  Background: Telephone nursing is the first line of contact for many
care-seekers and aims at optimizing the performance of the healthcare system by
supporting and guiding patients to the correct level of care and reduce the
amount of unscheduled visits. Good statistical models that describe the effects
of telephone nursing are important in order to study its impact on healthcare
resources and evaluate changes in telephone nursing procedures.
  Objective: To develop a valid model that captures the complex relationships
between the nurse's recommendations, the patients' intended actions and the
patients' health seeking behavior. Using the model to estimate the effects of
telephone nursing on patient behavior, healthcare utilization, and infer
potential cost savings.
  Methods: Bayesian ordinal regression modeling of data from randomly selected
patients that received telephone nursing. Inference is based on Markov Chain
Monte Carlo methods, model selection using the Watanabe-Akaike Information
Criteria, and model validation using posterior predictive checks on standard
discrepancy measures.
  Results and Conclusions: We present a robust Bayesian ordinal regression
model that predicts 76% of the patients' healthcare utilization after telephone
nursing and we found no evidence of model deficiencies. The model reveals a
risk reducing behavior and the effect of the telephone nursing recommendation
is 7 times higher than the effect of the patient's intended action prior to
consultation if the recommendation is the highest level of care. But the effect
of the nurse's recommendation is lower, or even non-existing, if the
recommendation is self-care. Telephone nursing was found to have a constricting
effect on healthcare utilization, however, the compliance to nurse's
recommendation is closely tied to perceptions of risk, emphasizing the
importance to address caller's needs of reassurance.
