Incidence, nature and causes of avoidable significant harm in primary care in England: retrospective case note review.

OBJECTIVE: To estimate the incidence of avoidable significant harm in primary care in England; describe and classify the associated patient safety incidents and generate suggestions to mitigate risks of ameliorable factors contributing to the incidents. DESIGN: Retrospective case note review. Patients with significant health problems were identified and clinical judgements were made on avoidability and severity of harm. Factors contributing to avoidable harm were identified and recorded. SETTING: Primary care. PARTICIPANTS: Thirteen general practitioners (GPs) undertook a retrospective case note review of a sample of 14 407 primary care patients registered with 12 randomly selected general practices from three regions in England (total list size: 92 255 patients). MAIN OUTCOME MEASURES: The incidence of significant harm considered at least 'probably avoidable' and the nature of the safety incidents. RESULTS: The rate of significant harm considered at least probably avoidable was 35.6 (95% CI 23.3 to 48.0) per 100 000 patient-years (57.9, 95% CI 42.2 to 73.7, per 100 000 based on a sensitivity analysis). Overall, 74 cases of avoidable harm were detected, involving 72 patients. Three types of incident accounted for more than 90% of the problems: problems with diagnosis accounted for 45/74 (60.8%) primary incidents, followed by medication-related problems (n=19, 25.7%) and delayed referrals (n=8, 10.8%). In 59 (79.7%) cases, the significant harm could have been identified sooner (n=48) or prevented (n=11) if the GP had taken actions aligned with evidence-based guidelines. CONCLUSION: There is likely to be a substantial burden of avoidable significant harm attributable to primary care in England with diagnostic error accounting for most harms. Based on the contributory factors we found, improvements could be made through more effective implementation of existing information technology, enhanced team coordination and communication, and greater personal and informational continuity of care.

Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches.

Learning from patient safety incident reports is a vital part of improving healthcare. However, the volume of reports and their largely free-text nature poses a major analytic challenge. The objective of this study was to test the capability of autonomous classifying of free text within patient safety incident reports to determine incident type and the severity of harm outcome. Primary care patient safety incident reports (n=31333) previously expert-categorised by clinicians (training data) were processed using J48, SVM and Naïve Bayes.The SVM classifier was the highest scoring classifier for incident type (AUROC, 0.891) and severity of harm (AUROC, 0.708). Incident reports containing deaths were most easily classified, correctly identifying 72.82% of reports. In conclusion, supervised ML can be used to classify patient safety incident report categories. The severity classifier, whilst not accurate enough to replace manual processing, could provide a valuable screening tool for this critical aspect of patient safety.

Understanding the epidemiology of avoidable significant harm in primary care: protocol for a retrospective cross-sectional study.

INTRODUCTION: Most patient safety research has focused on specialist-care settings where there is an appreciation of the frequency and causes of medical errors, and the resulting burden of adverse events. There have, however, been few large-scale robust studies that have investigated the extent and severity of avoidable harm in primary care. To address this, we will conduct a 12-month retrospective cross-sectional study involving case note review of primary care patients. METHODS AND ANALYSIS: We will conduct electronic searches of general practice (GP) clinical computer systems to identify patients with avoidable significant harm. Up to 16 general practices from 3 areas of England (East Midlands, London and the North West) will be recruited based on practice size, to obtain a sample of around 100 000 patients. Our investigations will include an 'enhanced sample' of patients with the highest risk of avoidable significant harm. We will estimate the incidence of avoidable significant harm and express this as 'per 100 000 patients per year'. Univariate and multivariate analysis will be conducted to identify the factors associated with avoidable significant harm. ETHICS/DISSEMINATION: The decision regarding participation by general practices in the study is entirely voluntary; the consent to participate may be withdrawn at any time. We will not seek individual patient consent for the retrospective case note review, but if patients respond to publicity about the project and say they do not wish their records to be included, we will follow these instructions. We will produce a report for the Department of Health's Policy Research Programme and several high-quality peer-reviewed publications in scientific journals. The study has been granted a favourable opinion by the East Midlands Nottingham 2 Research Ethics Committee (reference 15/EM/0411) and Confidentiality Advisory Group approval for access to medical records without consent under section 251 of the NHS Act 2006 (reference 15/CAG/0182).

A cross-sectional mixed methods study protocol to generate learning from patient safety incidents reported from general practice.

INTRODUCTION: Incident reports contain descriptions of errors and harms that occurred during clinical care delivery. Few observational studies have characterised incidents from general practice, and none of these have been from the England and Wales National Reporting and Learning System. This study aims to describe incidents reported from a general practice care setting. METHODS AND ANALYSIS: A general practice patient safety incident classification will be developed to characterise patient safety incidents. A weighted-random sample of 12,500 incidents describing no harm, low harm and moderate harm of patients, and all incidents describing severe harm and death of patients will be classified. Insights from exploratory descriptive statistics and thematic analysis will be combined to identify priority areas for future interventions. ETHICS AND DISSEMINATION: The need for ethical approval was waivered by the Aneurin Bevan University Health Board research risk review committee given the anonymised nature of data (ABHB R&D Ref number: SA/410/13). The authors will submit the results of the study to relevant journals and undertake national and international oral presentations to researchers, clinicians and policymakers.

Pediatric immunization-related safety incidents in primary care: A mixed methods analysis of a national database.

BACKGROUND: Children are scheduled to receive 18-20 immunizations before their 18th birthday in England and Wales; this approximates to 13 million vaccines administered per annum. Each immunization represents a potential opportunity for immunization-related error and effective immunization is imperative to maintain the public health benefit from immunization. Using data from a national reporting system, this study aimed to characterize pediatric immunization-related safety incident reports from primary care in England and Wales between 2002 and 2013. METHODS: A cross-sectional mixed methods study was undertaken. This comprised reading the free-text of incident reports and applying codes to describe incident type, potential contributory factors, harm severity, and incident outcomes. A subsequent thematic analysis was undertaken to interpret the most commonly occurring codes, such as those describing the incident, events leading up to it and reported contributory factors, within the contexts they were described. RESULTS: We identified 1745 reports and most (n=1077, 61.7%) described harm outcomes including three deaths, 67 reports of moderate harm and 1007 reports of low harm. Failure of timely vaccination was the potential cause of three child deaths from meningitis and pneumonia, and described in a further 113 reports. Vaccine administration incidents included the wrong number of doses (n=476, 27.3%), wrong timing (n=294, 16.8%), and wrong vaccine (n=249, 14.3%). Documentation failures were frequently implicated. Socially and medically vulnerable children were commonly described. CONCLUSION: This is the largest examination of reported contributory factors for immunization-related patient safety incidents in children. Our findings suggest investments in IT infrastructure to support data linkage and identification of risk predictors, development of consultation models that promote the role of parents in mitigating safety incidents, and improvement efforts to adapt and adopt best practices from elsewhere, are needed to mitigate future immunization-related patient safety incidents. These priorities are particularly pressing for vulnerable patient groups.