Performance evaluation of a multinational data platform for critical care in Asia

Prevalence of frailty and association with patient centered outcomes: A prospective registry-embedded cohort study from India

PURPOSE

We aimed to study the prevalence of frailty, evaluate risk factors, and understand impact on outcomes in India.

METHODS

This was a prospective registry-embedded cohort study across 7 intensive care units (ICUs) and included adult patients anticipated to stay for at least 48 h. Primary exposure was frailty, as defined by a score ≥ 5 on the Clinical Frailty Scale and primary outcome was ICU mortality. Secondary outcomes included in-hospital mortality and resource utilization. We used generalized linear models to evaluate risk factors and model association between frailty and outcomes.

RESULTS

838 patients were included, with median (IQR) age 57 (42,68) yrs.; 64.8% were male. Prevalence of frailty was 19.8%. Charlson comorbidity index (OR:1.73 (95%CI:1.39,2.15)), Subjective Global Assessment categories mild/moderate malnourishment (OR:1.90 (95%CI:1.29, 2.80)) and severe malnourishment (OR:4.76 (95% CI:2.10,10.77)) were associated with frailty. Frailty was associated with higher odds of ICU mortality (adjusted OR:2.04 (95% CI:1.25,3.33)), hospital mortality (adjusted OR:2.36 (95%CI:1.45,3.84)), development of stage2/3 AKI (unadjusted OR:2.35 (95%CI:1.60, 3.43)), receipt of non-invasive ventilation (unadjusted OR:2.68 (95%CI:1.77, 4.03)), receipt of vasopressors (unadjusted OR:1.47 (95%CI:1.04, 2.07)), and receipt of kidney replacement therapy (unadjusted OR:3.15 (95%CI:1.90, 5.17)).

CONCLUSIONS

Frailty is common among critically ill patients in India and is associated with worse outcomes.

STUDY REGISTRATION

CTRI/2021/02/031503.

SOFA and APACHE II scoring systems for predicting outcome of neurological patients admitted in a tertiary hospital intensive care unit

Background

The field of neurology encompasses the study and treatment of disorders that affect the nervous system, and patients with neurological conditions often require specialized care, particularly in the ICU. Predictive scoring systems are measures of disease severity used to predict patient outcomes. The aim of this study was to compare the discriminative power of commonly used scoring systems, namely the sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation II (APACHE II) in the ICU of a tertiary care hospital.

Methods

This retrospective study included patients with neurological disorders in the ICUs of Tribhuvan University Teaching Hospital from 1 January 2022 to 31 December 2022.

Results

A total of 153 patients were included. The mean age of the patients was 54.76 ± 17.32 years with higher male predominance (60.78%). Ischaemic stroke was the most common neurological disorder. There were 58 patients (37.9%) who required mechanical ventilation and all-cause mortality was 20.9%. The mean SOFA score was significantly higher (P=0.002) in survivors, whereas the mean APACHE II did not show a significant difference (P=0.238). Receiver operating characteristic (ROC) analysis showed the area of curve (AUC) of SOFA score was 0.765 and of APACHE II was 0.722.

Conclusions

SOFA score had comparatively higher discriminative power than APACHE II. Assessment of the performance of scoring systems in a specific ICU setting improves the sensitivity and applicability of the model to these settings.

National ICU Registries as Enablers of Clinical Research and Quality Improvement

OBJECTIVES

Clinical quality registries (CQRs) have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. This narrative review describes the challenges, proposed solutions, and evidence generated by National ICU registries as facilitators for research and quality improvement.

DATA SOURCES

English language articles were identified in PubMed using phrases related to ICU registries, CQRs, outcomes, and case-mix.

STUDY SELECTION

Original research, review articles, letters, and commentaries, were considered.

DATA EXTRACTION

Data from relevant literature were identified, reviewed, and integrated into a concise narrative review.

DATA SYNTHESIS

CQRs have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. The initial experience in European countries and in Oceania ensured that through locally generated data, ICUs could assess their performances by using risk-adjusted measures and compare their results through fair and validated benchmarking metrics with other ICUs contributing to the CQR. The accomplishment of these initiatives, coupled with the increasing adoption of information technology, resulted in a broad geographic expansion of CQRs as well as their use in quality improvement studies, clinical trials as well as international comparisons, and benchmarking for ICUs.

CONCLUSIONS

ICU registries have provided increased knowledge of case-mix and outcomes of ICU patients based on real-world data and contributed to improve care delivery through quality improvement initiatives and trials. Recent increases in adoption of new technologies (i.e., cloud-based structures, artificial intelligence, machine learning) will ensure a broader and better use of data for epidemiology, healthcare policies, quality improvement, and clinical trials.

Mixed methods study protocol for combining stakeholder-led rapid evaluation with near real-time continuous registry data to facilitate evaluations of quality of care in intensive care units

Background

Improved access to healthcare in low- and middle-income countries (LMICs) has not equated to improved health outcomes. Absence or unsustained quality of care is partly to blame. Improving outcomes in intensive care units (ICUs) requires delivery of complex interventions by multiple specialties working in concert, and the simultaneous prevention of avoidable harms associated with the illness and the treatment interventions. Therefore, successful design and implementation of improvement interventions requires understanding of the behavioural, organisational, and external factors that determine care delivery and the likelihood of achieving sustained improvement. We aim to identify care processes that contribute to suboptimal clinical outcomes in ICUs located in LMICs and to establish barriers and enablers for improving the care processes.

Methods

Using rapid evaluation methods, we will use four data collection methods: 1) registry embedded indicators to assess quality of care processes and their associated outcomes; 2) process mapping to provide a preliminary framework to understand gaps between current and desired care practices; 3) structured observations of processes of interest identified from the process mapping and; 4) focus group discussions with stakeholders to identify barriers and enablers influencing the gap between current and desired care practices. We will also collect self-assessments of readiness for quality improvement. Data collection and analysis will be led by local stakeholders, performed in parallel and through an iterative process across eight countries: Kenya, India, Malaysia, Nepal, Pakistan, South Africa, Uganda and Vietnam.

Conclusions

The results of our study will provide essential information on where and how care processes can be improved to facilitate better quality of care to critically ill patients in LMICs; thus, reduce preventable mortality and morbidity in ICUs. Furthermore, understanding the rapid evaluation methods that will be used for this study will allow other researchers and healthcare professionals to carry out similar research in ICUs and other health services.

Incidence, risk and impact of ICU readmission on patient outcomes and resource utilisation in tertiary level ICUs in Nepal: A cohort study

Background: Readmissions to Intensive Care Units (ICUs) result in increased morbidity, mortality, and ICU resource utilisation (e.g. prolonged mechanical ventilation), and as such, is a widely utilised metric of quality of critical care. Most of the evidence on incidence, characteristics, associated risk factors and attributable outcomes of unplanned readmission to ICU are from studies performed in high-income countries This study explores the determinants of risk attributable to unplanned ICU readmission in four ICUs in Kathmandu, Nepal. Methods: The registry-embedded eCRF reported data on case mix, severity of illness, in-ICU interventions (including organ support), ICU outcome, and readmission characteristics. Data were captured in all adult patients admitted between September 2019 and February 2021. Population and ICU encounter characteristics were compared between those with and without readmission. Independent risk factors for readmission were assessed using univariate analysis. Results: In total 2955 patients were included in the study. Absolute unplanned ICU readmission rate was 5.69 % (n=168) for all four ICUs. Median time from ICU discharge to readmission was 3 days (IQR=8,1). Of those readmitted, 29.17% (n=49) were discharged at night following their index admission. ICU mortality was higher following readmission to ICU(p=0.016) and mortality was increased further in patients whose primary index discharge was at night(p= 0.019).  Primary diagnosis, age, and use of organ support in the first 24hrs of index admission were all independently attributable risk factors for readmission. Conclusions: Unplanned ICU readmission rates were adversely associated with significantly poorer outcomes, increased ICU resource utilisation. Clinical and organisational characteristics influenced risk of readmission and outcome.

Mixed methods study protocol for combining stakeholder-led rapid evaluation with near real-time continuous registry data to facilitate evaluations of quality of care in intensive care units

Background: Improved access to healthcare in low- and middle-income countries (LMICs) has not equated to improved health outcomes. Absence or unsustained quality of care is partly to blame. Improving outcomes in intensive care units (ICUs) requires delivery of complex interventions by multiple specialties working in concert, and the simultaneous prevention of avoidable harms associated with the illness and the treatment interventions. Therefore, successful design and implementation of improvement interventions requires understanding of the behavioural, organisational, and external factors that determine care delivery and the likelihood of achieving sustained improvement. We aim to identify care processes that contribute to suboptimal clinical outcomes in ICUs located in LMICs and to establish barriers and enablers for improving the care processes. Methods: Using rapid evaluation methods, we will use four data collection methods: 1) registry embedded indicators to assess quality of care processes and their associated outcomes; 2) process mapping to provide a preliminary framework to understand gaps between current and desired care practices; 3) structured observations of processes of interest identified from the process mapping and; 4) focus group discussions with stakeholders to identify barriers and enablers influencing the gap between current and desired care practices. We will also collect self-assessments of readiness for quality improvement. Data collection and analysis will be performed in parallel and through an iterative process across eight countries: Kenya, India, Malaysia, Nepal, Pakistan, South Africa, Uganda and Vietnam. Conclusions: The results of our study will provide essential information on where and how care processes can be improved to facilitate better quality of care to critically ill patients in LMICs; thus, reduce preventable mortality and morbidity in ICUs. Furthermore, understanding the rapid evaluation methods that will be used for this study will allow other researchers and healthcare professionals to carry out similar research in ICUs and other health services.

Mixed methods study protocol for combining stakeholder-led rapid evaluation with near real-time continuous registry data to facilitate evaluations of quality of care in intensive care units

Background: Improved access to healthcare in low- and middle-income countries (LMICs) has not equated to improved health outcomes. Absence or unsustained quality of care is partly to blame. Improving outcomes in intensive care units (ICUs) requires delivery of complex interventions by multiple specialties working in concert, and the simultaneous prevention of avoidable harms associated with the illness and the treatment interventions. Therefore, successful design and implementation of improvement interventions requires understanding of the behavioural, organisational, and external factors that determine care delivery and the likelihood of achieving sustained improvement. We aim to identify care processes that contribute to suboptimal clinical outcomes in ICUs located in LMICs and to establish barriers and enablers for improving the care processes. Methods: Using rapid evaluation methods, we will use four data collection methods: 1) registry embedded indicators to assess quality of care processes and their associated outcomes; 2) process mapping to provide a preliminary framework to understand gaps between current and desired care practices; 3) structured observations of processes of interest identified from the process mapping and; 4) focus group discussions with stakeholders to identify barriers and enablers influencing the gap between current and desired care practices. We will also collect self-assessments of readiness for quality improvement. Data collection and analysis will be performed in parallel and through an iterative process across eight countries: Kenya, India, Malaysia, Nepal, Pakistan, South Africa, Uganda and Vietnam. Conclusions: The results of our study will provide essential information on where and how care processes can be improved to facilitate better quality of care to critically ill patients in LMICs; thus, reduce preventable mortality and morbidity in ICUs. Furthermore, understanding the rapid evaluation methods that will be used for this study will allow other researchers and healthcare professionals to carry out similar research in ICUs and other health services.

Incidence, risk and impact of unplanned ICU readmission on patient outcomes and resource utilisation in tertiary level ICUs in Nepal: A cohort study

Background: Unplanned readmissions to Intensive Care Units (ICUs) result in increased morbidity, mortality, and ICU resource utilisation (e.g. prolonged mechanical ventilation), and as such, is a widely utilised metric of quality of critical care. Most of the evidence on incidence, characteristics, associated risk factors and attributable outcomes of unplanned readmission to ICU are from studies performed in high-income countries This study explores the determinants of risk attributable to unplanned ICU readmission in four ICUs in Kathmandu, Nepal. Methods: The registry-embedded eCRF reported data on case mix, severity of illness, in-ICU interventions (including organ support), ICU outcome, and readmission characteristics. Data were captured in all adult patients admitted between September 2019 and February 2021. Population and ICU encounter characteristics were compared between those with and without readmission. Independent risk factors for readmission were assessed using univariate analysis. Results: In total 2948 patients were included in the study. Absolute unplanned ICU readmission rate was 5.60 % (n=165) for all four ICUs. Median time from ICU discharge to readmission was 3 days (IQR=8,1). Of those readmitted, 29.7% (n=49) were discharged at night following their index admission. ICU mortality was higher following readmission to ICU(p=0.016) and mortality was increased further in patients whose primary index discharge was at night(p= 0.019).  Primary diagnosis, age, and use of organ support in the first 24hrs of index admission were all independently attributable risk factors for readmission. Conclusions: Unplanned ICU readmission rates were adversely associated with significantly poorer outcomes, increased ICU resource utilisation. Clinical and organisational characteristics influenced risk of readmission and outcome.