Public examination of a doctoral dissertation in the field of nursing science
Doctoral candidate: MHS Taina Pitkäaho
Time and venue: 6.5.2011 at 12 noon, Snellmania Lecture Hall L21, Kuopio Campus
Due to the increasing demands of caring for the ageing population and decreasing nursing resources, novel solutions are required in planning and evaluating nurse staffing. The complex adaptive systems model is a modern framework for understanding the health care system and nurse staffing as being adaptable to change, containing the capability of self-organisation and having non-linear relations between different agents.
The aim of this health service system study was to describe and analyse nurse staffing and nursing outcome and their interrelations by utilising data-based indicators. In addition, the aim was to produce a prediction model for nurse staffing and nursing outcome.
The data consisted of 67 622 inpatient and outpatient visits and administrative information on 746 hospital nurses. The data were collected from 35 somatic inpatient units within three acute care hospitals as monthly time series in a one-year period (2008). Statistical and graphical descriptions were used. Differences between the hospitals and variation in the time series were tested. The relationship between nurse staffing and nursing outcome was examined with a linear mixed model and Naive Bayesian Classification.
Differences emerged in nurse staffing and nursing outcome between the hospitals, as well as variation within the time series. Nursing outcome was explained and predicted by several nurse staffing indicators, including unit census and nursing hours per patient day. Case mix, proportion of registered nurses and support services of nurse staffing were non-linear predictors of length of stay which revealed the complexity of the system. Prediction information about the effects of nurse staffing on nursing outcome was produced, as well as a prediction model of their interconnection.
The most important outcome of the study was the proof of a non-linear relationship between nurse staffing and nursing outcome by means of Naive Bayesian Classification. Additionally, a novel description of nurse staffing and nursing outcome with a time series was presented. In the complex health care environment, nurse staffing should be flexible; there are no grounds for rigidly specified nurse staffing levels. Rather, nurse staffing should be viewed through nursing outcome; what are the effects of a given nurse staffing level on patient, staff and organisational outcomes. Nurse leaders and health policy-makers in various administrative structures need easily accessed and applied information on nurse staffing for multiprofessional decision-making.Nursing science should utilise health care system register data as research material and apply methods that are suitable for analysing complexity, such as Bayesian methods.
The doctoral dissertation of Master of Health Sciences Taina Pitkäaho, entitled Nurse staffing and nursing outcome in a complex acute health care system will be examined at the Faculty of Health Sciences. The opponent in the public examination will be Research Professor Marja-Leena Perälä of the National Institute for Health and Welfare and the custos will be Professor Katri Vehviläinen-Julkunen of the University of Eastern Finland.
Photo available for download at http://www.uef.fi/vaitoskuvat
Contact: Taina Pitkäaho, GSM 040 0564936, taina.pitkaaho(at)pp.inet.fi
Publishing year: 2011Back to this years article listing