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.

Determinants of Implementation of a Critical Care Registry in Asia: Lessons From a Qualitative Study.

BACKGROUND: The Collaboration for Research, Implementation, and Training in Critical Care in Asia (CCA) is implementing a critical care registry to capture real-time data to facilitate service evaluation, quality improvement, and clinical studies. OBJECTIVE: The purpose of this study is to examine stakeholder perspectives on the determinants of implementation of the registry by examining the processes of diffusion, dissemination, and sustainability. METHODS: This study is a qualitative phenomenological inquiry using semistructured interviews with stakeholders involved in registry design, implementation, and use in 4 South Asian countries. The conceptual model of diffusion, dissemination, and sustainability of innovations in health service delivery guided interviews and analysis. Interviews were coded using the Rapid Identification of Themes from Audio recordings procedure and were analyzed based on the constant comparison approach. RESULTS: A total of 32 stakeholders were interviewed. Analysis of stakeholder accounts identified 3 key themes: innovation-system fit; influence of champions; and access to resources and expertise. Determinants of implementation included data sharing, research experience, system resilience, communication and networks, and relative advantage and adaptability. CONCLUSIONS: The implementation of the registry has been possible due to efforts to increase the innovation-system fit, influence of motivated champions, and the support offered by access to resources and expertise. The reliance on individuals and the priorities of other health care actors pose a risk to sustainability.

Development of a quality indicator set to measure and improve quality of ICU care in low- and middle-income countries.

PURPOSE: To develop a set of actionable quality indicators for critical care suitable for use in low- or middle-income countries (LMICs). METHODS: A list of 84 candidate indicators compiled from a previous literature review and stakeholder recommendations were categorised into three domains (foundation, process, and quality impact). An expert panel (EP) representing stakeholders from critical care and allied specialties in multiple low-, middle-, and high-income countries was convened. In rounds one and two of the Delphi exercise, the EP appraised (Likert scale 1-5) each indicator for validity, feasibility; in round three sensitivity to change, and reliability were additionally appraised. Potential barriers and facilitators to implementation of the quality indicators were also reported in this round. Median score and interquartile range (IQR) were used to determine consensus; indicators with consensus disagreement (median < 4, IQR ≤ 1) were removed, and indicators with consensus agreement (median ≥ 4, IQR ≤ 1) or no consensus were retained. In round four, indicators were prioritised based on their ability to impact cost of care to the provider and recipient, staff well-being, patient safety, and patient-centred outcomes. RESULTS: Seventy-one experts from 30 countries (n = 45, 63%, representing critical care) selected 57 indicators to assess quality of care in intensive care unit (ICU) in LMICs: 16 foundation, 27 process, and 14 quality impact indicators after round three. Round 4 resulted in 14 prioritised indicators. Fifty-seven respondents reported barriers and facilitators, of which electronic registry-embedded data collection was the biggest perceived facilitator to implementation (n = 54/57, 95%) Concerns over burden of data collection (n = 53/57, 93%) and variations in definition (n = 45/57, 79%) were perceived as the greatest barrier to implementation. CONCLUSION: This consensus exercise provides a common set of indicators to support benchmarking and quality improvement programs for critical care populations in LMICs.

Impact of COVID-19 on non-COVID intensive care unit service utilization, case mix and outcomes: A registry-based analysis from India.

Background: Coronavirus disease 2019 (COVID-19) has been responsible for over 3.4 million deaths globally and over 25 million cases in India. As part of the response, India imposed a nation-wide lockdown and prioritized COVID-19 care in hospitals and intensive care units (ICUs). Leveraging data from the Indian Registry of IntenSive care, we sought to understand the impact of the COVID-19 pandemic on critical care service utilization, case-mix, and clinical outcomes in non-COVID ICUs.  Methods: We included all consecutive patients admitted between 1 st October 2019 and 27 th September 2020. Data were extracted from the registry database and included patients admitted to the non-COVID or general ICUs at each of the sites. Outcomes included measures of resource-availability, utilisation, case-mix, acuity, and demand for ICU beds. We used a Mann-Whitney test to compare the pre-pandemic period (October 2019 - February 2020) to the pandemic period (March-September 2020). In addition, we also compared the period of intense lockdown (March-May 31 st 2020) with the pre-pandemic period. Results: There were 3424 patient encounters in the pre-pandemic period and 3524 encounters in the pandemic period. Comparing these periods, weekly admissions declined (median [Q1 Q3] 160 [145,168] to 113 [98.5,134]; p=0.00002); unit turnover declined (median [Q1 Q3] 12.1 [11.32,13] to 8.58 [7.24,10], p<0.00001), and APACHE II score increased (median [Q1 Q3] 19 [19,20] to 21 [20,22] ; p<0.00001). Unadjusted ICU mortality increased (9.3% to 11.7%, p=0.01519) and the length of ICU stay was similar (median [Q1 Q3] 2.11 [2, 2] vs. 2.24 [2, 3] days; p=0.15096). Conclusion: Our registry-based analysis of the impact of COVID-19 on non-COVID critical care demonstrates significant disruptions to healthcare utilization during the pandemic and an increase in the severity of illness.