Broken Wings and Resilience after Critical Illness

Patient and Caregiver-Derived Health Service Improvements for Better Critical Care Recovery

OBJECTIVES

To engage critical care end-users (survivors and caregivers) to describe their emotions and experiences across their recovery trajectory, and elicit their ideas and solutions for health service improvements to improve the ICU recovery experience.

DESIGN

End-user engagement as part of a qualitative design using the Framework Analysis method.

SETTING

The Society of Critical Care Medicine's THRIVE international collaborative sites (follow-up clinics and peer support groups).

SUBJECTS

Patients and caregivers following critical illness and identified through the collaboratives.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Eighty-six interviews were conducted. The following themes were identified: 1) Emotions and experiences of patients-"Loss of former self; Experiences of disability and adaptation"; 2) Emotions and experiences of caregivers-"Emotional impacts, adopting new roles, and caregiver burden; Influence of gender roles; Adaptation, adjustment, recalibration"; and 3) Patient and caregiver-generated solutions to improve recovery across the arc of care-"Family-targeted education; Expectation management; Rehabilitation for patients and caregivers; Peer support groups; Reconnecting with ICU post-discharge; Access to community-based supports post-discharge; Psychological support; Education of issues of ICU survivorship for health professionals; Support across recovery trajectory." Themes were mapped to a previously published recovery framework (Timing It Right) that captures patient and caregiver experiences and their support needs across the phases of care from the event/diagnosis to adaptation post-discharge home.

CONCLUSIONS

Patients and caregivers reported a range of emotions and experiences across the recovery trajectory from ICU to home. Through end-user engagement strategies many potential solutions were identified that could be implemented by health services and tested to support the delivery of higher-quality care for ICU survivors and their caregivers that extend from tertiary to primary care settings.

Understanding Patients' Perceived Health After Critical Illness: Analysis of Two Prospective, Longitudinal Studies of ARDS Survivors

BACKGROUND

Perceived health is one of the strongest determinants of subjective well-being, but it has received little attention among survivors of ARDS.

RESEARCH QUESTION

How well do self-reported measures of physical, emotional, and social functioning predict perceived overall health (measured using the EQ-5D visual analog scale [EQ-5D-VAS]) among adult survivors of ARDS? Are demographic features, comorbidity, or severity of illness correlated with perceived health after controlling for self-reported functioning?

STUDY DESIGN AND METHODS

We analyzed the ARDSNet Long Term Outcomes Study (ALTOS) and Improving Care of Acute Lung Injury Patients (ICAP) Study, two longitudinal cohorts with a total of 823 survivors from 44 US hospitals, which prospectively assessed survivors at 6 and 12 months after ARDS. Perceived health, evaluated using the EQ-5D-VAS, was predicted using ridge regression and self-reported measures of physical, emotional, and social functioning. The difference between observed and predicted perceived health was termed perspective deviation (PD). Correlations between PD and demographics, comorbidities, and severity of illness were explored.

RESULTS

The correlation between observed and predicted EQ-5D-VAS scores ranged from 0.68 to 0.73 across the two cohorts and time points. PD ranged from -80 to +34 and was more than the minimum clinically important difference for 52% to 55% of survivors. Neither demographic features, comorbidity, nor severity of illness were correlated strongly with PD, with |r| < 0.25 for all continuous variables in both cohorts and time points. The correlation between PD at 6- and 12-month assessments was weak (ALTOS: r = 0.22, P < .001; ICAP: r = 0.20, P = .02).

INTERPRETATION

About half of survivors of ARDS showed clinically important differences in actual perceived health vs predicted perceived health based on self-reported measures of functioning. Survivors of ARDS demographic features, comorbidities, and severity of illness were correlated only weakly with perceived health after controlling for measures of perceived functioning, highlighting the challenge of predicting how individual patients will respond psychologically to new impairments after critical illness.

Transitions of Care After Critical Illness-Challenges to Recovery and Adaptive Problem Solving

OBJECTIVES

Investigate the challenges experienced by survivors of critical illness and their caregivers across the transitions of care from intensive care to community, and the potential problem-solving strategies used to navigate these challenges.

DESIGN

Qualitative design-data generation via interviews and data analysis via the framework analysis method.

SETTING

Patients and caregivers from three continents, identified through the Society of Critical Care Medicine's THRIVE international collaborative sites (follow-up clinics and peer support groups).

SUBJECTS

Patients and caregivers following critical illness.

INTERVENTIONS

Nil.

MEASUREMENTS AND MAIN RESULTS

From 86 interviews (66 patients, 20 caregivers), we identified the following major themes: 1) Challenges for patients-interacting with the health system and gaps in care; managing others' expectations of illness and recovery. 2) Challenges for caregivers-health system shortfalls and inadequate communication; lack of support for caregivers. 3) Patient and caregiver-driven problem solving across the transitions of care-personal attributes, resources, and initiative; receiving support and helping others; and acceptance.

CONCLUSIONS

Survivors and caregivers experienced a range of challenges across the transitions of care. There were distinct and contrasting themes related to the caregiver experience. Survivors and caregivers used comparable problem-solving strategies to navigate the challenges encountered across the transitions of care.

Prediction Models for Physical, Cognitive, and Mental Health Impairments After Critical Illness: A Systematic Review and Critical Appraisal

OBJECTIVES

Improved ability to predict impairments after critical illness could guide clinical decision-making, inform trial enrollment, and facilitate comprehensive patient recovery. A systematic review of the literature was conducted to investigate whether physical, cognitive, and mental health impairments could be predicted in adult survivors of critical illness.

DATA SOURCES

A systematic search of PubMed and the Cochrane Library (Prospective Register of Systematic Reviews ID: CRD42018117255) was undertaken on December 8, 2018, and the final searches updated on January 20, 2019.

STUDY SELECTION

Four independent reviewers assessed titles and abstracts against study eligibility criteria. Studies were eligible if a prediction model was developed, validated, or updated for impairments after critical illness in adult patients. Discrepancies were resolved by consensus or an independent adjudicator.

DATA EXTRACTION

Data on study characteristics, timing of outcome measurement, candidate predictors, and analytic strategies used were extracted. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool.

DATA SYNTHESIS

Of 8,549 screened studies, three studies met inclusion. All three studies focused on the development of a prediction model to predict (1) a mental health composite outcome at 3 months post discharge, (2) return-to-pre-ICU functioning and residence at 6 months post discharge, and (3) physical function 2 months post discharge. Only one model had been externally validated. All studies had a high risk of bias, primarily due to the sample size, and statistical methods used to develop and select the predictors for the prediction published model.

CONCLUSIONS

We only found three studies that developed a prediction model of any post-ICU impairment. There are several opportunities for improvement for future prediction model development, including the use of standardized outcomes and time horizons, and improved study design and statistical methodology.

Peer Support in Critical Care: A Systematic Review

OBJECTIVES

Identifying solutions to improve recovery after critical illness is a pressing problem. We systematically evaluated studies of peer support as a potential intervention to improve recovery in critical care populations and synthesized elements important to peer support model design.

DATA SOURCES

A systematic search of Medical Literature Analysis and Retrieval System Online, Cumulative Index to Nursing and Allied Health Literature, PsychINFO, and Excertpa Medica Database was undertaken May 2017. Prospective Register of Systematic Reviews identification number: CRD42017070174.

STUDY SELECTION

Two independent reviewers assessed titles and abstracts against study eligibility criteria. Studies were included where 1) patients and families had experienced critical illness and 2) patients and families had participated in a peer support intervention. Discrepancies were resolved by consensus and a third independent reviewer adjudicated as necessary.

DATA EXTRACTION

Two independent reviewers assessed study quality with the Newcastle-Ottawa Scale and the Cochrane Risk of Bias Tool, and data were synthesized according to the Preferred Reporting Items for Systematic Reviews guidelines and interventions summarized using the Template for Intervention Description and Replication Checklist.

DATA SYNTHESIS

Two-thousand nine-hundred thirty-two studies were screened. Eight were included, comprising 192 family members and 92 patients including adults (with cardiac surgery, acute myocardial infarction, trauma), pediatrics, and neonates. The most common peer support model of the eight studies was an in-person, facilitated group for families that occurred during the patients' ICU admission. Peer support reduced psychologic morbidity and improved social support and self-efficacy in two studies; in both cases, peer support was via an individual peer-to-peer model. In the remaining studies, it was difficult to determine the outcomes of peer support as the reporting and quality of studies was low.

CONCLUSIONS

Peer support appeared to reduce psychologic morbidity and increase social support. The evidence for peer support in critically ill populations is limited. There is a need for well-designed and rigorously reported research into this complex intervention.

Unplanned early hospital readmission among critical care survivors: a mixed methods study of patients and carers

BACKGROUND

Many intensive care (ICU) survivors experience early unplanned hospital readmission, but the reasons and potential prevention strategies are poorly understood. We aimed to understand contributors to readmissions from the patient/carer perspective.

METHODS

This is a mixed methods study with qualitative data taking precedence. Fifty-eight ICU survivors and carers who experienced early unplanned rehospitalisation were interviewed. Thematic analysis was used to identify factors contributing to readmissions, and supplemented with questionnaire data measuring patient comorbidity and carer strain, and importance rating scales for factors that contribute to readmissions in other patient groups. Data were integrated iteratively to identify patterns, which were discussed in five focus groups with different patients/carers who also experienced readmissions. Major patterns and contexts in which unplanned early rehospitalisation occurred in ICU survivors were described.

RESULTS

Interviews suggested 10 themes comprising patient-level and system-level issues. Integration with questionnaire data, pattern exploration and discussion at focus groups suggested two major readmission contexts. A 'complex health and psychosocial needs' context occurred in patients with multimorbidity and polypharmacy, who frequently also had significant psychological problems, mobility issues, problems with specialist aids/equipment and fragile social support. These patients typically described inadequate preparation for hospital discharge, poor communication between secondary/primary care, and inadequate support with psychological care, medications and goal setting. This complex multidimensional situation contrasted markedly with the alternative 'medically unavoidable' readmission context. In these patients medical issues/complications primarily resulted in hospital readmission, and the other issues were absent or not considered important.

CONCLUSIONS

Although some readmissions are medically unavoidable, for many ICU survivors complex health and psychosocial issues contribute concurrently to early rehospitalisation. Care pathways that anticipate and institute anticipatory multifaceted support for these patients merit further development and evaluation.