Timely and appropriate care is the key to achieving good outcomes in acutely ill patients, but the effectiveness of critical care may be limited in resource-limited settings. This study sought to understand how to implement best practices in intensive care units (ICU) in low- and middle-income countries (LMIC) and to develop a point-of-care training and decision-support tool. An internationally representative group of clinicians performed a 22-item capacity-and-needs assessment survey in a convenience sample of 13 ICU in Eastern Europe (4), Asia (4), Latin America (3), and Africa (2), between April and July 2012. Two ICU were from low-income, 2 from low-middle-income, and 9 from upper-middle-income countries. Clinician respondents were asked about bed capacity, patient characteristics, human resources, available medications and equipment, access to education, and processes of care. Thirteen clinicians from each of 13 hospitals (1 per ICU) responded. Surveyed hospitals had median of 560 (interquartile range [IQR]: 232, 1,200) beds. ICU had a median of 9 (IQR: 7, 12) beds and treated 40 (IQR: 20, 67) patients per month. Many ICU had ≥ 1 staff member with some formal critical care training (n = 9, 69%) or who completed Fundamental Critical Care Support (n = 7, 54%) or Advanced Cardiac Life Support (n = 9, 69%) courses. Only 2 ICU (15%) used any kind of checklists for acute resuscitation. Ten (77%) ICU listed lack of trained staff as the most important barrier to improving the care and outcomes of critically ill patients. In a convenience sample of 13 ICU from LMIC, specialty-trained staff and standardized processes of care such as checklists are frequently lacking. ICU needs-assessment evaluations should be expanded in LMIC as a global priority, with the goal of creating and evaluating context-appropriate checklists for ICU best practices.
1 October 2018 in Current Opinion in Critical Care
Purpose of review: The burden of critical illness in low-income and middle-income countries (LMICs) is substantial. A better understanding of critical care outcomes is essential for improving critical care delivery in resource-limited settings. In this review, we provide an overview of recent literature reporting on critical care outcomes in LMICs. We discuss several barriers and potential solutions for a better understanding of critical care outcomes in LMICs. Recent findings: Epidemiologic studies show higher in-hospital mortality rates for critically ill patients in LMICs as compared with patients in high-income countries (HICs). Recent findings suggest that critical care interventions that are effective in HICs may not be effective and may even be harmful in LMICs. Little data on long-term and morbidity outcomes exist. Better outcomes measurement is beginning to emerge in LMICs through decision support tools that report process outcome measures, studies employing mobile health technologies with community health workers and the development of context-specific severity of illness scores. Summary: Outcomes from HICs cannot be reliably extrapolated to LMICs, so it is important to study outcomes for critically ill patients in LMICs. Specific challenges to achieving meaningful outcomes studies in LMICs include defining the critically ill population when few ICU beds exist, the resource-intensiveness of long-term follow-up, and the need for reliable severity of illness scores to interpret outcomes. Although much work remains to be done, examples of studies overcoming these challenges are beginning to emerge.
OBJECTIVES: To determine whether the “Checklist for Early Recognition and Treatment of Acute Illness and Injury” decision support tool during ICU admission and rounding is associated with improvements in nonadherence to evidence-based daily care processes and outcomes in variably resourced ICUs. DESIGN, SETTINGS, PATIENTS: This before-after study was performed in 34 ICUs (15 countries) from 2013 to 2017. Data were collected for 3 months before and 6 months after Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation. INTERVENTIONS: Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation using remote simulation training. MEASUREMENTS AND MAIN RESULTS: The coprimary outcomes, modified from the original protocol before data analysis, were nonadherence to 10 basic care processes and ICU and hospital length of stay. There were 1,447 patients in the preimplementation phase and 2,809 patients in the postimplementation phase. After adjusting for center effect, Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation was associated with reduced nonadherence to care processes (adjusted incidence rate ratio [95% CI]): deep vein thrombosis prophylaxis (0.74 [0.68–0.81), peptic ulcer prophylaxis (0.46 [0.38–0.57]), spontaneous breathing trial (0.81 [0.76–0.86]), family conferences (0.86 [0.81–0.92]), and daily assessment for the need of central venous catheters (0.85 [0.81–0.90]), urinary catheters (0.84 [0.80–0.88]), antimicrobials (0.66 [0.62–0.71]), and sedation (0.62 [0.57–0.67]). Analyses adjusted for baseline characteristics showed associations of Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation with decreased ICU length of stay (adjusted ratio of geometric means [95% CI]) 0.86 [0.80–0.92]), hospital length of stay (0.92 [0.85–0.97]), and hospital mortality (adjusted odds ratio [95% CI], 0.81 (0.69–0.95). CONCLUSIONS: A quality-improvement intervention with remote simulation training to implement a decision support tool was associated with decreased nonadherence to daily care processes, shorter length of stay, and decreased mortality.
15 May 2013 in American Journal of Respiratory and Critical Care Medicine
Processes to ensure world-wide best-practice for critical care delivery are likely to minimize preventable death, disability and costly complications for any healthcare system's sickest patients, but no large-scale efforts have so far been undertaken towards these goals. The advances in medical informatics and human factors engineering have provided possibility for novel and user-friendly clinical decision support tools that can be applied in a complex and busy hospital setting. To facilitate timely and accurate best-practice delivery in critically ill patients international group of intensive care unit (ICU) physicians and researchers developed a simple decision support tool: Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN). The tool has been refined and tested in high fidelity simulated clinical environment and has been shown to improve performance of clinical providers faced with simulated emergencies. The aim of this international educational intervention is to implement CERTAIN into clinical practice in hospital settings with variable resources (included those in low income countries) and evaluate the impact of the tool on the care processes and patient outcomes. To accomplish our aims, CERTAIN will be uniformly available on either mobile or fixed computing devices (as well as a backup paper version) and applied in a standardized manner in the ICUs of diverse hospitals. To ensure the effectiveness of the proposed intervention, access to CERTAIN is coupled with structured training of bedside ICU providers.