A patient safety organization (PSO) is a group, institution, or association that improves medical care by reducing medical errors. Common functions of patient safety organizations are data collection and analysis, reporting, education, funding, and advocacy.In the 1990s, reports in several countries revealed a staggering number of patient injuries and deaths each year due to avoidable errors and deficiencies in health care, among them adverse events and complications arising from poor infection control. In the United States, a 1999 report from the Institute of Medicine called for a broad national effort to prevent these events, including the establishment of patient safety centers, expanded reporting of adverse events, and development of safety programs in health care organizations. Although many PSOs are funded and run by governments, others have sprung from private entities such as industry, professional, and consumer groups.
Quality improvement (QI) methods have been used extensively to support the delivery of safe, timely, effective, equitable, and cost-effective health care. While QI initiatives have demonstrated benefits, critical gaps in design and implementation undermine their impact. Systemic reviews and expert commentaries point to recurring challenges, including limited understanding and appreciation of the system in which the work takes place; poorly articulated aims; absence of guiding content theories for scalable implementation; weak implementation strategies; inadequate mechanisms for measurement, evaluation, and learning; and insufficiently structured approaches to communication and dissemination. These gaps limit learning, impact, replication, sustainability and scalability. To address these gaps, the Institute for Healthcare Improvement (IHI) developed the Core Components Guide, a practical framework for designing, implementing, and evaluating QI initiatives. Grounded in Deming's System of Profound Knowledge and the Model for Improvement, the guide includes six interrelated components: System Understanding, Improvement Aim, Measurement, Evaluation and Learning, Content Theory, Execution Theory, and Dissemination and Communication. Together, these components provide a structured approach to align interventions with context, clarify program theory, and embed iterative learning cycles. This manuscript introduces the Core Components, illustrates their application through a case study, and shares lessons learned from operationalizing the guide across diverse settings. By integrating improvement and implementation science principles, the Core Components Guide strengthens design, promotes fidelity, and increases the potential for impact, replication, scale, and sustainability of QI initiatives. This Guide offers actionable strategies for QI leaders and policymakers to build stronger foundations for improvement, evaluation, and dissemination.
BACKGROUND:Improvement science has supported the methodological foundations for the application of quality improvement (QI) in healthcare. However, concerns persist regarding the rigour of QI evaluation. Theories, Models and Frameworks (TMFs) from implementation science support the uptake of evidence-based practices but their use to guide the evaluation of QI initiatives remains insufficiently characterised. OBJECTIVES:To identify which implementation science TMFs have been used to evaluate QI initiatives in healthcare, assess how these TMFs were applied in the evaluation, and compare the TMFs' intrinsic methodological attributes. METHODS:We conducted a scoping review following Arksey and O'Malley's framework. Eligible studies were published between 2010 and 2025 and evaluated a QI initiative using at least one TMF. Peer-reviewed literature was searched in PubMed, Scopus and Web of Science. Grey literature was retrieved through targeted Google searches. TMFs were evaluated at the article level according to their application in each study and at the TMF level according to their intrinsic methodological attributes. RESULTS:Out of 1824 records screened, 80 studies were included. 23 unique TMFs were identified. Of these, the most frequently used were the Reach, Effectiveness, Adoption, Implementation and Maintenance framework (27%) and the Consolidated Framework for Implementation Research (20%). Although 94% of studies used TMFs to guide data collection or analysis, only 43% explicitly tested construct relationships or causal pathways. TMFs demonstrated high conceptual clarity and structure but limited equity and sociocultural responsiveness. CONCLUSIONS:Application of TMFs in the evaluation of QI initiatives was heterogeneous. No single TMF captured the full range of evaluative functions. More rigorous evaluation requires an integrative approach that combines complementary TMFs to examine context, mechanisms of improvement and outcomes. Prospective operationalisation of TMF constructs, particularly equity, within study design and evaluation is essential to strengthen reproducibility and improve the transferability of findings across settings.
Introduction: Many pregnancy-related deaths can be avoided if health care workers reliably provide prompt, evidence-based care during the final stages of pregnancy and delivery. We report the impact on the institutional maternal mortality ratio (iMMR) of a quality improvement (QI) initiative that focused on establishing timely and reliable obstetric care in public Brazilian hospitals for the primary causes of maternal deaths.Methods: The QI initiative used a quasi-experimental time-series design implemented in 19 Brazilian maternity hospitals comparing 3 periods: baseline (January 2018 to November 2019), implementation (December 2019 to March 2021), and post-implementation (April 2021 to September 2021). We used a sequential approach, referred to as the "4Rs" (Recognize, Rescue, Reassess, and Refer), with the Modified Early Obstetric Warning Score (MEOWS) as a key tool, to identify clinical deterioration and implement care bundles directed at the management of 3 principal life-threatening conditions around the time of birth: postpartum hemorrhage, sepsis, and hypertensive disorders of pregnancy (HDPs). Clinical staff received tailored training and support within a structured learning system that brought multiple teams together to rapidly test and implement evidence-based changes.Results: Comparing the baseline with the implementation period, run charts detected an overall reduction of 34.2% in all causes of maternal deaths (from 83.7 to 55 deaths per 100,000 live births). Additionally, the iMMR due to the 3 analyzed life-threatening conditions decreased by 60.9% between baseline and the combined implementation and post-implementation periods (from 44.1 to 17.2 deaths per 100,000 live births); postpartum hemorrhage-related deaths were reduced by 72.9% (from 11.7 to 3.17 deaths per 100,000 live births) and sepsis-related deaths were reduced by 100% (from 20.4 to 0 deaths per 100,000 liv births). No changes by HDP-related deaths were observed. There was a 178% increase in iMMR by all causes (mainly attributed to COVID-19) during the post-implementation period, but deaths related to life-threatening conditions either remained stable or decreased even further.Conclusion: Optimization of the steps in a care sequence and reliable implementation of care bundles directed at the principal life-threatening conditions around the time of birth, using QI, tailored training, and the MEOWS tool, seem to be feasible and promising approaches for reducing iMMR.
