The Impact of Discussing Long-Term Quality of Life Predictions in the ICU on Patients, Families, and Healthcare Professionals

Academic Background

Patients discharged from the Intensive Care Unit (ICU) often face a range of physical, psychological, and cognitive issues, collectively referred to as Post-Intensive Care Syndrome (PICS). Despite improvements in ICU survival rates, patients and their families frequently lack sufficient awareness of the long-term health impacts, leading to overly optimistic expectations regarding their future quality of life (QoL). These unrealistic expectations may affect patients’ mental recovery and could lead to biases in medical decision-making. Additionally, ICU healthcare professionals often face challenges when assessing long-term patient prognoses because quality of life depends not only on physical function but also on various subjective factors.

To enhance patients’ and families’ understanding of long-term QoL and promote Shared Decision-Making (SDM), researchers developed a personalized QoL prediction tool based on a predictive model and used it during family meetings in the ICU. This study aimed to evaluate the impact of this intervention on the experiences and outcomes of patients, families, and healthcare professionals.

Paper Source

This paper was co-authored by Lucy L. Porter, Koen S. Simons, Johannes G. van der Hoeven, Mark van den Boogaard, and Marieke Zegers. The research team came from Radboud University Medical Center and Jeroen Bosch Hospital in the Netherlands. The paper was published in the journal Intensive Care Medicine in 2025, with the DOI: 10.1007/s00134-025-07812-5.

Research Process

Study Subjects and Design

This study was a randomized controlled trial conducted in two hospitals in the Netherlands. The subjects were adult patients admitted to the ICU for at least 24 hours and their families. Patients were randomly assigned to either the intervention group or the usual care group. The intervention group discussed long-term QoL predictions based on a predictive model during family meetings, while the usual care group received standard care. The primary outcome was the experience of patients and families with shared decision-making during family meetings. Secondary outcomes included ICU professionals’ collaboration satisfaction, symptoms of anxiety and depression in patients and families, and patients’ QoL at 3 months and 1 year post-ICU admission.

Intervention Measures

The intervention consisted of three parts: 1. QoL Prediction Model: A predictive model developed using data from the Monitor-IC cohort study to predict changes in patients’ QoL one year after ICU admission. 2. Family Meeting Discussions: ICU physicians used the results of the predictive model to discuss future QoL with patients and families during family meetings. 3. Information Leaflet: A comprehensive information leaflet about recovery after ICU was provided to patients and families.

Data Collection and Analysis

Data were collected through questionnaires and electronic health records. Patients and families completed the COLLABORATE questionnaire within three days after the family meeting to assess the shared decision-making experience. Patients and families completed the Hospital Anxiety and Depression Scale (HADS) and EQ-5D-5L QoL questionnaire at 3 months and 1 year after ICU admission. ICU professionals completed collaboration satisfaction and ethical decision-making climate questionnaires before and after the study period.

Research Results

Primary Outcome

A total of 160 patients were included in the study, with 81 receiving the intervention and 79 receiving usual care. The results showed no significant differences in shared decision-making experiences between the intervention and usual care groups (median COLLABORATE scores of 89 vs. 93, p=0.6).

Secondary Outcomes

• Anxiety and Depression Symptoms in Patients and Families: One year after ICU discharge, there was a significant increase in depressive symptoms among family members in the usual care group (mean increase of 2.3 points, p=0.04), while the change in depressive symptoms was smaller in the intervention group (mean increase of 0.2 points).
• Collaboration Satisfaction of ICU Professionals: After the intervention, the collaboration satisfaction of healthcare professionals significantly improved (median increased from 37 to 40, p=0.01), but there was no significant change in the ethical decision-making climate.

Conclusion

The study showed that discussing personalized long-term QoL predictions during ICU family meetings had no significant impact on the shared decision-making experiences of patients and families, but it effectively reduced depressive symptoms in family members after ICU discharge and improved the collaboration satisfaction of healthcare professionals. This finding supports the introduction of predictive models in ICU clinical practice and emphasizes the importance of information delivery in the ICU environment.

Highlights of the Study

• Innovation: This study was the first to apply a personalized QoL predictive model based on big data to ICU clinical practice and validate its effectiveness through a randomized controlled trial.
• Practical Application Value: The study results indicate that this intervention can improve the mental health of family members and enhance the collaborative experience of healthcare professionals, offering potential clinical application value.
• Study Limitations: The baseline QoL of the study subjects was relatively high, and their ICU stay was relatively long, which may limit the generalizability of the study results.

Other Valuable Information

Future research could consider applying similar predictive models in other medical settings and explore whether structured communication training could further enhance the effectiveness of the intervention. Additionally, combining qualitative research methods to gain deeper insights into the experiences of patients and families may provide more perspectives for improving the intervention.