Improving Shared-Decision Making in the Intensive Care Unit Using Patient-reported Outcome Information

Intensive Care Unit Syndrome, Patient Engagement

Share decision making, Intensive Care Unit, Quality of life

The aim of this study is to evaluate the effect of incorporation of outcome information in the Intensive Care Unit (ICU) decision-making process on patient and family reported outcomes and experiences of patients, relatives and ICU clinicians in a randomized clinical trial design in the Jeroen Bosch Ziekenhuis and Radboudumc in the Netherlands.

Background Due to advances in critical care medicine, more patients survive their critical illness. However, many Intensive Care Unit (ICU) survivors suffer from physical, cognitive and/or mental problems impacting patients' quality of life (QoL). Because of a lack of long-term outcome information, ICU physicians make decisions regarding ICU treatment based on their clinical experience and intuition. Moreover, patients and relatives are often not involved in the decision-making process. To improve the ICU decision-making process and to make it more substantiated, the use of patient-reported outcome measures (PROMs) is of utmost importance. Therefore, the Radboudumc, in collaboration with six regional hospitals, including Jeroen Bosch Ziekenhuis (JBZ), set up a large-scale prospective cohort study, MONITOR-IC (www.monitor-ic.nl), to study long-term outcomes of ICU survivors', their QoL and their needs. This research sets out to evaluate the effect of incorporation of outcome information in the ICU decision-making process on patient and family reported outcomes and experiences of patients, relatives and ICU clinicians in a randomized clinical trial design in the Jeroen Bosch Ziekenhuis and Radboudumc in the Netherlands. Methods A prediction model for long-term QoL was previously developed using physiological, pathological, drug and treatment data from patients' electronic health record combined with PROMs from one centre of the MONITOR-IC. It was externally validated with the data of six other centres and an E-health tool was developed, incorporating this prediction model. For this research, the E-health tool will be incorporated in family meetings.

Netherlands