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Author(s): Matthieu Komorowski [sup.1] [sup.5], Maria del Pilar Arias López [sup.2] [sup.3], Anthony C. Chang [sup.4] Author Affiliations: (1) grid.7445.2, 0000 0001 2113 8111, Division of Anaesthetics, Pain Medicine, and [...]

Author(s): Vrindha Pari [sup.1], Eva Fleur Sluijs, Maria del Pilar Arias López, David Alexander Thomson, Swagata Tripathy, Sutharshan Vengadasalam, Bharath Kumar Tirupakuzhi Vijayaraghavan, Luigi Pisani, Nicolette de Keizer, Neill K. [...], 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 [less than or equal to] 1) were removed, and indicators with consensus agreement (median [greater than or equal to] 4, IQR [less than or equal to] 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.