Models of intensive care unit follow-up care and feasibility of intervention delivery: A systematic review

Using augmented intelligence to improve long term outcomes

PURPOSE OF REVIEW

For augmented intelligence (AI) tools to realize their potential, critical care clinicians must ensure they are designed to improve long-term outcomes. This overview is intended to align professionals with the state-of-the art of AI.

RECENT FINDINGS

Many AI tools are undergoing preliminary assessment of their ability to support the care of survivors and their caregivers at multiple time points after intensive care unit (ICU) discharge. The domains being studied include early identification of deterioration (physiological, mental), management of impaired physical functioning, pain, sleep and sexual dysfunction, improving nutrition and communication, and screening and treatment of cognitive impairment and mental health disorders.Several technologies are already being marketed and many more are in various stages of development. These technologies mostly still require clinical trials outcome testing. However, lacking a formal regulatory approval process, some are already in use.

SUMMARY

Plans for long-term management of ICU survivors must account for the development of a holistic follow-up system that incorporates AI across multiple platforms. A tiered post-ICU screening program may be established wherein AI tools managed by ICU follow-up clinics provide appropriate assistance without human intervention in cases with less pathology and refer severe cases to expert treatment.

Do critical illness survivors with multimorbidity need a different model of care?

There is currently a lack of evidence on the optimal strategy to support patient recovery after critical illness. Previous research has largely focussed on rehabilitation interventions which aimed to address physical, psychological, and cognitive functional sequelae, the majority of which have failed to demonstrate benefit for the selected outcomes in clinical trials. It is increasingly recognised that a person's existing health status, and in particular multimorbidity (usually defined as two or more medical conditions) and frailty, are strongly associated with their long-term outcomes after critical illness. Recent evidence indicates the existence of a distinct subgroup of critical illness survivors with multimorbidity and high healthcare utilisation, whose prior health trajectory is a better predictor of long-term outcomes than the severity of their acute illness. This review examines the complex relationships between multimorbidity and patient outcomes after critical illness, which are likely mediated by a range of factors including the number, severity, and modifiability of a person's medical conditions, as well as related factors including treatment burden, functional status, healthcare delivery, and social support. We explore potential strategies to optimise patient recovery after critical illness in the presence of multimorbidity. A comprehensive and individualized approach is likely necessary including close coordination among healthcare providers, medication reconciliation and management, and addressing the physical, psychological, and social aspects of recovery. Providing patient-centred care that proactively identifies critical illness survivors with multimorbidity and accounts for their unique challenges and needs is likely crucial to facilitate recovery and improve outcomes.

Instruments to assess post-intensive care syndrome assessment: a scoping review and modified Delphi method study

BACKGROUND

The assessment of post-intensive care syndrome (PICS) is challenging due to the numerous types of instruments. We herein attempted to identify and propose recommendations for instruments to assess PICS in intensive care unit (ICU) survivors.

METHODS

We conducted a scoping review to identify PICS follow-up studies at and after hospital discharge between 2014 and 2022. Assessment instruments used more than two times were included in the modified Delphi consensus process. A modified Delphi meeting was conducted three times by the PICS committee of the Japanese Society of Intensive Care Medicine, and each score was rated as not important (score: 1-3), important, but not critical (4-6), and critical (7-9). We included instruments with ≥ 70% of respondents rating critical and ≤ 15% of respondents rating not important.

RESULTS

In total, 6972 records were identified in this scoping review, and 754 studies were included in the analysis. After data extraction, 107 PICS assessment instruments were identified. The modified Delphi meeting reached 20 PICS assessment instrument recommendations: (1) in the physical domain: the 6-min walk test, MRC score, and grip strength, (2) in cognition: MoCA, MMSE, and SMQ, (3) in mental health: HADS, IES-R, and PHQ-9, (4) in the activities of daily living: the Barthel Index, IADL, and FIM, (5) in quality of life: SF-36, SF-12, EQ-5D-5L, 3L, and VAS (6), in sleep and pain: PSQI and Brief Pain Inventory, respectively, and (7) in the PICS-family domain: SF-36, HADS, and IES-R.

CONCLUSION

Based on a scoping review and the modified Delphi method, 20 PICS assessment instruments are recommended to assess physical, cognitive, mental health, activities of daily living, quality of life, sleep, and pain in ICU survivors and their families.