Journal of Patient Safety最新文献

Objectives: Limited evidence exists about differences in patient safety culture by employee role. We examine the relationship between role and patient safety culture.

Methods: Using 2021 to 2022 Hospital Survey on Patient Safety Culture (HSOPS) cross-sectional data (245,252 HSOPS respondents, 371 hospitals), we fit separate employee/respondent-level OLS regression models for 10 aspects of patient safety culture and 2 summary measures as a function of the employee's role, controlling for year, employee and hospital characteristics with hospital-level clustered standard errors (SEs) weighted to represent the nation.

Results: C-suite/executive/senior leaders reported the highest proportions of positive ratings for overall patient safety and all 10 aspects of patient safety culture. Managers/supervisors were most likely and unit staff (assistants/secretaries/clerks) were least likely to report safety events. Physicians reported the lowest proportion of positive overall patient safety ratings and ratings for communication and improvement. Care aides reported the lowest for teamwork, staffing/work pace, and response-to-error, nurses lowest for hospital management support and pharmacists lowest for handoffs and information exchange.

Conclusions: C-suite/executives/senior leaders, supervisors and managers have different perspectives of patient safety culture than physicians, care aides, nurses, and staff, revealing the need to improve patient safety culture for those who provide direct patient care and to improve communication across leaders and all employee roles. Hospitals should focus on improving communication and management support related to patient safety for physicians and on teamwork, staffing and work pace for care aides. Understanding the root of variability in how pharmacists assist and support patient handoffs and information exchange and how physicians, care aides and staff communicate, accept managerial input, and learn from errors are critical as they may affect safety and event reporting. Hospital leaders could also hold discussions at the microclimate level (unit) for those doing well and those not doing to discuss focusing on the culture of patient safety performance. Ensuring that communication is open and transparent across all hospital employees is critical to providing safe, effective patient care.

Objectives: To address the challenge of analyzing large volumes of patient safety event (PSE) reports, we developed and evaluated an AI-powered software tool. The primary goal was to assess the tool's potential to support analysts and uncover novel trends in patient safety databases.

Methods: A pilot evaluation was conducted with seven organizations (4 health care facilities and 3 patient safety organizations) to assess the tool's impact on analysts' workflows and their ability to uncover insights. Feedback was gathered through interviews with patient safety analysts using the tool. Two human factors experts analyzed the findings using a human cognition framework for information visualization to identify strengths and areas for improvement. Novel insights from PSE data were systematically recorded, capturing trends and themes that emerged during the analysis process.

Results: Participants from 6 of 7 institutions reported that the tool helped identify valuable insights, such as trends in procedural errors, inconsistencies in event categorization, and emerging issues with specific medications and devices. The emerging themes algorithm effectively highlighted previously undetected patterns by grouping related events and emphasizing novel keywords. However, participants noted some irrelevant keywords due to limitations in narrative data quality. The tool's design principles, including chunking information and highlighting key terms, improved efficiency in reviewing reports.

Conclusions: The AI-driven tool demonstrated potential to enhance patient safety by supporting analysts in detecting trends and patterns in PSE reports. Future iterations will address identified limitations and further refine its ability to organize data around user mental models for improved usability.

Background: Artificial intelligence (AI) technologies hold great promise for improving patient outcomes, reducing clinician workload, and enhancing patient engagement. However, improper design, implementation, and monitoring can introduce significant safety risks. Health care quality and safety leaders play a critical role in mitigating these risks. As AI adoption accelerates, understanding how these leaders perceive their institutions' progress in assessing and managing AI safety is critical for identifying gaps, addressing potential risks, and guiding safer clinical integration.

Methods: Semi-structured interviews were conducted with 22 quality and safety leaders from 19 US health care organizations between March and April 2024. Participants included leaders from both single hospitals and multi-hospital systems, with an average of 16 years of experience. None had formal AI training, but some reported practical exposure. Interviews focused on participants' knowledge of AI, organizational structures for AI governance, and barriers to safe AI implementation. Thematic analysis was used to identify common themes and knowledge gaps.

Results: Most organizations (78.9%) reported using steering committees for AI oversight, with some combining this with IT, research, or innovation teams. Barriers to AI implementation included interoperability challenges (78.9%), lack of AI expertise (68.4%), and difficulty evaluating AI effectiveness (52.6%). Participants highlighted the need for stronger governance and evidence-based tools but noted variability in their organizations' preparedness to adopt AI.

Discussion: Health care organizations lack standardized approaches to AI safety and often rely on fragmented governance structures. Leaders emphasized the need for enhanced expertise, solutions to barriers that affect implementation, and alignment of AI tools with organizational priorities.

Conclusions: Strengthening organizational knowledge, governance, and solution generation to barriers of implementation is essential to safely integrate AI into clinical care. Addressing these gaps will support patient safety and optimize AI's potential benefits.

Introduction: The operating room (OR) is a complex environment where errors significantly impact patient outcomes, and the ability of surgical teams to adapt and recover from unexpected disruptions-defined as resilience-is paramount. Frameworks offer structured approaches for analyzing resilience yet are variably applied throughout the relevant literature. This review aims to characterize how frameworks are used to study OR team resilience and examines the implications of inconsistent approaches.

Methods: After the Arksey & O'Malley framework, EMBASE, CINAHL, and MEDLINE were searched for studies published up to July 29, 2024. The search included keywords such as 'surgery' and 'resilience'. The included studies' reference lists were also manually searched. Studies focusing on the OR, examining the influence of human factors on team function and recovery, and reporting metrics for patient safety were included. Data extraction and content analysis were conducted independently by 2 reviewers, with results summarized narratively.

Results: Of 3165 studies identified, 9 met the inclusion criteria. Two utilized the systems engineering initiative for patient safety framework, and 2 incorporated the Oxford non-technical skills tool, whereas the remaining 5 developed an ad hoc approach to study operating team resilience. Notably, only 2 studies classified themselves as part of the resilience literature.

Conclusions: This review demonstrates inconsistent framework application in surgical resilience research, resulting in methodological variability and limited cross-study synthesis. Developing frameworks specific to the OR is essential for advancing this field and improving study classification. Expanding search strategies to include resilience-adjacent terms will further enhance research visibility.

To identify scientific evidence describing the development and/or use of mobile applications to support the education of health personnel, patients, and their caregivers, focusing on hospitalized patient safety. The review was conducted on 7 electronic databases: Medline, PubMed, Cochrane, Embase, Scopus, VHL, and Web of Science, in addition to gray literature. The study was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. The final findings were presented regarding authorship, year of publication, country of origin, study objective, methodological design, sample and setting, mobile application development process, and main findings. Of the 1996 studies found, after removing duplicates, 1784 abstracts were evaluated. After evaluating the full texts, 12 studies were considered relevant, and discussed essential aspects of patient safety, such as drug administration and infection prevention, following the international patient safety goals. The analyzed mobile applications covered different types of content, such as serious games, educational videos, animations, and simulations. The analysis revealed a variety of approaches, including analysis, design, development, implementation, and evaluation of the apps. Content validity and the usability of mobile applications were the main aspects investigated. There has been a growing development and use of mobile applications aimed at increasing knowledge about patient safety, showing a positive trend for educating the target audience. However, there is a lack of mobile applications that display attractive features for users.

Background: This study analyzes factors and challenges associated with adverse events reporting in Indonesian hospitals.

Methods: The mixed-method study design was used. The quantitative stage is analyzing data from the 2019 Health Facilities Research. The population in this stage is all hospitals in Indonesia, with a sample of 532 hospitals. Data were analyzed using the χ2 test and logistic regression. The qualitative stage, semi-structured interviews were conducted with participants from 6 hospitals in 2 provinces. The data were validated using the triangulation method and analyzed using thematic analysis. Data were collected from September 2023 to April 2024.

Results: The existence of the infection control committee, quality committee, patient safety committee, internal audits, services evaluation and quality control, accreditation status, regional category, and number of beds has been positively associated with adverse events reporting in Indonesian hospitals. The implementation of accreditation standards, the roles of these committees, and evaluation and audit activities contribute to improving quality and patient safety, encouraging incident reporting, which ultimately can reduce adverse events. Challenges to reporting come from both individual and organizational aspects.

Conclusions: These committees should be the main drivers in monitoring AE reporting and implementing evaluation and quality control. Enhancing the role of hospital accreditation through government support as a regulator is also necessary to improve reporting. The main challenge to reporting is the lack of willingness to report. Policymakers and hospital managers must urge to overcome these obstacles by developing an easy-to-use reporting system, eliminating negative perceptions after reporting, and providing appreciation.

Objective: The Austrian Inpatient Quality Indicators (A-IQI) are routinely measured quality and patient safety indicators derived from administrative data. A subset of these are sentinel indicators, for which even a single case of death leads to a conspicuous indicator. The purpose of this study was to assess the value of A-IQI sentinel indicators for detecting serious adverse events.

Methods: We retrospectively reviewed all inpatient treatment cases with abnormal sentinel indicators at a large university hospital in Austria from 2013 to 2022 using structured chart reviews with the Institute for Healthcare Improvement Global Trigger Tool. The detected adverse events were classified according to their severity, preventability, and causal relationship with the outcome. Positive predictive values were calculated for the individual sentinel indicators and for all indicators combined.

Results: A total of 189 adverse events in 107 cases (1 to 6 per case; mean: 1.77; SD: 1.4) were identified. 51.9% caused temporary impairment, 3.7% caused permanent harm, 5.3% required life-sustaining interventions, and 36% contributed to the patient´s death. 63.5% of the adverse events detected were assessed as potentially preventable. The positive predictive value of all sentinel indicators combined was 78.5% (95% CI: 70.7%-86.3%) for at least one adverse event and 55.1% (95% CI: 45.7%-64.6%) for an adverse event contributing to the patient's death.

Conclusions: Our preliminary results suggest that sentinel indicators might be useful for detecting serious and preventable adverse events. Further studies with larger case numbers are required to determine the actual value of these indicators for clinical risk management.

Background: Diagnostic errors are one of the most common and costly medical errors. Most diagnostic errors are due to provider cognitive processes and biases. With the widespread adoption of electronic health records (EHRs), and other health information technology (health IT), EHRs are now the central repository for clinical information and its design and use affect the diagnostic process and diagnostic errors. The goal of this study was to analyze patient safety event reports to determine health IT contributions to diagnostic errors. Understanding how the health IT contributes to diagnostic error will help direct improvement efforts.

Methods: From a data set consisting of 1,110,029 reports entered between 2015 and 2021, from 195 unique health care organizations across the United States, 2618 likely diagnostic error reports were retrieved. A sample of these reports were reviewed and those that were diagnostic related were coded by subject matter experts for whether the diagnostic error was preventable, the stage of the diagnostic process in which the error occurred, the type of error, how much health IT contributed to the error, what health IT system was responsible for the error, whether health IT was directly or indirectly responsible for the error, the type of health IT issue, whether copy and paste was mentioned and contributed to the error, whether the health IT contribution was preventable, the outcome of the error, and the severity of the error.

Results: There were 2618 reports with a general event type category that suggested a diagnostic error. Of these, 119 reports explicitly mentioned health IT and were found to have strong or moderate evidence of health IT contributing to the error. From the remaining 2499 reports, 250 were randomly sampled and 93 (37.2% of 250) had strong or moderate evidence of a health IT contribution. Further analysis of these 212 reports showed EHRs were the most commonly described type of health IT associated with diagnostic errors (58.5%) and most diagnostic errors occurred in the test phase of the diagnostic process (74.5%). Most reports that had health IT as a contributor to the diagnostic error were associated with patient harm (74.5%). There was a trend towards a higher degree of harm when the errors were health IT-related compared with when there was little evidence of health IT contribution.

Conclusions: Health IT, and specifically the EHR, is a contributor to diagnostic errors. To address these issues, improved reporting taxonomies and improvements in health IT system design are needed.

Objectives: Patient falls are an important public health issue, preventable by nurses through risk assessment and education. Here, we conduct a pilot study aimed at improving fall prevention knowledge and attitudes, and decreasing patient falls through use of a spaced-retrieval mobile app.

Methods: We collected baseline patient fall rates and Fall TIPS (Tailoring Interventions for Patient Safety) poster completion rates in 64 patient rooms and baseline self-report ratings of self-efficacy and attitudes (including self-efficacy for preventing patient falls, perceived safety climate and performance, perceived support, and job dedication) from nursing staff participants. Fifteen participants then used a spaced-retrieval app for 6 weeks (2-3 min/workday) to retrain fall prevention knowledge. After this, we again collected Fall TIPS poster completion rates, self-reported ratings, and patient fall rates.

Results: Knowledge of fall prevention strategies, self-efficacy, perceived safety performance, perceived support, and Fall TIPS poster completion rates improved significantly from pre-to-post app use. We found no differences in the other attitudinal measures or patient falls.

Conclusions: These findings suggest that engaging in spaced review of fall prevention protocols may yield short-term improvements in fall prevention knowledge, self-efficacy, and Fall TIPS poster completion rates while requiring minimal time.