Determining Postoperative Recovery and the Impact of Adverse Events in Neurosurgery Based on Self-reported, App-based Longitudinal Assessment

Résumé

Analyzing the impact of surgery and adverse events (AEs) on patients' well-being is of paramount importance as it provides essential information for benefit-risk assessment. Current methods in outcome research are static, resource-intensive and subject to missing-data issues. Moreover, AEs are inconsistently reported using various grading systems that usually do not account for patients' subjective well-being. These are severe drawbacks for outcome research as it hinders monitoring, comparison, and improvement of treatment quality. The increasing use of smartphones offers unprecedented opportunities for data collection. The investigators developed a free smartphone application to assess fluctuations of patients' well-being as a result of surgical treatment and possible AEs. The application is installed on each patient's smartphone and collects standardized data at defined timepoints before and after surgery (well-being, AE description and severity). By acquiring longitudinal patient-reported outcome before and after neurosurgical interventions, the investigators aim to determine the regular postoperative course for specific surgical procedures, as well as any deviation thereof, depending on the occurrence and severity of AEs. The investigators will evaluate the validity of existing AE classifications and, if necessary, propose a new patient-centered scheme. The investigators hope that this will result in an increase in standardized reporting of patient outcome, and ultimately allow for evidence-based patient information and decision-making.