Diagnostic errors related to acute abdominal pain in the emergency department

Development and Psychometric Analysis of a Patient-Reported Measure of Diagnostic Excellence for Emergency and Urgent Care Settings

BACKGROUND

Emergency and urgent care settings face challenges with routinely obtaining performance feedback related to diagnostic care. Patients and their care partners provide an important perspective on the diagnostic process and outcome of care in these settings. We sought to develop and test psychometric properties of Patient-Report to IMprove Diagnostic Excellence in Emergency Department settings (PRIME-ED), a measure of patient-reported diagnostic excellence in these care settings.

METHODS

We developed PRIME-ED based on literature review, expert feedback, and cognitive testing. To assess psychometric properties, we surveyed AmeriSpeak, a probability-based panel that provides sample coverage of approximately 97% of the U.S. household population, in February 2022 to adult patients, or their care partners, who had presented to an emergency department or urgent care facility within the last 30 days. Respondents rated their agreement on a 5-point Likert scale with each of 17 statements across multiple domains of patient-reported diagnostic excellence. Demographics, visit characteristics, and a subset of the Emergency Department Consumer Assessment of Healthcare Providers & Systems were also collected. We conducted psychometric testing for reliability and validity.

RESULTS

Over a thousand (n = 1116) national panelists completed the PRIME-ED survey, of which 58.7% were patients and 40.9% were care partners; 49.6% received care at an emergency department and 49.9% at an urgent care facility. Responses had high internal consistency within 3 patient-reported diagnostic excellence domain groupings: diagnostic process (Cronbach's alpha 0.94), accuracy of diagnosis (0.93), and communication of diagnosis (0.94). Domain groupings were significantly correlated with concurrent Emergency Department Consumer Assessment of Healthcare Providers & Systems items. Factor analyses substantiated 3 domain groupings.

CONCLUSIONS

PRIME-ED has potential as a tool for capturing patient-reported diagnostic excellence in emergency and urgent care.

Ten misconceptions regarding decision-making in critical care

Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system. Patient complexity, illness severity, and the urgency in initiating proper treatment all contribute to decision-making errors. Clinician-related factors such as fatigue, cognitive overload, and inexperience further interfere with effective decision-making. Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error. This evidence-based review discusses ten common misconceptions regarding critical care decision-making. By understanding how practitioners make clinical decisions and examining how errors occur, strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.

How do patients and care partners describe diagnostic uncertainty in an emergency department or urgent care setting?

OBJECTIVES

Little is known about how patients perceive diagnostic uncertainty. We sought to understand how patients and care partners perceive uncertainty in an emergency or urgent care setting, where making a final diagnosis is often not possible.

METHODS

We administered a survey to a nationally representative panel on patient-reported diagnostic excellence in an emergency department or urgent care setting. The survey included items specific to perceived diagnostic excellence, visit characteristics, and demographics. We analyzed responses to two open-ended questions among those who reported uncertainty in the explanation they were given. Themes were identified using an inductive approach, and compared by whether respondents agreed or disagreed the explanation they were given was true.

RESULTS

Of the 1,116 respondents, 106 (10 %) reported that the care team was not certain in the explanation of their health problem. Five themes were identified in the open-ended responses: poor communication (73 %), uncertainty made transparent (10 %), incorrect information provided (9 %), inadequate testing equipment (4 %), and unable to determine (4 %). Of the respondents who reported uncertainty, 21 % (n=22/106) reported the explanation of their problem given was not true.

CONCLUSIONS

The findings of this analysis suggest that the majority of patients and their care partners do not equate uncertainty with a wrong explanation of their health problem, and that poor communication was the most commonly cited reason for perceived uncertainty.

Predictors of 72-h unscheduled return visits with admission in patients presenting to the emergency department with abdominal pain

BACKGROUND

Unscheduled return visits (URVs) to the emergency department (ED) constitute a crucial indicator of patient care quality.

OBJECTIVE

We aimed to analyze the clinical characteristics of patients who visited the ED with abdominal pain and to identify the risk of URVs with admission (URVAs) from URVs without admission (URVNAs).

METHODS

This retrospective study included adult patients who visited the ED of Taipei Medical University Hospital because of abdominal pain and revisited in 72 h over a 5-year period (January 1, 2014, to December 31, 2018). Multivariable logistic regression analysis was employed to identify risk factors for URVAs and receiver operating characteristic (ROC) curve analysis was performed to determine the efficacy of variables predicting URVAs and the optimal cut-off points for the variables. In addition, a classification and regression tree (CART)-based scoring system was used for predicting risk of URVA.

RESULTS

Of 702 eligible patients with URVs related to abdominal pain, 249 had URVAs (35.5%). In multivariable analysis, risk factors for URVAs during the index visit included execution of laboratory tests (yes vs no: adjusted odds ratio [AOR], 4.32; 95% CI 2.99-6.23), older age (≥ 40 vs < 40 years: AOR, 2.10; 95% CI 1.10-1.34), Level 1-2 triage scores (Levels 1-2 vs Levels 3-5: AOR, 2.30; 95% CI 1.26-4.19), and use of ≥ 2 analgesics (≥ 2 vs < 2: AOR, 2.90; 95% CI 1.58-5.30). ROC curve analysis results revealed the combination of these 4 above variables resulted in acceptable performance (area under curve: 0.716). The above 4 variables were used in the CART model to evaluate URVA propensity.

CONCLUSIONS

Elder patients with abdominal pain who needed laboratory workup, had Level 1-2 triage scores, and received ≥ 2 doses of analgesics during their index visits to the ED had higher risk of URVAs.

Diagnostic delays among COVID-19 patients with a second concurrent diagnosis

BACKGROUND

Little is known about the effect of a new pandemic on diagnostic errors.

OBJECTIVE

We aimed to identify delayed second diagnoses among patients presenting to the emergency department (ED) with COVID-19.

DESIGNS

An observational cohort Study.

SETTINGS AND PARTICIPANTS

Consecutive hospitalized adult patients presenting to the ED of a tertiary referral center with COVID-19 during the Delta and Omicron variant surges. Included patients had evidence of a second diagnosis during their ED stay.

MAIN OUTCOME AND MEASURES

The primary outcome was delayed diagnosis (without documentation or treatment in the ED). Contributing factors were assessed using two logistic regression models.

RESULTS

Among 1249 hospitalized COVID-19 patients, 216 (17%) had evidence of a second diagnosis in the ED. The second diagnosis of 73 patients (34%) was delayed, with a mean (SD) delay of 1.5 (0.8) days. Medical treatment was deferred in 63 patients (86%) and interventional therapy in 26 (36%). The probability of an ED diagnosis was the lowest for Infection-related diagnoses (56%) and highest for surgical-related diagnoses (89%). Evidence for the second diagnosis by physical examination (adjusted odds ratios [AOR] 2.35, 95% confidence interval [CI] 1.20-4.68) or by imaging (AOR 2.10, 95% CI 1.16-3.79) were predictors for ED diagnosis. Low oxygen saturation (AOR 0.38, 95% CI 0.18-0.79) and cough or dyspnea (AOR 0.48, 95% CI 0.25-0.94) in the ED were predictors of a delayed second diagnosis.

Defining Diagnostic Error: A Scoping Review to Assess the Impact of the National Academies' Report Improving Diagnosis in Health Care

BACKGROUND

Standards for accurate and timely diagnosis are ill-defined. In 2015, the National Academies of Science, Engineering, and Medicine (NASEM) committee published a landmark report, Improving Diagnosis in Health Care , and proposed a new definition of diagnostic error, "the failure to ( a ) establish an accurate and timely explanation of the patient's health problem(s) or ( b ) communicate that explanation to the patient."

OBJECTIVE

This study aimed to explore how researchers operationalize the NASEM's definition of diagnostic error with relevance to accuracy, timeliness, and/or communication in peer-reviewed published literature.

METHODS

Using the Arskey and O'Malley's framework framework, we identified published literature from October 2015 to February 2021 using Medline and Google Scholar. We also conducted subject matter expert interviews with researchers.

RESULTS

Of 34 studies identified, 16 were analyzed and abstracted to determine how diagnostic error was operationalized and measured. Studies were grouped by theme: epidemiology, patient focus, measurement/surveillance, and clinician focus. Nine studies indicated using the NASEM definition. Of those, 5 studies also operationalized with existing definitions proposed before the NASEM report. Four studies operationalized the components of the NASEM definition and did not cite existing definitions. Three studies operationalized error using existing definitions only. Subject matter experts indicated that the NASEM definition functions as foundation for researchers to conceptualize diagnostic error.

CONCLUSIONS

The NASEM report produced a common understanding of diagnostic error that includes accuracy, timeliness, and communication. In recent peer-reviewed literature, most researchers continue to use pre-NASEM report definitions to operationalize accuracy and timeliness. The report catalyzed the use of patient-centered concepts in the definition, resulting in emerging studies focused on examining errors related to communicating diagnosis to patients.

Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients

Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a lack of high-performing models for the diagnosis of myocardial infarction in real-world scenarios. We aimed to train and validate a deep learning model using ECGs to predict myocardial infarction in real-world emergency department patients. We studied emergency department patients in the Stockholm region between 2007 and 2016 that had an ECG obtained because of their presenting complaint. We developed a deep neural network based on convolutional layers similar to a residual network. Inputs to the model were ECG tracing, age, and sex; and outputs were the probabilities of three mutually exclusive classes: non-ST-elevation myocardial infarction (NSTEMI), ST-elevation myocardial infarction (STEMI), and control status, as registered in the SWEDEHEART and other registries. We used an ensemble of five models. Among 492,226 ECGs in 214,250 patients, 5,416 were recorded with an NSTEMI, 1,818 a STEMI, and 485,207 without a myocardial infarction. In a random test set, our model could discriminate STEMIs/NSTEMIs from controls with a C-statistic of 0.991/0.832 and had a Brier score of 0.001/0.008. The model obtained a similar performance in a temporally separated test set of the study sample, and achieved a C-statistic of 0.985 and a Brier score of 0.002 in discriminating STEMIs from controls in an external test set. We developed and validated a deep learning model with excellent performance in discriminating between control, STEMI, and NSTEMI on the presenting ECG of a real-world sample of the important population of all-comers to the emergency department. Hence, deep learning models for ECG decision support could be valuable in the emergency department.

A structured approach to EHR surveillance of diagnostic error in acute care: an exploratory analysis of two institutionally-defined case cohorts

OBJECTIVES

To test a structured electronic health record (EHR) case review process to identify diagnostic errors (DE) and diagnostic process failures (DPFs) in acute care.

METHODS

We adapted validated tools (Safer Dx, Diagnostic Error Evaluation Research [DEER] Taxonomy) to assess the diagnostic process during the hospital encounter and categorized 13 postulated e-triggers. We created two test cohorts of all preventable cases (n=28) and an equal number of randomly sampled non-preventable cases (n=28) from 365 adult general medicine patients who expired and underwent our institution's mortality case review process. After excluding patients with a length of stay of more than one month, each case was reviewed by two blinded clinicians trained in our process and by an expert panel. Inter-rater reliability was assessed. We compared the frequency of DE contributing to death in both cohorts, as well as mean DPFs and e-triggers for DE positive and negative cases within each cohort.

RESULTS

Twenty-seven (96.4%) preventable and 24 (85.7%) non-preventable cases underwent our review process. Inter-rater reliability was moderate between individual reviewers (Cohen's kappa 0.41) and substantial with the expert panel (Cohen's kappa 0.74). The frequency of DE contributing to death was significantly higher for the preventable compared to the non-preventable cohort (56% vs. 17%, OR 6.25 [1.68, 23.27], p<0.01). Mean DPFs and e-triggers were significantly and non-significantly higher for DE positive compared to DE negative cases in each cohort, respectively.

CONCLUSIONS

We observed substantial agreement among final consensus and expert panel reviews using our structured EHR case review process. DEs contributing to death associated with DPFs were identified in institutionally designated preventable and non-preventable cases. While e-triggers may be useful for discriminating DE positive from DE negative cases, larger studies are required for validation. Our approach has potential to augment institutional mortality case review processes with respect to DE surveillance.

Not Like the Textbook: An Atypical Case of Ectopic Pregnancy

Ectopic pregnancy is a potentially life-threatening outcome of pregnancy that occurs with the implantation of an embryo outside of the endometrial cavity. Classically considered a “must not miss” diagnosis, ectopic pregnancy is a common emergency department presentation, associated with a symptom triad of amenorrhea, vaginal bleeding, and abdominal pain. However, varied presentations of ectopic pregnancy or lack of typical risk factors can complicate the evaluation and diagnosis of this condition. This case report describes an atypical presentation of ectopic pregnancy after a reported spontaneous abortion, in which the patient was initially discharged with a diagnosis of pelvic inflammatory disease. This case provides an illustration of ectopic pregnancy that presented without classically associated symptoms, and also highlights how anchoring bias and pre-emptive closure, among other cognitive biases, contributed to a missed diagnosis.

Use of e-triggers to identify diagnostic errors in the paediatric ED

BACKGROUND

Diagnostic errors (DxEs) are an understudied source of patient harm in children rarely captured in current adverse event reporting systems. Applying electronic triggers (e-triggers) to electronic health records shows promise in identifying DxEs but has not been used in the emergency department (ED) setting.

OBJECTIVES

To assess the performance of an e-trigger and subsequent manual screening for identifying probable DxEs among children with unplanned admission following a prior ED visit and to compare performance to existing incident reporting systems.

DESIGN/METHODS

Retrospective single-centre cohort study of children ages 0-22 admitted within 14 days of a previous ED visit between 1 January 2018 and 31 December 2019. Subjects were identified by e-trigger, screened to identify cases where index visit and hospital discharge diagnoses were potentially related but pathophysiologically distinct, and then these screened-in cases were reviewed for DxE using the SaferDx Instrument. Cases of DxE identified by e-trigger were cross-referenced against existing institutional incident reporting systems.

RESULTS

An e-trigger identified 1915 unplanned admissions (7.7% of 24 849 total admissions) with a preceding index visit. 453 (23.7%) were screened in and underwent review using SaferDx. 92 cases were classified as likely DxEs, representing 0.4% of all hospital admissions, 4.8% among those selected by e-trigger and 20.3% among those screened in for review. Half of cases were reviewed by two reviewers using SaferDx with substantial inter-rater reliability (Cohen's κ=0.65 (95% CI 0.54 to 0.75)). Six (6.5%) cases had been reported elsewhere: two to the hospital's incident reporting system and five to the ED case review team (one reported to both).

CONCLUSION

An e-trigger coupled with manual screening enriched a cohort of patients at risk for DxEs. Fewer than 10% of DxEs were identified through existing surveillance systems, suggesting that they miss a large proportion of DxEs. Further study is required to identify specific clinical presentations at risk of DxEs.

Bedside Clinicians' Perceptions on the Contributing Role of Diagnostic Errors in Acutely Ill Patient Presentation: A Survey of Academic and Community Practice

OBJECTIVES

This study aimed to explore clinicians' perceptions of the occurrence of and factors associated with diagnostic errors in patients evaluated during a rapid response team (RRT) activation or unplanned admission to the intensive care unit (ICU).

METHODS

A multicenter prospective survey study was conducted among multiprofessional clinicians involved in the care of patients with RRT activations and/or unplanned ICU admissions (UIAs) at 2 academic hospitals and 1 community-based hospital between April 2019 and March 2020. A study investigator screened eligible patients every day. Within 24 hours of the event, a research coordinator administered the survey to clinicians, who were asked the following: whether diagnostic errors contributed to the reason for RRT/UIA, whether any new diagnosis was made after RRT/UIA, if there were any failures to communicate the diagnosis, and if involvement of specialists earlier would have benefited that patient. Patient clinical data were extracted from the electronic health record.

RESULTS

A total of 1815 patients experienced RRT activations, and 1024 patients experienced UIA. Clinicians reported that 18.2% (95/522) of patients experienced diagnostic errors, 8.0% (42/522) experienced a failure of communication, and 16.7% (87/522) may have benefitted from earlier involvement of specialists. Compared with academic settings, clinicians in the community hospital were less likely to report diagnostic errors (7.0% versus 22.8%, P = 0.002).

CONCLUSIONS

Clinicians report a high rate of diagnostic errors in patients they evaluate during RRT or UIAs.

Effects of using an abdominal simulator to develop palpatory competencies in 3rd year medical students

BACKGROUND

Medical school faculty are hard pressed to provide clerkship students with sufficient opportunity to develop and practice their capacity to perform a competent clinical examination, including the palpatory examination of the abdomen. We evaluated the impact of training with an abdominal simulator, AbSim, designed to monitor the depth, location, and thoroughness of their palpation and to provide concurrent and summative feedback regarding their performance.

METHODS

All third-year medical students were given the opportunity to develop their palpatory skills with the AbSim simulator during the family medicine rotation. The performance of those who studied with the simulator was measured by its sensors, before and after a training session that included visual feedback regarding the depth and coverage of the student's manual pressure. Additionally, all students reported their confidence in their evolving abdominal palpation skills at the beginning and end of the rotation.

RESULTS

119 (86.9%) of 137 students filled out the initial questionnaire, and 73 (61.3%) studied with the abdominal simulator. The training produced a highly significant improvement in their overall performance (4 measures, p's < 0.001). Pre-training performance (depth calibration and thoroughness of coverage) was not related to the number of months of previous clinical rotations nor to previous internal medicine or surgery rotations. There was little relation between students' confidence in their abdominal examination skills and objective measures of their palpatory performance; however, students who chose the training started with less confidence, and became more confident after training.

CONCLUSIONS

Guided abdominal simulator practice increased medical students' capacity to perform an abdominal examination with more appropriate depth and thoroughness of palpation. Interpretation of changes in confidence are uncertain, because confidence was unrelated to objectively measured performance. However, students with low initial confidence in their abdominal examination seemed to be more likely to choose to study with the abdominal simulator.

Abdominal Pain in the Emergency Department: Missed Diagnoses

Abdominal pain is the most common chief complaint in the Emergency Department. Abdominal pain is caused by a variety of gastrointestinal and nongastrointestinal disorders. Some frequently missed conditions include biliary pathology, appendicitis, diverticulitis, and urogenital pathology. The Emergency Medicine clinician must consider all aspects of the patient's presentation including history, physical examination, laboratory testing, and imaging. If no diagnosis is identified, close reassessment of pain, vital signs, and physical examination are necessary to ensure safe discharge. Strict verbal and written return precautions should be provided to the patient.

Understanding diagnostic processes in emergency departments: a mixed methods case study protocol

INTRODUCTION

Diagnostic processes in the emergency department (ED) involve multiple interactions among individuals who interface with information systems to access and record information. A better understanding of diagnostic processes is needed to mitigate errors. This paper describes a study protocol to map diagnostic processes in the ED as a foundation for developing future error mitigation strategies.

METHODS AND ANALYSIS

This study of an adult and a paediatric academic ED uses a prospective mixed methods case study design informed by an ED-specific diagnostic decision-making model (the modified ED-National Academies of Sciences, Engineering and Medicine (NASEM) model) and two cognitive theories (dual process theory and distributed cognition). Data sources include audio recordings of patient and care team interactions, electronic health record data, observer field notes and stakeholder interviews. Multiple qualitative analysis methods will be used to explore diagnostic processes in situ, including systems information flow, human-human and human-system interactions and contextual factors influencing cognition. The study has three parts. Part 1 involves prospective field observations of patients with undifferentiated symptoms at high risk for diagnostic error, where each patient is followed throughout the entire care delivery process. Part 2 involves observing individual care team providers over a 4-hour window to capture their diagnostic workflow, team coordination and communication across multiple patients. Part 3 uses interviews with key stakeholders to understand different perspectives on the diagnostic process, as well as perceived strengths and vulnerabilities, in order to enrich the ED-NASEM diagnostic model.

ETHICS AND DISSEMINATION

The University of Michigan Institutional Review Board approved this study, HUM00156261. This foundational work will help identify strengths and vulnerabilities in diagnostic processes. Further, it will inform the future development and testing of patient, provider and systems-level interventions for mitigating error and improving patient safety in these and other EDs. The work will be disseminated through journal publications and presentations at national and international meetings.

Validation of an electronic trigger to measure missed diagnosis of stroke in emergency departments

OBJECTIVE

Diagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs).

METHODS

Using two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom-disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained reviewers evaluated medical records for presence/absence of missed opportunities in stroke diagnosis and stroke-related red-flags, risk factors, neurological examination, and clinical interventions. Reviewers also estimated quality of clinical documentation at the index ED visit.

RESULTS

We applied the e-trigger to 7,752,326 unique patients and identified 46,931 stroke-related admissions, of which 398 records were flagged as trigger-positive and reviewed. Of these, 124 had missed opportunities (positive predictive value for "missed" = 31.2%), 93 (23.4%) had no missed opportunity (non-missed), 162 (40.7%) were miscoded, and 19 (4.7%) were inconclusive. Reviewer agreement was high (87.3%, Cohen's kappa = 0.81). Compared to the non-missed group, the missed group had more stroke risk factors (mean 3.2 vs 2.6), red flags (mean 0.5 vs 0.2), and a higher rate of inadequate documentation (66.9% vs 28.0%).

CONCLUSION

In a large national EHR repository, a symptom-disease pair-based e-trigger identified missed diagnoses of stroke with a modest positive predictive value, underscoring the need for chart review validation procedures to identify diagnostic errors in large data sets.

nalyzing diagnostic errors in the acute setting: a process-driven approach

OBJECTIVES

We describe an approach for analyzing failures in diagnostic processes in a small, enriched cohort of general medicine patients who expired during hospitalization and experienced medical error. Our objective was to delineate a systematic strategy for identifying frequent and significant failures in the diagnostic process to inform strategies for preventing adverse events due to diagnostic error.

METHODS

Two clinicians independently reviewed detailed records of purposively sampled cases identified from established institutional case review forums and assessed the likelihood of diagnostic error using the Safer Dx instrument. Each reviewer used the modified Diagnostic Error Evaluation and Research (DEER) taxonomy, revised for acute care (41 possible failure points across six process dimensions), to characterize the frequency of failure points (FPs) and significant FPs in the diagnostic process.

RESULTS

Of 166 cases with medical error, 16 were sampled: 13 (81.3%) had one or more diagnostic error(s), and a total of 113 FPs and 30 significant FPs were identified. A majority of significant FPs (63.3%) occurred in "Diagnostic Information and Patient Follow-up" and "Patient and Provider Encounter and Initial Assessment" process dimensions. Fourteen (87.5%) cases had a significant FP in at least one of these dimensions.

CONCLUSIONS

Failures in the diagnostic process occurred across multiple dimensions in our purposively sampled cohort. A systematic analytic approach incorporating the modified DEER taxonomy, revised for acute care, offered critical insights into key failures in the diagnostic process that could serve as potential targets for preventative interventions.

Disagreements between emergency patients and physicians regarding chief complaint - Patient factors and prognostic implications

INTRODUCTION

The predictive power of chief complaints reported at presentation to the emergency department (ED) is well known. However, there is a lack of research on the coherence of patient versus physician reported chief complaints. The aim of this study was to determine the rate of disagreement between patients and physicians regarding chief complaint and its significance for the prediction of the outcomes number of resources used during ED work-up, hospitalisation, ICU admission, in-hospital mortality and hospital length of stay.

METHODS

In this secondary analysis of a study conducted over a time course of 9 weeks, consecutive emergency patients and their physicians were independently asked to report the chief complaint upon presentation. The two reports were assessed for pair-wise agreement.

RESULTS

Of 6722 emergency patients (mean age 53.3, 46.8% female), the median number of symptoms reported by patients was two and one reported by physicians. The rate of disagreement on chief complaints was 32.6%. Disagreement was associated with a higher number of resources (β = 0.24; CI, 0.18, 0.31, P <.001) and hospitalisation (OR = 1.31; CI, 1.16, 1.48, P <.001), using multivariable analyses. Patient factors associated with disagreement were age (OR = 1.01; CI, 1.01, 1.01, P <.001), number of patient reported symptoms (OR = 1.27; CI, 1.23, 1.32, P <.001) and male gender (OR = 1.12; 1.01, 1.25, P =.0285).

CONCLUSION

Disagreement on chief complaint between patient and physician may be an early marker for a complex work-up, requiring more resources and hospitalisations. The relevance of this finding is the newly identified signal of chief complaint replacement. It is easy to identify and should generate attention, as it affects a certain phenotype (older male patients with higher numbers of complaints).

The Diagnostic Error Index: A Quality Improvement Initiative to Identify and Measure Diagnostic Errors

OBJECTIVE

To develop a diagnostic error index (DEI) aimed at providing a practical method to identify and measure serious diagnostic errors.

STUDY DESIGN

A quality improvement (QI) study at a quaternary pediatric medical center. Five well-defined domains identified cases of potential diagnostic errors. Identified cases underwent an adjudication process by a multidisciplinary QI team to determine if a diagnostic error occurred. Confirmed diagnostic errors were then aggregated on the DEI. The primary outcome measure was the number of monthly diagnostic errors.

RESULTS

From January 2017 through June 2019, 105 cases of diagnostic error were identified. Morbidity and mortality conferences, institutional root cause analyses, and an abdominal pain trigger tool were the most frequent domains for detecting diagnostic errors. Appendicitis, fractures, and nonaccidental trauma were the 3 most common diagnoses that were missed or had delayed identification.

CONCLUSIONS

A QI initiative successfully created a pragmatic approach to identify and measure diagnostic errors by utilizing a DEI. The DEI established a framework to help guide future initiatives to reduce diagnostic errors.

Acute abdominal pain in triage: A retrospective observational study of the Manchester triage system's validity

OBJECTIVE

Roughly 5% to 10% of patients admitted to the emergency department suffer from acute abdominal pain. Triage plays a key role in patient stratification, identifying patients who need prompt treatment versus those who can safely wait. In this regard, the aim of this study was to estimate the performance of the Manchester Triage System in classifying patients with acute abdominal pain.

METHODS

A total of 9,851 patients admitted at the Emergency Department of the Merano Hospital with acute abdominal pain were retrospectively enrolled between 1 January 2017 and 30 June 2019. The study was conducted and reported according to the STROBE statement. The sensitivity and specificity of the Manchester Triage System were estimated by verifying the triage classification received by the patients and their survival at seven days or the need for acute surgery within 72 h after emergency department access.

RESULTS

Among the patients with acute abdominal pain (median age 50 years), 0.4% died within seven days and 8.9% required surgery within 72 hours. The sensitivity was 44.7% (29.9-61.5), specificity was 95.4% (94.9-95.8), and negative predictive value was 99.7% (99.2-100) in relation to death at seven days.

CONCLUSIONS

The Manchester Triage System shows good specificity and negative predictive value. However, its sensitivity was low due to the amount of incorrect triage prediction in patients with high-priority codes (red/orange), suggesting overtriage in relation to seven-day mortality. This may be a protective measure for the patient. In contrast, the need for acute surgery within 72 h was affected by under-triage.

RELEVANCE TO CLINICAL PRACTICE

The triage nurse using Manchester Triage System can correctly prioritise the majority of patients with acute abdominal pain, especially in low acuity patients. The Manchester Triage System is safe and does not underestimate the severity of the patients.

Second opinions, multiple physician appointments, and overlapping prescriptions in the paediatric population: A systematic literature review

OBJECTIVES

Doctor shopping, double doctoring, and overlapping prescriptions are often used as synonyms for multiple physician appointments in the same disease episode. Such behaviours translate into poor patient satisfaction and patient-doctor communication as well as abuse or misuse of drugs, increasing health care costs and resulting in negative health consequences. This systematic review of the literature was conducted to identify factors that drive doctor-shopping behaviour in children's caregivers.

METHODS

The search was conducted in PubMed and grey literature and was based on the following search terms: included doctor or physician shopping, drug seeking, double doctoring, children, and combinations of those. Overall, 500 records were identified, of which 11 were selected for qualitative synthesis. Data extracted considered definitions of doctor shopping, co-morbidities, and target population characteristics.

RESULTS

Definitions of doctor shopping were inconsistent. The frequency of doctor shopping was high for acute illnesses and ranged from 53% in children with a fever in Hong Kong to 18% at an emergency department in Canada. The incidence of this phenomenon was low when taking into account addictive drugs and was rated at 0.02% to 0.3% in the full paediatric population. This phenomenon was more prevalent in children younger than 1 year, in children with attention-deficit hyperactivity disorder (ADHD) and co-morbid psychiatric conditions, and in those whose caregivers themselves had psychiatric conditions. It was more frequent in cases with an acute disease (eg, fever, gastroenteritis, and urinary tract infection) than a chronic disease (eg, asthma).

CONCLUSIONS

The knowledge about doctor shopping by children's caregivers is limited, despite that this is a frequent behaviour. There is a need for further research covering a broader range of diseases. The causes and consequences of doctor shopping should be sought as well to investigate its relation to health care regulations and possibility to reduce unnecessary medical resource utilization.

Identifying trigger concepts to screen emergency department visits for diagnostic errors

OBJECTIVES

The diagnostic process is a vital component of safe and effective emergency department (ED) care. There are no standardized methods for identifying or reliably monitoring diagnostic errors in the ED, impeding efforts to enhance diagnostic safety. We sought to identify trigger concepts to screen ED records for diagnostic errors and describe how they can be used as a measurement strategy to identify and reduce preventable diagnostic harm.

METHODS

We conducted a literature review and surveyed ED directors to compile a list of potential electronic health record (EHR) trigger (e-triggers) and non-EHR based concepts. We convened a multidisciplinary expert panel to build consensus on trigger concepts to identify and reduce preventable diagnostic harm in the ED.

RESULTS

Six e-trigger and five non-EHR based concepts were selected by the expert panel. E-trigger concepts included: unscheduled ED return to ED resulting in hospital admission, death following ED visit, care escalation, high-risk conditions based on symptom-disease dyads, return visits with new diagnostic/therapeutic interventions, and change of treating service after admission. Non-EHR based signals included: cases from mortality/morbidity conferences, risk management/safety office referrals, ED medical director case referrals, patient complaints, and radiology/laboratory misreads and callbacks. The panel suggested further refinements to aid future research in defining diagnostic error epidemiology in ED settings.

CONCLUSIONS

We identified a set of e-trigger concepts and non-EHR based signals that could be developed further to screen ED visits for diagnostic safety events. With additional evaluation, trigger-based methods can be used as tools to monitor and improve ED diagnostic performance.

Operational measurement of diagnostic safety: state of the science

Reducing the incidence of diagnostic errors is increasingly a priority for government, professional, and philanthropic organizations. Several obstacles to measurement of diagnostic safety have hampered progress toward this goal. Although a coordinated national strategy to measure diagnostic safety remains an aspirational goal, recent research has yielded practical guidance for healthcare organizations to start using measurement to enhance diagnostic safety. This paper, concurrently published as an Issue Brief by the Agency for Healthcare Research and Quality, issues a "call to action" for healthcare organizations to begin measurement efforts using data sources currently available to them. Our aims are to outline the state of the science and provide practical recommendations for organizations to start identifying and learning from diagnostic errors. Whether by strategically leveraging current resources or building additional capacity for data gathering, nearly all organizations can begin their journeys to measure and reduce preventable diagnostic harm.

Identifying psychiatric diagnostic errors with the Safer Dx Instrument

OBJECTIVE

Diagnostic errors in psychiatry are understudied partly because they are difficult to measure. The current study aimed to adapt and test the Safer Dx Instrument, a structured tool to review electronic health records (EHR) for errors in medical diagnoses, to evaluate errors in anxiety diagnoses to improve measurement of psychiatric diagnostic errors.

DESIGN

The iterative adaptation process included a review of the revised Safer Dx-Mental Health Instrument by mental health providers to ensure content and face validity and review by a psychometrician to ensure methodologic validity and pilot testing of the revised instrument.

SETTINGS

None.

PARTICIPANTS

Pilot testing was conducted on 128 records of patients diagnosed with anxiety in integrated primary care mental health clinics. Cases with anxiety diagnoses documented in progress notes but not included as a diagnosis for the encounter (n = 25) were excluded.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

None.

RESULTS

Of 103 records meeting the inclusion criteria, 62 likely involved a diagnostic error (42 from use of unspecified anxiety diagnosis when a specific anxiety diagnosis was warranted; 20 from use of unspecified anxiety diagnosis when anxiety symptoms were either undocumented or documented but not severe enough to warrant diagnosis). Reviewer agreement on presence/absence of errors was 88% (κ = 0.71).

CONCLUSION

The revised Safer Dx-Mental Health Instrument has a high reliability for detecting anxiety-related diagnostic errors and deserves testing in additional psychiatric populations and clinical settings.

"Analysis of readmissions to the emergency department among patients presenting with abdominal pain"

BACKGROUND

Abdominal pain is one of the most common complaints among patients admitted to the Emergency Department (ED). Diagnosis and management of abdominal pain may be a challenge and there are patients who require admission to the ED more than once in a short period of time. Our purpose was to assess the incidence of readmissions among patients treated in the ED due to abdominal pain and to investigate the impact of readmission on the further course of treatment.

METHODS

We conducted a prospective observational study, which included patients admitted to the ED in one academic, teaching hospital presenting with non-traumatic abdominal pain in a three-month period. Analyzed factors included demographic data, details related to first and subsequent visits in the ED and the course of hospitalization.

RESULTS

Overall, 928 patients were included to the study and 101 (10.88%) patients were admitted to the ED more than once during three-month period. Patients visiting ED repeatedly were older (p = 0.03) and more likely to be hospitalized (p < 0.01) compared to single-visit patients. Patients during their subsequent visits spent more time in the ED (p = 0.01), had greater chance to repeat their appointment (p = 0.04), be admitted to the hospital (p < 0.01) and were more likely diagnosed with cholelithiasis (p = 0.03) compared to patients on their initial visit. If admitted to the surgical department they were also more often qualified for surgical procedure than patients on their first visit (p < 0.01). In a group of patients admitted to the surgical department there were no significant differences in rates of conversion, postoperative complications and mortality between subgroups.

CONCLUSIONS

Readmissions among patients presenting with abdominal pain are a common phenomenon with prevalence of 10.88%. They are most commonly associated with cholelithiasis and occur more frequently among older patients, which suggests, that elderly require more attention during ED managements.

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.

Factors Associated With Potentially Missed Diagnosis of Appendicitis in the Emergency Department

IMPORTANCE

Appendicitis may be missed during initial emergency department (ED) presentation.

OBJECTIVE

To compare patients with a potentially missed diagnosis of appendicitis (ie, patients with symptoms associated with appendicitis, including abdominal pain, constipation, nausea and/or vomiting, fever, and diarrhea diagnosed within 1-30 days after initial ED presentation) with patients diagnosed with appendicitis on the same day of ED presentation to identify factors associated with potentially missed appendicitis.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, a retrospective analysis of commercially insured claims data was conducted from January 1 to December 15, 2019. Patients who presented to the ED with undifferentiated symptoms associated with appendicitis between January 1, 2010, and December 31, 2017, were identified using the Clinformatics Data Mart administrative database (Optum Insights). The study sample comprised eligible adults (aged ≥18 years) and children (aged <18 years) who had previous ED visits within 30 days of an appendicitis diagnosis.

MAIN OUTCOMES AND MEASURES

Potentially missed diagnosis of appendicitis. Adjusted odds ratios (AORs) for abdominal pain and its combinations with other symptoms associated with appendicitis were compared between patients with a same-day diagnosis of appendicitis and patients with a potentially missed diagnosis of appendicitis.

RESULTS

Of 187 461 patients with a diagnosis of appendicitis, a total of 123 711 (66%; 101 375 adults [81.9%] and 22 336 children [18.1%]) were eligible for analysis. Among adults, 51 923 (51.2%) were women, with a mean (SD) age of 44.3 (18.2) years; among children, 9631 (43.1%) were girls, with a mean (SD) age of 12.2 (18.2) years. The frequency of potentially missed appendicitis was 6060 of 101 375 adults (6.0%) and 973 of 22 336 children (4.4%). Patients with isolated abdominal pain (adults, AOR, 0.65; 95% CI, 0.62-0.69; P < .001; children, AOR, 0.79; 95% CI, 0.69-0.90; P < .001) or with abdominal pain and nausea and/or vomiting (adults, AOR, 0.90; 95% CI, 0.84-0.97; P = .003; children, AOR, 0.84; 95% CI, 0.71-0.98; P = .03) were less likely to have missed appendicitis. Patients with abdominal pain and constipation (adults, AOR, 1.51; 95% CI, 1.31-1.75; P < .001; children, AOR, 2.43; 95% CI, 1.86-3.17; P < .001) were more likely to have missed appendicitis. Stratified by the presence of undifferentiated symptoms, women (abdominal pain, AOR, 1.68; 95% CI, 1.58-1.78; nausea and/or vomiting, AOR, 1.68; 95% CI, 1.52-1.85; fever, AOR, 1.32; 95% CI, 1.10-1.59; diarrhea, AOR, 1.19; 95% CI, 1.01-1.40; and constipation, AOR, 1.50; 95% CI, 1.24-1.82) and girls (abdominal pain, AOR, 1.64; 95% CI, 1.43-1.88; nausea and/or vomiting, AOR, 1.74; 95% CI, 1.42-2.13; fever, AOR, 1.55; 95% CI, 1.14-2.11; diarrhea, AOR, 1.80; 95% CI, 1.19-2.74; and constipation, AOR, 1.25; 95% CI, 0.88-1.78) as well as patients with a comorbidity index of 2 or greater (adults, abdominal pain, AOR, 3.33; 95% CI, 3.09-3.60; nausea and/or vomiting, AOR, 3.66; 95% CI, 3.23-4.14; fever, AOR, 5.00; 95% CI, 3.79-6.60; diarrhea, AOR, 4.27; 95% CI, 3.39-5.38; and constipation, AOR, 4.17; 95% CI, 3.08-5.65; children, abdominal pain, AOR, 2.42; 95% CI, 1.93-3.05; nausea and/or vomiting, AOR, 2.55; 95% CI, 1.89-3.45; fever, AOR, 4.12; 95% CI, 2.71-6.25; diarrhea, AOR, 2.17; 95% CI, 1.18-3.97; and constipation, AOR, 2.19; 95% CI, 1.30-3.70) were more likely to have missed appendicitis. Adult patients who received computed tomographic scans at the initial ED visit (abdominal pain, AOR, 0.58; 95% CI, 0.52-0.65; nausea and/or vomiting, AOR, 0.63; 95% CI, 0.52-0.75; fever, AOR, 0.41; 95% CI, 0.29-0.58; diarrhea, AOR, 0.83; 95% CI, 0.58-1.20; and constipation, AOR, 0.60; 95% CI, 0.39-0.94) were less likely to have missed appendicitis.

CONCLUSIONS AND RELEVANCE

Regardless of age, a missed diagnosis of appendicitis was more likely to occur in women, patients with comorbidities, and patients who experienced abdominal pain accompanied by constipation. Population-based estimates of the rates of potentially missed appendicitis reveal opportunities for improvement and identify factors that may mitigate the risk of a missed diagnosis.

Diagnostic error in the emergency department: learning from national patient safety incident report analysis

BACKGROUND

Diagnostic error occurs more frequently in the emergency department than in regular in-patient hospital care. We sought to characterise the nature of reported diagnostic error in hospital emergency departments in England and Wales from 2013 to 2015 and to identify the priority areas for intervention to reduce their occurrence.

METHODS

A cross-sectional mixed-methods design using an exploratory descriptive analysis and thematic analysis of patient safety incident reports. Primary data were extracted from a national database of patient safety incidents. Reports were filtered for emergency department settings, diagnostic error (as classified by the reporter), from 2013 to 2015. These were analysed for the chain of events, contributory factors and harm outcomes.

RESULTS

There were 2288 cases of confirmed diagnostic error: 1973 (86%) delayed and 315 (14%) wrong diagnoses. One in seven incidents were reported to have severe harm or death. Fractures were the most common condition (44%), with cervical-spine and neck of femur the most frequent types. Other common conditions included myocardial infarctions (7%) and intracranial bleeds (6%). Incidents involving both delayed and wrong diagnoses were associated with insufficient assessment, misinterpretation of diagnostic investigations and failure to order investigations. Contributory factors were predominantly human factors, including staff mistakes, healthcare professionals' inadequate skillset or knowledge and not following protocols.

CONCLUSIONS

Systems modifications are needed that provide clinicians with better support in performing patient assessment and investigation interpretation. Interventions to reduce diagnostic error need to be evaluated in the emergency department setting, and could include standardised checklists, structured reporting and technological investigation improvements.

Strategies to reduce diagnostic errors: a systematic review

Background

To evaluate the effectiveness of audit and communication strategies to reduce diagnostic errors made by clinicians.

Methods

MEDLINE complete, CINHAL complete, EMBASE, PSNet and Google Advanced. Electronic and manual search of articles on audit systems and communication strategies or interventions, searched for papers published between January 1990 and April 2017. We included studies with interventions implemented by clinicians in a clinical environment with real patients.

Results

A total of 2431 articles were screened of which 26 studies met inclusion criteria. Data extraction was conducted by two groups, each group comprising two independent reviewers. Articles were classified by communication (6) or audit strategies (20) to reduce diagnostic error in clinical settings. The most common interventions were delivered as technology-based systems n = 16 (62%) and within an acute care setting n = 15 (57%). Nine studies reported randomised controlled trials. Three RCT studies on communication interventions and 3 RCTs on audit strategies found the interventions to be effective in reducing diagnostic errors.

Conclusion

Despite numerous studies on interventions targeting diagnostic errors, our analyses revealed limited evidence on interventions being practically used in clinical settings and a bias of studies originating from the US (n = 19, 73% of included studies). There is some evidence that trigger algorithms, including computer based and alert systems, may reduce delayed diagnosis and improve diagnostic accuracy. In trauma settings, strategies such as additional patient review (e.g. trauma teams) reduced missed diagnosis and in radiology departments review strategies such as team meetings and error documentation may reduce diagnostic error rates over time.

Trial registration

The systematic review was registered in the PROSPERO database under registration number CRD42017067056.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0901-1) contains supplementary material, which is available to authorized users.

Two Decades Since To Err Is Human: An Assessment Of Progress And Emerging Priorities In Patient Safety

The Institute of Medicine's To Err Is Human, published in 1999, represented a watershed moment for the US health care system. The report dramatically raised the profile of patient safety and stimulated dedicated research funding to this essential aspect of patient care. Highly effective interventions have since been developed and adopted for hospital-acquired infections and medication safety, although the impact of these interventions varies because of their inconsistent implementation and practice. Progress in addressing other hospital-acquired adverse events has been variable. In the past two decades additional areas of safety risk have been identified and targeted for intervention, such as outpatient care, diagnostic errors, and the use of health information technology. In sum, the frequency of preventable harm remains high, and new scientific and policy approaches to address both prior and emerging risk areas are imperative. With the increasing availability of electronic data, investments must now be made in developing and testing methods to routinely and continuously measure the frequency and types of patient harm and even predict risk of harm for specific patients. This progress could lead us from a Bronze Age of rudimentary tool development to a Golden Era of vast improvement in patient safety.

What interventions could reduce diagnostic error in emergency departments? A review of evidence, practice and consumer perspectives

The purpose of this article is to synthesise review evidence, practice and patient perspectives on interventions to reduce diagnostic error in emergency departments (EDs). A rapid review methodology identified nine systematic reviews for inclusion. Six practice interviews were conducted to identify local contextual insights and implementation considerations. Finally, patient perspectives were explored through a citizen panel with 11 participants. The rapid review found evidence for the following interventions: second opinion, decision aids, guided reflection and education. Practitioners suggested three of the four interventions from the academic review: second opinion, decision aids and education. Practitioners suggested four additional interventions: improving teamwork, engaging patients, learning from mistakes and scheduled test follow-up. Patients most favoured interventions that improved communication through education and patient engagement, while also suggesting that implementation of state-wide standards to reduce variability in care and sufficient staffing are important to address diagnostic errors. Triangulating these three perspectives on the evidence allows for the intersections to be highlighted and demonstrates the usefulness of incorporating practitioner reflections and patient values in developing potential interventions.

Diagnostic error, quality assurance, and medical malpractice/risk management education in emergency medicine residency training programs

Background

Diagnostic errors in emergency medicine (EM) can lead to patient harm as well as potential malpractice claims and quality assurance (QA) reviews. It is therefore essential that these topics are part of the core education of trainees. The methods training programs use to educate residents on these topics are unknown. The goal of this study was to identify the current methods used to teach EM residents about diagnostic errors, QA, and malpractice/risk management and determine the amount of educational teaching time EM programs dedicate to these topics.

Methods

An 11-item questionnaire pertaining to resident education on diagnostic errors, QA, and malpractice was sent through the Council of Emergency Medicine Residency Directors (CORD) listserv. Differences in the proportions of responses by duration of training program were analyzed using chi-squared or Fisher’s exact tests.

Results

Fifty-four percent (91/168) of the EM programs responded. There was no difference in prevalence of formal education on these topics among 3- and 4-year programs. The majority of programs (59.5%) offer fewer than 4 h per year of additional QA education beyond morbidity and mortality rounds; a minority of the programs (18.8%) offer more than 4 h per year of medical malpractice/risk management education.

Conclusions

This needs assessment demonstrated that there is a lack of dedicated educational time devoted to these topics. A more formalized and standard curricular approach with increased time allotment may enhance EM resident education about diagnostic errors, QA, and malpractice/risk management.

Teaching Critical Thinking: A Case for Instruction in Cognitive Biases to Reduce Diagnostic Errors and Improve Patient Safety

Diagnostic errors contribute to as many as 70% of medical errors. Prevention of diagnostic errors is more complex than building safety checks into health care systems; it requires an understanding of critical thinking, of clinical reasoning, and of the cognitive processes through which diagnoses are made. When a diagnostic error is recognized, it is imperative to identify where and how the mistake in clinical reasoning occurred. Cognitive biases may contribute to errors in clinical reasoning. By understanding how physicians make clinical decisions, and examining how errors due to cognitive biases occur, cognitive bias awareness training and debiasing strategies may be developed to decrease diagnostic errors and patient harm. Studies of the impact of teaching critical thinking skills have mixed results but are limited by methodological problems.This Perspective explores the role of clinical reasoning and cognitive bias in diagnostic error, as well as the effect of instruction in metacognitive skills on improvement of diagnostic accuracy for both learners and practitioners. Recent literature questioning whether teaching critical thinking skills increases diagnostic accuracy is critically examined, as are studies suggesting that metacognitive practices result in better patient care and outcomes. Instruction in metacognition, reflective practice, and cognitive bias awareness may help learners move toward adaptive expertise and help clinicians improve diagnostic accuracy. The authors argue that explicit instruction in metacognition in medical education, including awareness of cognitive biases, has the potential to reduce diagnostic errors and thus improve patient safety.

Application of electronic trigger tools to identify targets for improving diagnostic safety

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.

Diagnostic Decision-Making in the Emergency Department

Emergency medicine requires diagnosing unfamiliar patients with undifferentiated acute presentations. This requires hypothesis generation and questioning, examination, and testing. Balancing patient load, care across the severity spectrum, and frequent interruptions create time pressures that predispose humans to fast thinking or cognitive shortcuts, including cognitive biases. Diagnostic error is the failure to establish an accurate and timely explanation of the problem or communicate that to the patient, often contributing to physical, emotional, or financial harm. Methods for monitoring diagnostic error in the emergency department are needed to establish frequency and serve as a foundation for future interventions.

Comparing nurse practitioners/physician assistants and physicians in diagnosing adult abdominal pain in the emergency department

BACKGROUND AND PURPOSE

This retrospective study compared nurse practitioners and physician assistants (NPs/PAs) with physicians on their assignment of Emergency Severity Index level 3 (ESI level 3) acute abdominal pain (AAP) in the emergency department (ED).

METHODS

Data obtained from a large ED group staffing four hospitals yielded 12,440 de-identified, adult patients diagnosed on ED admission with AAP ESI level 3 for descriptive analysis with logistic regression.

CONCLUSIONS

Results revealed that the comparison of ESI level 3 AAP diagnoses was consistent between admission and discharge 95.3% for physicians, 92.9% for NPs/PAs, and 97.1% for NP/PA and physician collaboration (χ = 46.01, p < .001). Logistic regression suggested that NP/PA had significantly reduced odds (31%) of consistent admitting/discharge diagnoses, whereas collaboration of NP/PA with physicians had significantly increased odds of consistent diagnosis (41%) compared with physicians alone. Two hospitals with similar distributions of NPs/PAs and physicians exhibited greater odds of consistent diagnoses over hospitals with disproportionate distributions; a secondary finding worth exploring. Consistent AAP ESI level 3 diagnoses by outcomes were admissions (>99%), discharges (94%), and left against medical advice/transferred (98%; χ = 102.94, p < .001).

IMPLICATIONS FOR PRACTICE

The highest percentage of consistent AAP ESI level 3 diagnoses between ED admission and discharge was when NPs/PAs and physicians collaborated.

Understanding diagnostic safety in emergency medicine: A case-by-case review of closed ED malpractice claims

The report Improving Diagnosis in Health Care calls for collaboration between professional liability insurance carriers and health care providers to identify opportunities to improve diagnostic performance. We used this collaborative approach and involved risk management/patient safety professionals and emergency medicine physician reviewers to analyze diagnosis-related emergency medicine closed claims from a large malpractice insurer. Our aim was to identify opportunities for risk reduction and to develop an approach for improving at-risk processes. Analysis of these cases revealed several missed opportunities in the diagnostic process. A collaborative approach offered greater insight into diagnosis process failures that may not have been evident if cases were reviewed in silos. Focused review findings led to a multidisciplinary improvement collaborative to develop clinical guidelines for improving at-risk practices and informed a simulation-based training initiative.

Errors in Diagnosis of Spinal Epidural Abscesses in the Era of Electronic Health Records

PURPOSE

With this study, we set out to identify missed opportunities in diagnosis of spinal epidural abscesses to outline areas for process improvement.

METHODS

Using a large national clinical data repository, we identified all patients with a new diagnosis of spinal epidural abscess in the Department of Veterans Affairs (VA) during 2013. Two physicians independently conducted retrospective chart reviews on 250 randomly selected patients and evaluated their records for red flags (eg, unexplained weight loss, neurological deficits, and fever) 90 days prior to diagnosis. Diagnostic errors were defined as missed opportunities to evaluate red flags in a timely or appropriate manner. Reviewers gathered information about process breakdowns related to patient factors, the patient-provider encounter, test performance and interpretation, test follow-up and tracking, and the referral process. Reviewers also determined harm and time lag between red flags and definitive diagnoses.

RESULTS

Of 250 patients, 119 had a new diagnosis of spinal epidural abscess, 66 (55.5%) of which experienced diagnostic error. Median time to diagnosis in error cases was 12 days, compared with 4 days in cases without error (P <.01). Red flags that were frequently not evaluated in error cases included unexplained fever (n = 57; 86.4%), focal neurological deficits with progressive or disabling symptoms (n = 54; 81.8%), and active infection (n = 54; 81.8%). Most errors involved breakdowns during the patient-provider encounter (n = 60; 90.1%), including failures in information gathering/integration, and were associated with temporary harm (n = 43; 65.2%).

CONCLUSION

Despite wide availability of clinical data, errors in diagnosis of spinal epidural abscesses are common and involve inadequate history, physical examination, and test ordering. Solutions should include renewed attention to basic clinical skills.

Epidemiology and outcomes of acute abdominal pain in a large urban Emergency Department: retrospective analysis of 5,340 cases

BACKGROUND

Acute abdominal pain (AAP) accounts for 7-10% of all Emergency Department (ED) visits. Nevertheless, the epidemiology of AAP in the ED is scarcely known. The aim of this study was to investigate the epidemiology and the outcomes of AAP in an adult population admitted to an urban ED.

METHODS

We made a retrospective analysis of all records of ED visits for AAP during the year 2014. All the patients with repeated ED admissions for AAP within 5 and 30 days were scrutinized. Five thousand three hundred and forty cases of AAP were analyzed.

RESULTS

The mean age was 49 years. The most frequent causes were nonspecific abdominal pain (NSAP) (31.46%), and renal colic (31.18%). Biliary colic/cholecystitis, and diverticulitis were more prevalent in patients aged >65 years (13.17% vs. 5.95%, and 7.28% vs. 2.47%, respectively). Appendicitis (i.e., 4.54% vs. 1.47%) and renal colic (34.48% vs. 20.84%) were more frequent in patients aged <65 years. NSAP was the most common cause in both age classes. Renal colic was the most frequent cause of ED admission in men, whereas NSAP was more prevalent in women. Urinary tract infection was higher in women. Overall, 885 patients (16.57%) were hospitalized. Four hundred and eighty-five patients had repeated ED visits throughout the study period. Among these, 302 patients (6.46%) were readmitted within 30 days, whereas 187 patients (3.82%) were readmitted within 5 days. Renal colic was the first cause for ED readmission, followed by NSAP. In 13 cases readmitted to the ED within 5 days, and in 16 cases readmitted between 5-30 days the diagnosis was changed.

CONCLUSIONS

Our study showed that AAP represented 5.76% of total ED visits. Two conditions (i.e., NSAP and renal colic) represented >60% of all causes. A large use of active clinical observations during ED stay (52% of our patients) lead to a negligible percentage of changing diagnosis at the second visit.