Results of the summarizing process for the arXiv paper: 1803.06109v1

Abstract: 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.