When Safety Event Reporting Is Seen as Punitive: "I've Been PSN-ed!"

STUDY OBJECTIVE: Reporting systems are designed to identify patient care issues so changes can be made to improve safety. However, a culture of blame discourages event reporting, and reporting seen as punitive can inhibit individual and system performance in patient safety. This study aimed to determine the frequency and factors related to punitive patient safety event report submissions, referred to as Patient Safety Net reports, or PSNs. METHODS: Three subject matter experts reviewed 513 PSNs submitted between January and June 2019. If the PSN was perceived as blaming an individual, it was coded as punitive. The experts had high agreement (κ=0.84 to 0.92), and identified relationships between PSN characteristics and punitive reporting were described. RESULTS: A total of 25% of PSNs were punitive, 7% were unclear, and 68% were designated nonpunitive. Punitive (vs nonpunitive) PSNs more likely focused on communication (41% vs 13%), employee behavior (38% vs 2%), and patient assessment issues (17% vs 4%). Nonpunitive (vs punitive) PSNs were more likely for equipment (19% vs 4%) and patient or family behavior issues (8% vs 2%). Punitive (vs nonpunitive) PSNs were more common with adverse reactions or complications (21% vs 10%), communication failures (25% vs 16%), and noncategorized events (19% vs 8%), and nonpunitive (vs punitive) PSNs were more frequent in falls (5% vs 0%) and radiology or laboratory events (17% vs 7%). CONCLUSION: Punitive reports have important implications for reporting systems because they may reflect a culture of blame and a failure to recognize system influences on behaviors. Nonpunitive wording better identifies factors contributing to safety concerns. Reporting systems should focus on patient outcomes and learning from systems issues, not blaming individuals.

Patient safety incidents in radiology: frequency and distribution of incident types.

BACKGROUND: Patient safety incidents may be a valuable source of information to learn from and to prevent future errors. PURPOSE: To determine the distribution of patient safety incident types in radiology according to the International Classification for Patient Safety (ICPS), and to comprehensively review those incidents that were either harmful or serious in terms of risk of patient harm and reoccurrence. MATERIAL AND METHODS: The most recent five-year database (2014-2019) of a radiology incident reporting system was evaluated. RESULTS: A total of 480 patient safety incidents were included. Top three ICPS incident types were clinical administration (119/480, 24.8%), resources/organizational management (112/480, 23.3%), and clinical process/procedure (91/480, 19.0%). Harm severities were none in 457 (95.2%) cases, mild in 14 (2.9%), moderate in 4 (0.8%), severe in 3 (0.6%), and unknown in one case. Subsequent Prevention Recovery Information System for Monitoring and Analysis (PRISMA) reviews were performed in 4 (0.8%) cases. The three patient safety incidents that caused severe harm (of which one underwent PRISMA review) involved resources/organizational management (n = 1), clinical process/procedure (n = 1), and medication/IV fluids (n = 1). Three other cases (with no harm in two cases and moderate harm in one case) that underwent PRISMA review involved resources/organizational management (n = 2) and medical device/equipment/property (n = 1). CONCLUSION: Radiology-related patient safety incidents predominantly occur in three ICPS domains (clinical administration, resources/organizational management, and clinical process/procedure). Harmful/serious incidents are relatively rare. The standardly and transparently reported findings from this study may be used for healthcare quality improvement, benchmarking purposes, and as a primer for future studies.

Problems with incident reporting: Reports lead rarely to recommendations.

AIM AND OBJECTIVE: To analyse trends in incident reporting over the last 5 years and determine how many reports led to recommendations? BACKGROUND: Patient safety incident reporting systems have been used in health care for years. However, they have a significant weakness in that reports often do not lead to any visible action. DESIGN: The study is a retrospective register study. STROBE checklist was applied in the preparation of the paper. METHODS: Data were collected from a web-based incident reporting database (HaiPro) for a social- and healthcare organisation in Finland, covering the period from 2011-2015. RESULTS: In total, 16,019 incident reports were analysed. In 2.7% (n = 426) of all reports, there was written recommendation to develop action that such incidents would not happen again. Those reports were classified into seven categories: education, introduction and information, introduction to work, patient care, guidelines, instruments and IT programmes, and the physical environment. CONCLUSIONS: Managers get major amount incident reports. There should be (a) a definition what kind of events should be reported, (b) a definition for how serious events managers have to make a recommendation and (c) control that recommendations are implemented. RELEVANCE TO CLINICAL PRACTICE: There is a need for more action to promote patient safety based on incident reports.

Cardiac surgery errors: results from the UK National Reporting and Learning System.

OBJECTIVE: To describe cardiac surgery-related incidents and compare the types and severity of incidents occurring in the operating room (OR) versus non-OR locations. We hypothesized that the type and severity of incidents in cardiac surgery would differ in the OR compared with non-OR locations. DESIGN: A retrospective cross-sectional study of all incidents categorized as cardiac surgery in the UK National Reporting and Learning System database between January 2003 and February 2007. Differences in proportions were evaluated by χ(2) or Fischer's exact test. The odds ratio of an event occurring in the OR compared with all non-OR settings was calculated using logistic regression. The harm susceptibility ratio ranked locations by the degree of harm. SETTING: All trusts performing cardiac surgery. PARTICIPANTS: None. INTERVENTION: None. MAIN OUTCOME MEASURES: Cardiac surgery incidents occurring in the OR versus non-OR. RESULTS: A total of 4828 (<1%) incidents from 55 trusts were designated as involving cardiac surgery patients during the study period; 21% occurred in the OR. Overall, 32% of incidents resulted in harm: 23% of OR and 34% of non-OR incidents. The distribution of incident type and harmful incidents differed in the OR compared with the non-OR setting (P < 0.05). CONCLUSIONS: Our findings offer unique insights into the types of incidents occurring during cardiac surgical care in the UK. In the OR, interventions should focus on reducing errors associated with medical devices/equipment, whereas outside the OR, they may focus on medication errors and patient accidents.

Risk management.

Every plan contains risk. To proceed without planning some means of managing that risk is to court failure. The basic logic of risk is explained. It consists in identifying a threshold where some corrective action is necessary, the probability of exceeding that threshold, and the attendant cost should the undesired outcome occur. This is the probable cost of failure. Various risk categories in dentistry are identified, including lack of liquidity; poor quality; equipment or procedure failures; employee slips; competitive environments; new regulations; unreliable suppliers, partners, and patients; and threats to one's reputation. It is prudent to make investments in risk management to the extent that the cost of managing the risk is less than the probable loss due to risk failure and when risk management strategies can be matched to type of risk. Four risk management strategies are discussed: insurance, reducing the probability of failure, reducing the costs of failure, and learning. A risk management accounting of the financial meltdown of October 2008 is provided.

Anatomy of Mine Rescue Teams' Casualty Incidents: A Basis for Medical Emergency Preparedness and Injury Prevention.

OBJECTIVE: Mine rescue teams bear a high risk of injury. To improve medical emergency preparedness and injury prevention, this work analyzed the causes and severity of mine rescue teams' casualty incidents, the primary injuries, and the link between the causes and the occurrences of the casualty incidents. METHODS: A total of 81 cases from 1953 to 2013 were used to analyze the casualty incidents of mine rescue teams based on the frequency of accidents. A panel with 4 rescue experts was set up to ensure the accuracy of the analysis. RESULTS: The 81 casualty incidents occurred in 7 types of rescue work and were due to 6 causes. Organizational and personal factors were the leading cause, followed by rescue skill and equipment factors. Problems with decision-making and command have gradually become the primary inducement of casualty incidents in recent years, with an average death toll reaching up to 6 to 7 people. The main injuries causing death to team members were blast injury, burns, poisoning, suffocation, blunt trauma, and overwork injury. Some of the injured died because of medical emergency response failure. CONCLUSION: The construction of emergency medical teams and the preparedness of disaster medicine need to be improved to reduce the mortality of the injured team members. Actions according to the causes of casualty incidents should be adopted for injury prevention. (Disaster Med Public Health Preparedness. 2019;13:695-699).

Profile of blood donors who presented adverse reactions to the donation.

OBJECTIVE: identify the adverse reactions presented by blood donors and outline their sociodemographic profile. METHOD: a quantitative, cross-sectional retrospective study of 780 records of blood donors from a public hemocenter in the southern region of Brazil, from December 2015 to January 2016. For the analysis the descriptive statistics was used. RESULTS: it was identified that throughout 12 months, the total blood donors corresponded to 27,300 people, in which 780 developed at least one reaction. They were characterized by female and recurrent donors, single, with a complete average level of education, ranging from 16 to 30 years, who triggered between 1 and 3 reactions. Mild reactions were more frequent, followed by moderate and severe reactions. CONCLUSION: There is a high rate of adverse reactions from donors emphasizing the need for changes in hemotherapy care practices.

A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis.

CONTEXT: Adverse events in healthcare are often collated in incident reports which contain unstructured free text. Learning from these events may improve patient safety. Natural language processing (NLP) uses computational techniques to interrogate free text, reducing the human workload associated with its analysis. There is growing interest in applying NLP to patient safety, but the evidence in the field has not been summarised and evaluated to date. OBJECTIVE: To perform a systematic literature review and narrative synthesis to describe and evaluate NLP methods for classification of incident reports and adverse events in healthcare. METHODS: Data sources included Medline, Embase, The Cochrane Library, CINAHL, MIDIRS, ISI Web of Science, SciELO, Google Scholar, PROSPERO, hand searching of key articles, and OpenGrey. Data items were manually abstracted to a standardised extraction form. RESULTS: From 428 articles screened for eligibility, 35 met the inclusion criteria of using NLP to perform a classification task on incident reports, or with the aim of detecting adverse events. The majority of studies used free text from incident reporting systems or electronic health records. Models were typically designed to classify by type of incident, type of medication error, or harm severity. A broad range of NLP techniques are demonstrated to perform these classification tasks with favourable performance outcomes. There are methodological challenges in how these results can be interpreted in a broader context. CONCLUSION: NLP can generate meaningful information from unstructured data in the specific domain of the classification of incident reports and adverse events. Understanding what or why incidents are occurring is important in adverse event analysis. If NLP enables these insights to be drawn from larger datasets it may improve the learning from adverse events in healthcare.

Interobserver Reliability of Spinal Adverse Events Severity System - Neuro (SAVES-N): A Prospective Adverse Event Reporting System for Neurosurgical Cases.

BACKGROUND: The reporting of adverse events (AEs) in neurosurgery uses inconsistent definitions and subjective grading systems. A standardized system for recording and describing AEs would allow valid comparisons to be drawn between different institutions, using different technologies, at different times. The Spinal Adverse Events Severity System - Neuro (SAVES-N) system is a modification of the well-validated SAVES-V2 system that encompasses complications from both cranial and spinal surgery. The objective of this study was to assess the interobserver reliability of SAVES-N in spinal and cranial neurosurgery. METHODS: Ten vignettes, including cranial and spinal neurosurgical cases, were assessed by groups of consultant neurosurgeons (n = 5) and neurosurgical registrars (n = 5) using the SAVES-N system. Interobserver reliability for the presence of AEs, the type of AE, and the SAVES severity grade of the AE were calculated using Gwet's AC2 and Fleiss' kappa and were interpreted using the thresholds described by Landis and Koch. RESULTS: Neurosurgeons had almost-perfect agreement (Gwet AC2 = 0.93), whereas registrars had substantial agreement (Gwet's AC2 = 0.74) in determining the presence or absence of AEs. Both neurosurgeons (Fleiss' kappa = 0.78) and registrars (Fleiss' kappa = 0.70) demonstrated substantial agreement within their groups as to the type of AE. Similarly, neurosurgeons (Gwet's AC2 = 0.94) and registrars (Gwet's AC2 = 0.81) both graded the severity of the AE with almost perfect agreement. CONCLUSIONS: The results of this study demonstrate that the scope of the well-validated SAVES-V2 system may be broadened to cranial neurosurgical cases by SAVES-N with substantial to almost-perfect interobserver reliability.

Application of HACCP for development of quality risk management in a water purification system

Abstract The present work reports the implementation of the Hazard Analysis Critical Control Point (HACCP) methodology to analyze the water purification system of a pharmaceutical site, in order to assure the system quality and prevent failures. As a matter of fact, the use of HACCP for development and implementation of Quality Risk Management (QRM) is not usual in pharmaceutical plants and it is applied here to improve the performance of the water purification system of a polymerization pilot plant used to manufacture pharmaceutical grade polymer microparticles. Critical Control Points (CCP) were determined with the aid of a decision tree and questions were made to characterize whether identified hazards constitute actual CCPs and should be monitored. When deviations were detected, corrective actions were performed and action plans were used for following-up and implementation of corrective actions. Finally, microbiological and physicochemical parameters were analyzed and the obtained results were regarded as appropriate. Therefore, it is shown that HACCP constitutes an effective tool for identification of hazards, establishment of corrective actions and monitoring of the critical control points that impact the process and the quality of the final pharmaceutical product most significantly.

Standardizing the classification of abortion incidents: the Procedural Abortion Incident Reporting and Surveillance (PAIRS) Framework.

OBJECTIVES: To develop and validate standardized criteria for assessing abortion-related incidents (adverse events, morbidities, near misses) for first-trimester aspiration abortion procedures and to demonstrate the utility of a standardized framework [the Procedural Abortion Incident Reporting & Surveillance (PAIRS) Framework] for estimating serious abortion-related adverse events. STUDY DESIGN: As part of a California-based study of early aspiration abortion provision conducted between 2007 and 2013, we developed and validated a standardized framework for defining and monitoring first-trimester (≤14weeks) aspiration abortion morbidity and adverse events using multiple methods: a literature review, framework criteria testing with empirical data, repeated expert reviews and data-based revisions to the framework. RESULTS: The final framework distinguishes incidents resulting from procedural abortion care (adverse events) from morbidity related to pregnancy, the abortion process and other nonabortion related conditions. It further classifies incidents by diagnosis (confirmatory data, etiology, risk factors), management (treatment type and location), timing (immediate or delayed), seriousness (minor or major) and outcome. Empirical validation of the framework using data from 19,673 women receiving aspiration abortions revealed almost an equal proportion of total adverse events (n=205, 1.04%) and total abortion- or pregnancy-related morbidity (n=194, 0.99%). The majority of adverse events were due to retained products of conception (0.37%), failed attempted abortion (0.15%) and postabortion infection (0.17%). Serious or major adverse events were rare (n=11, 0.06%). CONCLUSIONS: Distinguishing morbidity diagnoses from adverse events using a standardized, empirically tested framework confirms the very low frequency of serious adverse events related to clinic-based abortion care. IMPLICATIONS: The PAIRS Framework provides a useful set of tools to systematically classify and monitor abortion-related incidents for first-trimester aspiration abortion procedures. Standardization will assist healthcare providers, researchers and policymakers to anticipate morbidity and prevent abortion adverse events, improve care metrics and enhance abortion quality.

Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy.

PURPOSE: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. METHODS AND MATERIALS: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. RESULTS: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. CONCLUSIONS: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

Automated Classification of Clinical Incident Types.

We consider the task of automatic classification of clinical incident reports using machine learning methods. Our data consists of 5448 clinical incident reports collected from the Incident Information Management System used by 7 hospitals in the state of New South Wales in Australia. We evaluate the performance of four classification algorithms: decision tree, naïve Bayes, multinomial naïve Bayes and support vector machine. We initially consider 13 classes (incident types) that were then reduced to 12, and show that it is possible to build accurate classifiers. The most accurate classifier was the multinomial naïve Bayes achieving accuracy of 80.44% and AUC of 0.91. We also investigate the effect of class labelling by an ordinary clinician and an expert, and show that when the data is labelled by an expert the classification performance of all classifiers improves. We found that again the best classifier was multinomial naïve Bayes achieving accuracy of 81.32% and AUC of 0.97. Our results show that some classes in the Incident Information Management System such as Primary Care are not distinct and their removal can improve performance; some other classes such as Aggression Victim are easier to classify than others such as Behavior and Human Performance. In summary, we show that the classification performance can be improved by expert class labelling of the training data, removing classes that are not well defined and selecting appropriate machine learning classifiers.

Classifying laboratory incident reports to identify problems that jeopardize patient safety.

We developed a laboratory incident report classification system that can guide reduction of actual and potential adverse events. The system was applied retrospectively to 129 incident reports occurring during a 16-month period. Incidents were classified by type of adverse event (actual or potential), specific and potential patient impact, nature of laboratory involvement, testing phase, and preventability. Of 129 incidents, 95% were potential adverse events. The most common specific impact was delay in receiving test results (85%). The average potential impact was 2.9 (SD, 1.0; median, 3; scale, 1-5). The laboratory alone was responsible for 60% of the incidents; 21% were due solely to problems outside the laboratory's authority. The laboratory function most frequently implicated in incidents was specimen processing (31%). The preanalytic testing phase was involved in 71% of incidents, the analytic in 18%, and the postanalytic in 11%. The most common preanalytic problem was specimen transportation (16%). The average preventability score was 4.0 (range, 1-5; median, 4; scale, 1-5), and 94 incidents (73%) were preventable (score, 3 or more). Of the 94 preventable incidents, 30% involved cognitive errors, defined as incorrect choices caused by insufficient knowledge, and 73% involved noncognitive errors, defined as inadvertent or unconscious lapses in expected automatic behavior.

The Medical Event Reporting System for Transfusion Medicine: will it help get the right blood to the right patient?

The Medical Event Reporting System for Transfusion Medicine (MERS-TM) collects, classifies, and analyzes events that potentially could compromise the safety of transfused blood to facilitate system improvement. This system is designed to collect data on near misses as well as actual events. Near-miss events are a valuable source of data because they occur more frequently than, but share many characteristics and causes of, actual events. Further, although most current reporting efforts describe only what has occurred with little attention to what caused the event, MERS-TM includes a standardized method of causal analysis. The standardization provided by MERS allows users to compare their experience with that of other organizations, which speeds learning across the entire transfusion medicine community. Important features of the MERS-TM system are that it is able to capture threats, hazards, near misses, injuries, and deaths; characterizes failures and recoveries systematically; identifies and provides causal codes for the entire range of system defects including technical, organizational, cultural, and human factors; raises staff awareness about error management; is easily integrated with existing quality assurance programs; has a consistent and straightforward classification method; enables compliance with mandatory Food and Drug Administration reporting and accreditation requirements; has features to deal with a high volume of reports; supplies Web-based training, data entry, and analysis; and provides comparative benchmarks from comparable institutions.

Adverse events in primary care identified from a risk-management database.

BACKGROUND: The inevitability of adverse events in medicine arises from human fallibility, negligent care, limits of medical knowledge, risks inherent in medical practice, and biological variability among individuals. A better understanding of the nature and causes of adverse events is necessary to reduce their occurrence and limit their harm. This study describes adverse events identified from a risk-management database that occurred in an out-patient primary care setting. METHODS: Incident reports filed with the risk-management office of an academic medical center between January 1, 1991, and June 30, 1996, by eight primary health care clinics affiliated with the center were eligible for the study. Two independent reviewers assessed the incidents to determine whether there were adverse medical events. Incidents classified as adverse events were analyzed to determine the cause, potential preventability, and outcome. RESULTS: The prevalence of adverse events was 3.7 per 100,000 clinic visits over a period of 5 1/2 years. Twenty-nine of 35 (83%) adverse events were due to medical errors and were considered preventable. The causes of the adverse events included 9 diagnostic errors (26%), 11 treatment errors (31%), and 9 other errors (26%). Of the adverse events attributed to medical errors, 4 (14%) resulted in a permanent, disabling injury and 1 (3%) resulted in a death. CONCLUSIONS: Serious adverse events appear to occur infrequently in primary care outpatient practice, although these data probably underestimate the overall prevalence. To reduce or prevent the occurrence of adverse events in primary care, better systems for recognizing and tracking them and for assessing their causes are needed.

Analyzing planned maintenance (PM) inspection data by failure mode and effect analysis methodology.

There is no question that medical devices are becoming more reliable. However, we have had some difficulty finding a satisfactory method for providing persuasive documentary evidence that this improved reliability will allow us to relax our traditional planned maintenance (PM) practices without compromising patient safety. The acceptance and increasing use of Failure Mode and Effect Analysis (FMEA) by several of the oversight agencies, including the Joint Commission on Accreditation of Healthcare Organizations, provides us with an important opportunity to take another shot at this vexing problem. Using this proven FMEA methodology and some relatively simple rules to quantify the results of the routine PM inspections that all healthcare providers are still performing in considerable abundance, we have developed a method that allows us to reduce the test results to a simple, single measure (the Risk Score) that can be used to characterize the effectiveness and levels of safety of our current PM regimens. When tested on theoretical data and a sample of real PM inspection results, the method provides answers that seem reasonable. Although it will probably require some modification as we begin the standardized data gathering and gain working experience, it is our hope that this new approach will become generally accepted within the industry. This kind of positive response should enable us to persuade the various accrediting and licensing agencies to similarly accept the concept.

[Considerations about health risk management]. / Riflessioni sul risk management in sanità.

From the birth of doctrines of Risk Management to today a lot of time is passed. From the initial application in the field of the insurances and the management of the enterprises, theories inspired to the identification, evaluation and correction of connected risks to the activity and the industrial trial has been figurative to the health, field in which the application of these principles results to be how much never profit and productive of benefits above all for the patients that suffer consequences of errors but also for the physicians and the personnel that, perfectly inserted in an organization aware of the trials to put into effect, can bring their contribution to underline the weak points of the relief trial. The economic cost and consequences of errors can decrease if a new culture is established inspired to the learning and the communication of the adverse events, to minimize the possibility that they again occurs.

Why.

There are two kinds of cause and effect. The scientific notion that is taught as part of the formal model is rigorous, but often limited in its generalizability across situations. The study of cause and effect in natural settings is also a rigorous field, with several useful and easily applied techniques. Root cause analysis is a set of approaches to identifying the factors in natural settings that initiate a chain of events with outcomes of interest. It is easier to improve processes when their true root causes have been identified. Risk management is a special case of root cause analysis.