actions of geographically dispersed process stakeholders (doctors, community pharmacists and RACFs) in order to cope with the information silos that exist within and across different settings. The study setting involved three metropolitan RACFs in Sydney, Australia and employed a qualitative approach using semi-structured interviews, non-participant observations and artefact analysis. Findings showed that medication information was stored in silos which required specific actions by each setting to translate this information to fit their local requirements. A salient example of this was the way in which community pharmacists used the RACF medication charts to prepare residents' pharmaceutical records. This translation of medication information across settings was often accompanied by telephone or face-to-face conversations to cross-check, validate or obtain new information. Findings highlighted that technological interventions that work in silos can negatively impact the quality of medication management processes in RACF settings. The implementation of commercial software applications like electronic medication charts need to be appropriately integrated to satisfy the collaborative information requirements of the RACF medication process.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.