Improving patient safety reporting with the common formats: Common data representation for Patient Safety Organizations

Nursing leadership style and error management culture: a scoping review

PURPOSE

This paper aims to assess the influence of nursing leadership style on error management culture (EMC).

DESIGN/METHODOLOGY/APPROACH

This scoping review was conducted following the integrative review methodology of the Joanna Briggs Institute (JBI) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PubMed, CINAHL, Scopus, Web of Science, Embase and EBSCO databases were systematically searched to identify studies on nursing leadership, error management and measurement, and error management culture. The studies' methodological quality was then assessed using the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies.

FINDINGS

Thirteen manuscripts were included for review. The analysis confirmed that nursing leadership plays an important role in EMC and nurses' intention to report errors. Three emerging themes were identified: 1) leadership and EMC; 2) leadership and the intention to report errors; and 3) leadership and error rate.

RESEARCH LIMITATIONS/IMPLICATIONS

A major limitation of the studies is that errors are often analyzed in a transversal way and associated with patient safety, and not as a single concept.

PRACTICAL IMPLICATIONS

Healthcare managers should promote training dedicated to head nurses and their leadership style, for creating a good work environment in which nurses feel free and empowered to report errors, learn from them and prevent their reoccurrence in the future.

ORIGINALITY/VALUE

There is a positive relationship between nursing leadership and error management in terms of reduced errors and increased benefits. Positive nursing leadership leads to improvements in the caring quality.

Implementation of a health information technology safety classification system in the Veterans Health Administration's Informatics Patient Safety Office

OBJECTIVE

Implement the 5-type health information technology (HIT) patient safety concern classification system for HIT patient safety issues reported to the Veterans Health Administration's Informatics Patient Safety Office.

MATERIALS AND METHODS

A team of informatics safety analysts retrospectively classified 1 year of HIT patient safety issues by type of HIT patient safety concern using consensus discussions. The processes established during retrospective classification were then applied to incoming HIT safety issues moving forward.

RESULTS

Of 140 issues retrospectively reviewed, 124 met the classification criteria. The majority were HIT failures (eg, software defects) (33.1%) or configuration and implementation problems (29.8%). Unmet user needs and external system interactions accounted for 20.2% and 10.5%, respectively. Absence of HIT safety features accounted for 2.4% of issues, and 4% did not have enough information to classify.

CONCLUSION

The 5-type HIT safety concern classification framework generated actionable categories helping organizations effectively respond to HIT patient safety risks.

Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review

BACKGROUND

Healthcare systems represent complex organizations within which multiple factors (physical environment, human factor, technological devices, quality of care) interconnect to form a dense network whose imbalance is potentially able to compromise patient safety. In this scenario, the need for hospitals to expand reactive and proactive clinical risk management programs is easily understood, and artificial intelligence fits well in this context. This systematic review aims to investigate the state of the art regarding the impact of AI on clinical risk management processes. To simplify the analysis of the review outcomes and to motivate future standardized comparisons with any subsequent studies, the findings of the present review will be grouped according to the possibility of applying AI in the prevention of the different incident type groups as defined by the ICPS.

MATERIALS AND METHODS

On 3 November 2023, a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was carried out using the SCOPUS and Medline (via PubMed) databases. A total of 297 articles were identified. After the selection process, 36 articles were included in the present systematic review.

RESULTS AND DISCUSSION

The studies included in this review allowed for the identification of three main "incident type" domains: clinical process, healthcare-associated infection, and medication. Another relevant application of AI in clinical risk management concerns the topic of incident reporting.

CONCLUSIONS

This review highlighted that AI can be applied transversely in various clinical contexts to enhance patient safety and facilitate the identification of errors. It appears to be a promising tool to improve clinical risk management, although its use requires human supervision and cannot completely replace human skills. To facilitate the analysis of the present review outcome and to enable comparison with future systematic reviews, it was deemed useful to refer to a pre-existing taxonomy for the identification of adverse events. However, the results of the present study highlighted the usefulness of AI not only for risk prevention in clinical practice, but also in improving the use of an essential risk identification tool, which is incident reporting. For this reason, the taxonomy of the areas of application of AI to clinical risk processes should include an additional class relating to risk identification and analysis tools. For this purpose, it was considered convenient to use ICPS classification.

Deviations From Best Practice: Findings From a Certified Patient Safety Organization Remote-Verification Observational Study of Intravenous Compounding of Chemotherapeutic and Ancillary Drugs

Background: Chemotherapeutic and immunomodulatory medications can pose a serious risk to patient and healthcare provider safety because of complex processes, cytotoxicity, and prevalent medication use. Objective: To evaluate chemotherapeutic and ancillary medication compounding in hospital pharmacies using a remote verification system, focusing on pharmaceutical deviations from best practice, compounding time, medication waste, and cost. Methods: This retrospective, blinded observational study used a remote intravenous (IV) workflow verification system to examine IV chemotherapeutic compounding errors in large hospital systems. A Patient Safety Organization securely obtained >5000 compounding records and photos from the IV workflow system. Blinded pharmacists evaluated IV chemotherapy preparations using picture slide viewers to assess any deviations from best practice. Time variables, medication waste, STAT vs non-STAT orders, and cost were also evaluated. Results: The most frequently reported deviations from best practice included medications exceeding the >10% additive volume guideline (35.9%) and inaccurate dose labels (28.3%). Time flow analyses demonstrated a substantial increase in total compounding time per vial for 1 vs 2 vials. Most medications in this analysis had an average waste ranging from 0-.36 vials. STAT orders, accounting for 38.4% of all orders, wasted more medication than non-STAT orders. Gemcitabine cost analyses showed an association for number of vials and compounding time with overall cost per dose. Conclusion: Substantial inconsistencies between workflow stations were observed-highlighting the lack of standardization across chemotherapeutics, volume of medication waste during preparation, and the need to establish improved quality controls to safeguard patient and health care provider safety.

Medication adverse events in the ambulatory setting: A mixed-methods analysis

DISCLAIMER

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PURPOSE

To characterize ambulatory care adverse drug events reported to the Collaborative Healthcare Patient Safety Organization (CHPSO), a network of 400 hospitals across the United States, and identify addressable contributing factors.

METHODS

We abstracted deidentified ambulatory care CHPSO reports compiled from May 2012 to October 2018 that included medication-related adverse events to identify implicated medications and contributing factors. We dual-coded 20% of the sample. We quantitatively calculated co-occurring frequent item sets of contributing factors and then applied a qualitative thematic analysis of co-occurring sets of contributing factors for each drug class using an inductive analytic approach to develop formal themes.

RESULTS

Of 1,244 events in the sample, 208 were medication related. The most commonly implicated medication classes were anticoagulants (n = 97, or 46% of events), antibiotics (n = 24, 11%), hypoglycemics (n = 19, 9%), and opioids (n = 17, 8%). For anticoagulants, timely follow-up on supratherapeutic international normalized ratio (INR) values often occurred before the development of symptoms. Incident reports citing antibiotics often described prescribing errors and failure to review clinical contraindications. Reports citing hypoglycemic drugs often described low blood sugar events due to a lack of patient education or communication. Reports citing opioids often described drug-drug interactions, commonly involving benzodiazepines.

CONCLUSION

Ambulatory care prescribing clinicians and community pharmacists have the potential to mitigate harm related to anticoagulants, antibiotics, hypoglycemics, and opioids. Recommendations include increased follow-up for subtherapeutic INRs, improved medical record integration and chart review for antibiotic prescriptions, enhanced patient education regarding hypoglycemics, and alerts to dissuade coprescription of opioids and benzodiazepines.

Reporting Incidents in the Psychiatric Intensive Care Unit: A Retrospective Study in an Italian University Hospital

ABSTRACT

To evaluate the characteristics of the reported workplace violence in a psychiatric intensive care unit (PICU) by analyzing an electronic hospital incident reporting system (IRS). One hundred thirty reports were retrieved from January 2017 to June 2020, referring to assaults committed by patients (71% males) with an average age of 29.8 years (SD, 14.9). The most frequent psychiatric diagnosis was a neurodevelopmental disorder (33%). Physical aggression (84%) was more frequent than the other types of aggression. Nurses and unlicensed assistive personnel were the most frequent victims (65%). Aggressions were more frequent on Friday (18%) and between 4 p.m. and 8 p.m. (35%). A total of 64.9% of the incidents happened in the first 5 days of hospitalization. A significant association between physical aggression and diagnosis of neurodevelopmental disorder emerged. IRS could be helpful to identify high-risk patient groups and develop clinical strategies to reduce adverse events in clinical practice.

An International Perspective on Definitions and Terminology Used to Describe Serious Reportable Patient Safety Incidents: A Systematic Review

OBJECTIVES

Patients are unintentionally, yet frequently, harmed in situations that are deemed preventable. Incident reporting systems help prevent harm, yet there is considerable variability in how patient safety incidents are reported. This may lead to inconsistent or unnecessary patterns of incident reporting and failures to identify serious patient safety incidents. This systematic review aims to describe international approaches in relation to defining serious reportable patient safety incidents.

METHODS

Multiple electronic and gray literature databases were searched for articles published between 2009 and 2019. Empirical studies, reviews, national reports, and policies were included. A narrative synthesis was conducted because of study heterogeneity.

RESULTS

A total of 50 articles were included. There was wide variation in the terminology used to represent serious reportable patient safety incidents. Several countries defined a specific subset of incidents, which are considered sufficiently serious, yet preventable if appropriate safety measures are taken. Terms such as "never events," "serious reportable events," or "always review and report" were used. The following dimensions were identified to define a serious reportable patient safety incident: (1) incidents being largely preventable; (2) having the potential for significant learning; (3) causing serious harm or have the potential to cause serious harm; (4) being identifiable, measurable, and feasible for inclusion in an incident reporting system; and (5) running the risk of recurrence.

CONCLUSIONS

Variations in terminology and reporting systems between countries might contribute to missed opportunities for learning. International standardized definitions and blame-free reporting systems would enable comparison and international learning to enhance patient safety.

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward

ABSTRACT

Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of the ever-increasing volume of PSE reports, including the free-text narratives. As a result, there is a growing emphasis on applying text mining and natural language processing (NLP) approaches to assist in the processing and understanding of these narratives. Although text mining and NLP in healthcare have advanced significantly over the past decades, the utility of the resulting models, ontologies, and algorithms to analyze PSE narratives are limited given the unique difference and challenges in content and language between PSE narratives and clinical documentation. To promote the application of text mining and NLP for PSE narratives, these unique challenges must be addressed. Improving data access, developing NLP resources to practically use contributing factor taxonomies, and developing and adopting shared specifications for interoperability will help create an infrastructure and environment that unlocks the collaborative potential between patient safety, research, and machine learning communities, in the development of reproducible and generalizable methods and models to better understand and improve patient safety and patient care.

Barriers to Incident Reporting among Nurses: A Qualitative Systematic Review

Incident reporting in health care prevents error recurrence, ultimately improving patient safety. A qualitative systematic review was conducted, aiming to identify barriers to incident reporting among nurses. Joanna Briggs Institute methodology for qualitative systematic reviews was followed, with data extracted using JBI QARI tools, and selected studies assessed for methodological quality using Critical Appraisal Skills Program (CASP). A meta-aggregation synthesis was carried out, and confidence in findings was assessed using GRADE ConQual. A total of 921 records were identified, but only five studies were included. The overall methodological quality of these studies was good and GRADE ConQual assessment score was "moderate." Fear of negative consequences was the most cited barrier to nursing incident reporting. Barriers also included inadequate incident reporting systems and lack of interdisciplinary and interdepartmental cooperation. Lack of nurses' necessary training made it more difficult to understand the importance of incident reporting and the definition of error. Lack of effective feedback and motivation and a pervasive blame culture were also identified.

Ethical predictability of patient safety in Iranian hospitals

BACKGROUND

Receiving safe health care services is among the first rights of patients. Ethical predictability is influential to identify the patient safety concerns in hospitals.

OBJECTIVE

This study aimed to ascertain and compare ethical predictability of patient safety in selected hospitals in Mazandaran Province in Iran.

METHODS

A cross-sectional design was applied in the current study. By applying the multistage method for sampling, the statistical population consisted of clinical units of selected public, social security, and private hospitals. Out of the 18 public hospitals, five teaching hospitals, nine private and five social security hospitals, one hospital was randomly selected in Mazandaran Province from each cluster. In total, 938 patients participated in the study. Data entry and analysis was carried out by SPSS version 22 software.

RESULTS

The results showed that ethical predictability in social security hospitals was higher than the results in private and public hospitals (p < 0.001). In addition, among the selected dimensions of ethical predictability of patient safety in the selected hospitals, blood management was the highest dimension. Safe drug management, error management, infection control, and safe clinical services were the middle priorities and management and leadership of patient safety had the lowest mean in the ethical predictability of patient safety in the selected hospitals in the province.

CONCLUSION

Identifying the factors causing ethical predictability in order to improve patient safety and service quality, is of great help to managers and authorities in the field of health services. Such awareness helps managers to consider these factors in all decision making processes.

Sustainable Health Informatics: Health Informaticians as Alchemists

The digital transformation of health care delivery remains an elusive work in progress. Contextual variation continues to be a significant barrier to the development of sustainable health information systems. In this paper we characterize health informaticians as modern alchemists and use this characterization to describe informatics progress in addressing four key healthcare challenges. We highlight the need for informaticians to be diligent and loyal to basic methodological principles while also appreciating the role that contextual variation plays in informatics research. We also emphasize that meaningful health systems transformation takes time. The insight presented in this paper helps informaticians in our quest to develop sustainable health information systems.

[Quality of care analyses using ICD 11 : Detailed capture of treatment events]

The identification of treatment errors, the so-called "undesirable" or "critical incidents", is crucial for improving and developing the quality of care. The new International Statistical Classification of Diseases and Related Health Problems-ICD-11-supports a structured data collection in the context of the quality of care and patient safety. Documentation conceptually relies on the multiple coding of the three dimensions of a critical incident: harm, cause, and mode. In this way, it is possible to capture the event in great detail, including the reasons for it and the effects it has. An evaluation of this concept in a field trial using 45 clinical case studies showed good concordance in coding across the documented participants.As the ICD-11 permits the detailed capture of near misses and their context, it could be used for structured documentation in incident reporting systems (databanks for the anonymous reporting of treatment errors). In this way, the error reports can be gathered in a more systematic way, so that they can be used for better quality improvement.In quality assessment, it is important to consider the time of diagnosis. Thus, the feature present on admission (POA) is a diagnosis qualifier that is of substantial importance for quality assessment and is widely used internationally. Up to now, it has not been permanently available in Germany. ICD-11 includes the relevant code.

Lessons learned from introducing huddle boards to involve nursing staff in targeted observation and reporting of medication effect in a nursing home

Background

Medication administration and management in nursing homes can occur during all phases of the medication process. The aim of this study was to investigate if an introduction of a systematic use of huddle board led to an increased amount of documentation in the patient record of observations of effects and side effects following a change in medication.

Methods

A three-layer intervention approach combining huddle boards, educating the entire staff in medication observation and documentation, and frequent feedback to the staff about the outcome was applied. A standard was set for the expected reporting. Correlation between expected and actual reporting as an average was calculated and the staff received weekly updates on their observation–reporting results.

Results

The huddle board became a hub in providing an overview of the expectations of observations. To visualize the impact of the intervention, use of a run chart gave comprehensive information about the extent to which the expected goal of documentation was reached. Four different organizational steps and one individual action in the last step were taken to improve the observation–reporting. The identifying of the nonreporting nurses and individual staff guidance to these nurses resulted in a significant improvement in observation–reporting. The expected goal of 100% average reporting was achieved 6 months after all wards were included in the improvement project.

Conclusion

The combination of huddle boards, educating the entire staff in observation and documentation, and frequent feedback to the staff about the outcome proved to be a useful approach in medication safety work in nursing homes.

The Psychiatry Morbidity and Mortality Incident Reporting Tool Increases Psychiatrist Participation in Reporting Adverse Events

OBJECTIVES

Although the reporting of adverse events (AEs) is widely thought to be a key first step to improving patient safety in hospital systems, underreporting remains a common problem, particularly among physicians. We aimed to increase the number of safety reports filed by psychiatrists in our hospital system.

METHODS

We piloted an online survey for psychiatry-specific AE reporting, the Psychiatry Morbidity and Mortality Incident Reporting Tool (PMIRT) for a 1-year period. An e-mail prompt containing a link to the survey was sent on a weekly basis to all psychiatry department clinical staff. The primary outcome was the total number of events reported by psychiatrists through PMIRT; secondary outcomes were the total number of AEs and the number of serious harm events filed by psychiatrists in our hospital's formal event reporting system before and after implementation of the new protocol.

RESULTS

Psychiatrists filed 65 reports in PMIRT during the study period. The average number of AEs reported by psychiatrists in the hospital's formal event reporting system significantly increased after the intervention (P = 0.0251), and the average number of serious harm events reported by psychiatrists increased nonsignificantly (P = 0.1394).

CONCLUSIONS

The combination of an increase in awareness of event reporting with a psychiatry-specific AE reporting tool resulted in a significant improvement in the number of reports by psychiatrists.

Turning Data Into Information: Opportunities to Advance Rehabilitation Quality, Research, and Policy

Attention to health care quality and safety has increased dramatically. The internal focus of an organization is not without influence from external policy and research findings. Compared with other specialties, efforts to align and advance rehabilitation research, practice, and policy using electronic health record data are in the early stages. This special communication defines quality, applies the dimensions of quality to rehabilitation, and illustrates the feasibility and utility of electronic health record data for research on rehabilitation care quality and outcomes. Using data generated at the point of care provides the greatest opportunity for improving the quality of health care, producing generalizable evidence to inform policy and practice, and ultimately benefiting the health of the populations served.