Guest post by Phil Shields, RN, of Melbourne’s Centre for Health, Research and Education
Nursing informatics is a new and little understood area lying between the land of nursing on one side and the land of information technology on the other.
There has been increased interest in recent years in the capture and measurement of nursing quality outcomes by nursing bodies, governments and health organisations because hospitals are being asked to demonstrate efficiency, resource utilisation and value of patient care.
How are nursing interventions and their effect on patient outcomes best captured? One approach is the study of nurse-sensitive indicators and their ability to record nurse activity in a usable form suitable for both humans and computers.
Nursing quality and outcomes research within the discipline of nursing informatics has maintained a steady growth over the last decade. Nursing informatics is a sub-speciality of clinical informatics: it’s the study of nursing information and clinical communications. The tools of trade are terminology and communication systems. These tools are a means to an end, that is, to achieve the best possible patient outcomes.
We know that nurse-sensitive indicators exist in this area. They can be likened to capsules containing data both readable to humans and computers, recording nursing activity in their respective domains of structure, process and outcome in time.
These indicators can stand alone or communicate to other domains containing indicators. For example, a handwashing process indicator may record the date and time plus the location of handwashing. This indicator may be linked to an outcome indicator recording nosocomial (or hospital-acquired) infections or a structural indicator recording staff mix or patient acuity at the time.
I am undertaking a PhD to study and identify nurse-sensitive indicators through a process of software mediation. Mediation is a process of identifying similar terms in two documents. The online study uses simple software developed by Stanford University which has an element of machine artificial intelligence (AI) and human interaction to identify similar indicator labels between documents. The software identifies a similarity and the participants can either accept or reject the software’s suggestion. The usefulness and clinical application of these terms are then ranked by the participants. This study may be a stepping stone for a future Australian Nursing Minimum Data Set.
I am looking for nurses in all branches of nursing to participate in this study. The study would involve using AI software and online forms.
If you are perhaps interested in taking part in the study, you can flag your interest by Liking the Nursing Informatics Research Australia page on Facebook. Or you can email me for any further information at firstname.lastname@example.org
Phil Shields RN
Image credit: http://gelblogs.wordpress.com