Diagnostic errors in paediatric cardiac intensive care

Prevalence and Characteristics of Diagnostic Error in Pediatric Critical Care: A Multicenter Study

OBJECTIVES

Effective interventions to prevent diagnostic error among critically ill children should be informed by diagnostic error prevalence and etiologies. We aimed to determine the prevalence and characteristics of diagnostic errors and identify factors associated with error in patients admitted to the PICU.

DESIGN

Multicenter retrospective cohort study using structured medical record review by trained clinicians using the Revised Safer Dx instrument to identify diagnostic error (defined as missed opportunities in diagnosis). Cases with potential errors were further reviewed by four pediatric intensivists who made final consensus determinations of diagnostic error occurrence. Demographic, clinical, clinician, and encounter data were also collected.

SETTING

Four academic tertiary-referral PICUs.

PATIENTS

Eight hundred eighty-two randomly selected patients 0-18 years old who were nonelectively admitted to participating PICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of 882 patient admissions, 13 (1.5%) had a diagnostic error up to 7 days after PICU admission. Infections (46%) and respiratory conditions (23%) were the most common missed diagnoses. One diagnostic error caused harm with a prolonged hospital stay. Common missed diagnostic opportunities included failure to consider the diagnosis despite a suggestive history (69%) and failure to broaden diagnostic testing (69%). Unadjusted analysis identified more diagnostic errors in patients with atypical presentations (23.1% vs 3.6%, p = 0.011), neurologic chief complaints (46.2% vs 18.8%, p = 0.024), admitting intensivists greater than or equal to 45 years old (92.3% vs 65.1%, p = 0.042), admitting intensivists with more service weeks/year (mean 12.8 vs 10.9 wk, p = 0.031), and diagnostic uncertainty on admission (77% vs 25.1%, p < 0.001). Generalized linear mixed models determined that atypical presentation (odds ratio [OR] 4.58; 95% CI, 0.94-17.1) and diagnostic uncertainty on admission (OR 9.67; 95% CI, 2.86-44.0) were significantly associated with diagnostic error.

CONCLUSIONS

Among critically ill children, 1.5% had a diagnostic error up to 7 days after PICU admission. Diagnostic errors were associated with atypical presentations and diagnostic uncertainty on admission, suggesting possible targets for intervention.

Optimizing Pediatric Patient Safety in the Emergency Care Setting

Patient safety is the foundation of high-quality health care and remains a critical priority for all clinicians caring for children. There are numerous aspects of pediatric care that increase the risk of patient harm, including but not limited to risk from medication errors attributable to weight-dependent dosing and need for appropriate equipment and training. Of note, the majority of children who are ill and injured are brought to community hospital emergency departments. It is, therefore, imperative that all emergency departments practice patient safety principles, support a culture of safety, and adopt best practices to improve safety for all children seeking emergency care. This technical report outlined the challenges and resources necessary to minimize pediatric medical errors and to provide safe medical care for children of all ages in emergency care settings.

Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, and Beyond

Patient care in intensive care environments is complex, time-sensitive, and data-rich, factors that make these settings particularly well-suited to clinical decision support (CDS). A wide range of CDS interventions have been used in intensive care unit environments. The field needs well-designed studies to identify the most effective CDS approaches. Evolving artificial intelligence and machine learning models may reduce information-overload and enable teams to take better advantage of the large volume of patient data available to them. It is vital to effectively integrate new CDS into clinical workflows and to align closely with the cognitive processes of frontline clinicians.

A Research Agenda for Diagnostic Excellence in Critical Care Medicine

Diagnosing critically ill patients in the intensive care unit is difficult. As a result, diagnostic errors in the intensive care unit are common and have been shown to cause harm. Research to improve diagnosis in critical care medicine has accelerated in past years. However, much work remains to fully elucidate the diagnostic process in critical care. To achieve diagnostic excellence, interdisciplinary research is needed, adopting a balanced strategy of continued biomedical discovery while addressing the complex care delivery systems underpinning the diagnosis of critical illness.

Diagnostic error in the pediatric hospital: a narrative review

INTRODUCTION

Diagnostic error is a prevalent type of medical error that is associated with considerable patient harm and increased medical costs. The majority of literature guiding the current understanding of diagnostic error in the hospital setting is from adult studies. However, there is research to suggest this type of error is also prevalent in the pediatric specialty.

OBJECTIVES

The primary objective of this study was to define the current understanding of diagnostic error in the pediatric hospital through a structured literature review.

METHODS

We searched PubMed and identified studies focusing on three aspects of diagnostic error in pediatric hospitals: the incidence or prevalence, contributing factors, and related interventions. We used a tiered review, and a standardized electronic form to extract data from included articles.

RESULTS

Fifty-nine abstracts were screened and 23 full-text studies were included in the final review. Seventeen of the 23 studies focused on the incidence or prevalence, with only 3 studies investigating the utility of interventions. Most studies took place in an intensive care unit or emergency department with very few studies including only patients on the general wards. Overall, the prevalence of diagnostic error in pediatric hospitals varied greatly and depended on the measurement technique and specific hospital setting. Both healthcare system factors and individual cognitive factors were found to contribute to diagnostic error, with there being limited evidence to guide how best to mitigate the influence of these factors on the diagnostic process.

CONCLUSION

The general knowledge of diagnostic error in pediatric hospital settings is limited. Future work should incorporate structured frameworks to measure diagnostic errors and examine clinicians' diagnostic processes in real-time to help guide effective hospital-wide interventions.

Diagnostic Errors in Pediatric Critical Care: A Systematic Review

OBJECTIVES

To summarize the literature on prevalence, impact, and contributing factors related to diagnostic error in the PICU.

DATA SOURCES

Search of PubMed, EMBASE, and the Cochrane Library up to December 2019.

STUDY SELECTION

Studies on diagnostic error and the diagnostic process in pediatric critical care were included. Non-English studies with no translation, case reports/series, studies providing no information on diagnostic error, studies focused on non-PICU populations, and studies focused on a single condition/disease or a single diagnostic test/tool were excluded.

DATA EXTRACTION

Data on research design, objectives, study sample, and results pertaining to the prevalence, impact, and factors associated with diagnostic error were abstracted from each study.

DATA SYNTHESIS

Using independent tiered review, 396 abstracts were screened, and 17 studies (14 full-text, 3 abstracts) were ultimately included. Fifteen of 17 studies (88%) had an observational research design. Autopsy studies (autopsy rates were 20-47%) showed a 10-23% rate of missed major diagnoses; 5-16% of autopsy-discovered diagnostic errors had a potential adverse impact on survival and would have changed management. Retrospective record reviews reported varying rates of diagnostic error from 8% in a general PICU population to 12% among unexpected critical admissions and 21-25% of patients discussed at PICU morbidity and mortality conferences. Cardiovascular, infectious, congenital, and neurologic conditions were most commonly misdiagnosed. Systems factors (40-67%), cognitive factors (20-3%), and both systems and cognitive factors (40%) were associated with diagnostic error. Limited information was available on the impact of misdiagnosis.

CONCLUSIONS

Knowledge of diagnostic errors in the PICU is limited. Future work to understand diagnostic errors should involve a balanced focus between studying the diagnosis of individual diseases and uncovering common system- and process-related determinants of diagnostic error.

What Contributes to Diagnostic Error or Delay? A Qualitative Exploration Across Diverse Acute Care Settings in the United States

OBJECTIVES

Diagnostic error and delay is a prevalent and impactful problem. This study was part of a mixed-methods approach to understand the organizational, clinician, and patient factors contributing to diagnostic error and delay among acutely ill patients within a health system, as well as recommendations for the development of tailored, targeted, feasible, and effective interventions.

METHODS

We did a multisite qualitative study using focus group methodology to explore the perspectives of key clinician stakeholders. We used a conceptual framework that characterized diagnostic error and delay as occurring within 1 of 3 stages of the patient's diagnostic journey-critical information gathering, synthesis of key information, and decision making and communication. We developed our moderator guide based on the sociotechnical frameworks previously described by Holden and Singh for understanding noncognitive factors that lead to diagnostic error and delay. Deidentified focus group transcripts were coded in triplicate and to consensus over a series of meetings. A final coded data set was then uploaded into NVivo software. The data were then analyzed to generate overarching themes and categories.

RESULTS

We recruited a total of 64 participants across 4 sites from emergency departments, hospital floor, and intensive care unit settings into 11 focus groups. Clinicians perceive that diverse organizational, communication and coordination, individual clinician, and patient factors interact to impede the process of making timely and accurate diagnoses.

CONCLUSIONS

This study highlights the complex sociotechnical system within which individual clinicians operate and the contributions of systems, processes, and institutional factors to diagnostic error and delay.

Factors Associated With Diagnostic Error on Admission to a PICU: A Pilot Study

OBJECTIVES

Diagnostic errors can harm critically ill children. However, we know little about their prevalence in PICUs and factors associated with error. The objective of this pilot study was to determine feasibility of record review to identify patient, provider, and work system factors associated with diagnostic errors during the first 12 hours after PICU admission.

DESIGN

Pilot retrospective cohort study with structured record review using a structured tool (Safer Dx instrument) to identify diagnostic error.

SETTING

Academic tertiary referral PICU.

PATIENTS

Patients 0-17 years old admitted nonelectively to the PICU.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Four of 50 patients (8%) had diagnostic errors in the first 12 hours after admission. The Safer Dx instrument helped identify delayed diagnoses of chronic ear infection, increased intracranial pressure (two cases), and Bartonella encephalitis. We calculated that 610 PICU admissions are needed to achieve 80% power (α = 0.05) to detect significant associations with error.

CONCLUSIONS

Our pilot study found four patients with diagnostic error out of 50 children admitted nonelectively to a PICU. Retrospective record review using a structured tool to identify diagnostic errors is feasible in this population. Pilot data are being used to inform a larger and more definitive multicenter study.

The effect of the first-year residents orientation period on intensive care and hospital mortality, in a medical intensive care unit, within a developing country

PURPOSE

To determine whether the adaptation of junior residents, during their first week rotation period within the ICU, has any effect on ICU and hospital mortality rates, in a developing country.

MATERIALS AND METHODS

Patients who were admitted to the ICU were included, with 1207 out of 1547 of the admitted patients being eligible. The effect of age, gender, co-morbidities, the cause of the ICU admission, the presence of hospital-acquired infections, residents rotation week, admission time (weekday vs. weekend), number of patients admitted on the same day (one vs. two or more) and APACHE II score upon the ICU and hospital mortality rates were evaluated.

RESULTS

The first rotation week of junior residents is an independent risk factor determining hospital mortality (OR (95% CI) = 2.42 (1.23-4.76); p = .010). The effect of the first rotation week on intensive care mortality was not statistically significant (1.92 (0.97-3.84); p = .063). In addition, the presence of malignancy, sepsis-septic shock, hospital-acquired infection and high APACHE II score were found to be other independent determinants of increased hospital mortality.

CONCLUSION

The junior residents first rotation week is an independent risk factor on hospital mortality, in a tertiary medical intensive care unit, within a developing country.