There is a high potential for mobile learning and support applications in the medical domain. In a recent research initiative we developed together with the School of Medicine at the University College Cork, Ireland a smartphone app to train writing of medical discharge letters that are crucial for handovers (transferring information from one caregiver to another).
The so-called CLAS app is based on the “Cork Letter-Writing Assessment Scale” (created by Bridget Maher) and benefits from synergies between our different medical research projects like Handover, EMuRgency and BioApp.
Handover of patient information is a time of particular risk and it is important that accurate, reliable and relevant information is clearly communicated between one caregiver to another. The World Health Organization (WHO) lists accurate handovers as one of its High 5 Patient Safety initiatives (Joint Commission on Accreditation of Healthcare Organizations, 2011). Improperly conducted handovers lead to wrong treatment, delays in medical diagnosis, life threatening adverse events, patient complaints, medical litigation, increased health care expenditure, increased hospital length of stay and a range of other effects that impact on the health system.
The CLAS mobile app is designed to standardise and improve handover communication between hospital and General Practice. Mobile applications such as CLAS offer exciting opportunities for improving patient safety and minimising medical error at handover and are just the tip of the iceberg with regard to harnessing the vast potential of mobile communications and how medical professionals interact with each other and more importantly, how they interact with the patients. The CLAS mobile application is currently the basic of two ongoing research projects.
- Assessment of the quality of 200 hospital discharge letters using the CLAS scale.
- Assessment of the effect of the CLAS intervention on the letter-writing skills of 80 fourth year medical students.
Next to the medical research, we aim to further improve the CLAS app with typical mobile application features such as taking into account sensor information from the mobile device such as GPS coordinates and audio recordings. In addition, we want to make the CLAS app more interactive by enabling the end users (doctors and patients) to synchronise handover information, thus improving the quality of information transfer at handover.
At the upcoming mLearn conference in October in Helsinki we will present further details about the CLAS app in the context of a research paper.