Clinical Decision-Making: Observing the Smartphone User An Observational Study in Predicting Acute Surgical Patients’ Suitability for Discharge
INTRODUCTION: An accurate and rapid assessment of an acutely unwell patient’s clinical status is paramount for the physician. There is an increasing trend to rely on investigations and results to inform a clinician of a patient’s clinical status, with the subtleties of clinical observation often ignored. The aim of this study was to determine if a patient’s use of a smartphone during the initial clinical assessment by a surgical consultant could be used as a surrogate marker for patient well-being, represented as their suitability for same-day discharge.
METHODS: This was a prospective observational study performed over 2 periods at a tertiary hospital in South Australia. All patients admitted by junior surgical doctors from the emergency department to the acute surgical unit were eligible for inclusion. Upon consultant review, their status as a smartphone user was recorded in addition to their duration of hospital stay and basic demographic data. All patients and all but 1 of the consultants were blinded to the trial.
RESULTS: Two hundred and twenty-one patients were eligible for inclusion. Of these patients, 11.3% were observed to be using a smartphone and 23.5% of patients were discharged home on day 1. Those who were observed to be using a smartphone were 5.29 times more likely to be discharged home on day 1 and were less likely to be subsequently readmitted.
CONCLUSIONS: The addition of the smartphone sign to a surgeon’s clinical acumen can provide yet another tool in aiding the decision for suitability for discharge.
© 2018 Society of Hospital Medicine
CONCLUSION
While these observations might appear to be rather a simplistic way of trying to quantify whether or not a patient is fit for discharge, any clues that hint towards a patient’s well-being should be taken into account when making an overall assessment. The active use of a smartphone is one such measure.
Acknowledgments
The authors thank Emma Knight and Nancy Briggs from the Data Management & Analysis Centre, Discipline of Public Health, University of Adelaide.
Disclosure
No author nor the institution received any payment or services from a third party for any aspect of the submitted work and report no conflict of interest. There are no reported financial relationships with any entities by any of the authors. There are no patents pending based upon this publication. There are no relationships or activities that readers could perceive to have influenced, or give the appearance of influencing, the submitted work. The corresponding author is not in receipt of a research scholarship. The paper is not based on a previous communication.
