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More than two decades ago, the Agency for Healthcare Research and Quality developed its Patient Safety Indicators (PSIs) to monitor potentially preventable and severe adverse events within hospitals. Application of PSIs outside the US was explored more than a decade ago, but it is uncertain whether they remain relevant within Europe, as no up-to-date assessments of overall PSI-associated adverse event rates or interhospital variability can be found in the literature. This article assesses the nationwide occurrence and variability of thirteen adverse events for a case study of Belgium. We studied 4,765,850 patient stays across all 101 hospitals for 2016-18. We established that although adverse event rates were generally low, with an adverse event observed in 0.1 percent of medical hospital stays and in 1.2 percent of surgical hospital stays, they were higher than equivalent US rates and were prone to considerable between-hospital variability. Failure-to-rescue rates, for example, equaled 23 percent, whereas some hospitals exceeded nationwide central line-associated bloodstream infection rates by a factor of 8. Policy makers and hospital managers can prioritize PSIs that have high adverse event rates or large variability, such as failure to rescue or central line-associated bloodstream infections, to improve the quality of care in Belgian hospitals.

Objectives: To assess their construct validity, we compared results from 2 models used for estimating hospital standardized mortality ratios (HSMRs) in Belgium. The method of the Flemish Hospital Network (FHN) is based on a logistic regression for each of the 64 All Patient Refined Diagnosis-Related Groups that explain 80% of mortality and uses the Elixhauser score to correct for comorbidities. (H)SMRs published on the 3M-Benchmark-Portal are calculated by a simpler indirect standardization for All Patient Refined Diagnosis-Related Groups and risk of mortality (ROM) at discharge., Methods: We used administrative data from all eligible hospital admissions in 22 Flemish hospitals between 2016 and 2019 (FHN, n = 682,935; 3M, n = 2,122,305). We evaluated model discrimination and accuracy and assessed agreement in estimated HSMRs between methods., Results: The Spearman correlation between HSMRs generated by the FHN model and the standard 3M model was 0.79. Although 2 of 22 hospitals showed opposite classification results, that is, an HSMR significantly <1 according to the FHN method but significantly >1 according to the 3M model, classification agreement between methods was significant (agreement for 59.1% of hospitals, κ = 0.45). The 3M model ( c statistic = 0.96, adjusted Brier score = 26%) outperformed the FHN model (0.87, 17%). However, using ROM at admission instead of at discharge in the 3M model significantly reduced model performance ( c statistic = 0.94, adjusted Brier score = 21%), but yielded similar HSMR estimates and eliminated part of the discrepancy with FHN results., Conclusions: Results of both models agreed relatively well, supporting convergent validity. Whereas the FHN method only adjusts for disease severity at admission, the ROM indicator of the 3M model includes diagnoses not present on admission. Although diagnosis codes generated by complications during hospitalization have the tendency to increase the predictive performance of a model, these should not be included in risk adjustment procedures., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Hospital accreditation is a popular and widely used quality control and improvement instrument. Despite potential benefits, ques-tions are raised whether it constitutes appropriate use of hospitals' limited financial resources., Objective: This study aims to calculate the cost of preparing for and undergoing a first and second accreditation by the Joint Commission International or Qualicor Europe in acute-care hospitals., Method: All (n = 53) acute-care hospitals in Flanders (Belgium) were invited to participate and report on the costs in preparing for and undergoing a first and/or second accreditation cycle. To measure costs, a questionnaire with six domains and 90 questions was developed based on literature review, policy documents and a multidisciplinary expert group. All costs were recalculated to 2020 euro to correct for inflation and reported as medians with interquartile range., Results: A total of 25 hospitals (47%) participated in the study. Additional investments and direct operational costs for a first accreditation cycle amounted to 879.45 euro (interquartile range: 794.81) per bed and 3.8 full-time equivalent (FTE) per hospital additional new staff members were recruited for coordination and implementation of the trajectory. A second accreditation survey costed remarkably less with a total cost of extra investments and direct operational cost of 222.88 euro (interquartile range: 244.04) per bed and less investment in additional staff (1.50 FTE). Most of the costs were situated in consulting costs and investments in infrastructure. The median total extra cost (direct operational cost and additional investments) amounted to 0.2% of the hospital's operating income for a first accreditation cycle and 0.05% for a second cycle., Conclusion: A first accreditation cycle requires a strong financial commitment of hospitals, as many costs result from the preparation in the years prior to an accreditation survey. A second survey is less expensive for hospitals, but still requires a considerable effort in terms of budget and staff. Policy makers should be aware of these significant costs as hospitals are operating with public resources and budget is scarce. The identification of these costs is a necessary building block to evaluate cost-effectiveness of accreditation versus other quality improvement systems and the continuation of these accreditation systems and their costs needs further study and a thorough debate., (© The Author(s) 2022. Published by Oxford University Press on behalf of International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Hospitals demonstrated increased efforts into quality improvement over the past years. Their growing commitment to quality combined with a heterogeneity in perceptions among healthcare stakeholders cause concerns on the sustainable incorporation of quality into the daily workflow. Questions are raised on the drivers for a sustainable hospital quality policy. We aimed to identify drivers and incorporate them into a new, unique roadmap towards sustainable quality of care in hospitals., Design: A multi-method design guided by an eight-phase approach to develop a conceptual framework consists of multiple, iterative phases of data collection, synthesis and validation. Starting with a narrative review followed by a qualitative in-depth analysis and including feedback of national and international healthcare stakeholders., Setting: Hospitals., Results: The narrative review included 59 relevant papers focusing on quality improvement and the sustainability of these improved quality results. By integrating, synthesising and resynthesizing concepts during thematic and content analysis, the narrative review evolved to an integrated, co-creation roadmap. The Flanders Quality Model (FlaQuM) is presented as a driver diagram that features six primary drivers for a sustainable quality policy: (1) Quality Design and Planning, (2) Quality Control, (3) Quality Improvement, (4) Quality Leadership, (5) Quality Culture and (6) Quality Context. Six primary drivers are described in 19 building blocks (secondary drivers) and 104 evidence-based action fields., Conclusions: The framework suggests that a manageable number of drivers, building blocks and action fields may support the sustainable incorporation of quality into the daily workflow. Therefore, FlaQuM can serve as a useful roadmap for future sustainable quality policies in hospitals and for future empirical and theoretical work in sustainable quality management., Competing Interests: The authors have declared that no competing interests exist.

Background: Collaboration between policymakers, patients and healthcare workers in hospital quality of care policy setting can improve the integration of new initiatives. The aim of this study was to quantify preferences for various characteristics of a future quality policy in a broad group of stakeholders., Materials and Methods: 450 policymakers, clinicians, nurses, patient representatives and hospital board members in Flanders (Belgium) participated in five discrete choice experiments (DCE) on quality control, quality improvement, inspection, patient incidents and transparency. For each DCE, various attributes and levels were defined from a literature review and interviews with 12 international quality and patient safety experts., Results: For the attributes with the highest relative importance, participants exhibited a strong preference for quality control by an independent national organization and coordination of quality improvement initiatives at the level of hospital networks. The individual hospital was chosen over the government for setting up an action plan following patient complaints. Respondents also strongly preferred mandatory reporting of severe patient incidents and transparency by publicly reporting quality indicators at the hospital level., Conclusions: A future quality model should focus on a multicomponent approach with external quality control, improvement actions on hospital network level and public transparency. DCEs provide an opportunity to incorporate the attitudes and views for individual components of a new policy recommendation., Competing Interests: Declarations of Interest None., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Since 2009, hospital quality policy in Flanders, Belgium, is built around a quality-of-care triad, which encompasses accreditation, public reporting (PR) and inspection. Policy makers are currently reflecting on the added value of this triad.Methods: We performed a narrative review of the literature published between 2009 and 2020 to examine the evidence base of the impact accreditation, PR and inspection, both individually and combined, has on patient processes and outcomes. The following patient outcomes were examined: mortality, length of stay, readmissions, patient satisfaction, adverse outcomes, failure to rescue, adherence to process measures and risk aversion. The impact of accreditation, PR and inspection on these outcomes was evaluated as either positive, neutral (i.e. no impact observed or mixed results reported) or negative.Objectives: To assess the current evidence base on the impact of accreditation, PR and inspection on patient processes and outcomes.Results: We identified 69 studies, of which 40 were on accreditation, 24 on PR, three on inspection and two on accreditation and PR concomitantly. Identified studies reported primarily low-level evidence (level IV, n = 53) and were heterogeneous in terms of implemented programmes and patient populations (often narrow in PR research). Overall, a neutral categorization was determined in 30 articles for accreditation, 23 for PR and four for inspection. Ten of these recounted mixed results. For accreditation, a high number (n = 12) of positive research on adherence to process measures was discovered.Conclusion: The individual impact of accreditation, PR and inspection, the core of Flemish hospital quality, was found to be limited on patient outcomes. Future studies should investigate the combined effect of multiple quality improvement strategies. [ABSTRACT FROM AUTHOR]