Journal of Patient Safety最新文献

Objectives: For over 30 years, quality improvement (QI) methods have been used as a means of increasing the quality and safety of healthcare services, but with mixed success. One explanation highlighted in the literature for this outcome is the overemphasis on technical elements of change, and a failure to fully appreciate the human side of change. Behavioral insights (BI) is an approach that utilizes knowledge and tools from a broad range of scientific disciplines, such as neuroscience and behavioral psychology, to support behavior change. The aim of this paper is to explore the possibility of supplementing QI methods with tools and understanding from BI.

Methods: We outline a practical case that involved applying aspects BI methods into a QI program aimed at reducing the use of intravenous antibiotics in patients accessing services at a busy university hospital in Copenhagen, Denmark. We exemplify how to use BI tools to guide the analysis of staff behaviors during standard clinical processes and develop targeted interventions aimed at increasing actions and behaviors more aligned to best clinical practice.

Results: Outcomes suggest that it is possible to combine the models and methods from BI and QI in a way that is helpful in focusing attention on the human side of change when developing strategies for change. Potential psychological barriers identified from the analysis included the following: 'default inertia,' 'decision complexity,' 'risk aversion,' and biases related to confidence, confirmation, and omission.

Conclusions: Future quality improvement projects could benefit from integrating models and tools from BI to guide and support behavior change.

Objective: This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes.

Methods: Studies using MAUDE data were sourced from PubMed by searching for "MAUDE" or "Manufacturer and User Facility Device Experience" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow.

Results: As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107).

Conclusions: Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.

Objective: The objective of this work was to establish sustainable systems for quality improvement in an Academic Medical Center and Safety Net Hospital.

Method: High reliability principles of leadership engagement, a culture of safety, and sustainable performance improvement were used. Target areas for improvement were clinical outcomes for patients, public reputation scores, and lower cost of care. The system was based on annual focused goals with specific targets, improvement teams, transparent scorecards, and data driven work. Program visibility was championed by leaders. Consistent education on quality, safety, efficiency, and effectiveness for all employees created buy-in. Data review and accountability tracked progress, helped resource allocation, and defined next steps.

Results: In the first 5 years, all patient quality and safety metrics improved between 10% and 60%. This improvement resulted in higher CMS Star Ranking and Leapfrog patient safety grade. The next phase included maximizing value by expanding into hospital operations and finance with a focus on improved clinical documentation and reduced length of stay and cost of care. Clinical documentation improvement led to a 15% increase in comorbidity capture. This positively impacted reported outcomes and hospital payment by appropriate risk adjustment. Length of stay was addressed with a new care coordination program and physician-driven utilization review.

Conclusions: High reliability principles are applicable in a resource limited healthcare system. Improved clinical and operational results were achieved through goal setting, improvement teams, and data driven projects leading to creation of an office of operational excellence.

Background: To improve patient safety, it is important that healthcare facilities learn from critical incidents. Tools such as reporting and learning systems and team meetings structure error management and promote learning from incidents. To enhance error management in ambulatory care practices, it is important to promote a climate of safety and ensure personnel share views on safety policies and procedures. In contrast to the hospital sector, little research has been dedicated to developing feasible approaches to supporting error management and safety climate in ambulatory care. In this study, we developed, implemented, and evaluated a multicomponent intervention to address how error management and safety climate can be improved in ambulatory care practices.

Methods: In a prospective 1-group pretest-posttest implementation study, we sought to encourage teams in German ambulatory practices to use proven methods such as guidelines, workshops, e-learning, (online) meetings, and e-mail newsletters. A pretest-posttest questionnaire was used to evaluate level and strength of safety climate and psychological behavioral determinants for systematic error management. Using 3 short surveys, we also assessed the state of error management in the participating practices. In semistructured interviews, we asked participants for their views on our intervention measures.

Results: Overall, 184 ambulatory care practices nationwide agreed to participate. Level of safety climate and safety climate strength (rwg) improved significantly. Of psychological behavioral determinants, significant improvements could be seen in "action/coping planning" and "action control." Seventy-six percent of practices implemented a new reporting and learning system or modified their existing system. The exchange of information between practices also increased over time. Interviews showed that the introductory workshop and provided materials such as report forms or instructions for team meetings were regarded as helpful.

Conclusions: A significant improvement in safety climate level and strength, as well as participants' knowledge of how to analyze critical incidents, derive preventive measures and develop concrete plans suggest that it is important to train practice teams, to provide practical tips and tools, and to facilitate the exchange of information between practices. Future randomized and controlled intervention trials should confirm the effectiveness of our multicomponent intervention.Trial registration: Retrospectively registered on 18. November 2019 in German Clinical Trials Register No. DRKS00019053.

Background: Patient admissions at a U.S. tertiary care hospital occur via the emergency department (ED), or transfer center. We aim to compare the clinical outcomes of patients admitted from the ED to admissions coordinated by the transfer center.

Methods: Admissions to Mayo Clinic Hospital, Rochester, MN, between July 2019 to June 2021 were identified in this retrospective study and categorized into two cohorts-transfer center and ED. The two cohorts were then matched for age, sex, admitting service, and Charlson Comorbidity Index. Univariate and multivariate analyses were performed to compare hospital length of stay (LOS), mortality, 30-day mortality, and 30-day readmissions between the two cohorts.

Results: 73,685 admissions were identified, of which 24,262 (33%) were transfer center admissions. In the matched cohorts (n = 19,093, each), in-hospital mortality (2.4% versus 1.9%), 30-day mortality (5.4% versus 3.9%), 30-day readmission (12.7% versus 7.2%), and LOS (6.4 days versus 5.1 days) were significantly higher ( P < 0.001) among the admissions coordinated by transfer center. A higher palliative care consultation rate (9.4% versus 6.2%, P < 0.001), and a lower proportion of home discharges home (76.2% versus 82.5%, P < 0.001) among transfer center admissions was observed. Similar findings were noted in multivariate analysis, even when adjusting for LOS.

Conclusions: Transfer center admissions had higher in-hospital mortality, LOS, 30-day mortality, and 30-day readmission compared to ED admissions. This study also highlights new considerations for palliative care consultation before transfer acceptance, especially to avoid futile transfers. Additional studies analyzing factors behind the outcomes of transfer center admissions are required.

Objectives: Pharmacists constitute a crucial component of the healthcare system, significantly influencing the provision of medication services and ensuring patient safety. This study aims to understand the characteristics and risk factors for complaints against pharmacists through Health and Disability Commissioner (HDC) published decisions.

Methods: This study adopts a retrospective, qualitative approach. An inductive content analysis technique was used to analyze 37 complaints against pharmacists published decisions from the New Zealand Health and Disability Commissioner website to investigate a range of underlying risk factors contributing to the occurrence of complaints against pharmacists.

Results: A set of 20 categories of risk factors emerged through the content analysis and were subsequently grouped into five overarching themes: pharmacist individual factors, organizational factors, system factors, medication-specific factors, and external environmental factors.

Conclusions: The findings of this study provide valuable insights that expand the understanding of risk management in pharmacist practice, serving as a valuable resource for regulatory bodies, policymakers, educators, and practitioners. It is recommended not only to focus solely on individual pharmacists but also to consider integrating their environment and individual behaviors to proactively address situations prone to errors and subsequent complaints.

Objectives: Accidental falls are among the leading hospitals' adverse events, with incidence ranging from 2 to 20 events per 1.000 days/patients. The objective of this study is to assess the relationship between in-hospital falls and the score of 3 DEPendence and Clinical-Social Fragility indexes.

Methods: A monocentric case-control study was conducted by retrieving data of in-hospital patients from the electronic health records.

Results: Significant differences between the mean scores at the hospital admission and discharge were found. The BRASS scale mean (SD) values at the admission and at the discharge were also significantly higher in cases of in-hospital falls: at the admission 10.2 (±7.7) in cases versus 7.0 (±8.0) in controls ( P = 0.003); at the discharge 10.0 (±6.4) versus 6.7 (±7.5) ( P = 0.001). Barthel index mean (SD) scores also presented statistically significant differences: at the admission 60.3 (±40.6) in cases versus 76.0 (±34.8) in controls ( P = 0.003); at discharge 51.3 (±34.9) versus 73.3 (±35.2) ( P = 0.000).Odds ratios were as follows: for Barthel index 2.37 (95% CI, 1.28-4.39; P = 0.003); for Index of Caring Complexity 1.45 (95% CI, 0.72-2.91, P = 0. 255); for BRASS index 1.95 (95% CI, 1.03-3.70, P = 0.026). With BRASS index, the area under the curve was 0.667 (95% CI, 0.595-0.740), thus indicating a moderate predictive power of the scale.

Conclusions: The use of only Conley scale-despite its sensitivity and specificity-is not enough to fully address this need because of the multiple and heterogeneous factors that predispose to in-hospital falls. Therefore, the combination of multiple tools should be recommended.